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Algorithms

audio

The walkAudio() and selectAudio() functions are designed to work with audio data, with walkAudio() creating distinguishable features and selectAudio() querying specific features of audio, but they are not implemented in the provided code snippet.

ffmpeg commands

The FFmpeg command converts an input .mp4 video file to an output .webm file using VP9 video codec, Opus audio codec, and a constant rate factor of 30, with an automatically determined video bitrate and a fixed 128k audio bitrate.

To convert an input video file to a .webm file, the FFmpeg command is used with the following parameters: ffmpeg -i input.mp4 -c:v libvpx-vp9 -crf 30 -b:v 0 -b:a 128k -c:a libopus output.webm. This command uses the VP9 video codec, Opus audio codec, and a constant rate factor of 30 to control the video quality.

The FFmpeg command is used to stream video and audio from an RTMP source to YouTube Live, using the H.264 codec for video and the AAC codec for audio. The command sets various settings for video and audio encoding, including bitrate, frame rate, and sampling rate, and outputs the stream in FLV format at a specified URL.

image magik commands

These ImageMagick commands process an input image, resizing, sharpening, and converting it to JPEG. They also apply effects to create a glow and potentially reduce noise by compositing modified copies of the image onto the original.

This code uses ImageMagick commands to process and convert an image file, involving resizing, compressing, enhancing, and despeckling the image. The code consists of three ImageMagick commands and a final echo command that prints "done" to the console.

The code is a pair of scripts, one for Windows and one for Unix/Linux, that use image conversion tools to process multiple image file types in bulk. The scripts convert images to various formats, resize and scale them, and apply enhancements to create final images with a consistent ".jpg" format.

This code uses ImageMagick's convert command to resize and enhance an input image, applying various filters and processing techniques, and saving the final output as a new image file.

The code resizes and enhances an input image using ImageMagick's convert command, applying techniques such as despeckling and alpha channel processing. The final output image is saved as a new file, with adjustable quality settings and a maximum width of 600 pixels.

This bash script searches for image files in a specified directory, enhances and converts them to JPEG format, and renames them by removing "-final" extensions and appending ".jpg" extensions. The script uses commands like find, convert, and mv to perform these operations, relying on ImageMagick and parameter expansion for file manipulation.

The scripts use ImageMagick commands to process an input image, removing extra space, resizing, rotating, and adding a watermark, with the final result being output to a new file. The scripts are identical in their functionality, but differ in their file paths and line endings, suggesting a possible Windows version (Script 2) alongside a Unix-based version (Script 1).

llama vision

This JavaScript code implements a large language model using the node-llama-cpp library, providing functions to initialize and interact with the model. It includes functions for initializing chat sessions, loading LLM models, and analyzing prompts, with optional error handling.

This code defines an async function named analyzeImage that takes an image path, reads the image file, converts it to base64, and uses a Large Language Model (LLM) to analyze the image, returning the result.

The llmDeceive function generates a response to a given prompt using an LLaMA model, initializing a session with a specific configuration and session settings. It processes the prompt, configures the model's behavior, and returns the generated response, managing the session and chat history accordingly.

The llmVoice function generates text-to-speech output using the LLaMA model, taking a prompt and optional session object as parameters. It sends the prompt to the model, returning the generated result and resetting the chat history if the provided session is the same as the current session.

The code imports necessary modules, sets the HOMEPATH variable, configures a TTS model, and defines a generateSpeech function to synthesize speech from a prompt and save it to a file. The generateSpeech function is then exported as the default export of the module.

The code imports the OuteTTS library, configures a text-to-speech model, and defines a function llmSpeech to convert text to speech, which is then exposed to be used outside of this code module.

The code consists of imported modules, functions, and notes for an asynchronous Python script that uses custom modules browser_use and langchain_ollama to execute a search task on the r/LocalLLaMA subreddit. The script defines two asynchronous functions: run_search() and main().

Makes a request to the LLaMA Vision API with an optional image and prompt, returning the response message from the API. The function uses async/await syntax and assumes the LLaMA Vision API is running on http://localhost:11434/api/chat.

The code imports Node.js modules, defines environment configurations, and exports a function launchChats that launches chat services using Node.js. The function loops through the environment configurations and uses child_process to run a new Node.js process for each configuration.

The code requires modules for file operations and HTTP requests, defines a constant for the output directory path, and includes an asynchronous function doStableRequest to generate an image based on a given prompt. This function makes a POST request to the stable diffusion API, processes the response, and returns an object containing the seed, image buffer, image path, and prompt.

The doBackgroundMask function is an asynchronous process that takes an image, extracts its base64 representation, applies a background mask using the rembg API, and writes the masked image to a file. It involves file system operations, image processing, and HTTP requests to the rembg API.

The doInpaintMask function performs inpainting on an image using a provided mask and text prompt, sending a POST request to a local stable diffusion API endpoint.

The code imports modules for interacting with the file system, working with file paths, and making HTTP requests. It defines a function doImage2Image that takes an image and a prompt, processes the image, makes a POST request to generate an image, and returns the seed and generated image.

The code imports various modules and functions, then defines an asynchronous function whiskImages that takes four arguments and handles different types of input for its first two arguments, subject and scene.

llama

This code defines an asynchronous function askLlamaMatchingFunction that searches for matching functions based on a given query by utilizing imported functions and caching cell and RPC function data. The function stores, filters, and queries LLM functions to return an array of matching functions.

This function, askLlamaAboutCategories, queries the Llama language model about categories related to a given query and returns a list of notebook filenames containing matching categories.

The askLlamaGeneralizeCategories function generalizes a list of categories by iteratively refining the list with the LLM until a satisfactory result is obtained. It returns a refined list of categories and updates the function cache if necessary.

The code defines two functions: askLlamaToGeneralize and askLlamaToGeneralizeAll, which use a large language model to generalize lists of categories into shorter lists. The askLlamaToGeneralizeAll function batches the categories and calls askLlamaToGeneralize for each batch, then filters out duplicates from the results.

The askLlamaAboutFunctions function is an asynchronous query that matches a given input with a function listed in an array, providing an optional description and categorization. It constructs a query string, sends it to a Large Language Model, and returns the matched function name.

The askLlamaAboutCode function takes a string of code, uses an LLM to provide a short breakdown, and logs the prompt and response. It limits input code to 2048 characters and trims the LLM response.

The code provides a module that exports a function askLlamaAboutNotebooks which asks the LLaMA language model about functions in notebook files within a directory and its subdirectories. The function breaks down the query into chunks of 20 and sends them to the model for response.

The provided code defines three asynchronous functions: askLlamaToSummerize, askLlamaToGeneralize, and askLlamaToImplement, which interact with a Large Language Model (LLM) to perform tasks such as summarizing queries and improving code snippets. These functions are exported as an object and can be used in other parts of the application.

The code imports functions from modules, defines a storeLlamaFunction to store metadata in a functionCache object, and generates and updates code in a cacheCell to export the metadata. The storeLlamaFunction is then exported as a module.

This JavaScript code imports functions from other modules to interact with a large language model (LLM) for code summarization and caching, then iterates through a cache of cells to retrieve and store the cached data using these LLM functions.

The code imports necessary modules, defines constants and variables, and creates LLaMA-related objects for initializing and interacting with a large language model. It includes two main functions: createSession for creating a new model instance and initSession for initializing a new chat session with the model.

llm blogging

The blogAboutCode function generates a blog post about a project's code history, using a specified timeframe and model. It retrieves the commit history, extracts commits, and logs the first and last commit hashes.

parsePatch Function Summary

summary Object

• files (object)
• File names as keys and objects containing:

• additions (array)
• deletions (array)

• totalAdditions (number): The total number of added lines in the patch.
• totalDeletions (number): The total number of deleted lines in the patch.

llm chat

The storeResponse function stores user interactions, analyzing the content, emotions, and context, and returns an object containing metadata about the interaction. It selects a model, checks for existing conversation files, and updates the conversation data in memory and the file system, generating a summary and keywords for the interaction.

This code is a Node.js module that imports necessary modules and variables, defines functions for retrieving recent messages from conversations, and implements file system operations for loading and storing conversation data. The module exports the messageRecents function, along with other variables and constants, allowing it to be used in other applications.

The relevantHistory function retrieves relevant conversation history files based on a given prompt, returning an array of file names. This function requires importer.import('general chit chat') to be called prior to usage and uses synchronous file system operations, logging input and output to the console.

The relevantKeywords function searches through a user's past conversations to find relevant keywords for a given prompt, using a specified model to retrieve and match keywords. It returns an array of keywords that match the prompt, eliminating duplicates and extraneous characters from extracted keywords.

The code imports constants and uses two functions, askLlamaMatchTimestamps and matchingTimestamps, to process timestamps and generate responses based on keywords and prompts. The matchingTimestamps function iterates over conversations, generates messages, and calls the askLlamaMatchTimestamps function to match timestamps with the generated responses, returning an array of matching timestamps.

This code defines a set of functions and constants to facilitate interacting with an API, including generating a description of the API functions and asking the user to match a prompt with an API function. The code exports four values, allowing other parts of the program to access and use the API functions and their corresponding exports and descriptions.

The handleConversation function is an asynchronous function that handles a conversation by classifying the prompt, storing the response, generating a response from a language model, and storing the final response. It takes five parameters, including promptModel, session, prompt, image, and otr, and returns the final response after processing the language model's output and storing relevant information.

The classifyPrompt function takes a prompt and image as input, matches the prompt to a specific function, and executes that function with the provided arguments to generate a response. The function iterates over matching functions, imports and parameterizes each one, and returns the result with additional memories, except for the doStableRequest function which returns a combined object.

This code consists of two functions, listMemories and findMemories, which are used to retrieve memories from a file system, with listMemories transforming memory keys into dates and returning an array of strings. The findMemories function searches for memories in a specific file or in a history of files, returning the memories object and caching the result for future reuse.

The code imports necessary modules and constants, then defines an asynchronous function manageMemories that handles memory management, including loading and saving memories based on user input. The function uses regular expressions to match user responses to different memory functions, such as saving, removing, or listing memories, and performs the corresponding actions.

llm dnd

llm scaffold

The code defines a constant PROFILE_PATH and an asynchronous function llmScaffold(github) that scaffolds a project. The llmScaffold function is exported as a module, allowing it to be used elsewhere in the application.

The code imports various modules and defines a function called generateBash which generates shell code using a Large Language Model (LLM) and saves it to a GitHub repository. The function checks the repository's existence, updates it if necessary, extracts code blocks from the LLM's response, and writes them to a new file in the repository.

The generateCode function is an asynchronous function that generates code based on a given prompt and project repository, and handles various steps such as resolving the Github path and cloning the repository. If no codeFile is provided, the function uses the llmCode function to ask the user for a file to edit based on the prompt, and logs the prompt and potential file name(s) generated by the AI model.

This Node.js script uses various libraries and functions to generate code based on a given prompt, involving operations such as Git clone, code generation using a Large Language Model (LLM), and output file naming. The makeCode function takes a prompt and optional repository URL as input, generates code, and returns the code blocks, while also handling errors and edge cases.

This Node.js script uses a Large Language Model (LLM) to generate code by constructing prompts, sending them to the LLM, and extracting code blocks from the response. The script performs tasks such as project path resolution, Git pull, and code interpretation to ensure the code is up-to-date and accurate before sending the prompt to the LLM.

This Node.js script uses a large language model (LLM) to generate code blocks for a project by fetching code from the LLM and extracting relevant blocks. The script handles errors, resolves GitHub repository and notebook file paths, executes a git pull command, and logs the generated code blocks to the console.

The decodeJupyterNotebook function decodes the content of a Jupyter Notebook file by reading it into a string, parsing it as JSON, and logging the content of code cells. It takes a single argument, filePath, which is the path to the Jupyter Notebook file, and raises an error if there are any issues with file reading or parsing.

llm tools

The code imports necessary modules and functions, defines constants for file system paths and regular expression patterns, and defines a function cellNeedsTidying to check if a cell in a chat log needs tidying. The cellNeedsTidying function checks five conditions, including the existence of certain properties like emotions, date, and dat, to determine if the cell needs tidying.

This code imports a module named select llm and assigns it to the selectModel constant. It also defines a constant array EMOTIONS containing 77 string values representing different emotions.

The code defines a storeChatHistory function that stores chat history data in a JSON file using Node.js's built-in fs and path modules, and exports it as a module.

Alternatively, you can condense it into two sentences:

The code uses Node.js's built-in modules to interact with files and paths, and defines a storeChatHistory function that stores chat history data in a JSON file. This function is then exported as a module for use in other parts of the application.

This code defines two asynchronous functions, askLlamaAboutConversation and askLlamaAboutCategory, that utilize a large language model for text analysis and summarization. The functions are designed to work with a create llm session module and are exported as a JavaScript module.

The code imports various modules and functions, defines two functions getChatHistory and askLlamaToRespondLike, and utilizes file system operations to read and write chat log files. The code has some areas for improvement, including inconsistent use of async/await, blocking file reads, and legacy syntax.

llm writing

The askLlamaToWriteBusinessPlan function generates a business plan using a prompt model, taking in topic, name, and prompt model parameters, and processing user and AI responses to extract goals and Executive Summaries. The function is not fully completed, with the remaining code likely intended to sort responses based on the Hero's Journey framework.

This code imports various functions and modules, including selectModel, askLlamaForAChapterSynopsis, and Remarkable, in order to generate content. It also defines a constant APOTHEOSIS with narrative descriptions and uses an importer to load various functions and modules from other files.

The arguelLlama function is an asynchronous function that engages in a debate process with a Large Language Model (LLM) using two prompts, iterating 10 times to allow the LLM to respond to its own previous responses. It returns an array of responses from the LLM in the debate process, with optional additional processing or logging performed by a callback function.

The askLlamaWriteEssay function uses LLM to generate an essay on a given topic by creating a chapter outline, selecting a random name, and writing long essay sections for each chapter.

The askLlamaWriteEssay function uses LLM to generate an essay on a given topic by creating a chapter outline and writing long essay sections for each chapter. The function selects a random name for the essay and uses Markdown to format the chapter titles and descriptions.

The GGUF SPECIFICATIONS object contains a list of model names and their corresponding specifications, while the GGUF_INSTRUCTIONS object contains a list of model names and their corresponding instructions or behaviors. The instructions for specific models, such as 'Code', provide templates for the response, while others are set to 'void 0' indicating no specific instruction is defined.

The askLlamaForAChapterSynopsis function asynchronously generates a list of chapter or character synopses for a given topic by interacting with an LLM (Large Language Model), logging the user's prompt and the LLM's response, and parsing the response to extract the synopsis titles and descriptions. The function returns an object with key-value pairs representing the synopses, assuming the LLM's response contains a list of numbered titles followed by their descriptions.

A TODO comment is a note indicating that the code requires modifications to a business plan and research plan, and it typically does not contain executable code. This section is for documentation purposes only.

The analyzeSpreadsheet function reads an Excel file from a specified path (or a default location if not provided) and extracts cell values from a specified sheet and range. It returns an array of these cell values, with optional parameters for specifying the sheet name and range.

The elaborateLlama function analyzes an XLSX spreadsheet, creates prompt sequences from its data, and sends them to a Large Language Model (LLM) for responses, which are then logged and written to a temporary text file. The function is designed to handle asynchronous operations and can be exported as a module for use in other applications.

opencv

This code utilizes OpenCV and other libraries to detect people in images, track motion, and draw bounding boxes around detected individuals. The code consists of several functions, including image loading, motion detection, and person tracking, with a TODO comment indicating the need to implement video recording and uploading functionality.

This code imports necessary libraries for computer vision tasks and defines three functions: percent_motion to calculate the percentage of white pixels in a thresholded image, image_grayscale to convert an image to grayscale, and diff_images to compute the absolute difference between two frames. The functions are exported as part of the module namespace for use in other scripts.

The code imports OpenCV and glob libraries, sets output video properties, and defines a write_video function that creates an output video from a list of images. The function gets the list of images, defines a VideoWriter object, writes each image to the video, and releases the object after cleanup.

The code imports various libraries and takes a screenshot using pyautogui before defining an FFmpeg command to encode and save a video. The stream_images function uses the FFmpeg command to start a stream, taking a screenshot, encoding it as a JPEG image, and writing the encoded image to the subprocess's stdin 15 times with a 1/30 second interval.

The code imports necessary libraries, loads credentials from a service account JSON file, and sets up a YouTube API client using the googleapiclient library. The live_stream function is defined to create a new live stream on YouTube, utilizing the API client and specifying parameters such as title, description, and scheduled start time.

This Python script uses the Flask web framework and Google API Client Library to create a simple web application that authenticates users with Google and authorizes them to access the YouTube API using OAuth 2.0 authentication.

The script imports necessary libraries and sets environment variables for Google API authentication, then creates a Flask application instance. It defines a single route, /authorize, which handles the OAuth 2.0 authorization flow, generating a URL to redirect users to the Google authorization page for consent and offline access.

The code imports various libraries and modules to interact with the operating system, handle JSON data, build a web application, and make HTTP requests, and configures the Google API for YouTube. It defines functions to authorize and list live broadcasts using the YouTube API, sanitize file names, and maps function names to their corresponding functions in the module.

The code imports necessary libraries, defines constants and two functions (create_livestream and sanitize_filename), and exports the create_livestream function for use. The create_livestream function creates a new live stream on YouTube by authorizing the user, building a YouTube API client, and inserting the live stream details, while the sanitize_filename function replaces invalid characters in a string with underscores.

The code imports necessary libraries, defines constants and functions for interacting with the YouTube API, and exports two main functions: list_livestream and youtube_authorize. These functions allow users to authorize with the YouTube API and list their live streams, with the option to sanitize filenames and handle OAuth 2.0 credentials.

This code binds a live stream to a YouTube broadcast using the YouTube API, utilizing functions to import necessary modules and notebooks, authorize API credentials, retrieve broadcast and stream information, and execute the binding request. The bind_stream_to_broadcast function returns the stream information and broadcast ID, and is exported for use in other modules.

The transition_stream function uses the YouTube API to authorize and bind a stream to a broadcast, then starts a subprocess to write images to an FFmpeg stream, waiting indefinitely until interrupted. The code includes unused sections for creating stream data and transitioning the broadcast status to 'live', which are likely part of a larger script or implementation.

stable diffusion

trainmodel

This code imports necessary libraries, including Keras for building neural networks, and additional libraries like Pandas for data manipulation and NumPy for numerical computation, as well as the os module for operating system functions. The imported libraries are used for tasks such as image processing, data analysis, and neural network model creation.

The TRAIN_DIR and TEST_DIR variables define the paths to the directories containing training and test images, respectively.

The createdataframe function takes a directory path as input and returns two lists: image_paths and labels, containing the paths to images and their corresponding labels, respectively. It traverses the directory structure to extract this information.

This code creates an empty Pandas DataFrame named train and initializes it with image and label data by calling the createdataframe function, which returns the training set data. The returned data is then unpacked and assigned as separate columns to the DataFrame.

This code snippet prints the value of the train variable to the console. The output will be the value of train, which could be any data type such as a string, integer, or float.

An empty DataFrame named test is created using pandas. Data is then assigned to two columns, image and label, from the results of the createdataframe function called with the TEST_DIR argument.

This code block prints the value of the variable test and its 'image' key, assuming test is a dictionary with the key 'image'.

Alternatively, in two sentences:

This code block is designed to print two values from an object called test: the object itself and its 'image' key.

The tqdm library can be imported in Jupyter notebooks using the line from tqdm.notebook import tqdm. This imports the tqdm function from the tqdm.notebook module, enabling the use of progress bars in Jupyter notebooks.

The extract_features function extracts features from a list of images and returns a 4D numpy array containing the features. It assumes images are loaded as grayscale arrays and does not perform any preprocessing or feature extraction.

The extract_features function extracts features from an input image, taking the image data from the training dataset as input. It returns the extracted features from the input image, which are stored in the train_features variable.

The code is designed to extract features from an image, with a function extract_features(image) responsible for this task. It utilizes a dictionary test containing image data and a variable test_features to store the extracted features.

This code normalizes feature values in training and testing datasets by dividing them by 255.0, effectively converting pixel values from a range of [0, 255] to [0, 1]. This is a common normalization technique in deep learning, suitable for image classification problems.

The LabelEncoder class from scikit-learn's preprocessing module converts non-numerical labels into numerical labels. It provides three key methods: fit(), transform(), and inverse_transform(), which are used to encode, transform, and decode labels respectively.

The code creates a LabelEncoder instance, fits it to the 'label' column of the train dataset, and uses it to encode categorical labels into numerical values. This is a typical preprocessing step in machine learning pipelines.

This code snippet uses Label Encoding to transform categorical data in the 'label' column of the 'train' and 'test' datasets into numerical representations. The transformation is performed using the transform() method, assuming that a LabelEncoder instance named le has been initialized elsewhere in the code.

The to_categorical function converts integer class vectors into binary class matrices, useful for classification problems. It takes integer class vectors and returns one-hot encoded matrices, where each row represents a sample and each column represents a class.

This CNN model architecture uses the Keras Sequential API and consists of multiple convolutional and pooling layers, followed by a flatten layer and fully connected layers to classify inputs into 7 categories. The model architecture includes 12 Conv2D layers with various filter sizes and ReLU activation, 4 Dropout layers for regularization, 3 Flatten layers, and 3 Dense layers with ReLU and softmax activation.

The model.compile() method in Keras is used to compile a model by specifying the optimization algorithm, loss function, and evaluation metric. It returns the compiled Keras model.

The fit function is used to train a model on given input and output data, with options to adjust batch size and number of epochs.

The fit function takes in the input data x, output data y, and additional parameters such as batch_size, epochs, and validation_data.

To save a deep learning model, its architecture can be serialized to a JSON file using model.to_json() and written to a file with json_file.write(model_json). Additionally, the model's weights and architecture can be saved to an H5 file with model.save("emotiondetector.h5").

To load a Keras model from a JSON file, you can use the model_from_json function from the keras.models module. This is achieved by importing the function with from keras.models import model_from_json.

To load a facial emotion recognition model, you need to open a JSON file, read its contents into a Keras model, and then load the model's weights from a corresponding HDF5 file. This process is typically performed using the steps outlined in the provided code breakdown.

This code assigns a list of seven emotions to a variable named label. The list contains emotions such as 'angry', 'happy', and 'neutral' that can be used to store or reference these emotions in a program.

The ef function preprocesses an input image by converting it to grayscale and normalizing pixel values to the range [0, 1]. It returns a preprocessed image feature with shape (1, 48, 48, 1).

This code snippet loads an image, applies preprocessing and prediction using a machine learning model, and then extracts and prints the predicted label. The code utilizes various functions, including ef for image transformation and a model's predict method for making predictions.

The code import statement import matplotlib.pyplot as plt brings in the matplotlib library and assigns it a shorter alias plt for convenience. The %matplotlib inline magic command, used in Jupyter Notebooks, displays plots directly in the notebook window.

This code loads an image using OpenCV, makes a prediction on it using a model, and prints the predicted label. The image is then displayed using Matplotlib, reshaped to a 48x48 matrix and mapped to grayscale colors.

This code snippet involves loading an image, making a prediction using a machine learning model, and visualizing the original image, with unknown implementations of the ef function and label list.

The code appears to involve loading an image, preprocessing it using an unknown function ef, and passing it through a deep learning model model to make a prediction. The prediction is then printed, and the preprocessed image is reshaped and displayed using matplotlib.

This code snippet appears to load and preprocess an image, make a prediction using a machine learning model, and then display the original image and print the predicted label. The image is loaded from a specified path, preprocessed using a function ef, and then passed to a model for prediction, which selects a label from a list or dictionary based on the predicted output.

This code snippet processes an image by loading it, applying a custom image processing function ef(), and using a machine learning model to make a prediction. The predicted label is then printed, along with a display of the processed image in grayscale.

Analytics

budgeting

calculations for life

This code determines the proportion of the author's life spent with a friend named Jim, factoring in years of friendship, visit frequency, vacation duration, and life expectancy.

This JavaScript script calculates and logs various statistics related to life, including the percentage of life spent sleeping and masturbating, based on assumptions of 7 hours of sleep per night and 1 hour of masturbation per day. The output includes the percentage of life spent sleeping, the percentage of the year spent masturbating, and the percentage of life spent masturbating.

The getSequenceNumeral function generates a sequence numeral by calculating the sum of multiples of a given prefix pre at each power of 10, and adds the remainder of a count count divided by 10.

The function takes two parameters: pre and count, and returns the generated sequence numeral, as demonstrated in the example getSequenceNumeral(3, 1).

data collection

This code defines a function scrapeAlert that fetches and saves data from a website based on a given ID, and exports it for use elsewhere.

The searchAll function is a main exported function that retrieves search results from multiple search engines in parallel using the multiCrawl function, and saves the results to a JSON file in the user's Collections/searches directory. The function takes an optional query parameter and returns a promise that resolves to an object containing search results, with the file name constructed from the query string and the current date.

The code imports necessary modules, defines an options object, and exports a scheduleSearch function that creates a new event on a Google Calendar with a customizable search query. The scheduleSearch function checks for authentication, creates a new event, and returns a Promise that can be resolved with the event's details.

The getJoke function imports required modules and makes a GET request to a web page to retrieve a list of jokes, extracting the questions and answers using regular expressions. It then returns a random joke from the list, or resolves with the existing joke data if it has already been loaded.

The code imports necessary modules, defines constants for timeouts and connections, and implements two key functions: deQueue for recursively dequeuing tasks from an input queue and multiCrawl for parallel crawling using Selenium connections. The multiCrawl function uses deQueue to crawl through an input list and returns a promise with the crawl results.

crawlRecursive(url, depth, searches)**:

The crawlRecursive function is a recursive web crawler that starts at a specified initial URL, iteratively retrieves links from the crawled pages, and stores them in a cache, with the ability to manage recursion depth and cache updates. The function uses a series of steps, including crawling, cache management, link extraction, recursion, and termination, to fetch and process links from the web pages.

This code snippet appears to be a Node.js module that handles caching web pages, importing various modules, and defining functions to cache and retrieve data based on URLs. The functions include caching file creation, searching for existing caches, checking cache validity, and storing cache data in files, with various options for cache restraint and URL sanitization.

This code snippet relies on the puppeteer library and internal modules to extract information from web pages, including style URLs, links, and HTML content. It also includes utility functions to calculate expiration dates based on Cache-Control headers and extract URLs from CSS content using regular expressions.

The analyzeCache function analyzes the cache file for a given URL, extracting statistics such as the number of cache objects, distinct domains, and repeated URLs. It returns an object with various statistics, including the count of pages, caches, and domains, as well as the URLs for the 10 largest objects and repeated URLs.

This JavaScript code imports the Google Calendar API and defines an options object with a calendar ID. It also exports a scheduleSearch function that takes a search parameter and schedules a new event on the specified calendar, using OAuth authentication if it is defined in the options object.

This Node.js script uses various custom modules to scrape websites, save PDFs and screenshots, and collect bookmarks from Google Takeout, with error handling and logging in place.

The searchResultsToJson(url) function extracts search results from a given URL and returns them in JSON format, containing the URL, query, and results. It logs the URL and session ID, sends a request, extracts the search query and results, maps them to a desired format, and catches any errors that occur during the process.

movie database

This code imports data from IMDb TSV files (principals, titles, and names) and stores it in a structured SQLite database.

This code provides a set of functions for interacting with a SQLite database containing movie information, including methods for searching by Levenshtein distance and retrieving actor and title data. The functions use a mix of synchronous and asynchronous programming, with prepared statements and promise chains to improve security, performance, and readability.

The code initializes a SQLite database and defines a function dropTitles to drop indices and a table from the database. It also prepares a query to count the number of rows in the name table, but the result is not utilized.

This code searches for documents containing "express js" in the "books" index and "book" type within an Elasticsearch database.

This code sets up a SQLite database schema for storing IMDb movie data, including tables for movies, actors, titles, crew, and episodes, along with indexes to optimize data retrieval.

parsing email addresses

This code provides a function getEmailFormat that searches the web for email address formats associated with a given query, combining results from both a specific site (rocketreach.co) and a general search. It extracts potential email addresses using a regular expression and returns a list of found formats.

This JavaScript code stores a long list of institutions in a string variable, containing many duplicates and a mix of institutions from various types and locations. Potential use cases include data analysis, database population, and algorithmic decision-making, where the data may need to be cleaned, formatted, and analyzed.

reconcile timeline data

resume

This code fetches course enrollment data from a Google Sheet and generates an SVG image of a D3.js pie chart visualizing the data. It uses imported functions to retrieve the data and create the chart.

This code imports a function to create a pie chart of course data and then displays the resulting chart as an SVG image on a webpage.

socializing

Art

stable diffusion

This code sets up paths to access images generated by a text-to-image AI, likely Stable Diffusion, specifically targeting a folder containing images of desserts in a manga anime style.

virtual worlds

Cloud Services

aws

This code defines a webhook handler function that validates incoming requests, retrieves a result based on a specified function, and returns the result as a JSON response.

This code provides a function latestS3 that retrieves the 5 most recently modified files from an S3 bucket, optionally filtering them based on a given pattern. It's designed to be used both as a server-side module and potentially in a client-side environment.

To interact with AWS Lambda using the AWS SDK in JavaScript, you can import the SDK, initialize an AWS Lambda client, and invoke a Lambda function with a custom payload. The AWS Lambda client handles potential errors and success cases by calling context.done in case of an error and context.succeed with the payload in case of a successful function call.

cloudflare

The cloudflared tunnel run command allows internet traffic to reach a local application or service through a Cloudflare Tunnel. The command typically requires a unique tunnel ID, such as 64d274ab-b0a4-4ef0-9636-e623dd02ac5c, to identify the tunnel instance.

deploy host

The deployAws function packages project files into a zip archive and deploys them to the AWS Lambda function eloqua_test in the us-west-2 region.

The powershell.exe command launches the PowerShell command-line interface and allows for various switches to customize its behavior. The main command, & {... }, executes a script block that imports a namespace, creates an array, and uses the Compress-Archive cmdlet to compress a file into an archive named index.zip.

The code defines two configuration objects, zuoraConfig and eloquaConfig, which contain settings for Zuora and Eloqua APIs, respectively, and are populated using environment variables. Each object contains properties that store authentication credentials, API URLs, and other configuration settings necessary for making API requests.

The provided code snippet contains environment variables stored in a JSON object, which include credentials and URLs for both Zuora and Eloqua APIs. These variables include sensitive information such as API keys, passwords, and client secrets.

google cloud api

This code is a set of functions for interacting with Google Cloud's Compute Engine API, using the google-auth-library and googleapis libraries to authenticate and make requests to the API. The functions, including listUrlMaps, listTargetProxies, and listGlobalForwards, follow a common pattern to retrieve metadata from the API and return promises that resolve to objects with the desired data.

This code is a test suite that uses various functions to list different resources (url maps, target proxies, global forwards, backend buckets) from a Google Cloud project, and asserts that each list is non-empty. The test suite uses functions such as listUrlMaps, listTargetProxies, listGlobalForwards, and listBackendBuckets to retrieve the lists of resources and logs the results to the console.

The waitForOperation function waits for a specified Google operation to complete and returns the target link when finished, using a recursive approach with a 500ms delay between checks.

The code imports functions from a Core module and defines several functions to manage Google Cloud resources, including creating backend buckets and SSL certificates, and listing various Google Cloud items. However, the functions are not fully implemented and contain TODO comments, suggesting that the code is a partial implementation of a larger application.

The code imports necessary modules and functions, defines variables, and sets up a test suite using Mocha to verify that the listGlobalForwards function correctly lists global forwards. The test case calls the function with project and proxy parameters, checks the result, and logs any errors or failures to the console.

The code defines a test suite with three test cases to add a subdomain to a load balancer, involving inserting a backend bucket, adding a frontend, and updating a URL map, with each test case having a 60-second timeout.

Alternatively, you can summarize it in two sentences:

The code is a test suite that adds a subdomain to a load balancer, consisting of three test cases to insert a backend bucket, add a frontend, and update a URL map. Each test case has a 60-second timeout and includes assertions to verify the returned values are not empty.

The code requires several modules for DNS operations and uses custom functions from a module named ../Core to perform tasks such as creating a Google Cloud DNS managed zone and inserting an address. The createZone function creates or retrieves a managed zone with a given subdomain, while the insertAddress function attempts to insert an address into the DNS managed zone.

This code uses the Mocha testing framework to test the addIP function, which adds an external IP to a project and bucket, with error handling and a 60-second timeout. The code also utilizes a custom importer module and built-in Node.js assert module for assertions.

This JavaScript code authorizes access to Google APIs by resolving the path to a credentials file, using the Google Auth library to authenticate, and exporting a function to obtain a Google client instance. The authorization function returns a Google client instance with specific scopes.

The code imports various functions and modules, including getSheet for retrieving data from a Google Sheets API and addIP for performing a DNS lookup, and defines a setupBackend function that uses these functions to set up a Google Cloud Backend. The setupBackend function takes link and domain as arguments, performs a series of operations to set up the backend, and returns the domain value.

google cloud commands

This script synchronizes a local directory with a Google Cloud Storage bucket, but only if a directory path is provided as input.

This script grants read access to all users on a specified Google Cloud Storage bucket and its contents, provided a bucket name is given as input.

This Bash script processes HTML files in a specified directory, sets their content type to "text/html; charset=utf-8", and uploads them to Google Cloud Storage.

This Bash script takes three command-line arguments and prints each one to the console on a separate line.

This script deploys a Node.js function to Google Cloud Functions, taking the function name as input and configuring it to be triggered by HTTP requests.

google rpc

This Firebase Cloud Function provides a remote procedure call (RPC) endpoint, allowing clients to execute functions defined elsewhere and receive results as JSON responses. It handles CORS requests, extracts function names from incoming data, and utilizes a custom getResult function to execute the requested logic.

This Firebase Cloud Function, using Express.js middleware, provides a remote procedure call (RPC) endpoint that accepts function names from requests, executes them, and returns the results as JSON responses. It also logs the results and handles cookies and CORS.

This code defines a Google Cloud Function that, when triggered, creates a copy of a "study sauce template" based on provided parameters and sends the result back to the requester.

This code provides a framework for creating cloud functions by defining a generic handler and a function to generate specialized handlers from code snippets.

This code imports modules and functions from Core.js and uses them to import specific functions from other modules, such as selectAst and makeHandler. The code then uses these functions to create a handler for a function named load ckeditor and leaves some commented out code that appears to have been used for testing or logging purposes.

google storage api

This code defines functions for managing Google Cloud Storage buckets, including listing existing buckets, creating new ones, and setting public access.

This code snippet is a unit test that verifies the functionality of a function designed to create a Google Cloud Storage bucket. It imports the function, sets up test parameters, calls the function, and asserts that a bucket was successfully created.

This code defines a utility function called streamToOutput that downloads a file from a URL or processes a stream and saves it to a local file. It handles directory creation and utilizes imported functions for file fetching and stream processing.

This code provides a utility function called fetchOrStream that downloads a file from a URL or processes an existing stream, writing its content to a specified write stream. It handles both scenarios using a single function and returns a Promise for asynchronous execution.

This code provides a utility function called streamToGoogle that uploads files or streams to a specified Google Cloud Storage bucket, handling bucket creation and metadata.

This code provides a function copyFileBucket that copies a file within a Google Cloud Storage bucket, utilizing Google Cloud APIs for authentication and file manipulation.

This code tests the streamToGoogle function, which uploads a file to Google Cloud Storage, by asserting that a valid URL is returned after the upload.

Core

aspects

This code defines a system for inserting debugging information into JavaScript code by modifying its Abstract Syntax Tree (AST) and injecting calls to a logging function.

The code imports functions from a Core module and uses them to conditionally transpile a code snippet, adding missing imports if a variable $ is defined. If the condition is met, the transpiled code is output as plain text with the added imports.

cache

compile

The logger function logs a message to the console and returns a closure that can be used to print additional messages, but with a prefix of "wtf? ". The test function demonstrates the usage of logger by calling it and logging "wtf? undefined" to the console.

files

The code is a Node.js module that generates a word cloud for a project. It uses the d3 library to convert a word cloud to SVG and the path module to work with file and directory paths.

The code consists of three main functions: icons, wordCount, and projectTree, which perform tasks such as iconizing file types, counting words, and creating a project tree. The projectTree function imports and processes modules to generate a formatted tree data.

The globMatch and glob functions recursively search for file paths matching a specified pattern in a project directory, and return an array of matching file paths. The functions handle various types of patterns, including directory patterns, and can be used to filter out ignored files based on the ignores array.

This JavaScript code utilizes the assert and glob modules to test the glob functionality by searching for files containing the string 'index' in the current directory and exports the results as a module.

This code imports modules and exports a listInProject function that searches for files in a specified directory using glob patterns.

This code exports an array of file patterns to be ignored by a tool, containing patterns for various file types and directories.

The code imports dependencies and defines a listProjects function that scans a directory for project files based on a regular expression pattern, returning an object with project paths and names. The function is then exported as a module for use in other JavaScript files.

This code is a Mocha test suite that uses the importer module to import two functions, listInProject and listProjects, which are used to test file system operations in a project directory.

The fixImports function resolves missing imports in a project by finding matching files based on their syntax structure and updating package.json to include new dependencies. It uses the fs, path, and importer modules to find code files, resolve imports, and update package.json.

This script imports dependencies, defines three functions (matchCurlyBraces, findLongFunctions, and their usage), and exports the findLongFunctions function as a module. The findLongFunctions function analyzes a project for long functions with excessive curly braces and lines of code.

The code declares variables and calculates the project path by concatenating environment variables. It then calls the findLongFunctions function to find and return potentially long functions in the project, handling the result with a then and catch block.

This JavaScript code imports modules, defines two functions (getDirectory and matchFilename) that handle directory and file matching, and exports them as a module. The matchFilename function filters files based on a pattern and returns a new path by joining the directory path with the file name, unless they are the same.

The mkdirpSync function creates directories and their parents synchronously if they do not exist, and throws any other error if an issue occurs. It ignores the EEXISTS error and throws others.

This code exports two functions, chext and chroot, which manipulate file paths by changing extensions and checking/file paths. The code uses regular expressions and the path module for these functions.

The mockTypescriptFs function creates a mock file system for TypeScript by combining an in-memory file system with the original Node.js file system, and returning a mock object that can be used to mock the typescript module. The function also uses mock-require to mock various TypeScript file system functions.

This code imports modules, performs file system operations, and processes Jupyter notebooks by reading, updating, and writing them back to the file system. It searches for notebooks in a specified project path and its subdirectories.

import

The code defines a function importNotebook to import a notebook, which interprets the notebook using the interpret function from the Core module, and then makes a module based on the notebook's language.

The code imports Node.js modules and defines two functions: getCached, which returns a cached module if it exists and is up-to-date, and makeModule, which creates and caches a new module object.

The provided code consists of two functions, runPythonModule and makePythonModule, designed to execute and manage Python modules in a Node.js environment. The runPythonModule function runs a Python module and captures its output, while the makePythonModule function creates a new Python module from provided code and returns its exports.

The makeESModule function creates an ES module from a given code string by first checking for a cached module, then setting up a context object, creating a new ES module instance, caching and exporting the module, linking and exporting dependencies, and optionally logging the process.

The code imports modules, defines constants, and constructs paths to DLL files, before implementing two functions: buildDLL, which compiles DLLs from code, and makeDLL, which imports and interprets code, then logs extracted namespace information to the console.

The code is part of a larger project that generates dynamic libraries (dylibs) from code, using Node.js modules and the ffi-rs library for interoping with Rust code. It defines several functions, including generateCallback and makeDylib, which are used to interact with and create dylibs.

The code consists of two functions: resultMarkdown which formats a single result in markdown, and displayCell which formats an array of results in markdown, and exports displayCell as a module.

The code creates a database using Fuse.js for tokenized search and a custom search function levSearch, and exports functions for database creation, querying, and cell lookup. If Fuse.js is unavailable, it uses the custom search function instead.

The code initializes and manages a cache system, loading data from notebooks and creating a database to store cache cells. It also provides a function to interpret queries, searching for files with matching extensions or cells in the cache database as needed.

This code provides functions to filter and search notebook files based on various queries and criteria. Functions support searching local files, filtering filenames, and querying a database or cache for matching notebook files.

The regexToArray function takes a regular expression and a string, and returns an array of objects containing information about the matches found. Each object contains the starting index, length, and optional group value of a match.

Executes an array of promises concurrently and returns the aggregated result.

Takes an array of functions or promises and returns a promise that resolves with a concatenated result.

The getCells function extracts notebook cells from a JSON-formatted notebook file based on specified cell types, and returns an array of notebook cells with additional metadata. It resolves the notebook path, reads the file, extracts kernel and cells, filters by type, adds metadata, and returns the modified cells array.

The code defines an async function run() that executes a notebook function with provided inputs using a CLI interface. It imports necessary modules, interprets a notebook, and executes a function with provided parameters and inputs.

intent

Project Overview
The jupyter_ops project is a comprehensive tool with various extensions, including notebook exporters, intent exporters, and databases, available for cloning or downloading from the GitHub repository https://github.com/megamindbrian/jupyter_ops. It can be used in multiple ways, including command line interface, marketing site intent.io, Jupyter notebooks, and various languages using native imports, with results displayed in different formats such as output, console, or notebook.

This code snippet appears to be a header or introduction to a larger section of text, providing information about a large language model named Llama and its capabilities. The code is purely documentary and does not contain any executable code, but rather serves as a heading to provide context and clarity.

This code snippet is documentation explaining the concept of "intent," a mechanism for providing instructions to a system, and suggests examples of its usage in various scenarios. It aims to guide users on how to effectively utilize "intent" for tasks like data processing and web interactions.

This code snippet declares a large language model named Llama that provides clear and concise answers in markdown format. The model's characteristics and functions are outlined, including the use of markdown for formatting text and the output format of the model's answers.

The code begins with a philosophical statement that a program's purpose is essential, and every child process must have a reason to exist for logging and monitoring. A defect is defined as any value other than 1, implying a deviation from the expected default state, possibly tied to the concept of purpose or ambition.

This humorous code snippet uses the famous "42" answer from The Hitchhiker's Guide to the Galaxy to playfully suggest that readily available information sources often provide the answers we seek, even if we don't already know them.

kernels

This code defines a Node.js module that exports a JSON interface object and two functions, wireJson and pathJson, which transform a kernel_json object into a new object that conforms to the JSON interface. The functions, wireJson and pathJson, modify the argv property of the kernel_json object to include specific elements, such as a connection file or a path, depending on their existence.

The code imports modules from the Core module using the require function and an importer object, and then uses the imported functions to create a JSON object and perform logging and interface output. The JSON object is created using the wireJson function and contains properties such as display_name, argv, and language, which are then logged to the console along with the result of an interface function call.

This code exports a set of functions that generate JSON objects for different kernel types used in kernel communication, including Python, Node.js, Jupyter Notebook, Bash, and Processing. Each function combines a base configuration with user-provided kernel JSON data to create a complete JSON object for use in kernel communication.

The languageInterface JavaScript object is defined with properties for mimetypes, names, file extensions, versions, and tool settings, then exported as a module using module.exports.

The code imports necessary modules and data, and defines the kernelInfoInterface object with various properties that provide information about a kernel. The nativeKernelInfo function takes a kernel_info object, extends it with additional information, and returns an object with language, kernel, and meta data.

The code imports modules and interfaces from a parent folder and defines a metaKernelInterface object with various properties. This object is then exported as a module, providing an interface for interacting with a kernel in a programming environment.

The code consists of two main functions, reassignProperties and nativeMetaKernel, which interact with a meta_kernel object to fill in properties, create a new kernel instance, and perform installation and initialization tasks. The code imports various modules and functions from the ../Core directory, utilizing an extend function, metaKernelInterface, and nativeMethods to create a new kernel instance and perform additional tasks.

This code defines a set of functions for a meta kernel that manages and interacts with other kernels, including initialization, installation, messaging, and execution handling. The module exports these functions, which depend on libraries such as mkdirp, fs, and jupyter-kernelspec, and can be used by other applications to interact with kernels.

This code defines a Node.js application with a socket-based kernel implementation, featuring meta-programming capabilities. It exports functions for initializing and responding to socket messages, and creates a new kernel instance from a provided meta_kernel object.

The code is part of a Node.js application that interacts with a meta kernel, providing various functions to execute commands, inspect the system, and handle messages, while also managing subprocesses and enforcing an interface.

The code consists of several functions that interact with a meta kernel, including executing commands, inspecting the system, handling messages, and managing subprocesses. The code also enforces an interface and contains TODO comments suggesting it is still a work-in-progress.

The code imports dependencies from a Core module and defines a testProcessKernel function that creates a new kernel object, performs some operations on it, and resolves a Promise with the kernel object. The testProcessKernel function is exported as a module and can be integrated with an external $ object, which is used to send its result or error to the outside.

This code imports modules and functions from a parent directory, sets up event listeners, and defines functions for initializing and responding to incoming messages in a meta kernel. The code exports the main functions (replMetaKernal, do_respond, and do_init) to be used elsewhere in the program.

This JavaScript module exports a testProcessKernel function that creates a new kernel instance and tests its functionality by executing a message and shutting down the kernel. The function uses the bashKernel function to create a new kernel instance and sets up a custom do_respond function to simulate a response to executed messages.

The code defines a JavaScript object wireKernelInterface that extends the properties of metaKernelInterface and implements required and optional kernel interface methods, as well as custom reply and protocol methods. The object is then exported as a module using module.exports, making it available for use in other parts of the application.

The code consists of four functions: status, onError, onStdout, and onStderr, which handle responses to kernel requests, error handling, and standard output and error messages, respectively. These functions utilize the do_respond and respond methods to send messages to the shell and iopub sockets, providing status updates, error notifications, and streaming data.

The provided code is a Node.js module for a Jupyter kernel that handles messages between the kernel and the front-end, including setting up sockets, sending responses, and handling incoming messages.

Alternatively, you can break it down into two sentences:

The code initializes the kernel by setting up sockets, binding them to the kernel, and sending an idle status message back to the front-end. It also handles incoming messages from the front-end, sending responses and handling different message types, including control, shell, and stdin messages.

The code imports various modules and functions, defines two helper functions addCB and wireKernel, and creates a wireKernel class that extends the kernel object with methods to handle requests. The wireKernel class and its interface are then exported as a module.

This code imports a module, declares variables and functions, and defines four functions (do_execute, do_display, do_shutdown, do_complete) that handle different types of requests, increment a counter, store functions and send responses, and execute promise chains to perform tasks and send replies.

This code sets up a system to handle different types of requests, including execution, display, shutdown, and completion, and defines functions to send responses and execute tasks accordingly. The code also uses promise chains to manage asynchronous operations and send replies to the kernel.

This Node.js module exports a function nodeMetaKernel that returns a meta kernel for Node.js, which has methods for executing, checking, and initializing code. The meta kernel uses Babel for code transpilation and sandboxed execution with vm.runInThisContext, and is wrapped with the socketMetaKernel function.

The code imports custom modules from the ../Core directory and uses them to test the functionality of a nodeMetaKernel module, including logging its output and that of its do_message method. The testNodeMetaKernel function is then exported as a module and run in a test environment where the $ variable is defined.

The code imports various modules and functions, including a utility function to parse version numbers, and defines a nodeKernel function that uses the imported modules to create a Node.js kernel. The nodeKernel function is then exported as a module, making it available for use in other parts of the application.

The bashKernel function creates a kernel for executing Bash code by initializing a kernel instance with a configuration that runs Bash code and echoes input, while the bashLanguage function defines a language interface object for Bash code with properties such as name, version, and file extension. The bashLanguage function uses Object.assign to merge the provided properties with a default language_info object.

This module exports four functions (parseMessage, hash, json, and collapseMessage) and several variables for message processing, formatting, and cryptographic operations. The functions can be used for tasks such as parsing messages, generating hashes, JSON-stringifying data, and collapsing messages into a compact format.

The setupSockets function establishes multiple sockets based on a provided configuration and returns a promise resolving to an object with established sockets. A related setupSocket function creates a single socket connection, also returning a promise that resolves to the established socket object.

languages

This is a MATLAB code snippet that contains a comment in Markdown format, indicating it is a sample definition for MATLAB.

The Node.js environment is defined by a set of global objects and modules, including process, require, module, and exports, which provide essential functionality for building applications. Core modules such as http, fs, and path offer additional capabilities, while tools like node and npm enable developers to run and manage their projects.

The code defines a transpiler composition function that loads user input into a tree data structure and generates code using a visitor and generator. It then exports composed transpilers for JavaScript to Java and JavaScript to Python, making it possible to translate JavaScript code into these languages.

This code offers functions for manipulating code represented as an Abstract Syntax Tree (AST), including adding, replacing, and removing nodes, with a focus on the transpile function for modifying the AST structure.

This code imports modules and functions from a Core file, and uses a replaceCore function to manipulate a JavaScript code string. The manipulated code is then conditionally executed using the mime function on a global variable $, if it is defined.

The code is using a CSS selector and the Cheerio library to parse HTML and select specific elements, specifically targeting an element named "importer" that is a direct child of an element with a type attribute containing "StaticMemberExpression".

Additionally, it loads an HTML document or string into a Cheerio object using the cheerio.load() function.

A variable named keywords is declared and assigned an array of 10 string values, including common programming concepts such as variable types and function calls.

This code reads an HTML file, parses it, serializes it to XHTML, and then parses the XHTML string as an XML document using various Node.js modules. It then uses an XPath expression to select specific nodes from the XML document and logs the selected nodes to the console.

This code provides a Babel plugin that modifies notebook code before transpilation, likely for a specific environment, by applying a series of transformations to the code.

The code imports the Babel compiler and a custom importer module, then uses the importer to specify a preset for Babel transpilation. A test code string with a missing import statement is transpiled using Babel, and the resulting code is logged to the console, where it is equivalent to a completed import statement.

The given code creates a mapping between PHP and JavaScript functions using two main objects, fromPhpToJavascript and fromJavascriptToPhp, which contain key-value pairs of function names and their corresponding implementations in the other language. The phpToJs array maps PHP functions to their JavaScript equivalents, and the jsToPhp array is created by reversing the elements of each inner array in phpToJs for the inverse mapping.

This JavaScript code defines a collection of 19 custom functions that mimic various PHP functions, allowing for PHP-like behavior in a JavaScript environment. The functions include array manipulation, string handling, and number processing, among others, with some notes on potential caveats and jQuery-specific functionality.

This code provides two functions, toLogString and toSafeString, that work together to convert a potentially mixed array of values into a human-readable string, handling different data types safely and consistently.

notebook

This code snippet is a placeholder comment reminding developers or users that a README file should be present in this location. It serves as a note for documentation purposes and should be ignored as it doesn't contain executable code.

This script automates the process of integrating JavaScript code generated from Jupyter Notebook cells back into the original notebooks. It finds corresponding JavaScript files, extracts their content, and replaces the code cells in the notebooks with the retrieved JavaScript.

This code defines a function replaceCore that rewrites JavaScript code to substitute calls to the "Core" module with calls to a custom function named importNotebook. It achieves this by analyzing the code's Abstract Syntax Tree (AST) and making targeted modifications.

This code provides a function to statically replace dynamic imports in code by analyzing the Abstract Syntax Tree (AST) and substituting them with predefined templates. It leverages a custom importer module and transpile function to achieve this transformation.

The code imports specific functions from a ../Core module and defines a string of JavaScript code, which is then used to replace imports using the imported replaceCore function. The replaced code is sent as a MIME message with a text/plain type, if the $ object is defined and has the required properties.

This code provides a function, addImports, that automatically inserts import statements into code based on the identification of global function calls. It leverages an AST parser, a cache of exports, and a transpiling function to achieve this.

This code snippet illustrates how a function called addImports can automatically insert missing import statements into JavaScript code, potentially aiding in code completion or refactoring.

This code provides tools for managing and exporting Jupyter Notebooks, specifically handling import dependencies and generating function handlers for deployment. It recursively analyzes notebooks, extracts import information, and likely produces output files containing functions based on the processed code.

This code snippet modifies JavaScript code by injecting caching logic into the AST (Abstract Syntax Tree). This optimization likely improves performance and reduces bundle size by caching imported modules.

The getExtension function determines the appropriate file extension for a code cell based on its language and type, such as .js, .md, or .py. This function is designed to be used in a notebook environment for organizing and processing code.

The niceName function generates user-friendly filenames for code cells by extracting information from the cell's content and applying formatting rules. This function is designed to create descriptive and consistent filenames for better code organization within a notebook environment.

The authorTemplate function creates a formatted header comment for code, including copyright details and markdown content, which can be easily reused in other code files.

The code prints the value of the global object to the console using console.log(global), which retrieves and displays the global scope in Node.js. The global object represents the global variables and functions.

patterns

The walkTree function recursively traverses an object or array, executing functions or evaluating expressions at each level, and returns the resulting value. It is exported as a module for use in other parts of the application.

This code appears to be a function that evaluates templates or expressions and returns an array of results, which can be either plain results or objects with an evaluate method, depending on the input settings. The function takes an array of strings or an object with settings as input and returns an array of results based on the provided settings.

The evaluateDom function evaluates a given XPath query or CSS selector on a DOM document, catching errors and handling various query formats and types, including those with wildcards. It returns an array of node values or a single value (number, string, or boolean) depending on the query type.

This code is a JavaScript testing module that uses the esprima and escodegen libraries to parse and generate code, and the assert library to make assertions on the code's syntax. The module exports two test functions, testProgram and testSelect, which can be used to test the code's structure and behavior.

The code imports a function from a Core module and assigns it to the getBookmarksFromTakeout variable. It then conditionally executes a block of code that accesses and prints the links property of a nested object if the $ symbol is defined in the current scope.

The promiseOrResolve function returns a promise that resolves to the value of a specified property on an object, using an optional callback function if the property is undefined, or resolves to undefined if the property does not exist.

Here is a brief explanation of the function's behavior in two sentences:

The function checks if the object has the specified property, and if so, returns a resolved promise with the property value if it's not undefined. If the property is undefined, the function returns a promise that resolves the property value using the callback function.

The code defines a class hierarchy in JavaScript using ES6 class syntax, with a parentClass and childClass that extend each other, but is wrapped in an if statement that checks if a variable $ is defined, which may cause issues.

This module exports two functions, extend and override, which create a new class by inheriting properties from a parent class, allowing for property overriding and extension. The functions are demonstrated through example usage and unit tests, showcasing their functionality and flexibility.

This code provides a collection of functions (typeErrorTemplate, standardCompare, arrayCompare, objectCompare, and interface) for comparing and validating values against expected structures, with the ability to handle type mismatches and loose comparisons.

The code includes several functions for comparing and validating values, including standardCompare, arrayCompare, and objectCompare, which compare arrays and objects against expected structures. The typeErrorTemplate function is used to create custom error messages for type mismatches, and the interface function provides a general-purpose comparison function.

The code demonstrates the behavior of the myInterface and overrideClass functions, showing how they merge and override properties of an object. It tests how these functions handle property overrides, logging different values to the console depending on the object properties and their order of creation.

pyimport

This code defines a module that provides a function called get_parameter_names, which takes a string of source code as input and returns a list of parameter names as strings. The function uses the ast module to parse the source code and extract the parameter names from the first function definition it finds.

The code imports necessary modules and initializes a dictionary to store module instances, and then defines several functions for manipulating URLs, importing notebook modules, and building dynamic libraries. The import_notebook function imports notebook modules based on a query string and context, and uses different methods to import code depending on the language of the notebook.

This code is part of a build system for dynamic libraries (.dylib) that imports necessary libraries, sanitizes URLs, and builds libraries using external functions and regular expressions. It involves interpreting code, extracting library information, compiling object files, and creating dynamic libraries using various tools and compiler flags.

This module includes three functions: get_questions extracts questions from markdown and source code, accumulate_markdown accumulates markdown leading up to code cells in a Jupyter notebook, and cache_cells generates cache entries from a Jupyter notebook. The module also defines a dictionary __all__ that specifies which functions are importable.

The code imports necessary libraries and defines a schema to build a Whoosh index, which is then used to store and retrieve data. It allows for searching by ID, filename, and fuzzy search by questions, with the ability to add more strategies as needed.

The get_cells function imports a Jupyter Notebook file, extracts cell metadata, and formats it into a list of dictionaries with language, filename, and unique ID information. The function takes two parameters: the notebook path and a list of cell types to extract, and returns the formatted list of cells.

The run_internal function is an asynchronous function that runs a notebook program by importing it, finding a function to execute, mapping user inputs to function parameters, converting types, and executing the function, while the run_async function runs this process asynchronously using asyncio.gather.

rpc

This code configures access control for Jupyter Notebooks by mapping specific functionalities to permission groups, determining which users or roles can access them. It uses a dictionary-like structure to define these mappings, enabling fine-grained control over notebook permissions.

This code categorizes code cells into predefined groups based on their language, content, metadata, and other factors, likely for organization or analysis within a code editor.

This code defines a function getPermissions that determines the permissions for code cells based on a search query, combining predefined public permissions with cell-specific classifications.

The groupPermissions function filters and organizes code cell permissions based on provided groups and optional search queries, allowing for fine-grained access control.

This code processes user commands, checks for duplicates, retrieves user settings, and prepares the command for potential execution, likely as a scheduled Google Calendar event.

This code manages the execution and storage of RPC commands as Google Calendar events, allowing for tracking and logging of command history.

The getResult function acts as a command dispatcher, verifying user permissions and extracting parameters before executing a requested command.

This code defines an environment configuration using Mustache templating, allowing for dynamic generation of settings based on environment variables.

This code converts an OpenAPI specification into a format compatible with Google Discovery, facilitating integration with Google APIs.

This code automates the process of fetching API discovery documents, converting them to a specific format, and saving them to local files. It is likely used to prepare API documentation or configuration for a system that relies on Google Discovery.

syntax

The code imports dependencies, including a selectAst function, and uses it to define a getRequires function that extracts require statements from JavaScript code. The getRequires function is then exported as a module, making it available for use in other parts of the application.

This code imports a getRequires function from a module, uses it to extract required modules from a JavaScript code string, and exports the result as a module. The code is conditionally executed when a variable $ is defined in the global scope, printing the expected output: ../Core, glob, and path.

The relativeImports function analyzes a code snippet to identify required modules, categorizing them into local, built-in, packages, and missing modules. It returns an object with arrays of these categories, using various checks and resolutions to determine the type and location of each module.

This code provides a module that exports a function coreDependencies which retrieves and logs package dependencies from notebooks in a project directory, excluding cache.ipynb.

The code imports dependencies, defines a testCoreDependencies function that calls and returns a coreDependencies function, and exports it as a module. The function is conditionally executed if the global variable $ is defined, likely for debugging or testing purposes.

The getExports function uses the selectAst function to extract exports and function names from the Abstract Syntax Tree (AST) of a given code, and returns a filtered array of unique function names. The function is then exported as a module, allowing it to be used in other parts of the application.

The code imports modules, defines a code snippet, and a function to test the behavior of getExports, which is expected to return a specific output when executed with the code snippet.

The code imports modules and defines a function testGetExports() to test the behavior of getExports() on a given code snippet. The expected output of testGetExports() is a specific string containing lines of code that modify the exports object.

The code defines a getParameters function that extracts function parameters from a given code string by using XPath queries to parse an Abstract Syntax Tree (AST). The function is exported as a module and can be used in other parts of the application to retrieve function parameters.

The code imports a module named importer and a function get parameter names from it, assigns it to the getParameters variable, and defines a function to test it. However, the purpose of the code is unclear without more context, but it appears to be a test case for the getParameters function.

The getImports function extracts import information from a given code string by parsing an Abstract Syntax Tree (AST) and selecting specific nodes using XPath-like query strings. It is exported as a module and returns an array of import information, removing duplicates in the process.

This code imports modules, defines sample JavaScript code, and tests a function getImports on various inputs, including a file and a string, and logs the results in a conditional block.

The wireKernelInterface object is a JavaScript implementation of the Meta Kernel protocol, defining properties and methods for handling various requests and replies, such as execution, inspection, and communication. The object is exported as a module using module.exports, allowing other JavaScript files to import and use it.

The code imports dependencies, defines a function to remove Unicode characters, and implements a treeToStr function to recursively convert a statement tree to a string, handling various data types and attributes. The treeToStr function traverses the tree, escaping special characters and including type attributes in the string representation.

The htmlToTree function takes an HTML string or tree as input and returns the corresponding tree structure by parsing and recursively processing its child nodes using the accumulateChildNodes function.

Alternatively, you can also summarize it in two sentences:

The htmlToTree function uses the JSDOM library to parse the input HTML and process its child nodes using the accumulateChildNodes function. It can handle HTML strings, arrays, and text nodes, and it recursively processes attribute objects to convert their attributes to properties.

This code imports necessary modules, defines functions for parsing and converting JavaScript code into HTML, and exports the testASTArray function for use in other modules. It also includes functionality for encoding HTML entities and assumes the presence of specific functions and an object ($) in the execution environment.

The code imports modules and functions from a parent directory, defines a function testHtmlTree to translate HTML into a tree-like structure using the htmlToTree function, and provides an example usage of the function by parsing HTML from a Google search page and logging the result to the console. The code also includes a conditional statement to check if the $ variable is defined, but no code is executed within the block.

The Node.js module exports two functions, selectAst and makeExpr, which are used for parsing and manipulating JavaScript code, and require dependencies such as esprima and escodegen. The functions work together to convert code to HTML, generate string representations of ASTs, and parse code to extract its structure and content.

The code tests a given code string by selecting specific HTML nodes and logging their properties to the console. The code uses several functions from the importer, which is imported from the ../Core module, to perform the necessary operations.

The code uses the acorn JavaScript parser to parse code and collect comments and tokens, and the ../Core module to export necessary functions. It exports the selectAcorn(descriptor, code) function, which parses the code, selects an AST, and converts it to a tree structure using the htmlToTree(call) function.

The code requires two dependencies (assert and importer) and defines two functions: makeCombinations, which generates all possible combinations of a given array of values, and makeXpaths, which constructs a specific XPath expression based on a given node's properties. The makeXpaths function uses the selectDom function to select the first occurrence of the classifiers from the node and constructs the XPath expression based on properties such as tag name, ID, class names, and index.

The code requires several modules and defines a function testMakeXpaths that tests the functionality of the makeXpaths function by generating XPath expressions for a function declaration node and asserting that its parent has an expected attribute. The function also logs the result, including an HTML representation of the tree structure if the $ variable is defined.

The minXpath function takes an array of XPath expressions and a context object, filters them to match exactly one DOM element, sorts them by length, and returns the shortest one. It is exported as a module named minXpath for use in other parts of the application.

The convertXPathToCss function takes an XPath expression and converts it to a CSS selector, performing replacements such as removing // separators, replacing contains with attribute selectors, and rewriting descendant combinators. The function returns the converted CSS selector.

The exprToXpath function takes in a code parameter and uses various dependencies to convert it into an XPath expression, including selecting function declarations, extracting parameter names, and creating minimizing expressions. This function is then exported as a module, making it available for use in other parts of the application.

The code checks if the global object $ is defined and, if so, calls the exprToXpath function with a callback that imports the importer object, which is then used to log an Xpath variable to the console. The replaceCore function is commented out, but its implementation is not provided in the code snippet.

The code is a Node.js module that exports a function testExpressions, which generates an XPath expression from the findImport function and searches for cells in the cellCache array that match the expression. If the $ variable is defined, the function is called and its result is sent to the $ object using the sendResult method.

This code snippet, likely written in JavaScript, declares a variable named STATEMENTS and selects elements in an XML or HTML document using XPath expressions that target elements with specific attribute values. The XPath expressions are combined using a logical OR operator to select elements with either "Declaration" or "Statement" in their type attribute.

The code var CALLS = defines a variable named CALLS and assigns it a string value. The string value is a JavaScript comment //CallExpression, enclosed in template literals to prevent it from being interpreted as a comment.

The code declares a variable named BRANCHES with a string value of //IfStatement|SwitchStatement, which appears to be a delimiter or pattern for identifying specific programming constructs. This variable stores a string that may be used to separate or identify different types of programming constructs, such as conditional statements and compound statements.

Databases

active directory

caches

database commands

This shell script uses awk to transform a MySQL dump file into a format compatible with SQLite, while preserving MySQL KEY clauses as separate commands. The script can be used by piping the MySQL dump file to the script, then piping the output to sqlite3, as shown in the example usage section.

docker ghost

git commands

These two Git commands apply staged changes to a repository, but the second command additionally resets the working directory and index before allowing for selective staging of changes.

This code snippet showcases two methods for applying patches in Git: using a visual diff tool (git difftool) and a text-based approach with the patch command.

These Git commands help you visualize and explore your project's commit history, with options for displaying a graphical representation, listing branches, and controlling the level of detail in the output.

These Git commands configure credential caching, allowing Git to store your login information for remote repositories in a cache for a year, saving you from repeatedly entering credentials.

This code automates the process of committing and pushing all changes in your Git repository to both GitHub (the default remote) and Bitbucket, even if there are errors pushing to Bitbucket.

This code snippet updates a local Git repository to match the remote repository, discarding any uncommitted changes and rewriting the commit history.

This code adds a remote repository ("MEDIA") as a submodule within the "PROJECT1" project, enabling version control and management of both projects together.

git

This code defines a function that renames files within a Git repository by first identifying files to rename using a pattern and then executing Git commands to perform the renaming. It utilizes a third-party renamer module to help with the file identification and renaming process.

This code snippet is a test case for the renameUsingGit function, aiming to rename all .css files to .scss within a specific Git repository.

This code analyzes a Git repository and generates a structured representation of its commit history, essentially creating a visual "tree" of branches and commits that can be used for visualization or further processing.

This code manages and visualizes Git branches by resetting them to their parent commits and generating SVG representations of the resulting tree structure.

This code defines a function that compares two specific Git commits within a project, outputs the differences to a directory, and utilizes Gulp and Promises for task management.

This code automates a Git rebase and npm package installation process by creating a calendar event that executes a script containing these commands. The event is configured to run within a specified project directory.

This code automates Git repository and build workflows using calendar events, triggering builds and tests while also updating existing events with the latest commit information.

This code provides tools for cloning and creating deep copies of Git repositories, allowing for isolated project environments for testing or experimentation.

The globBranch function automates the process of cloning a Git repository, resetting to a specific commit, and creating new branches based on modified files matching provided patterns. It simplifies the workflow of isolating and managing changes within a project.

This code provides utilities for interacting with Git repositories, enabling you to fetch remote information, retrieve branch names, and parse commit logs.

npm

This code updates dependency versions in a project's package.json file to match the versions actually installed, using information from npm list.

This code checks if a local npm server is running by sending a request to a specified host and port and verifying the response status code.

This code provides a customized npm execution function that allows for controlled npm command execution within a specific project directory. It handles installation, error management, and progress logging, making it a more robust way to interact with npm within a larger application.

raid

The mdadm create command is used to create a new linear RAID device, /dev/md0, using the device /dev/sdb1. The command is executed with options such as --level=1, -n 1, -f, and --raid-disk=2 to specify RAID level and disk configuration.

registry

The code queries the registry for the MSBuildToolsPath value in two versions (4.0 and 14.0) of the MSBuild tools path using the reg.exe command.

Alternatively, in two sentences:

The code uses the reg.exe command to query the registry for the MSBuildToolsPath value in two versions (4.0 and 14.0) of the MSBuild tools path. The expected output is the value of MSBuildToolsPath for each specified registry path.

sql to json

This code initializes a MySQL connection using credentials from a JSON file and defines several functions to interact with the database, including executing queries, showing tables, parsing data types, and selecting objects. The functions are designed to parse and manipulate data in a MySQL database, with features such as filtering out sensitive columns and converting data types.

sqlite node

The code imports Node.js modules for file system interactions (fs) and SQLite database interactions (sqlite3), and defines a database connection using a specified SQLite database file. It then reads and executes SQL commands from a separate file, passing the commands to the database instance for execution.

Docker

docker commands

These Docker commands build an image named "act-selenium", list all your local Docker images, and display information about all your Docker containers, both running and stopped.

This code checks for a running Docker container by name and, if found, stops and removes it.

This code cleans up a Docker system by removing all unused images, containers, networks, volumes, and build caches.

This code removes all Docker containers, regardless of their running status, by first listing their IDs and then using those IDs to target the docker rm command.

This code removes all Docker images by first listing their IDs and then using those IDs to target the docker rmi command.

This code forcefully removes all Docker images from your system by piping a list of image IDs to the docker rmi command.

This Windows batch script iterates through a list of all Docker container IDs and forcefully removes each container.

This Windows batch script removes all Docker images by iterating through a list of image IDs obtained from docker images -q and using docker rmi to delete each one.

This Windows batch script identifies and removes all dangling Docker images from your system.

To build Docker images, use the provided commands, such as docker build -t <image_name>:<tag> --target <stage>, to create images with specific tags. To push Docker images to a registry, use the docker push command with the image name and tag, such as docker push briancullinan/quake3e:<tag>.

docker demo

This code snippet determines the operating system and sets a variable notebook to the path of a corresponding Jupyter Notebook file for either Windows or macOS. If the platform is neither Windows nor macOS, it signals an error.

This code generates a Dockerfile for a Selenium environment with VNC support by converting bash commands into Docker RUN instructions and combining them with code retrieved from an external importer function.

dotnet

This Dockerfile uses a multi-stage build process to create a.NET Core image by first building the application with Mono and then building the.NET Core image with ASP.NET Core. The final image includes the published application files and exposes port 80 for the container to run.

install Docker on Mac

This code checks for the presence of Docker on the system by executing the docker ps command and signals completion with a message indicating whether Docker is installed or not.

This code installs the rimraf and JSONStream packages using npm and logs both the standard output and standard error of the installation process to the console.

install Docker on Windows

This code checks if Docker is installed by running the docker ps command and signals completion with a message indicating whether Docker is found or not.

This code downloads the "elevate" tool from GitHub, extracts it to a local directory, and signals completion of the process. It uses https to download the file, fs to write it to disk, and child_process to execute a PowerShell command for extraction.

This code downloads the Docker installer from the Docker website and saves it to the current working directory, notifying a task manager upon completion.

This code installs Docker on a Windows system, handling the installation process and configuring necessary firewall and network settings using elevated privileges.

This code installs NativeScript build tools on Windows using npm, leveraging elevated privileges and potentially making network configuration adjustments.

node install

This code sets up a development environment for NativeScript on a Debian system by installing Node.js, necessary packages, and configuring security settings.

This script updates package lists and installs a collection of development, networking, and system administration tools on a Debian-based system.

This Dockerfile builds a PHP 7.0 Apache image with additional dependencies and configurations, including installing Composer, configuring Apache, and generating a self-signed SSL certificate. It also sets environment variables and copies web content and configuration files to the image, ultimately creating a customized PHP development environment.

Exercises

falsey javascript

In JavaScript, an empty array [] is considered a truthy value, meaning it's treated as true in a boolean context, resulting in unexpected comparisons when using the loose equality operator ==. This leads to [] == true returning true and [] == false returning false.

In the given code breakdown, console.log() prints output to the console, while the OR operator (||) returns the first truthy value from its operands. In JavaScript, empty arrays ([]) are considered falsy values, whereas non-empty arrays (['not falsey enough']) are considered truthy values.

This line of code uses the logical OR operator (||) to evaluate two expressions, an empty string ('') and a non-empty string ('unempty strings'). Due to how JavaScript handles falsy values, it will always log 'unempty strings' to the console, regardless of the value of the first expression.

The JavaScript code console.log(0 || 1) logs the result of the conditional expression 0 || 1 to the console, which evaluates to 1 because 1 is the first "truthy" value encountered. This is due to the || operator's behavior of returning the first truthy value it encounters.

The provided code uses the logical OR operator (||) to return an object with a default property set to true if the left side (a null value) is falsy. In this case, the expression returns { default: true } because null is considered falsy in JavaScript.

The JavaScript code attempts to log the type of an undefined variable undef to the console, but throws a ReferenceError instead. When trying to log the result of the expression undef || {"too much": false}, it returns the object literal {"too much": false} to the console due to the undefined value of undef.

fizz buzz

This JavaScript code implements the FizzBuzz challenge, which prints "Fizz" for multiples of 3, "Buzz" for multiples of 5, "FizzBuzz" for multiples of both, and the number itself otherwise, from 1 to 100.

The isFib function checks if a given number is a Fibonacci number by generating Fibonacci numbers until it finds a match or exceeds the input number. It returns true if the number is a Fibonacci number and false otherwise, as demonstrated in the provided example usage.

The sortDesc function combines two arrays arr1 and arr2 and sorts the concatenated array in descending order. However, the code then attempts to check each element in the sorted array to ensure it is greater than the previous one, throwing an error if this condition is not met, which suggests a logical flaw in the code logic.

math

The code generates all possible permutations of an input array and combines them with operator combinations to create mathematical equations in both standard and nested formats. It uses functions such as spliceClone, permute, solve, and reduce to generate and evaluate these equations, storing the results in variables like permutations, operators, and equations.

python codekatas solutions

The palindrome(string) function checks if the input string, with all lower-case characters, is the same when reversed. It does this by comparing characters from the start and end of the string, working its way towards the center, and returns True if no mismatches are found.

The merge(a, b) function merges two sorted lists a and b in descending order into a single list, with a time complexity of O(n log n). It does this using a list comprehension that pops the largest element from either list at each iteration, as implemented by return [max(a, b).pop(0) for _ in a+b].

The last_word_length function takes a string as input and returns the length of its last word. It does this by counting non-space characters from the end of the string until it encounters a space.

The find_in_sorted function performs a binary search on a sorted list of numbers to find a target value, returning its index if found, and -1 otherwise. It uses a binary search algorithm to efficiently search through the list by repeatedly dividing the search interval in half.

The simplify_path function takes a Unix-style file path as input, splits it into tokens, and uses a stack to remove unnecessary directory references, returning the simplified path. The function handles various edge cases, including parent directories (..), multiple parent directories (...), and trailing slashes.

The create_max function takes an input number num as a string and an integer k as parameters, returning the maximum number that can be formed by removing digits from num and keeping at most k digits. The function uses a stack to iteratively select the largest digits from num until a maximum number of k digits have been chosen.

The code implements a singly linked list node class (ListNode) and a function (reverse_list) to reversely iterate through the linked list, swapping the next node reference, and returning the new head of the reversed list.

Alternatively, you could also condense it into two sentences:

The ListNode class represents a node in a singly linked list, with methods for initialization, string representation, and equality comparison. The reverse_list function takes the head of a linked list as input and returns the new head of the reversed list, achieved through iterative traversal and node reference swapping.

The ListNode class represents a node in a singly linked list with attributes and methods for initialization, string representation, and equality comparison. The reverse_list function is a recursive function that reverses a singly linked list by updating the next attribute of each node to point to the previous node in the reversed list.

The max_profit function calculates the maximum possible profit from a list of stock prices by iterating through the list and adding up the differences between each pair of consecutive prices. The function returns 0 as the total profit if the input list is empty, contains only one price, or has prices in descending order.

The subsets function generates all possible subsets of a given list by recursively building upon itself, removing and adding elements to create new subsets. It returns a list containing all possible subsets of the input list, including the empty set and the original list itself.

The string_permutations(s) function generates all possible permutations of a given string s and returns them in a sorted list. If the input string is empty, it returns a list containing an empty string, otherwise it recursively generates all permutations of the string.

The QuickSort algorithm is a divide-and-conquer sorting technique that uses the partition function to reorder an array such that all elements less than or equal to the pivot are on its left. The quicksort function recursively sorts the left and right subarrays generated by partitioning the input array until the base case is reached, where the subarray contains only one element or is empty.

The mergesort algorithm is implemented through two main functions: merge which combines two sorted lists and mergesort which recursively sorts a list using the mergesort algorithm.

The shortest_path function finds the shortest path between two nodes (u and v) in a graph g by performing a breadth-first search (BFS) traversal. It returns the path as a list of nodes if found, otherwise returns -1.

Frameworks

Angular 2

This code snippet, executed in a Bash shell, uses the Angular CLI (ng) to start the development server for an Angular application.

To start the Webpack development server, use the command webpack dev-server --inline --progress --port 9090.

The command npm run ng:build executes a script named ng:build in the project's root directory, equivalent to running ng build --prod --aot.

This code opens a new tab in the default browser with the specified URL (https://material.angular.io/components/category/forms) and sets the tab's height to 600 pixels and delays loading JavaScript by 2 seconds.

The routing constant is exported from the file, configuring the routing with the RouterModule from @angular/router. The routing configuration uses an array of routes and disables the use of the URL's hash for client-side routing.

This CSS code defines two styles for HTML anchor tags, one using a direct hex code and the other using a CSS variable for a more scalable and maintainable design. The direct hex code sets the text color to #fe5000, while the variable assignment uses a CSS variable @primary to achieve the same result.

Angular components

This code defines an Angular component for a search bar, including its template, styling, search functionality, and routing configuration, along with a module to encapsulate and share it.

This code defines an Angular service called SearchService that handles search requests by sending a POST request to a specified URL with the search query and returns an observable response.

This Angular component, ResultsComponent, displays search results, fetching them from a service and using Prism.js to highlight code snippets within each result.

This code defines a Socket.IO server-side handler that receives search requests, performs searches across multiple sources, and sends the combined results back to the client.

This code sets up a project environment by determining the user's home directory path, appending a project directory path, initializing a server, and establishing a connection to the server using Socket.IO. It then sends a "close" event to the server, likely to terminate the connection.

This Angular code defines an AuthModule that handles user login, including a login form component, routing, and authentication logic using an AuthService.

This Angular code provides an AuthService that handles user login by making a POST request to a server and returning an observable with the login result.

angular core modules

This code establishes a shared Angular module (SharedModule) that provides commonly used components, directives, services, and modules to other parts of the application, enhancing code organization and reusability.

angular render service

This code implements a server-side rendering engine for Angular applications using Express, allowing for pre-rendered HTML to be sent to the client. It leverages Angular's platformDynamicServer and renderModuleFactory to compile and render the application for a given URL.

angular-cli

This code snippet contains a history of Angular CLI commands used to generate various components, services, and modules for an application across multiple modules, including account, activity, card, emails, groups, and home. The commands cover a range of operations, such as generating modules, services, and components, with some commands creating nested components within modules.

build Angular components

This code provides a way to mock the Angular CLI (ng) within tests, allowing for controlled execution and simulation of file system interactions and TypeScript compilation. This enables more reliable testing of Angular projects.

This code provides a function to build an Angular application for server-side deployment using Webpack, incorporating project-specific configurations and gulp helpers. It automates the compilation process and returns the compiled server-side JavaScript code.

This code creates a new Angular project called "new-portal" using @angular/cli, generates an "AppServer" module, and prepares the project for building and serving. The code also outlines missing functionality, including building in memory, integrating a sockify server, accepting logins and encrypting passwords, and sending mock responses to test interfaces.

display angular

This code defines a function that extracts <style> and <script> tags from HTML content, processing links and scripts to include their content dynamically. It then combines the extracted styles and scripts into a single string and returns the result.

This code renders an Angular application within an iframe by combining rendered HTML, extracted scripts and styles, and dynamically loading additional JavaScript files. It returns a promise that resolves with the complete HTML containing the embedded Angular application.

This code is a JavaScript implementation that imports modules and sets up variables for a universal project, including a rate limit and file system module. It defines several functions for outputting Angular app code slowly, compressing code, and handling errors, and executes the main workflow by fetching Angular app code, compressing it, and outputting script pieces.

This code sets up an HTTPS server using Express.js, configures it to use a private key and certificate, and initializes a sockify server to handle incoming connections. It also imports specific functions from the Core module, injects new modules into the sockify server, and calls various functions to set up the search provider and selenium server.

The automock module is imported from a specific file path, allowing for code mockups to be created. The automock.mockValue function is used to create a mock value, which returns a function that logs its name parameter to the console when called.

How code should look

This code defines a function that checks if a user input contains the word "attachments" and logs the entire input if it does, suggesting a basic command interpretation system.

Jupyter language kernels

This code snippet installs and configures a Bash kernel for Jupyter Notebook, enabling users to run Bash commands within their notebooks.

This code installs and configures the IPython kernel for Python 2, enabling users to run Python code in Jupyter Notebook.

This code snippet provides instructions for setting up and installing the icsharp project on a Mac, requiring the user to first install Mono and then clone, build, and install the project using provided scripts.

This code breakdown lists four commands for navigating and running scripts in a Unix-like system, including changing directories, compiling C# code, running the Bash shell, and executing a shell script named build.sh. The commands assume a Unix-like system, such as Linux or macOS, and that the build.sh script is executable and located in the same directory.

The grep command-line utility is used to search for strings, with options such as -r for recursive search, / for file path separation, and --e/-e for specifying a search pattern. In this case, it searches for files containing the string 'xunit.runners'.

This code sets up a Ruby development environment with a specific Ruby version (2.4.1) using rbenv and Homebrew, including dependencies for building extensions and tools for working with ZeroMQ.

This code installs Jupyter Notebook and JupyterLab, enabling Python kernel support and configuring them for use.

To install TypeScript, you need to have Node.js and npm installed on your system, and then run the command npm install -g typescript to install the TypeScript compiler globally. To verify the installation, run the command tsc -v to check the version number of the installed TypeScript compiler.

To install Istanbul TypeScript, run the command npm install -g itypescript in your terminal, which installs the package globally on your system. This command uses Node Package Manager (npm) to install the itypescript package, a TypeScript plugin for Istanbul code coverage reporting.

autorewire

This code snippet ensures the underscore and underscore.string libraries are installed in a Node.js project by checking for their presence and installing them using npm if needed.

This code implements a basic JavaScript mocking framework called AutoMock that allows you to replace functions, objects, or properties with stubs during testing. It uses underscore for utility functions and tracks original and mock objects to prevent circular references.

d3 dates

This code sets up the foundational structure for a D3.js swimlane chart, defining scales, axes, and the basic SVG elements, but lacks the code to render the actual chart elements.

This code creates an interactive heatmap visualization that displays time-series data, grouping it by day and coloring each day based on the total time spent. It uses D3.js to generate the SVG elements and apply the color scale.

d3

This code generates an SVG image of a word cloud by using D3.js and the d3-cloud library to layout and style words based on their frequency. It takes an array of word objects as input and returns an SVG string representing the word cloud.

This code generates a tiered pie chart visualization using D3.js to represent hierarchical data, allowing for a clear visual representation of data structure and proportions.

This code block includes conditional statements, asynchronous function calls, and error handling using the $ object, which appears to be a utility or API object.

This code generates a basic pie chart using D3.js, taking data as input and returning an SVG representation of the chart with labeled slices.

This code prepares node and edge data for hierarchical visualization by establishing parent-child relationships and propagating branch information, effectively structuring the data as a tree.

This code prepares data and sets up the structure for a D3.js visualization of a hierarchical tree, likely representing a file system or organizational chart, but lacks the code to render the visual elements.

de-linting

This code provides a function delintCode that lints code using ESLint, optionally fixes identified issues, and returns both the original and fixed code along with linting results.

The delintCell function takes code as input and uses the delint library to analyze it for potential errors or style issues. It then returns the results of this analysis.

This code tests a de-linting service by exporting and deploying a module, de-linting a project directory, and verifying the process's successful completion.

This code provides a function to format code within a project directory using WebStorm and potentially import project settings from a .idea directory.

git repos

This code sets up a local Git repository for Selenium testing by either cloning an existing repository with the "Buy_funnel" branch or creating a new one if it doesn't exist.

This script automates the setup of a Selenium project by cloning a specific Git branch ("branch1") if it doesn't already exist locally.

This script clones a GitHub repository named "repository" into a local "project" directory, only if the "master" branch doesn't already exist locally.

This Dockerfile fragment sets up a basic SSH environment within a container by creating directories, copying a private key, and initializing the known_hosts file.

This Dockerfile sets up a container for running Selenium tests by copying project files, installing dependencies, and configuring the entry point script to execute the tests.

This code snippet configures npm to use a specified proxy server for package downloads and registry access, while also disabling strict SSL certificate validation.

This code snippet launches a Selenium container in the background, mapping necessary ports for access, and then displays a list of running containers.

This command runs a Node.js test suite within a Docker container named "selenium" by executing the test script using npm.

gulp

This Gulp script automates the replacement of a specific string within project files, likely for build or deployment purposes, and handles asynchronous execution with error handling.

This code snippet provides a function tasksToPromise that allows you to run a series of Gulp tasks asynchronously and obtain a Promise that resolves when all tasks are finished.

This Gulp script is a build script for an Angular project that automates tasks such as code replacement, file copying, and dependency resolution using various modules and functions. The script defines several Gulp tasks, including project relatives and server module, and uses the gulp-replace module to replace specific code patterns in JavaScript files.

This code creates a project directory and asynchronously executes a function called applyUniversal within it, sending the result or any errors to an external system.

This code sets up a Gulp task to continuously watch for changes in TypeScript files and automatically rebuild the project when changes are detected.

This code defines a function searchNotebooks that searches for text within Jupyter Notebook files in a project directory and returns a promise that resolves with an array of matching cells.

This code imports a module named Core to use its importer function, which imports another module named search notebooks using gulp to search for notebooks. The search result is then processed asynchronously, formatted as markdown, and sent to the user, with error handling if the search fails.

identity server

The code imports necessary modules, sets environment variables and file paths, and defines a helper function bashToRun to process code. The main function identityDockerfile creates a Dockerfile with a VNC connection by processing commands using the importer module and saving the processed code to the Dockerfile.

The DOCKERFILE variable is assigned the absolute path of the current working directory, where the module file is located. The identityDockerfile function is called with DOCKERFILE as an argument, likely to perform an operation related to the Dockerfile at that path.

This code defines a function getIdentityServer that automates the process of building, running, and managing a Docker container for an identity server, ensuring a fresh container is used each time.

The code sends an HTTP request to an identity server, handling the response and any errors through asynchronous operations and result/error handling functions. The process involves initiating the request, sending a request to the identity server, and then handling the response or error through a then block and catch block respectively.

jupyter interaction

This code snippet manages code execution and output display within a Jupyter Notebook environment, handling various output types and communication with the kernel.

jupyter

The CSS code sets font styles for text and code cells, using 'Roboto' as the primary font for text cells and 'Roboto Mono' for code cells, both with a font size and line height of 18 pixels. This overrides any other line height styles to maintain consistency across the cells.

jwt in csharp

The GetUrlContent method retrieves the content of a specified URL by creating a WebClient instance, reading from the URL using a StreamReader, and returning the content as a string. However, it does not handle exceptions that may occur during the process, so proper error handling should be implemented in a production environment.

karma template

This code automates the creation of Angular component test files by finding component .ts files, generating corresponding .spec.ts files using a template, and filling in component titles and import statements.

ngx-translate

The Node.js module getTranslations extracts translation keys and values from HTML files in a specified project directory, returning an object with flat translation keys as properties and arrays of values as values. The function uses glob to find HTML files, regular expressions to extract translations, and reduces the results into a single object for ease of use.

This code analyzes translation keys to identify misplaced, unused, and missing keys, helping ensure consistency and completeness across different language versions of a project.

node express

This Node.js code requires and imports several modules, including express, mime, and jsdom, to create a web server and interact with file systems and HTML documents. It also defines variables for output directories, port numbers, hostnames, and CSS queries, and logs a message to the console indicating that Express is ready.

This code sets up an Express.js server and creates a reverse proxy middleware to forward requests to a specified host. It also includes error handling and asynchronous function initialization, allowing the server to be started or stopped and handled accordingly.

The mime function is called with an object that contains a key-value pair for the MIME type text/html, which renders an HTML string that defines an iframe element. The iframe loads content from an HTTP URL specified with placeholders for a host and port variable, which are likely to be dynamically replaced.

This code initializes an asynchronous operation that makes a request to a specified URL, processes the response to extract image sources, and updates an array with the sources. It also includes error handling to notify the operation in case of any errors that occur during the process.

The code initializes variables, maps an array of image sources to promises, and resolves them to write response bodies to files. The execution of these promises creates HTML and HTML print strings, which are then processed by a utility or framework object to generate a Markdown string.

This code checks if a server variable exists and is not undefined, then calls its close() method if it does. It is likely used in a server or network context to properly close the server when it is no longer in use.

The code sets up an Express web server that uses CORS, body parsing, and the getResult function to process incoming requests, and returns a JSON response with a status code of 200 if successful. The server is configured to listen on port 8181, handles error and process events, and exports a start function that returns a promise that does nothing.

This Express.js server code sets up endpoints for OAuth2 authentication, Eloqua, and Zuora, including authorization, token requests, data imports, synchronizations, and exports. Although the code is functional, many endpoints return sample responses, simulating interactions with the respective systems without actual data processing or interactions.

The directoryToHtml function takes a directory path and optional parameters, and returns an HTML string representing the directory listing, excluding files starting with a dot or containing explicit content. The function uses fs and path modules to read directory contents and dynamically generate HTML links for files and subdirectories.

This Node.js module exports two functions: handleDirectory and BASE_DIRECTORY. The handleDirectory function handles requests to directories, resolving file paths, checking permissions and types, and generating HTML responses based on the file type and request authentication.

The code is divided into three main sections: Head, Body, and Styles, which define metadata, content, and CSS styles for the HTML document. It also integrates Amplitude.js to create a music player with various visualizations, such as album art, waveforms, and sliders, stored in HTML elements with data-amplitude-song-info attributes.

The provided HTML code has a basic structure consisting of a head section with metadata and styles, and a body section containing content such as a directory listing, links, and an image display. The code uses internal CSS styles to customize the appearance, as well as external stylesheet and script links, and includes placeholders for variables like session IDs and file URLs.

node simple-imap

This code establishes a secure connection to a Gmail inbox using OAuth 2.0 authentication and the IMAP protocol.

This code provides a function to programmatically search and retrieve emails from an IMAP server, allowing for filtering by sender, subject, date range, and mailbox.

This code snippet connects to an IMAP server using the node-imap-client library and handles both successful and error scenarios by sending appropriate results or errors to a client or other application component.

This code automates email command processing by retrieving emails, extracting commands, processing them, generating responses, and sending them back to the sender. It utilizes a custom importer module for various functions like email searching, sending, command filtering, and result storage.

This code snippet processes email messages, extracts their subjects and senders, and generates an HTML list of these details for display.

This code downloads email attachments, saves them to a local directory, and generates HTML and Markdown previews for display.

This code defines a reusable function sendEmail that sends emails via Gmail using Nodemailer, securely retrieving credentials and handling email sending asynchronously.

This code uses the imap-simple library to connect to an IMAP server and append a new email to the 'Drafts' mailbox. It requires the user's email address, password, and IMAP server hostname, and uses Transport Layer Security (TLS) encryption to establish a secure connection.

notebook extensions

promisify automock socketio

This code defines a function promisifyMock that creates mock implementations for asynchronous functions in a request object, enabling easier testing by replacing these functions with controlled stubs.

This code creates a Socket.IO server that uses a custom mocking system to replace dependencies with event-based communication, allowing for real-time data sharing between clients.

sockifyClient creates a mock Socket.IO client that intercepts function calls on a dependency object and emits events to a server, enabling testing of Socket.IO interactions in a serverless context.

This code sets up a Socket.IO server and client for testing, handling potential port conflicts by retrying server startup if necessary.

This set of functions provides functionality for file operations, including deletion, creation, reading, and closing, with associated error handling for potential issues such as permission problems or file non-existence. Additionally, there are methods for sending results or errors to the client, assuming that the $.sync() method has been called beforehand.

register jupter kernels

This script installs a C# kernel for Jupyter Notebook, allowing users to execute C# code within the Jupyter environment. It takes command-line options to specify user or system-wide installation and an optional prefix directory.

svn commands

This Docker command runs an svnserve container with automatic restart, mapping the host directory /Users/briancullinan/Documents/svn to the container directory, and exposing port 3690 for version control operations. The command uses the gcscaglia/docker-svnserve image with the latest available version.

test runner

This code defines a function testCells that executes JavaScript code within a Mocha testing framework, enabling the testing of code snippets or Jupyter notebook cells.

This code sets up a file watcher that automatically re-runs JavaScript tests whenever changes are detected in specified files, allowing for continuous testing during development.

twilio

This code defines a webhook handler for Twilio that creates a calendar event for each incoming text message.

The setReminder function schedules a Google Calendar event to send a Twilio message at a given time, handling OAuth authentication and calendar ID resolution.

This code defines a function sendTwilio that uses your Twilio account credentials to send text messages to a specified phone number. It takes the recipient's phone number and the message content as input and returns the unique identifier of the sent message.

This code defines a function that uses the Twilio API to make phone calls, taking a phone number and optional message as input.

zuora to eloqua

This code provides a set of functions to interact with the Zuora API, enabling users to initiate, track, and retrieve bulk data exports.

This code fetches a complete product catalog from the Zuora API, handling pagination to retrieve all products across multiple pages.

This code unit tests a module responsible for interacting with the Zuora API to initiate, monitor, and retrieve data exports. These tests use mocking to simulate API responses and verify the module's functionality in handling various export stages.

This code snippet constructs a SQL query to retrieve data about active subscriptions from a database, filtering by subscription status, date range, currency, and excluding specific rate plans and products. The query is incomplete and requires further development to include additional filtering criteria.

This code unit tests a function that generates a Zuora query for retrieving renewal data, ensuring it includes the correct start date based on the provided date range.

This code provides functions for authenticating with Eloqua using OAuth and making API requests, including a function specifically for checking the status of bulk imports.

This code unit tests an Eloqua import service, verifying its ability to obtain a valid OAuth token, create a bulk import instance, and successfully upload data to Eloqua. It uses Sinon.js for mocking dependencies and assert for making assertions about the test results.

This code processes subscription data by categorizing rate plans into product types and extracting account-specific information, including the latest charges and contact details.

This code snippet tests the accuracy of data mapping from Zuora to Eloqua, verifying that contact information and account details are correctly transferred between the two systems.

The getUniqueRatePlans function provides a sample dataset of account and subscription information, likely for testing or demonstration purposes. The data includes various details such as account IDs, contact information, rate plans, and billing details.

This code provides reusable templates for interacting with a data system, enabling bulk data imports, record creation, and potentially temporary imports. The templates use placeholders to dynamically reference fields and data sources.

This code tests a function that generates import definitions for Eloqua, ensuring it correctly includes the provided instance ID in the generated template. The test uses a placeholder instance ID and asserts that it is present in the resulting JSON output.

This code provides mock data and configurations for testing interactions with Eloqua's API, simulating real-world scenarios without requiring live connections.

This code provides functions to retrieve a specific custom data object and its corresponding import definition from the Eloqua API, likely for managing renewal-related data imports.

This code unit tests the eloqua existing import module, which checks for the existence of custom data objects and import definitions within the Eloqua API. The tests use Sinon.js to mock API responses and assert the module's expected behavior.

This Lambda function automates the export of data from Zuora to Eloqua, handling data mapping and upload to Eloqua's system.

This code uses unit tests to ensure that an AWS Lambda function correctly handles the process of uploading data from Zuora to Eloqua, including calling the necessary functions for data retrieval, mapping, and upload. The tests use sinon to mock dependencies and assert to verify the function's behavior.

This AWS Lambda function processes events to retrieve Zuora account data and bulk upload it to Eloqua, handling errors and returning appropriate responses. It requires additional development to implement features for import template creation and single record updates.

This code unit tests an AWS Lambda function responsible for syncing data between Zuora and Eloqua, ensuring it correctly calls functions to export data from Zuora and upload it to Eloqua. The tests use sinon to mock dependencies and assert to verify function calls and arguments.

This code provides a function to fetch renewal data from Zuora for a given time period and returns it in a usable JSON format. It leverages modules for querying Zuora, exporting data, and converting CSV to JSON.

This code unit tests the exporter module, which handles Zuora API interactions for data export, by mocking API responses and verifying expected behavior in retrieving queries and initiating exports.

This code provides a module for retrieving Zuora account information, including email addresses and the last four digits of associated credit cards, by making API calls and chaining promises to process the results. The getZuoraAccounts function is the main entry point, accepting a list of email addresses and returning an array of account details.

This code unit tests the accounts module's functionality to retrieve Zuora account information by mocking API calls and verifying that the correct query is sent to the Zuora API.

This code defines a function bulkUploadEloqua that securely authenticates with Eloqua, handles import definition setup, and then uploads account data in bulk to Eloqua. It's likely designed to be used within a Lambda function for serverless execution.

This code unit tests the bulkUploadEloqua function within the dataImporter module, verifying its interaction with the Eloqua API by mocking API calls and asserting the correct function execution order.

This code defines a set of test cases for a system integrating Zuora and Eloqua, focusing on data transfer and various subscription management scenarios. The tests cover data export, product matching, end-to-end data flow, and a range of user interactions with subscriptions.

This code calculates the total price of a subscription by retrieving product and pricing information from a catalog export and applying discounts, while also identifying areas for future improvement.

This code filters a set of Zuora subscription records based on various criteria, including Reseller of Record (ROR) and subscription details, and then calculates the total number of records that meet the specified conditions.

The code imports necessary modules and variables, including lodash, fs, and importer, and sets up a PROFILE_PATH variable to point to the user's home directory. It then defines a series of functions to query the Zuora API, including getContact, getAccount, and others, and provides an example of how to use these functions in an async function.

This code is a JavaScript program that performs conditional logic, retrieves configuration and token data from a JSON file, and makes API calls to Eloqua using OAuth authentication. The program handles both successful and error scenarios, logging responses or sending errors to the client as needed.

The code depends on various libraries and modules, including lodash, xlsx, and fs, and imports functions such as getZuoraMonth and getCatalog from other modules. The code initializes Zuora by checking for the existence of the zuora object, retrieving the current month, logging product rate plans, and catching any errors that occur during the process.

Frontends

blog

This code is written in a templating language, likely Handlebars, and consists of sections including inline comments, template inclusions, headers, loops, and embedded HTML content. It uses Handlebars helpers to conditionally render contents, iterate over a collection of objects, and display dynamic values from the objects in the collection.

brians resume

The getBookmarkFolders function retrieves bookmarks from Takeout, groups them by half-hour interval, reduces the grouped bookmarks to an array of unique folder names, and filters out duplicates. The function is exported as a module and executed asynchronously, with error handling, when a global object $ is defined.

The updateInterestPage function updates a Google Sheets document's "Interests" page by retrieving bookmarks, filtering them by categories, and updating the document's rows with the formatted data. This function is exported as a module and, if a $ object is defined, it is executed asynchronously, with results sent to $.sendResult and errors sent to $.sendError.

The messageHistory function is an asynchronous function that retrieves relevant history files, extracts keywords and timestamps, loads conversations, and asks the user for input to filter matching timestamps. It then logs the filtered matching timestamps, providing a list of related and unique timestamps that closely match the subject.

The messageResume function breaks down a large HTML resume into smaller sections, prompting the user for a short summary and related answers. It extracts text from the HTML, iterates over it in chunks, and returns an array of user responses joined by newline characters.

The messageFilesystem function is an asynchronous function that retrieves information about available projects and their related files by interacting with the file system and user input. It generates a prompt, filters related projects and files, and logs user responses and project information, although it has some potential performance and logging issues that should be addressed.

The code defines a function accessInternet that uses Selenium to extract articles from websites or search for knowledge on the internet based on user input, and summarizes the results using the summarizeArticle function.

The accessInternet function is an asynchronous function that takes a prompt model, session object, and prompt string as input and performs various tasks based on user input. These tasks include extracting articles from websites, searching for knowledge on the internet, and summarizing the results using the summarizeArticle function.

The askOtherLLMs function allows you to asynchronously ask other Large Language Models (LLMs) a question by specifying the model, session, and prompt. It currently returns an undefined asynchronous value.

The renderMessages(req, res) function is responsible for rendering a set of messages for a specific conversation based on user query parameters, by parsing dates, loading conversation files, filtering messages, and rendering them in a formatted format. It utilizes Markdown rendering with the remarkable library to format AI-generated messages, and limits the number of rendered messages to 25.

The code sets up an Express.js server that handles various routes for a chat application, including handling conversations, rendering messages, and serving static files. The startServer function is exported as a module, allowing it to be used in other parts of the application to start the server.

The renderHistory function retrieves and processes conversation history files from a specified project path, sorting and grouping the data by hour and identifying missing conversation summaries. It achieves this through file system operations, JSON parsing, and data grouping, but requires additional logic to be implemented for extracting time frames and creating date ranges.

The chat interface consists of a container element, off-the-record option, text entry section, and message display section, with a button to submit text and a link to scroll to a specific section.

The chat interface HTML structure includes a container element for the chat interface, a text entry section with a text area and send button, and a message display section. The interface also includes an off-the-record option and a link to scroll to a specific section when clicked.

This CSS stylesheet sets the basic styles for a chat application, including global styles, container styles, chat program styles, chat inner styles, messages styles, text entry styles, and drag and drop styles. It defines elements such as the container, chat inner, messages, text entry, and drag and drop areas with styles for layout, colors, and typography to create a visually cohesive chat interface.

This HTML-written resume, belonging to Brian Cullinan, highlights his contact information, personal details, and skills aimed at securing a full-time position as a residential field agent with the FBI. With over 24 years of programming experience, language skills, and business experience, Brian emphasizes his fast context switching, quick learning ability, and compassion in his resume summary.

convert spreadsheet

This code is a comment in a programming language, serving as a placeholder for a README file's documentation. It's a temporary note for developers to fill in later.

The code requires various modules, defines constants and functions, and exports an asynchronous function getSheet which retrieves or creates a new sheet based on its link and domain, and adds or updates the sheet's data in a Google Sheets document. The getSheet function uses other functions such as addSheet, updateRow, getInfo, and isInvalidDomain to perform its operations.

The code imports necessary functions from the importer module and defines an asynchronous importSheet function that retrieves information from a Google Sheet, including templates, properties, and resources. The function exports the importSheet function as a module, making it available for use in other scripts.

The code defines several functions for data comparison, filtering, and rendering, including compareLink for comparing data values with links, unfilteredData for logging and rendering original data, and filteredData for filtering data based on links and base locations. It also includes error handling to prevent multiple keys from being returned when data is not categorical.

The provided code appears to be part of a template rendering engine that processes Google Sheets data, utilizing functions from the importer object to load, process, and render templates. It includes functions like getTemplateProperties and matchSections that recursively process template properties and sections, respectively.

This module contains several utility functions that aid in data processing and rendering, including string manipulation, class extraction, dynamic property definition, and table row rendering. These functions provide functionality for tasks such as escaping special characters, defining properties, and rendering HTML tables with dynamic classes.

Five functions are provided in this module: safeName, toJSON, segment, wrapTemplate, and wrapTemplate (exported as the main module export). The wrapTemplate function is the most complex, creating a wrapped HTML template with metadata and rendering it with provided properties, while the other functions perform specific string transformations and handling.

The code is a JavaScript function named collectRoutes that collects and processes URL paths as part of a routing mechanism, using functions from the ../Core module to generate Google Sheets templates. The function iterates over the URL paths, removes duplicates, and creates new templates associated with each link, returning a promise that resolves when all links have been processed.

The code is a part of a web application or static site generator written in JavaScript, which transforms HTML templates into a format usable by a static site generator. It does this by selecting and processing image and URL elements, replacing text nodes with Markdown, adding IDs to headings and paragraphs, and using several dependencies such as stream and remarkable.

This Node.js script collects and renders template resources, streams the rendered template to Google Cloud, and returns a promise chain that resolves when the file has been streamed successfully, with environment-specific logic to determine which streaming function to use.

The code requires several modules for file system operations and importing functionality, and defines three main functions: initSync, copyAllFiles, and importTest. The importTest function imports sheet resources, filters out existing files, and returns a promise resolving with new files to be copied, using copyAllFiles and initSync functions.

The getTemplateByUrl function resolves a template for a given URL path by filtering a templates object based on the path segments, whereas the getEntryTemplate function resolves the entry template from the templates object by filtering for keys with a template property. The getTemplateByUrl function is exported as a module for use in other parts of the code.

The package.json file is a standard file used to manage dependencies and metadata of a Node.js project, providing information on the project's name, description, license, and dependencies. The project requires Node.js version 8 or later and npm version 4 or later, and its dependencies include Google Cloud APIs, a templating engine, and text processing libraries.

discord activities

This code appears to be a JavaScript snippet that handles events and requests when certain elements are clicked, and also fetches query parameters from the URL. However, it contains unused variables, potential mistakes in event listeners, and debugging statements that can be removed in production code.

This code manages the Discord OAuth flow by exchanging a handshake message, authorizing the user, and fetching an access token to authenticate with the Discord API. It uses event listeners to respond to messages from the parent window, sending POST requests and authentication messages to complete the OAuth flow.

The code imports Discord API modules, defines constants, and an asynchronous activityCommands function that manages bot commands for a specific guild, including registering, updating, and deleting commands.

This function is then exported as a module.

The getCommands function from the discord api package is imported and stored in the current scope using destructuring, allowing it to be utilized in the script. The getCommands function is then exported as a module, making it available for use in other JavaScript files.

This Node.js script manages a collection of Discord bots by launching and running multiple instances of a bot service, each with its own configuration and environment settings. The launchDiscord function allows users to specify which bot to launch by providing an index in the DISCORD_SERVICES array.

The code imports dependencies from a 'discord gateway' module and defines allowed user IDs, authenticates routes using a session-based system, and handles unauthenticated requests. The authenticateRoute function checks for a valid session and user ID, and exports the authentication function, as well as the INSTANCES and SESSIONS variables, from the current module.

The getToken function is an asynchronous handler that retrieves an access token for the Discord API using the client credentials flow, making a POST request to the oauth2/token endpoint and storing user information in the INSTANCES and SESSIONS objects. The function returns the access token data as a JSON response, setting various cookies for user authentication and storing a random nonce for future commands.

discord games

The code imports functions from the Discord API module and defines an array of command names (ALL_COMMANDS) that will be synced with the Discord API. The syncCommands function retrieves the list of commands from the Discord API, registers or updates commands as needed, and repeats this process for each command in the ALL_COMMANDS array.

discord imagine

The patchInteractionImageAttachment function is an asynchronous function that patches an interaction image attachment with the given prompt, image buffer, token, and content type. It returns a promise that resolves to the result of the patch request.

The code defines two asynchronous functions: doHallucinate and doImagineProxy, which generate images based on user input and interact with the Discord API using various imported modules and functions. The functions handle different scenarios, such as guilds, typing indicators, and rating checks, to ensure a secure and interactive experience.

The code defines functions related to Discord bot commands, including imagineCommands which handles image generation, and other functions for various interactions. The code uses async/await syntax and imports modules from a library called importer, but the purpose and specifics of some functions and variables are unclear.

The code defines an asynchronous doVision function that retrieves and describes images from URLs, including those from Discord channels, using a machine vision proxy. The function updates the interaction's content with the image description.

discord player

The playerCommands function is a JavaScript module that manages Discord bot commands by registering, updating, and deleting commands, as well as removing unused commands, using various functions from imported Discord modules.

The code sets up an Express app, importing necessary modules and variables, and defining several routes to handle requests, including token endpoint, root, and directory requests. The app also defines a discordLogin function to handle Discord login requests and generates HTML code using the directoryToHtml function, but does not start the server instance, which is stored in the server variable.

discord remote

The activityCommands function is used to manage bot commands for a specific Discord guild, registering or updating the remote command and removing any unnecessary commands. It retrieves existing commands, iterates over them, and returns an updated list of commands for the guild.

The code sets up an Express.js app, importing necessary modules and configuring routes for authentication, key tracking, and monitor management, as well as API endpoints for token retrieval and server monitoring. The app can be started or closed via the discordExpress and closeExpress functions, which manage the app's lifecycle based on the presence of participants in the activity and the server's running state.

This Node.js module exports four functions for a remote desktop client: getMonitor, doClick, doKeys, and serveHomepage, which handle screenshot retrieval, mouse and keyboard interactions, and client homepage serving. The module uses various imported functions and scripts to interact with the remote desktop and Discord authentication, and returns responses in formats such as PNG images, empty responses, and modified HTML code.

The HTML document has a standard structure with a <head> for metadata and external links, and a <body> for content, and is secured by a Content Security Policy (CSP) that specifies allowed sources for content execution. The CSS styles define the layout and appearance of the HTML elements, applying various properties to elements such as .container, .livedev, and specific HTML tags like h1, h2, img, and iframe.

This code adds event listeners to various elements on a web page to capture user interactions, including clicks, key presses, and button clicks, and sends POST requests to a server with session IDs and relevant data. The code also parses query parameters from the URL and sets the session ID property, and defines a function to retrieve checked input values from elements with the class "container".

discord tools

The doDiscordPdf function is an asynchronous module that generates a temporary PDF, patches a Discord interaction's image attachment with the PDF, and updates the interaction with an error message if the PDF creation fails. It utilizes various external libraries and Node.js modules, including discord api, collect all bookmarks, browser crawler tools, and domain cache tools, to retrieve a cache, perform a browser request, and interact with the file system.

The code imports various modules and defines functions to interact with the Discord API, interpret code, and summarize articles. It exports three main functions: doInterpret, doSystemUsage, and doSummary, which are used to provide user interaction and generate content on demand.

The doDistill function is an asynchronous workflow manager that interacts with LLM modules and the Discord API to generate and post responses to user prompts. It uses conditional statements to determine the next step in the workflow, selecting an LLM tool based on user input and generating a short or long answer accordingly.

The code imports necessary functions from various modules and defines three asynchronous functions (doEssay, doBusiness, and doStory) that generate content (essays, business plans, and stories) based on user input and return them as image attachments. Each function selects a prompt model, triggers typing, updates interaction, generates content using respective LLM functions, and returns the content as an image attachment using postMessageImageAttachment.

The doMesh function is a Node.js module that exports an asynchronous function for a Discord bot, generating an OBJ model and posting an image attachment to a channel. It selects a "Mesh" model, generates the OBJ model, extracts the data, and posts the image attachment after sending a typing indicator and updating the interaction.

The code defines an interaction module that exports three functions (doInteraction, doMention, and doPrivate) to handle different types of interactions with the bot, including greetings, mentions, and private messages. Each function uses a combination of imported modules and functions to generate responses, such as triggering typing, selecting models, and creating messages.

The code imports various modules to interact with the Discord API and language models, and defines a list of commands to be registered with the Discord API. The syncChat function synchronizes the chat commands with the Discord API, registering the hello and prompt commands if they are not already present, and mapping them to corresponding functions from the discord llm interactions module.

The code imports various dependencies and defines a list of available commands, then outlines four functions (doDeceive, doArgument, doMention, and doPrivate) that interact with these commands using various discord API functionalities. Each function generates a response to a user's prompt or message using either the llmDeceive module or the argueLlama function, with some functions creating new messages or updating interactions with the generated responses.

The code imports various Discord-related modules and defines an array of command names (ALL_COMMANDS) that will be registered or updated in the Discord bot. The syncTools function retrieves a list of commands, updates the bot's commands, and assigns functions to each command in the interactionsCommands object.

The postMessageImageAttachment function is an asynchronous function that posts a message with an image attachment to a Discord channel, using a POST request to the Discord API with a multipart/form-data payload. The function takes four parameters: prompt, buff, channelId, and content, and returns a promise that resolves when the request is complete.

discord voice

The code initializes a Discord bot, connects to a voice channel, and plays text-to-speech audio using the outetts library and FFmpeg, leveraging asynchronous programming for efficient execution.

The code sets up a Discord bot, connects to a voice channel, and utilizes FFmpeg for audio processing, allowing for text-to-speech functionality. It follows best practices for coding and documentation, utilizing modular and reusable design principles.

discord

The code establishes and manages a WebSocket connection to Discord, handling events such as connection opening, message receiving, and connection closing, with functions like authorizeGateway() and closeGateway(). It also includes functions like requestAuthQ() for making requests to the Discord API, although this function appears to be incomplete and intended to handle a queue of requests.

The code is a Discord bot implementation that initializes variables and functions for handling WebSocket connections, sending heartbeats, and processing gateway messages. The gatewayMessage function is the main entry point for processing messages from the WebSocket server, and it updates the sequence number, logs messages, and performs different actions based on the op value of the gateway message.

This module exports various constants and variables used in a Discord bot application, including environment variables, local filepaths, and token and secret retrieval. The module provides default values for these variables, and can be accessed by importing the module.

The code imports various Discord API modules and variables, then defines a triggerTyping function to send a POST request to a specified channel. Finally, it exports a comprehensive set of Discord-related functions and variables, including authorization, request, channel, guild, message, command, thread, and user functions.

The Discord API functions provided allow you to send messages, delete messages, update messages, get pinned messages, pin and unpin messages, and provide a convenient interface for authenticated requests to the Discord API. The functions are available for import and use in other parts of the application through the module.exports object.

This module provides a set of functions for interacting with Discord channels, including retrieving user and guild channels, fetching messages from a channel with pagination, deleting a channel, and exporting these functions for use in other modules. The functions utilize a request authentication function requestAuthQ and configuration variables imported from separate modules to perform their respective operations.

This code utilizes several functions to interact with the Discord API, including registering and retrieving commands, updating interactions and commands, and requesting authentication. These functions, such as registerCommand, getCommands, and requestAuthQ, send HTTP requests (GET, POST, PATCH) to the Discord API to perform their respective operations.

This code imports dependencies and exports three functions: userGuilds, getGuildRoles, and userConnections, which interact with the Discord API to retrieve user information, guild roles, and user connections, respectively. The functions are asynchronous and use the request function to make HTTP requests to the Discord API, with optional parameters for specifying user or guild IDs.

This JavaScript module provides four Discord-related functions: createThread, archivedThreads, activeThreads, and addThreadMember, which can be used to interact with threads in a Discord channel. The functions are exported as a single object and can be imported and used in other modules.

The code imports an authenticated HTTP request client requestAuthQ from the 'discord request' module and defines an async function getUser that retrieves a user's details from the Discord API. The getUser function is exported as a module, allowing it to be imported and used in other JavaScript files.

This code implements a timer system that stores and manages multiple timers with their corresponding expiration times, allowing for functions to be executed at specified intervals. The system exports three functions: timeout for creating promises that resolve after a delay, delay for waiting for a specified time, and wait for conditional waiting.

The code imports dependencies from discord API and utilities, and defines a deleteCommands function that retrieves a list of commands for a specified guild, skips exceptions, and deletes each command after a 3-second timeout. The deleteCommands function is then exported as a module for use in other applications.

documentation

This Node.js module exports a function getRpcSpecFromCells that generates REST API documentation from Jupyter notebooks by grouping permissions, iterating over cells, and creating method objects. It returns an object containing documentation details such as title, name, description, and parameters.

The code imports necessary functions and sets the environment to 'STUDY_LOCAL', then conditionally executes a block of code and finally calls main functions to convert notebooks to OpenAPI, extract RPC information, and test permissions. The main functions are executed within a promise chain that handles success and error cases.

The code is a JavaScript part of a larger project that manages and exports notebooks and functions, with the exportAll function being the main entry point. It generates an index page and a search page, but several TODO comments indicate areas that need to be implemented or improved.

Highlight.js styles and script, along with additional language scripts, are imported and initialized. The highlight.js plugin and all code in the document are then added and highlighted.

An HTML document is composed of a root <html> element, containing metadata in the <head> element and content in the <body> element. The document uses styles and variables to dynamically generate content and layout properties.

edit anywhere

This single line of code in a readme.md file contains a line comment indicating that the file is a placeholder or template, with readme.md being the file being commented on.

This code provides a reusable function to fetch a GitHub Gist by its ID using the Octokit library and handles both successful retrieval and potential errors. It is designed to be used in other parts of an application.

The code imports a module and a function (getGist) from it to read Gist files, and then uses conditional execution to call the getGist function with a specific Gist ID if a variable $ is defined. The result of the getGist function is sent using the $ object's sendResult method, and any errors are sent using the sendError method.

This code provides a function updateGist that allows you to update the content of a GitHub Gist using the Octokit library. It handles authentication (currently commented out) and updates the specified Gist with the provided file changes.

This code updates a GitHub Gist with modified web page content, likely scraped from a URL, and tracks changes made to the HTML.

This code prepares a Node.js environment to interact with Git using the wasm-git library, setting up a virtual filesystem and defining a function to map MIME types to icons. It also includes the beginnings of a function to retrieve a file tree from the Git repository.

The applyAcl function takes an ACL and an HTML document, makes elements matching the ACL selectors editable, and returns the modified HTML. This is likely used to control which parts of a webpage users can edit.

This code creates a dynamic web page that integrates web scraping, Git file access, and HTML manipulation, likely for web development or content management purposes.

This code modifies CSS stylesheets by adding a prefix to selectors, effectively renaming elements within the stylesheet for purposes like theming or component isolation.

This code snippet is a part of a web crawler or data extraction tool that loads and processes previously scraped web pages from a local cache. It parses URLs, matches them against cached data, and extracts stylesheets and images for further processing.

This code implements real-time saving for editable content on a webpage using CKEditor 5 and a custom server-side endpoint to handle the saving process.

marketing scripts

This code sets up a simple online checkout system using Stripe.js, allowing users to purchase products by clicking a button and securely handling payment processing.

The contactUs function handles incoming contact form submissions, stores the data in a Google Sheet, and redirects the user upon successful submission.

The package.json file defines the "SheetToWeb" Node.js project, outlining its dependencies, version requirements, and other metadata necessary for installation and management using npm.

opengl

The createWindow function initializes SDL and OpenGL, creates a window with the title "C++ SDL2 Window | OpenGL" and size 1000x800, and enables double buffering and a core profile, before returning the window ID.

This function uses SDL functions such as SDL_Init, SDL_GL_SetAttribute, SDL_GL_CreateContext, SDL_CreateWindow, and SDL_GL_SwapWindow for event handling and window management.

The code defines an asynchronous doFrame function that initializes and calls OpenGL functions, and an asynchronous testOpenGL function that creates a window and sets an interval to repeatedly call doFrame with the window object. The testOpenGL function is exported as a module.

This C++ code defines a 3D transformation system using SDL for rendering, which consists of classes and functions for representing points, vectors, and matrices, as well as applying transformations such as rotation, translation, and connection drawing. The system uses the SDL library for rendering and includes functions for calculating dot products, applying composite transformations, and getting rotation matrices.

qemu configs

The qemu-system-x86_64 command is used to launch a QEMU virtual machine with various settings and devices, including graphics, network, and storage configurations. By combining different options, such as CPU, memory, and device specifications, the command can be customized to create a virtual machine with specific hardware requirements.

The QEMU system emulation command utilizes the qemu-system-x86_64 emulator to create a virtual x86_64 system with various hardware components, including a graphics card, network interfaces, storage devices, and USB controllers. The command enables acceleration and allocates 3 GB of RAM to the emulated system.

This command boots a virtual machine with QEMU, allocates 3 GB of RAM, and connects to it with a Spice server using the Spice client, while also configuring various settings such as CPU, graphics, network, and disk image.

The command boots a virtual machine using qemu-system-x86_64 with specified settings for CPU, memory, and graphics. It then connects to the VM using the Spice client, allowing remote access and managing the VM through a graphical interface.

The provided command launches a QEMU virtual machine on an x86-64 system with 2 virtual CPUs, 3 GB of memory, and various devices such as ATI VGA graphics, virtio network interface, and a virtual hard disk file. The command is customizable and may require modification based on the specific environment and configuration, with notable options including -enable-kvm for KVM acceleration and -accel hvf for improved Intel system performance.

The provided code snippet contains two identical QEMU sessions with the same parameters, but the second session has an added option -cpu host which specifies that the virtual machine should use the host CPU. This option is the only difference between the two sessions, and it allows the virtual machine to utilize the same CPU model as the physical machine running the QEMU session.

This Bash script sets up a virtual machine using QEMU and a VNC viewer called spicy, allowing for remote access and control. The script can be run to launch a virtual machine with a VNC connection, automatically connecting to it with the VNC viewer.

This Bash script runs a QEMU virtual machine (VM) with various settings, such as enabling KVM acceleration, attaching a virtual disk, and allocating 1 GB of RAM. The script then connects to the VM using Remmina remote viewer, using the SpICE protocol over a specified port.

The QEMU command creates a virtual machine with a Windows 10 ISO file, enables VirtIO drivers and networking, and configures various device settings. The command also allocates 6144 MB of memory and synchronizes the VM's clock with the host system's clock.

qt

The code creates a simple Qt application that displays a window with three buttons arranged horizontally using a QHBoxLayout. The application runs until the user closes the window, at which point the event loop ends and the application terminates.

The textQtApp function asynchronously imports the 'qt qml widget' module and calls its main function with arguments 0 and an empty string. This function is then exported as a module, relying on the importer object to handle module imports.

The code initializes a Qt application by loading a QML string that describes a simple rectangle with a button, and then creates a QQuickWidget to host the QML content. The application is executed, and an alternative method is also demonstrated where the QML content is loaded from a data URL using the setSource function of the QQuickWidget.

study sauce

The code is a Node.js module for rendering and templating card data in a Google Sheets integration, utilizing ES6 syntax and promises for asynchronous operations. It consists of parsing card data, rendering cards with a unique document name, template data, and resources, and relies on external modules and functions for its functionality.

The code requires several modules, including path, fs, and google-auth-library, and imports custom functions from the ../Core module for interacting with Google Sheets. The authorizeProfile function is the main function, which handles OAuth2 authentication, user data retrieval, and redirects to the home page with the user link.

This code utilizes oauth2Client to interact with Google services, generating unique IDs and extracting user profile data, which is then stored in a Google Sheets document. It consists of four main functions: safeName for string modification, extractProfile for user data extraction, receiveCode for handling OAuth authorization, and exports the receiveCode and extractProfile functions.

The renderUser function is a Node.js module that retrieves and renders templates from Google Sheets for a given user, incorporating user-specific data and links. The function, which returns a promise, is part of a larger application that utilizes Google Sheets as a data source for templates.

This JSON configuration file contains metadata and dependencies for a project, including its name, description, license, and required Node.js and npm versions. It also lists dependencies on various libraries, including Google Cloud APIs, Markdown parsers, cookie management, and CORS.

The createStudyPack(email) and createCards(cards) functions both call methods on the jupyter_ops.studysauce object, but always return false. They appear to be primarily used for rendering and rendering cards, with the createCards(cards) function also manipulating an iframe element in the document.

Games

quake 3 commands

These commands allow you to remove the quarantine attribute from a file, install necessary headers for macOS development, and sign an application with a code signature. The commands are: xattr -d com.apple.quarantine /Applications/ioquake3/ioquake3.app, open /Library/Developer/CommandLineTools/Packages/macOS_SDK_headers_for_macOS_10.14.pkg, and sudo codesign --force --deep --sign - path-to-app.app.

To make two executable files (openarena.ub) on macOS accessible, two chmod +x commands are used to add execute permissions to the files located at /Applications/openarena-0.8.8/OpenArena.app/Contents/MacOS/openarena.ub and /Applications/openarena-0.8.8/OpenArena 0.8.8 r28.app/Contents/MacOS/openarena.ub.

This code is a series of shell commands used to launch and configure a Quake III Arena game server, including launching the game server, client, and dedicated server. The commands set various game settings, such as the game directory, mode, and configuration file, and execute specific maps and modes.

The docker run command starts a new container from an image, allowing interactive shell access, setting shared memory size, and mapping host ports to container ports. The command is used to run a Quake 3 game container with a bash shell, and remotely access it using a VNC key (VND7Z-M22AB-MQD7R-GAAKF-2B3EA).

This Bash script sets up a virtual Linux environment to run Quake III Arena and provides remote VNC access, initializing the X11 server and game with customized settings. The script also sets up signal handling, VNC server setup, and stores process IDs for later use, with cleanup functions to terminate all processes when complete.

Systemd service configuration files manage system services, including two specific services: quake3-proxy and quake3-server. These services are configured to restart automatically if they fail and are started when the system reaches the multi-user target.

The Quake 3 game launch script is a macOS script that utilizes the open command to launch Quake 3 games with various settings and configurations. The script includes common arguments such as setting game paths and enabling cheats, as well as game-specific settings like disabling triangle rendering and binding key commands.

The q3map2.exe/q3map2 tool is used to convert, optimize, and prepare 3D maps for Quake 3 Arena and Quake 2 games, with various commands available for tasks such as lighting, rendering, visualization, and meta information addition.

This collection of batch scripts and commands is used to preprocess and convert Quake 2 maps, including converting .bsp and .md2 files, normalizing vertices, and compiling hinted maps on both Windows and macOS platforms.

The provided code consists of a series of batch scripts and commands designed to preprocess and convert Quake 2 maps, including Windows and macOS versions. These scripts handle tasks such as converting .bsp and .md2 files, normalizing vertices, and compiling hinted maps, all essential steps in preparing Quake 2 maps for use.

These scripts and commands are used to convert various image files to TGA format, with options to handle different file types (PCX, JPG, JPEG) and color spaces. They use tools like wal2tga, convert, and find to automate the conversion process in Windows and Bash environments.

This script converts all .wav files in the current directory and its subdirectories to .opus format, using either a Windows command-line script or a Bash translation. The script can also be modified to simply echo the file paths instead of performing the conversion.

The provided list contains 11 Quake 3 Arena maps, each associated with a specific difficulty level or mode, including deathmatch maps and a few original maps created by notable authors. The list ranges from the introductory map "q3start" to more challenging maps like "q3badplace" and "q3darkzone" at difficulty levels 4 and 6, respectively.

The code executes the map2q3.exe file with specific command parameters to run a Quake 2 game, including the game map and settings. The executable file is located in the Z:\Downloads\map2q3\bin\win32 directory and utilizes game data and maps from Z:\.quake2\baseq2.

This document outlines three scripts: a CMake build script, an emcc compiler script, and a dpmaster script, which are used to build and compile various projects, including a C file and a Quake3Arena file. Each script utilizes specific flags and options to generate different output types, such as Unix Makefiles, WebAssembly code, and JavaScript files.

The command decompresses and extracts the contents of an archived shell script (linuxq3ademo.gz.sh) using the tail, gzip, and tar commands. The command assumes the presence of the linuxq3ademo.gz.sh file in the current directory and utilizes standard Linux toolset commands to perform the extraction.

This Bash script automates the conversion of Quake 3 map files (.bsp,.map) into other formats using tools such as quake3e_q3map2 and Blender. The script searches for files with specified extensions, checks for file existence and size, and performs conversions and recompilations as necessary.

quake 3 model conv

This Python script uses the Blender API to import 3D models from various formats (e.g.,.map,.bsp,.obj) and export them as MD3 files, with the option to scale the model down by 50% and export it with a "-half" suffix. The script performs these tasks using the Blender API's import and export operators, with some error handling for specific exceptions.

quake 3

This code extracts .pk3 files from .zip archives found in a specified directory, using a custom importer module for file listing and parallel processing.

This code automates the extraction of specific files, such as map files and screenshots, from Quake 3 PAK archives. It uses the node-stream-zip library to read the archives and extracts the desired files to specific locations.

This code snippet uses the node-stream-zip library to list all .bsp files found within a specified ZIP archive. It's designed to be reusable as a module within a larger application.

This code provides a utility for extracting files from Quake 3 game archives (.pk3 and .zip) by defining functions to handle individual archive extraction (readPak) and recursive extraction of multiple archives within a directory (extractPaks). This utility enables users to access Quake 3 game assets and resources.

This code creates an index of Quake 3 maps stored in .pk3dir archives, listing each map and its associated files. It generates a structured JSON manifest for each archive, making it easier to manage and access the maps.

This JavaScript code implements the core logic of the MD4 cryptographic hash function, processing 64-byte chunks of data through a series of rounds involving bitwise operations and constant additions. It does not, however, include the full implementation, which would also require initialization, padding, and finalization steps.

This code calculates the MD4 checksum of a ZIP archive, which can be used to verify file integrity or identify specific archives. It reads the ZIP file, extracts CRC values from its entries, and then computes the checksum using the MD4 algorithm.

This code calculates the CRC checksum of a specific Quake 3 game archive file and can be used to verify its integrity by comparing the result to known checksum values. It imports a checksum function, defines a test function, and exports the function for use in other parts of the application.

This code analyzes Quake game maps stored in JSON format, identifying and logging any missing textures for each map.

This code automatically converts images in a directory to PNG format for transparency support, while using existing JPGs for non-transparent images to maintain quality. It uses shell commands and image processing tools to handle the conversions efficiently.

This code converts audio files within a Quake 3 game directory to the Opus format using the opusenc command-line tool.

This code provides a function called convertScripts that copies specified file types from a given directory to a new directory within the same parent folder. It handles creating necessary directories and ensures each file is copied only if it doesn't already exist in the output location.

This JavaScript code defines a configuration object containing lists of file extensions and directory names commonly used in a software project, likely a game. This object can be used for tasks like file filtering, directory navigation, and asset management within the project.

This code snippet prepares to process a list of image files by importing necessary modules for file system interaction, pattern matching, directory creation, and file renaming. It utilizes a predefined imagelist containing details about each image to guide the processing steps.

This code defines a function convertMap that modifies Quake 3 map files by replacing entities, classes, and textures, scaling the map, and optionally adding a skybox. The modified map is then saved to a new file.

The scaleMap function modifies a Quake 3 map file by scaling the coordinates of its brush entities and origins by a specified amount. This is likely used for resizing or adjusting the scale of map geometry.

The translateMap function scales the geometry of a map represented in a text file by modifying brush and origin coordinates based on a provided scaling factor. This allows for flexible resizing and repositioning of the map data.

This code automates the process of standardizing or customizing textures in Quake 3 map files by replacing texture references with predefined replacements from a list of common textures and a custom override dictionary.

This code modifies a map file by replacing specific entity classes with predefined alternatives, allowing for customization and potential behavior changes within the map. It achieves this by using a mapping of old classes to new ones and performing a series of string replacements within the map file content.

This code standardizes entity references in Quake 2 map files by replacing generic entity names with corresponding model names from a predefined entities definition file.

This code analyzes Quake map files to calculate their bounding boxes and potentially adds skyboxes to them.

The addHints function modifies Quake 3 map files by adding boundary or hint information, either based on the map's name or a provided pattern, likely for purposes like skybox placement or collision detection.

This code analyzes Quake map files, extracts entity and brush data, and applies predefined hints or modifications based on the extracted information.

This code determines if a point is inside a polygon by checking if any ray originating from the point intersects the polygon's edges.

This code analyzes a Quake 2 map file to find missing sound files referenced by "noise" entities.

This code analyzes Quake map files to extract and list the textures used within them.

This code snippet parses a text file, likely a Quake game configuration, to extract shader definitions enclosed within curly braces. It returns an object mapping shader names to their corresponding definitions.

This code snippet automates the collection of all shader definitions from a Quake 3 mod directory, storing them in a JSON file for convenient access.

This code analyzes a Quake 3 map file, identifies used textures, locates them within the mod directory, and optionally organizes them into a specified output directory.

This code automates the disassembly of Quake 3 game files (QVMs) into human-readable format using the qvmdis utility, aiding in code analysis and reverse engineering.

quake3 server connector

The code imports the discordApi module and the authorizeGateway function, which are then used in the testMessage function to create and send a message in a Discord channel. The testMessage function is exported as a module, making it available for use in other parts of the application.

The code imports necessary functions from custom modules, then defines an asynchronous function syncCommands that synchronizes Discord commands by authorizing the gateway, retrieving existing commands, and registering or deleting specific commands based on their presence. The function uses functions like authorizeGateway, getCommands, registerCommand, and deleteCommand to perform these tasks.

The code imports necessary modules and defines constants and functions for interpreting and reading commands from Discord channels. It includes functions for interpreting a single command and reading all commands from specified channels, which can be filtered by channel ID, username, or empty string.

The code imports a module from Core.js and uses it to define a function testChannel that exports a function respondCommand from a module, which takes a channel argument and calls respondCommand with it.

The code is a Discord bot that responds to challenge commands, which trigger the launch of a Quake III Arena server with customized settings based on environment variables and command input. The bot uses regular expressions to parse challenge commands, connects to a Quake III Arena server via the serverApi module, and handles errors by displaying a message when no servers are available.

The code is a Discord bot written in JavaScript using the Discord.js library, which imports various modules for interacting with the Discord API and performing specific bot functions. The bot defines regular expressions, arrays, and a configuration function that extracts command content and attachments, computes a filename, and creates a new file based on the command's content and attachments.

The code initializes a UDP client socket, imports various modules, and sets up constants and variables, including an array to store master information and an object to store the next response. It defines two functions, mergeMaster and updateInfo, which are used to merge incoming master information and handle incoming UDP messages, respectively.

The testRcon function is an asynchronous module that retrieves a list of server masters, logs the list, sends an RCON command to the first master, waits for a second, and closes the UDP client, before being exported as a module. This function utilizes the serverApi to interact with the Quake 3 server, including importing and executing specific functions for listing masters and sending RCON commands.

These are four functions used to extract and parse information from server-related input strings:

• Functions getServersResponse and statusResponse extract server information, while infoResponse extracts server information in a simplified format. The function parseConfigStr parses configuration strings into objects.

The code defines a formatQuake3Response function that extracts and processes data from a Quake 3 server response string using regular expressions, conditional logic, and object manipulation, and returns an embed object or the original response string if data is not available.

Alternatively, you can condense it into two sentences:

The code defines a formatQuake3Response function that extracts data from a Quake 3 server response string using regular expressions and conditional logic.

The function returns an embed object with server information and player data if available, or the original response string if data is not available.

This JavaScript code is a Quake 3 server client parser that defines constants, functions, and variables related to the Quake 3 network protocol. It includes functions for parsing messages, generating checksums, and reading strings, as well as variables for entity states and other game engine-related data structures.

This Node.js code implements a Huffman coding compression and decompression library using a WebAssembly module, allowing for the compression and decompression of messages. The code includes functions for writing and reading bits to and from a memory array, as well as a function for decompressing messages using the Huffman coding algorithm.

The code imports various modules and defines two asynchronous functions, getServerChannel and updateChannelThread, which interact with the Discord API to fetch and manipulate channels and threads in a Discord server. The getServerChannel function finds a suitable channel based on a server's gametype and settings, while the updateChannelThread function updates an existing thread or creates a new one if it doesn't exist.

The code imports necessary modules, sets a default value for the DEFAULT_CHANNEL variable, and defines a list of server addresses to monitor. It then iterates over the server list, calls the monitorServer function for each server, and defines a startResponder function to start a command responder with a 1-second interval to respond to user commands.

This code is a Node.js script that establishes an SSH connection to a remote server, downloads a URL using wget, and modifies a file on the server by appending a specific format to the end of the file. The script also includes error handling and exports the remoteGet function for use in other modules.

The lookupDNS function, a JavaScript module, performs a DNS lookup on a given IP address and caches the result for subsequent lookups. It uses the dns module to asynchronously retrieve the DNS information, and returns the cached or newly looked-up result as a promise.

The removeCtrlChars function removes control characters and trims whitespace from a given string, returning the processed string. It uses regular expressions to match and remove control characters in specific formats, and is exported as a module for use in other parts of the application.

The code is a Quake 3 server management tool that queries server status, captures all stats, and logs chat messages. It uses various modules and functions to interact with the server, including the gamedig module for querying server status and the sendRcon function for sending RCON commands to the server.

The spectateServer function is an asynchronous function that establishes a connection with a Quake 3 server, retrieves game state and team information, and sets up a chat listener to forward messages to Discord. The function uses various imported modules to interact with the Quake 3 server, Discord API, and Discord gateway.

quakejs

This code creates a global object named master and makes it available for use in other parts of the application.

This code provides a module for interacting with Quake 3 servers, allowing you to connect to master servers to find available game servers and retrieve detailed information about specific servers.

This code provides functions to parse various types of responses from a Quake 3 server, extracting information like server details, player lists, and game state.

This code provides utilities for encoding and decoding out-of-band (OOB) data, a method used to send special instructions or metadata within a network stream.

This code acts as a Quake 3 server browser, connecting to a master server to retrieve a list of servers and then scanning each server for detailed information. It logs the server details and scanned information, and handles connection errors by attempting to reconnect.

Google

google calendar data

This code retrieves Google Calendar events matching a specific query ("study sauce") between two dates and then summarizes those events, sending the result to a client.

This code defines a function that converts a Chrome-specific date format (microseconds since a specific epoch) into a standard JavaScript Date object. It's designed to make working with Chrome's date representation easier within a JavaScript application.

This code extracts structured bookmark data from Chrome's exported HTML files found in Google Takeout, enabling programmatic access and manipulation of the bookmarks. It uses a custom DOM parsing function to navigate the HTML structure and retrieve relevant information about each bookmark.

This code retrieves and processes today's browsing history from a Chrome SQLite database, likely for analysis or reporting.

This code extracts bookmarks from a Google Takeout file and sends the extracted data to another system for further use.

This code synchronizes your Chrome browsing history with a Google Calendar, creating time-based events for each bookmark folder. It groups bookmarks by half-hour intervals and generates calendar events with summaries and descriptions based on the bookmark data.

This code synchronizes your Chrome browsing history from Takeout files into a Google Calendar, creating a visual timeline of your online activity grouped by half-hour intervals.

This code automates the process of syncing your Chrome browsing history and bookmarks with Google Calendar by downloading, extracting, and processing your Google Takeout archive.

This code synchronizes Chrome data and sends the outcome (success or error) to a client application.

google calendar graphs

This code retrieves events from a Google Calendar, filters them based on a query, and creates a line graph visualizing the dates and durations of the filtered events.

This code searches Google Calendar for events matching given keywords and generates a heatmap visualization of the results, showing the frequency of events over time.

This code creates an interactive swimlane chart visualizing Google Calendar events grouped by search query, allowing you to see the schedule of events for each keyword over time.

This code analyzes Google Calendar events based on provided search queries, calculates the frequency of events for each query, and visualizes the results as a pie chart.

google calendar

This code provides a function to authenticate with the Google Calendar API, handling both existing tokens and OAuth 2.0 authorization for new tokens.

This code retrieves and processes a list of events from a user's Google Calendar, handling authorization, date corrections, and pagination.

This code retrieves upcoming events from a Google Calendar, parses parameters from their descriptions, and prepares them for task execution.

The code defines a test suite for a "calendar service" using the describe function, which includes a test named "should list events from around today" that asserts an array of events is not empty. The test logic involves calling two functions, correctCalendarId and listEvents, with specific parameters to retrieve a list of events around today.

The correctTimeLimits function converts natural language date and time expressions (like "tomorrow morning") into standardized ISO 8601 format for use with APIs or systems requiring a specific date format. It achieves this by using the chrono library to parse the natural language and ISODateString to format the dates.

The correctCalendarId function determines the appropriate Google Calendar to use based on a provided calendarId, handling cases where the ID is undefined, "primary", or needs to be resolved from a list of available calendars. It fetches the calendar list if necessary, selects a matching calendar, and returns the modified options object with the correct calendar ID.

The getDaysEvents function retrieves events from a specified Google Calendar for a given day, utilizing a cache to improve performance and efficiency. It parses the input date, constructs the date range, fetches events from the API, and returns a filtered list of non-deleted events.

This code manages Google Calendar events, likely by updating existing events, merging information, and identifying duplicates.

This code creates a function that simplifies the process of adding new events to a Google Calendar, handling calendar ID validation and API calls.

google contacts

This code fetches contacts from Google Contacts using the Google People API and provides a way to search for specific contacts by name or email address.

This code analyzes a user's Google Contacts to categorize them based on their membership in various contact groups, determining both contact frequency and group affiliations.

The code imports modules from a main module, initiates an asynchronous execution context, and uses promise handling to execute and process results from a getSettings function. The getSettings function is called with an email address and returns a promise that is handled with .then for successful results and .catch for errors.

google drive

The code requires various modules and defines several variables for interacting with the Google API, specifically the Google Drive API. It includes a function called authorizeDrive that authenticates with the Google API using a credentials file and returns a client instance for the Google Drive API.

This JavaScript code uses the Mocha testing framework to test two functions, listDrive and insertPermission, which interact with the Google Drive API. The test calls listDrive to retrieve files, filters the result to include only "Untitled" files, and then concurrently calls insertPermission for each of these files with a specific email address.

The listDrive function is a Node.js module that exports a single function, which returns a list of files from Google Drive after authenticating with Google Drive using the authorizeDrive function. The function retrieves the list of files using the files.list method and returns an empty array if no files are found.

The insertPermission function, located in a Node.js module, takes a file ID and a user's email address as input and returns a promise that resolves to the ID of a newly created permission. The function authorizes access to Google Drive, creates a new permission on the specified file, and extracts the permission ID from the response before exporting it as a module for use elsewhere.

The createSheet(email) function creates a Google Sheets document, inserts permissions for two emails, and exports it as a module, using the authorizeSheets and insertPermission modules to handle authorization and permission insertion.

The code imports a function createSheet from a Core module to create a Google Drive sheet, and then writes a unit test to verify that the function successfully creates a sheet with a given email address.

The copyFile function copies a file in Google Drive by its ID and assigns a new title, and returns the ID of the copied file. It uses the drive.files.copy method and the authorizeGoogleDrive function to authenticate and perform the file copy operation.

The code imports dependencies and creates a google object to simplify access to Google APIs, then defines two functions: listDriveFiles to list files in a specified Google Drive folder, and listDrive to list files in the root folder. The listDrive function is exported, and an optional section allows it to be executed using a $.sendResult method in a testing or debugging context.

The code imports necessary dependencies, sets up constants for Google Drive authentication and file paths, and defines two asynchronous functions: convertGoogleDoc to convert Google Docs to various output types and downloadDocs to download Google Docs from a specified folder. The code uses Node.js modules such as path, fs, and google-auth to perform tasks, and includes error handling mechanisms to prevent file corruption or security issues.

This code defines an HTTP function named getSignedUrl that generates a signed URL for a file in Google Cloud Storage, allowing a user to upload a file to the specified bucket and file name. The function takes a POST request, retrieves the user's authorization (TODO), and creates a temporary upload URL with a 5-minute expiration time.

The copyStudy function duplicates a Google Drive file named "Study sauce template" and grants permissions for a specified email address. It achieves this by listing files, copying the file, inserting permissions, and retrieving a sheet identifier, before returning the new file ID.

The code imports necessary modules and defines a copyMarketing function to copy a Google Drive file named "Marketing site" and grant permissions to a specified email address. The function executes a sequential workflow of listing Google Drive files, copying the file, inserting permissions, and retrieving a sheet identifier (although the latter's purpose is unclear).

google maps

This code uses the Google Maps Places API to find places near a given location or by name, returning a list of matching results.

The code provides a function called placeDetails that retrieves detailed information about a Google Places location using its ID and your Google Maps API key. It utilizes the request library to make an API call and returns the parsed JSON response containing place details.

This code uses the Google Maps Geocoding API to convert an address ("Kazimierz World Wine Bar") into geographic coordinates (latitude and longitude). It then handles the API response, likely sending the results to a user interface or another part of the application.

This code efficiently retrieves geolocation data for a list of destinations, leveraging a cache to speed up subsequent requests and reduce API calls.

This code fetches and processes depth map data for a given Google Street View panorama, enabling applications to access 3D information about the captured environment.

This code fetches and assembles a panoramic image from Google Street View, allowing for dynamic display and manipulation of street-level imagery.

This code downloads a Google Street View panorama, extracts its depth map, and generates a grayscale image representing the depth information.

google scheduling

This code snippet manages and visualizes Google Calendar events, allowing for batch retrieval, event time adjustments, and potential heatmap-based visualization.

This code generates a heatmap visualization of Google Calendar events based on specified keywords, calculating the total time spent on those events. It uses the Google Calendar API to fetch events, calculates event durations, and visualizes the results using a heatmap.

This code searches a Google Calendar for events matching given keywords and logs the summaries of the found events. It then sends the results (or any errors) to an external system for further processing.

google search api

This code defines a function that performs custom Google searches using the Google Custom Search Engine API, handling authentication and returning the search results data. It's designed to be reusable in other parts of an application.

This code performs a web search using a custom search engine and sends the results (or any errors) to an external system for further processing. It uses promises to handle the asynchronous nature of the search operation.

This code configures authentication with the Google Custom Search Engine API by locating credentials and defining the necessary scope, providing a function to obtain an authorized client for API requests.

google sheets

This code analyzes a Google Sheet document to identify and categorize its sheets as either templates or data sheets based on their titles. It then returns an organized object containing these categorized sheets.

This code snippet is a unit test that verifies if a function called getTemplates successfully retrieves at least one template from a specified Google Sheet. It uses assertions to check the result and includes optional logging for debugging.

The getInfo function takes a Google Sheet URL, authenticates with the Google Sheets API, and returns a structured object containing information about the spreadsheet and its sheets. This function is designed to be used by other parts of an application to access Google Sheet data.

The getDataSheet function retrieves data from a specified worksheet in a Google Sheet and converts it into a structured array of objects. This function is designed to be used by other parts of an application to easily access and work with Google Sheet data.

This code defines a function getRows that retrieves data from a specified worksheet in a Google Sheet, handling authentication and API interactions to return the data as an array of rows.

This code snippet is a unit test that verifies the ability to retrieve and process data from a specific Google Sheet using functions from a local module. It asserts the existence of a data sheet and checks if the processed data array contains at least one element.

The addRow function adds a new row to a specified sheet in a Google Sheet by leveraging the updateRow function from a local module. It takes the sheet URL, the new row data, and the sheet number as input.

The getSheetByName function efficiently retrieves a specific worksheet from a Google Sheet by name or index, utilizing caching to optimize performance. It handles both direct worksheet objects and spreadsheet IDs with worksheet names or indices as input.

The updateRow function updates a specific row in a Google Sheet based on a matching condition, utilizing helper functions for data formatting and range calculation. It leverages the Google Sheets API to perform the update and returns the modified row data.

This code snippet is a unit test that verifies the functionality of a function responsible for adding a new row of data to a specified Google Sheet. It asserts that the function successfully adds a row by checking if a row is returned after the function is called.

This code sets up authentication with the Google Sheets API and provides a function, authorizeSheets, that returns an authorized client for interacting with Google Sheets securely.

Languages

antlr

This line of code is a remark in a Markdown README.md file. It is a placeholder for actual documentation or content.

The selectCode function is an asynchronous function that detects the language of a file, parses it using ANTLR, transforms the parsed output into HTML, selects specific DOM elements, and returns the result as a string.

The selectCode function is an asynchronous function that performs language detection, ANTLR parsing, and HTML transformation on a given file. It catches any errors that occur during the parsing process and returns the result as a string, along with an error message if an error occurs.

This JavaScript code imports necessary modules, defines an asynchronous function testAntlr that interprets and generates type information from a code snippet, and writes the result to a file named tree.json. The function is exported as a module and can be executed asynchronously using the $.async() function, with its result handled by the $.sendResult or $.sendError functions depending on its success or failure.

This code is designed to parse a directory structure for grammar files and extract language information for a parser generator tool, likely ANTLR. It utilizes two key functions: findGrammars(directory) to recursively extract language information from grammar files, and getParser(language) to search for corresponding parser files.

This JavaScript code appears to be part of a parser or tree-traversal function that handles tasks such as special character handling, filtering object properties, and converting a tree-like data structure to a string representation. The main function, treeToStr, recursively traverses the tree, extracting information from statement objects and using parser objects to resolve rule names and input strings.

This code defines four functions for working with Abstract Syntax Trees (ASTs) generated by the ANTLR4TS parser generator, including functions for converting object types to strings, creating generic tokens and contexts, and generating generic visitors. The code exports a module containing a generic visitor function.

The GenericVisitor class contains methods for extracting specific information from the abstract syntax tree (AST) of a programming language, such as identifiers, properties, types, and binary expressions, but three of the methods are currently empty and unused.

The antlrToESTree function converts an ANTLR-generated tree into an ESTree (ECMA Script Abstract Syntax Tree) by performing various operations such as node replacement and logging. It uses functions like selectDom, treeToHtml, and replace to manipulate the tree and create a new ESTree representation.

The code imports modules from the ../Core directory and uses the selectAst function to select a part of the Abstract Syntax Tree (AST) based on a specific pattern, then logs the resulting HTML tree to the console. The code expects to receive a specific output in the form of a JSON object representing the AST node, with three different expected outputs shown for different types of AST nodes.

The ext_to_lang object is a lookup table that maps file extensions to their corresponding programming languages, with 61 entries defined.

The ext_to_lang object is a data structure that contains a list of key-value pairs, mapping file extensions to programming languages. With 61 entries, this object can be used as a lookup table to identify the language of a file based on its extension.

The generateAntlr function is an asynchronous function that performs a series of tasks including globbing grammar files, compiling and transpiling them using different commands and tools, and handling potential errors. The function is exported as a module, allowing it to be imported and used in other parts of the application.

balanced

The balanced function identifies and extracts a balanced substring within a given string, delimited by two specified markers, a and b. It handles potential nested delimiters and returns information about the balanced substring's position and content.

bison

This is a placeholder for project documentation in a README.md file.

This code provides a utility for selecting and manipulating code structures based on a grammar and a selection descriptor, likely used in a larger code analysis or transformation tool. It parses code, allows for querying specific parts using a descriptor, and converts the selected code into a string representation.

This JavaScript parser, created using the Jison library, takes an input string and generates an indented Abstract Syntax Tree (AST) from it. The parser defines a grammar and uses a parser instance to parse the input string, resulting in an AST with a specific structure, including a root node hex_strings and child nodes representing hex strings.

csharp

The code defines a class Euler within the Rosetta namespace, containing methods for calculating the product of common prime factors of numbers from 1 to 20, with several issues and room for optimization. The code can be improved by fixing the bugs in the PrimeFactors and Overlap methods, and using more efficient algorithms and data structures for prime factorization.

This code imports necessary modules, defines constants, and creates a.NET function using edge-js to call a function from a C# assembly. The testEdge function is then exported as a module to be used elsewhere.

The getNamespacesBySize function parses C# code and retrieves namespaces based on their size, sorting them in descending order. It is exported as a module and takes a string of C# code as input, returning an array of namespace names.

The getClassNames function asynchronously extracts class names from C# code, optionally filtered by a specified namespace, and returns a sorted array of class names.

The getClassNames function takes C# code and an optional namespace as input and returns a sorted array of class names. It uses an ANTLR parser to extract class definitions and filter them based on the provided namespace.

The getClassParams function retrieves method parameters from a given C# code snippet using the antlr library's select function, and returns the results as an array of arrays containing method names and parameters. The function can optionally focus on a specific class, or extract parameters from all classes in the code if no class name is provided.

json

This code provides a utility for extracting specific parts of a JSON file based on a given selection criteria, but its functionality is incomplete due to an unfinished walkJson function.

This code tests the selectJson function by reading a package.json file, simulating a slow data stream, and extracting the "dependencies" section from the JSON data. It demonstrates how to use selectJson with a stream input and logs the result.

minimatch

This code defines a function expandTop that parses and expands nested braced sections within a string, likely representing a structured data format. It uses helper functions to handle escaping, splitting, and transforming the string based on its syntax.

This code parses simplified glob patterns, converting them into regular expressions for matching files and directories. It handles special characters, escaping, and nested patterns to accurately represent the glob syntax in a regular expression format.

This code provides a minimatch function that allows you to match filenames against simplified glob-like patterns by converting them into regular expressions. It handles brace expansions, splits patterns into segments, parses them into regexps, and efficiently tests filename matches against the resulting expression.

The code imports the'minimatch' module, a third-party pattern matching library, using a custom 'import' function and tests two paths against specified patterns. The results of these tests are then output, indicating that both paths match their respective patterns.

python

This code defines three functions: prime_factors to calculate the unique prime factors of a number, overlap to remove duplicate elements from two lists, and uses these functions to calculate the product of unique prime factors of numbers from 1 to 20. The functions are then exported as part of the module, making them available for import by other modules.

The code imports necessary libraries and sets up ANTLR directory to parse C language code, and defines a custom FunctionExtractor class to extract function names from the parsed code. A get_functions function is then defined to take a code string as input, parse it using ANTLR, and extract function names using the FunctionExtractor class.

The Node.js module provides a function pythonParams that uses the ANTLR4 tool to parse Python code and extract function parameters, returning them as an array of objects.

And here's a slightly expanded version in two sentences:

This Node.js module uses the ANTLR4 tool to parse Python code and extract function parameters, which are then returned as an array of objects. The module exports a single function, pythonParams, which can be used to analyze Python code and extract function parameter information.

regexp

xpath

This module is designed to build a lexer and parser for XPath expressions, importing and utilizing various libraries, including ply and eulxml.xpath. It defines custom lexing rules, utility functions, and exports the lexer, parser, and parsing and serialization functions for use in other modules.

This Python module defines classes and functions for representing XPath expressions as Abstract Syntax Trees (ASTs) and serializing them into valid XPath expressions. The module includes classes for different types of expressions, such as unary and binary expressions, and functions for serializing the ASTs into strings.

This code defines a lexer for XPath expressions using the ply module, specifying tokens and their corresponding regular expression patterns to recognize XPath operators, separators, and literal values. The lexer can be used as a foundation for building a parser that constructs an abstract syntax tree (AST) for further processing, making it a crucial component for XPath expression analysis.

This code is an implementation of an XPath parser using the ply module, which defines the rules for parsing XPath expressions and creates an abstract syntax tree (AST) representation of the parsed expressions. The parser is composed of multiple grammar rules for basic expressions, path expressions, and paths, which are used to construct an AST representation of the parsed expressions.

Marketing

2017 Update

This code snippet is a sequence of commands in a Jupyter Notebook environment, including the magic command "%reload_ext" to reload an extension and the "gvmagic" command for GPU acceleration or visualization. The code also includes a comment to discard any friendly remarks and focus only on the documentation or output.

This JavaScript code customizes the output area in a Jupyter Notebook or similar environment to prevent excessive scrolling by setting the auto-scroll threshold to 9999. This setting is likely used for debugging or logging purposes where a large amount of output is generated.

The code is a visual representation of a process using Graphviz, comprising a single 'digraph' statement with a name 'apply' and several nodes and edges that outline the steps from registering a new customer to upgrading a plan. The code includes various attributes for nodes and edges, a subgraph for available plans, and a specific layout direction and edge color specification.

This Graphviz code creates a directed graph representing a purchase funnel flow with multiple stages, including a landing site, trial flow, and purchase funnel. The graph consists of four main clusters with nodes (represented by shapes) and edges (lines) that indicate the flow of customers between stages, including decision points and conditional labels.

The Graphviz DOT language is used to create graphical representations of nodes and edges, allowing for the definition of nodes, edges, clusters, and edge routing. The language provides various attributes for styling and appearance, including font, color, and style, to customize the look of the graph, as demonstrated in an example graph representing an Angular 2 application architecture.

ECommerce

This Python code renews the gvmagic extension in a Jupyter Notebook using the %reload_ext magic command, which reloads an extension and updates it with any recent modifications. The context suggests that the author is working in a Jupyter Notebook environment and intends to apply any changes made to the gvmagic extension.

The code is written in JavaScript and sets the auto_scroll_threshold property of IPython.OutputArea to 9999, effectively disabling auto-scrolling in an IPython environment. This is done by setting a large value (9999) that is unlikely to be reached, preventing unnecessary scrolling.

This Graphviz DOT file defines a directed graph named apply with a specified font, direction, and node properties, and includes subgraphs for cluster_available_plans with nested subclusters. The graph has a hierarchical structure with a main graph and subclusters containing nodes with specific shapes and labels.

The code represents an e-commerce Angular portal as a directed graph, including clusters for customers, purchases, and products, with various nodes and edges styling and invisible connections. The graph is configured to display the different stages of the purchase process, including billing information, confirmation, and progress tracking, within a "Purchase Funnel" subgraph.

Good UX Intro

This JavaScript code uses the $TS library to configure and display a screen or display area named 'act.com' with specified dimensions, zoom level, and cropping settings.

The $TS.screen() function takes a URL or domain (act.com) and an object with properties such as zoom level, width, and crop coordinates to capture a screenshot of a webpage. This function can be customized to capture a specific area of the webpage based on the provided parameters.

The code snippet uses the $TS.screen function to render the webpage at act.com with specified options, including a zoom level of 0.5, a width of 680 pixels, and a cropped rectangle of 400x800 pixels. This suggests that the webpage will be captured or rendered with a partial view.

This JavaScript code utilizes the $TS.screen() function to set up a screen context with specific settings for the domain 'act.com'. The code sets the zoom level, width, and crop region of the screen context using various parameters.

Landing Pages

This code sets up a screen for the domain act.com using the $TS.screen function, with specified options for zoom, width, and height. The options include a zoom level of 0.5, a width of 680 pixels, and a cropped height of 400 pixels.

This code loads a webpage into the browser's viewport using the $TS object, specifying a URL and initial rendering settings, including zoom, width, and height. The initial settings are set to 50% zoom, 680 pixels in width, and 400 pixels in height, with content cropping if necessary.

This code uses the $TS.screen function to simulate a browser screen and load the URL act.com/en-uk. The simulated screen is configured with a zoom level of 50%, a width of 680 pixels, and a cropped height of 400 pixels.

This code snippet uses the $TS.screen method to set up a responsive or mobile viewport with a specific width, height, and zoom level. The configuration options include a zoom level of 0.5, a width of 680 pixels, and a height of 400 pixels.

This code uses the $TS.screen function to set up a screen, specifying device identifier 'act.com/fr-fr' and an object with custom settings for zoom, width, and cropped height. The zoom is set to 50%, width to 680 pixels, and cropped height to 400 pixels.

This code is written in TypeScript and uses the $TS object to open a new tab in the browser with customized settings. The code can be used for testing or demonstration purposes, allowing for the customization of the new tab's appearance.

A JavaScript code snippet uses the $TS object to call the screen function, opening or switching to the French-Canadian version of a website (act.com/fr-ca) with customized settings for zoom, width, and height. This code is likely part of a larger application or script that handles browser screens or tabs.

The code calls the $TS.screen function, passing in a URL (act.com/pl-pl) and an object with settings for zoom, width, and height. The function is likely used for browser automation or testing, and adjusts the page's zoom, width, and height accordingly.

The code uses the $TS object to open the URL act.com/nl-nl/producten/act-pro in a new window with specific settings, including a zoom level of 50% and a size of 680x400 pixels.

The code opens a web page in a new tab or window using the TS.screen function, with customizable parameters such as zoom level, width, and cropping height. The specific URL being opened is 'act.com/nl-nl/producten/act-premium'.

The code calls the $TS.screen function with a URL and an object of configuration options, which includes setting the zoom to 50%, width to 680 pixels, and crop height to 400 pixels.

The code uses the $TS object to display a webpage with specific settings, such as zooming, width, and crop height. It displays the webpage at act.com/au/products/act-pro with a 50% zoom, 680px width, and 400px crop height.

The $TS.screen() function opens a new screen in the TS application, navigating to the specified URL (act.com/au/products) with customizable options such as zoom level, width, and cropping height.

The code uses the TS.screen function to open a new screen with the URL act.com/fr-fr/produits/act-premium, specifying a zoom level of 0.5, a width of 680 pixels, and a height of 400 pixels. This code is likely used for cross-browser or cross-platform testing within a testing framework such as TestStudio.

The $TS.screen() function call is used to display the website act.com/fr-fr/produits/act-premium with specific settings, including a 50% zoom level, 680-pixel width, and a 400x400 crop region.

This code displays a webpage in a specific size and zoom level using the $TS.screen function, with parameters such as URL, zoom, width, and height. The parameters are used for testing or demonstration purposes.

The code uses the $TS object to open a new browser tab or window with the specified URL act.com/fr-fr/produits/act-emarketing. The new tab or window is configured with a zoom level of 50%, a width of 680 pixels, and a height of 400 pixels.

This code opens a webpage or displays content in a specified way using the $TS object and the screen function. It takes the URL of the webpage to be displayed and settings such as zoom, width, and height as parameters.

The $TS.screen function call opens the URL 'act.com/fr-fr/produits/connexions' in a screen with specified options, including a 50% zoom level, 680x400 pixel resolution, and cropping. This is done using the TinyScreen.js library.

This JavaScript code snippet uses the $TS function to load a webpage (act.com/fr-fr/produits/nouveautes) and control its view. The screen method is called with a URL and an object specifying the desired zoom level (0.5), width (680), and height (400) of the screen view.

Wireframing

The code provides instructions for cloning a GitHub repository, building a Docker image, and running a Docker container to run a Jupyter notebook environment. The Docker container is run with interactive shell access, mapping port 8888 and mounting a directory to share files between the host machine and the container.

The code imports the Node.js os module and uses its hostname() function to retrieve the hostname of the system.

The code imports the Node.js os module, which provides information about the operating system. It then uses the hostname() function on the os object to retrieve the hostname of the system.

The code uses the console.log() function to print the string 'Hello NodeJS' to the console. This is achieved by passing the string as an argument to the console.log() function.

The npmls function executes the npm ls --json command and logs the result as a JSON object. It takes a callback function as a parameter, which is executed when the command finishes, returning an error object if the command fails, or the output as a JSON string if it succeeds.

The code imports the exec function to run a command in a new shell and uses it to execute npm install nodegit. The error and output streams of the executed command are redirected to the system's error and output streams for display in the console.

This code clones a Git repository from a specified URL to a local directory, checks out a specific branch, and logs the resulting repository object to the console. It uses the Nodegit library to clone the repository and handles errors that may occur during the process.

The code imports the exec function from Node.js's child_process module and uses it to execute a shell command that changes the directory, installs packages using npm, and redirects the child process's error and output streams to the parent process's standard error and standard output streams. The code also contains commented-out code that appears to be a remnant from a previous version of the script.

The code accesses the HOME environment variable using process.env.HOME. It returns the value of the HOME variable, which can be logged to the console as shown in the example.

This JavaScript code snippet uses the child_process module to execute a shell command in a child process and capture its output and error streams. The command compiles a project using Webpack with specific flags, and the output and error messages are redirected to the parent process's console.

This code reads three JavaScript files synchronously from the file system using Node.js's fs module and stores their contents in variables. An HTML string is then created that includes the script elements, which decode and execute the base64-encoded JavaScript code from the three files using eval() and atob().

This code is a script that dynamically updates a file, rebuilds a project using Webpack, and generates an HTML page with an iframe pointing to the updated index.html file. However, the code has some unused variables and features that are not logged or handled, suggesting it may be a partial or outdated implementation.

The code initializes a process to convert a webpage to an image using the wkhtmltoimage command, with options such as quality and format, and logs the command-line arguments used. The process's output is then piped through a base64 encoder and logged, with the encoded output being passed to the $TS.jpg() function when complete.

The code uses the map function to apply an anonymous function to each element in a vector, adding 23 to each number. The resulting new sequence is [24 25 26].

The provided Graphviz code is a directed graph written in DOT language, defining a process flow diagram with nodes and edges that represent stages and transitions in the process, and specifying various properties such as layout direction, font, and color.

The Graphviz code defines a directed graph with a specific layout direction and font properties, and it outlines a process flow diagram with nodes and edges representing various stages and transitions. The code also specifies default properties for nodes and edges, allowing for customization of the graph's appearance.

Selenium

What is Selenium

This code snippet sets up and manages a Selenium server using Docker, ensuring a clean and consistent environment by removing existing containers and building a new one. It utilizes Docker to manage the server and returns a promise for asynchronous handling of the setup process.

This code provides a function vncIframe that generates an HTML snippet embedding a VNC viewer iframe, allowing you to easily integrate VNC viewing into your web application. It takes optional connection parameters and dynamically constructs the iframe's source URL with encoded options.

The vncIframe function generates an HTML snippet embedding a VNC viewer iframe, dynamically constructing the iframe's source URL based on provided connection parameters and encoding them for URL safety.

The runSeleniumCell function sets up a Selenium WebDriver session and executes a user-defined search within a web browser, leveraging imported functionalities for tasks like element manipulation and form interaction. It's designed to be reusable and can be integrated into a larger framework or library based on the presence of the $ global variable.

The testLive function automates a website test by navigating to a specific URL and clicking a login link. It uses a WebDriver client to perform these actions and likely returns a result object.

auth

avidbrain

This code defines a function called testLogin that automates the process of logging into a website by navigating to the login page, entering credentials, and submitting the login form. It is likely used for testing purposes or integration with other tools.

This code imports a module named Core and a function called runSeleniumCell, which is then used to execute a Selenium test with the argument 'test avidbrain'. The test's result is handled asynchronously using then() and catch() methods, sending the outcome or any error that may occur as a result.

facebook connections

This code automates the process of scraping Facebook friend data using Selenium, storing it in a file, and providing a method to access the extracted friend URLs. It utilizes jsdom for parsing the scraped HTML and custom modules for interacting with Facebook and managing data.

This JavaScript code initializes asynchronous execution using the $.async() function and then runs a series of Selenium tasks, specifically logging into Facebook and liking all Facebook posts. The code handles task results by extracting functions from the result object and calling them, and also handles errors by sending them to an unknown object $..

The code imports the Core module, extracts the collectFacebookProfiles function, and sets up asynchronous execution using $.async(). It then executes the collectFacebookProfiles function, handling the result and error using the $.sendResult() and $.sendError() functions.

This code automates the process of sending friend requests on Facebook by navigating to a profile, clicking the "Add Friend" button, confirming the request, and handling potential errors.

This code automates the process of finding new Facebook friends from scraped posts and connecting with them using Selenium.

The code is a JavaScript function that uses the async/await syntax to handle asynchronous operations by calling the addFacebookFriends function and handling its result or error using the then and catch methods. The addFacebookFriends function returns a promise that is resolved by sending the result with $.sendResult(r) or rejected by sending the error with $.sendError(e).

facebook data

This code automates Facebook login using Puppeteer. It first checks if the user is already logged in, and if not, it fills in the username and password, submits the form, and handles potential CAPTCHAs.

The readFacebookProfileInfo function automates the process of extracting a Facebook profile's name, description, and URL from a given profile page. It uses web scraping techniques to locate and interact with elements on the page, ultimately returning a structured object containing the extracted data.

This code automates the process of scraping Facebook posts, fetching their URLs and extracting details like descriptions and participant profiles using Puppeteer.

This code automates the scraping of Facebook event details, including its description and discussions, using Puppeteer.

This code automates the scraping of Facebook event data from HTML files, extracts event URLs, and stores the scraped information in a JSON file.

The code is designed to scrape Facebook events and send the result or error to a recipient, using a function scrapeFacebookEvents() that returns a promise and is called asynchronously. The code uses then and catch methods to handle the resolved promise and any errors that occur, respectively, and sends the result or error to a recipient using sendResult(diff) and sendError(e) functions.

This code provides a function scrapeFacebookFriends that automates the process of logging into Facebook, extracting unique friend URLs from the user's friends page, and storing them in an array. It utilizes Selenium for browser automation and XPath for element selection.

This code tracks changes in a Facebook user's friend list by scraping their friend list from Facebook, comparing it to previous lists, and identifying new and removed friends. It then exports this functionality for use in other parts of an application.

This JavaScript code retrieves the difference between a user's Facebook friends and LinkedIn connections and sends the result or error to the client using the getFriendsDiff() function, which returns a promise that is then handled by the .then() and .catch() methods. If an error occurs, the $.sendError(e) function is called to send an error message to the client, while successful results are sent to the client using the $.sendResult(diff) function.

This code automates the process of unfollowing users on Facebook by identifying and clicking unfollow buttons on the user's "Following" page. It uses a custom module and promises for efficient and concurrent unfollowing.

The code uses the selenium cell function to automate two tasks (log in facebook and unfollow everyone facebook) and handles their execution and errors using a series of then and catch blocks.

The code defines three functions: getUninvited, clickInvite, and clickConnect, which together automate the process of inviting individuals to a fundraiser event by identifying uninvited participants and simulating clicks on them.

facebook messaging

This code automates the process of retrieving and reading unread Facebook threads by logging into the user's account, navigating to the unread messages page, listing the threads, and then reading the content of each thread. It is designed to be used as a reusable function within a larger application.

This code automates Facebook message responses by identifying messages containing a specific command pattern ("megamind [command]"), processing the commands, and sending automated replies. It uses a custom module to interact with Facebook and manage the command processing and response generation.

This code automates the process of logging into Facebook, retrieving thread information, and downloading message content from specific threads, storing the data in a JSON file. It utilizes Selenium for web automation and asynchronous programming techniques to handle the interactions efficiently.

This code automates the process of collecting and managing URLs of Facebook message threads, storing them in a JSON file for later use. It utilizes web automation tools to interact with Facebook and handles both regular and archived threads.

This code extracts information about participants in Facebook message threads by navigating to each participant and scraping their profile data using web automation techniques.

The code imports a module from a file named Core and uses it to run a Selenium cell with the argument 'messages from facebook'. The result of the Selenium cell is then processed through a series of promise chains and error handling blocks to ultimately send the result to the $. object.

This code automates the process of sending messages on Facebook, handling thread navigation, multi-line message formatting, and error handling using web automation techniques.

facebook webdriver

The code imports necessary dependencies, including Selenium, and defines environment variables for a user's profile directory and password file. The enterFacebook function is an asynchronous function that automates a Facebook sign-in process, including finding and filling out form elements, waiting for and handling potential CAPTCHA or other issues, and submitting the form.

The listFriends function is an asynchronous module that lists Facebook friends using Selenium WebDriver, either by logging in and using an existing driver or creating a new one. It extracts friend links from the Facebook suggestions page, filters out duplicates, and returns the result, while handling errors by quitting the Selenium WebDriver session and re-throwing the error.

The friendFacebook function performs a series of actions to navigate to a Facebook profile page, check for the "Add Friend" button, and click it to send a friend request. The function is designed to handle user login and profile navigation using Selenium WebDriver and is exported as a module for use in other code.

forms

This code defines a module that exports two functions: one for filling dropdown menus and another for mapping object data to form fields, likely for web form interaction.

This code automates the selection of a dropdown menu option on a webpage by finding the dropdown and the desired option based on their labels and values.

The fillForm function automates filling out web forms by taking an object of field names and values and using a custom selectDropdown function to populate dropdown menus with the specified values.

This code automates website logins by using Selenium to locate and fill in username, password, and submit fields on various websites. It retrieves login credentials based on the website's hostname and handles potential errors during the process.

This code automates the login process to multiple websites defined in a JSON file, likely for the purpose of web scraping or further interaction, using a custom multiCrawl function. It reads credentials from a local file and executes the logins asynchronously, sending results and handling errors through a testing framework.

github

This code downloads a ZIP archive from GitHub, extracts its contents, and returns a list of files found within the extracted archive. It's likely used to retrieve and process specific files from GitHub repositories.

google authorize

This JavaScript module handles OAuth2 authentication with Google Calendar using various external libraries and provides error handling and fallback scenarios to recover from connection issues. The module defines four primary functions: storing tokens, exchanging codes for OAuth2 tokens, error fallback, and renewing existing tokens, with the last function having incomplete documentation and implementation.

The authorizeSelenium function uses the client object to navigate to a provided auth URL, log in using the loginGoogle function, and interact with various HTML elements on the page to retrieve the value of a textarea element.

This code imports dependencies for a Node.js application, sets up OAuth 2.0 credentials, and creates an instance of the OAuth2Client class to request an access token. The access token is requested using the getToken method of the oauth2Client instance, and the result is handled through a promise with a callback function for both successful and error cases.

google takeout

This code snippet automates the creation and download of a Google Takeout archive for a specified product, handling navigation, login, size selection, archive creation, and download completion.

This code snippet provides a function googleTakeout that automates the download of a Google Takeout archive for specified products, leveraging Selenium WebDriver for browser automation and custom commands for login and download initiation.

The code imports a module and a specific function, then calls the function with an argument to initiate a Google Takeout action. It also sets up asynchronous execution and error handling using a .then callback for successful results and a .catch callback for errors.

This code parses a Chrome browser history file to categorize and count website visits, likely for the purpose of visualizing browsing habits using a pie chart. It identifies common websites visited and provides a summary of their frequency.

google timeline

This code provides functions to automate interactions with the Google Maps timeline, including navigating to the page, logging in, selecting a specific date, and handling different page states.

This code snippet extracts structured timeline data, such as dates, titles, durations, and locations, from a webpage, likely a social media platform or personal website. It uses XPath expressions to target specific elements and chrono-node to parse dates from the extracted text.

This code processes Google Timeline data to identify and categorize destinations by finding nearby geographical locations associated with each timeline entry. It then calculates average coordinates for these destinations and filters out entries that are not relevant.

This code snippet correlates Google Calendar events with nearby locations based on location names, event summaries, and event locations, likely for analyzing travel patterns or daily routines. It identifies matching events and locations, logging the results for further analysis.

This code snippet defines a function loadLocations that parses a JSON file containing location data, groups locations by date, and stores them in a cache for efficient retrieval. It uses a custom importer module to stream the JSON data and process it asynchronously.

This code snippet processes location history data from Google Takeout and combines it with timeline data from Google Calendar, likely for analysis or visualization purposes. It uses Selenium to scrape timeline data and writes the reconciled data to JSON files.

This code snippet provides a function timelineEvents that retrieves timeline event data for a specified date from a JSON file stored in a user-specific directory. It handles both date object and string inputs and constructs a unique file path based on the date.

linkedin connections

This code snippet synchronizes LinkedIn contact data with a local storage directory by scraping new contacts from LinkedIn and comparing them to existing data. It uses Selenium to automate the web scraping process and identifies new contacts for storage.

This code snippet uses Selenium to scrape comprehensive data from a LinkedIn profile, including basic information and details from various sections like experience, skills, and recommendations. It employs techniques to load all content, including hidden sections, to ensure complete data extraction.

This code fetches a list of LinkedIn connections, prioritizing loading from a cached file if it's recent, otherwise scraping the data from LinkedIn and saving it to a local file. It uses Selenium to automate the web scraping process.

The code imports a module and a function from it, then uses asynchronous execution to call the function, which returns a promise. The promise is handled with .then for success and .catch for errors, sending the result or error to the $.sendResult or $.sendError functions, respectively.

This code automates LinkedIn interactions by retrieving a list of connections and sending connection requests to specified profiles.

This code automates the process of connecting with LinkedIn contacts using Selenium to control a web browser. It takes a list of connections or a single connection as input and attempts to connect with a random subset of them.

This code snippet imports a module, specifically the addLinkedinConnections function, and executes it asynchronously using the $.async() and .then()/.catch() methods. The addLinkedinConnections function is called with null and an empty string as arguments, and the result is sent using the $.sendResult(r) method, while any errors are sent using $.sendError(e).

linkedin messages

This code provides a function loginLinkedIn that automates the process of logging into LinkedIn using Selenium, handling potential CAPTCHA challenges and returning a boolean indicating success or failure.

This code automates the process of extracting a LinkedIn user's profile information, including name, title, URL, phone number, and email address.

This code automates the process of collecting URLs of LinkedIn threads by scrolling through the messages page and extracting thread links until no new threads are found.

This code snippet is designed to interact with LinkedIn, extracting information about participants in a given thread and attempting to read messages within that thread. It uses a client object to control interactions with the LinkedIn website, but the specifics of this object and how it works are not provided.

This code automates the scraping of LinkedIn thread data, including messages and participant information, storing the results in local JSON files. It utilizes Selenium for web interaction and relies on external modules for file handling and data processing.

The code imports a module and a specific function named scrapeLinkedInThreads, and then executes this function asynchronously using a promise chain to handle both successful and failed results. The scrapeLinkedInThreads function returns a promise that is resolved either by sending the result with sendResult or by sending an error with sendError if it fails.

linkedin webdriver

The loginLinkedIn function logs a user into LinkedIn using the enterLinkedIn function, which retrieves login credentials from a hardcoded JSON file and uses Selenium to fill in the login form. The loginLinkedIn function does not check if the login was successful, it only checks if the user is logged in, and the enterLinkedIn function does not handle errors robustly.

The listConnections function is an asynchronous module that retrieves a list of unique LinkedIn connections' URLs by utilizing Selenium to navigate to the user's my network page, check for login status, and retrieve connections until at least 10 unique connections are found. If no driver is provided, it creates a new instance using getClient() and logs in to LinkedIn using loginLinkedIn(), before proceeding with the connection retrieval process.

orchestration

This code provides a function to resize and position a browser window into a grid layout, allowing for the management of multiple browser instances in a structured manner. It uses a client object (likely Selenium) to interact with the browser and calculates window positions based on a specified grid structure.

This code provides functions to control browser windows and tabs, with the primary purpose of ensuring that only a single window remains open after a series of actions. It achieves this by closing all other windows and tabs, leaving a designated window active.

This code provides a way to open multiple URLs in separate browser windows and arrange them in a tiled layout using Selenium WebDriver. It leverages imported functions for window resizing and URL management to achieve this functionality.

This code uses Selenium to manage multiple browser sessions, resizing and retrieving URLs from each window across all active sessions. It is designed for use in a testing environment and can be executed asynchronously.

The sendJoke function automates the process of fetching two jokes and posting them as separate Facebook messages within a designated browser window using Selenium WebDriver.

The sendFacebookThanks function checks a Facebook thread for a "dream" related message and automatically sends a "Are you living the dream?" message if none is found.

The code imports a module named Core and a function named selenium cell from it, which is used to interact with the Selenium cell. It also defines an array of Facebook message URLs and includes a TODO comment to replace the current implementation with RPC commands.

The cleanUpSessions function manages and closes all active Selenium WebDriver sessions, cleans up session data, and restarts the Selenium server to ensure a clean environment for subsequent tests.

This code automates screenshot capture from Selenium WebDriver sessions and uploads them to an AWS S3 bucket for storage.

reddit

The code imports necessary libraries and defines functions enterReddit and loginReddit to interact with the Reddit website using Selenium WebDriver. However, the code has several issues, including recursive function calls, unhandled errors, and incomplete implementation, which need to be addressed.

The redditPost function automates posting on Reddit using Selenium WebDriver, taking parameters such as content, start page, and driver instance to create and submit a post. It handles errors and uses Markdown formatting for the title and body, with optional title generation using a Large Language Model.

The code imports a'reddit post' module using the importer.import() function and assigns it to a constant redditPost. The testPost function, which uses redditPost, is then exported as a module, making it available for importing in other JavaScript files.

The redditWeekly function scrapes top links and posts from Reddit, extracts summaries, generates alternative summaries, and posts them to a specified page, with TODO comments indicating areas for further development.

The redditList function is an asynchronous function that retrieves a list of Reddit posts from a specified subreddit, handling parameters such as the start page and time span. It iteratively retrieves posts using the redditLinks function, checks for posts older than the specified time span, and introduces a delay between iterations to prevent infinite loops.

The redditLinks function uses Selenium WebDriver to scrape Reddit posts from a specified subreddit or URL, extracting title, timestamp, link, and comment count for each post, and returning an array of objects with additional metadata.

The redditLinks function scrapes Reddit posts from a specified subreddit or URL using Selenium WebDriver, extracting key metadata for each post. It returns an array of objects containing the scraped data, along with the URL of the next page of posts.

The testScraper function, exported as a module, scrapes Reddit links using a Selenium client instance, which is obtained by calling the getClient function, and returns the scraped results. The function takes an optional startPage parameter, defaulting to a specific Reddit URL, and modifies it if necessary to include a protocol.

scraping

The extractArticle function extracts the article content from a given HTML page in plain text, retrying if the page crashes, and returns the extracted content as a single string. It uses Selenium WebDriver to load the page, select text elements, and handle errors such as stale element references and page crashes.

The testExtractor function extracts data from a specified webpage using the selenium client and returns the extracted data as an object. It uses the extractArticle function to scrape data from the webpage and imports functions from the selenium client and extract llm article modules.

The summerizeArticle function is an asynchronous function that summarizes an article in two ways: a detailed summary and a single sentence summary. It creates an LLM session, sends prompts for both types of summaries, and returns the results as an array.

This code imports necessary modules for extracting content from a website, interacting with a web browser, and summarizing the extracted content. A function testExtractor is then defined, which uses Selenium to extract and summarize content from a webpage and returns the summary.

The summerizeAll function extracts and summarizes all links from a provided startPage or links array by selecting a link scraping tool, scraping links, extracting article content, summarizing articles, and persisting summaries. The function uses various modules and functions, including getClient, extractArticle, summerizeArticle, defaultCollector, and persistSummaries, and is exported as a module for use elsewhere.

This code imports necessary modules and functions, assigns project-related constants, and defines an array of 14 conversion prompts for text rewriting. The imported functions include safeURL, getNearestSunday, and summarizeArticle, among others.

This JavaScript module imports required modules and functions, defines constants and functions for file operations, URL manipulation, and data collection, and exports these functions for use in other parts of the application.

selenium commands

The Xvfb command starts a virtual display server with specified characteristics, including resolution, color depth, and extensions. The command Xvfb :0 -ac -screen 0 1024x768x24 +extension RANDR is used to start a specific virtual display server with 1024x768 resolution, true color, and RANDR extension enabled.

To start a Selenium server with Chrome browser in headless mode, the code sets the DISPLAY environment variable, runs the Java Virtual Machine, and specifies the path to the Selenium standalone JAR file. The command also sets JVM system properties to customize the Chrome browser's behavior, including running in full-screen, disabling sandboxing, and running in incognito mode.

This code exports the DISPLAY environment variable to redirect the display to the first display, then launches Google Chrome in full-screen mode to open a development server at http://localhost:4200. It appears to be a Linux-specific script used for testing or demonstration purposes.

This Dockerfile uses the selenium standalone chrome debug image as its base, exposes ports 4200, 4444, and 3000, and sets up directories and environment variables for a Chrome browser testing environment. It also modifies the entry_point.sh script to modify Chrome preferences and change the exit behavior to report a cleaner shutdown.

selenium demo

This code imports the exec function, which enables Node.js to execute shell commands and interact with the spawned processes.

selenium server

This code sets up a REST API using Express.js to enable a web application to control a Selenium WebDriver instance running on a separate server, automating browser interactions. It uses Socket.IO for communication and a custom importer module to execute a Jupyter notebook containing Selenium server logic.

The code sets up routes for a WebdriverIO application using Express.js, defining handlers for GET and POST requests to various paths using route parameters and callback functions. Each route is associated with a callback that is called when the route is matched, and is likely being used by the WebdriverIO client to automate web browsers.

This code creates a REST API using Express for navigating and interacting with web pages in a Chrome browser instance, utilizing the Chrome Debugging Protocol. It provides functions for waiting for page loads and navigating to specific URLs, as well as API endpoints for retrieving and setting the current URL of the active tab.

The findElements function uses the Chrome debugger API to find elements on a webpage based on an input selector, and is called by two express routes to handle POST requests. The function and express router are exported as part of the module, allowing it to be used in other applications.

This code requires three external modules (fs, path, and express) and sets up environment variables and file paths to interact with a file system and create a web server. It defines several functions, including deleteSession, createSession, and getSessionCapabilities, and sets up an Express router with routes for creating, deleting, and retrieving session information.

The code defines a Node.js module that interacts with a ChromeDriver session using RESTful API endpoints and includes a function to retrieve window handles from the ChromeDriver. However, the code has several issues, including a function that doesn't use its intended parameter, a non-standard library that may require additional setup, and unimplemented routes in the Express router.

This code defines a clickElement function that simulates a mouse click on an element with a specified id using the Chrome debugger, and exports it along with an Express router instance that listens for POST requests to click elements. The clickElement function uses a sequence of Chrome debugger commands to resolve the element, evaluate a promise, and simulate a mouse click at the resolved coordinates.

send social message

service auth

This code provides functions to retrieve and decrypt credentials stored in a JSON file, allowing access to them based on a hostname. It uses AES-256 encryption and retrieves a decryption password from either an environment variable or a local file.

This code securely stores user credentials by encrypting them using AES-256-CTR and managing them in a JSON file, ensuring data privacy and protection.

This code imports a module and a specific function from it, using Node.js's require function and the import method of the imported module. It then uses the imported function to save credentials, passing in an object with 'host', 'password', and 'username' properties, with the password masked for security.

The readPasswordsHtm function reads an HTML file (passwords.htm), extracts host and credential information from each table row, and saves the encrypted credentials to a JSON file.

The readPasswordsHtm function reads an HTML file (passwords.htm), extracts host and credential information from each table row using regular expressions. The extracted credentials are then saved to a JSON file in an encrypted format using the saveCredentials function.

This code automates the process of downloading Google passwords from the Google Password Manager website by navigating to the site, logging in, extracting password data from each row, and saving it to a file.

This code imports a module and function using the require and import functions, and then uses the imported runSeleniumCell function to initiate an asynchronous operation to download passwords from Google. The code uses promise chaining with then and catch methods to handle the result and any errors that may occur during the operation.

This code automates the Google sign-in process using Selenium, handling both username and password entry, and includes logic to select an account from multiple options if necessary.

stack overflow

utilities

The scrollClient function is an asynchronous function that scrolls a webpage to a specific position based on a given CSS selector, or to the top or bottom of the page if no selector is provided. It uses various functions such as selectDom and evaluateDom to dynamically import and evaluate code on the client-side to achieve the desired scroll position.

The getAllUntil function is an asynchronous function that retrieves and filters data from the DOM using Selenium WebDriver, allowing for conditional scrolling and optional filtering. It recursively retrieves data, filters it based on a callback function, and returns the collected data when no more data is found or the scrolling condition is met.

The clickSpa function simulates a click on an element with a specific profile URL by appending an a element to the page and executing a command to click on it, waiting for 1 second before resolving.

The clickSpa function simulates a click on an element with a specific profile URL by creating an a element and setting up an event listener to remove it after a delay. The function waits for 1 second before resolving the promise, and catches any errors that occur during execution.

This code defines a verifyHuman function that is intended to verify whether a user is a human, but its purpose and functionality are unclear. The function optionally imports the selenium client module and exports a module, but lacks error handling and a clear verification mechanism.

The testVerify function is an asynchronous function that checks if a provided page parameter is falsy, sets it to a default value if so, navigates to the specified page using a Selenium driver, and calls the verifyHuman function to verify a user is human. The testVerify function is then exported as a module, making it available for use in other JavaScript files.

webdriver

This Node.js script uses Selenium WebDriver to create a Chrome browser session, setting environment variables and defining Chrome profile paths based on the operating system. The getClient function creates a new Chrome browser session by setting Chrome profile paths, adding arguments, and returning a promise with the created client instance.

The code is designed to manage sessions by reading and writing data to a sessions.json file, utilizing environment variables and file system modules. It exports two functions, readSessions and updateOrAddSession, which handle reading and updating the sessions array, respectively.

The code defines an asynchronous function testDriver that imports a getClient module, sets up a web driver, navigates to Facebook, waits for 4 seconds, and then closes the driver. The function is exported as a module.

The code imports necessary classes and functions from the selenium-webdriver module and defines a function closeAllWindows that closes all browser windows except the one specified by the keep argument. The function creates a new instance of WebDriver, gets an array of window handles, and iterates over them to close all windows except the one specified by keep.

The code defines a set of commands for interacting with a web browser using Selenium WebDriver, including launching apps, setting network conditions, and sending DevTools commands. The commands are configured using the configureExecutor function, which takes an executor instance and a vendor prefix as arguments to customize the command URLs for specific vendors.

The code imports necessary modules for interacting with web browsers and defines constants and functions for managing Selenium sessions, including verifying individual sessions and retrieving active sessions. The getSessions function is exported as a module export, which can be used to retrieve and verify available Selenium sessions.

The code imports three functions (selectDom, evaluateDom, and walkTree) from separate modules and uses them in an asynchronous function called getAllXPath to execute a script on a web page. The getAllXPath function takes three parameters and returns the result of calling the selectDom function after making the evaluateDom and walkTree functions available on the web page.

The getAllQuery function is defined as an asynchronous function that executes a script in a browser context using the driver.executeScript method, which involves importing and utilizing external functions for querying and evaluating the DOM. The function takes three parameters - driver, select, and an optional ctx object - and returns the result of executing the queryDom function.

The code requires two modules: ../Core and webdriverio, and imports specific functions and constants from ../Core. It defines a function createWebdriverClient that creates a WebdriverIO client configuration object with various settings and capabilities, including browser name, Chrome-specific options, and log level.

The connectSession function connects a client to a session by managing existing sessions, creating a new one if necessary, and configuring the client's connection retry timeout. It returns the client's session ID if successful, or throws an error if an issue occurs.

This code defines a module that reads session data from a JSON file at SESSIONS_PATH and returns an array of session data. It also includes error handling to reset the session array if an error occurs while reading the file.

This Node.js module manages lock files and session data, providing functions to lock/unlock files and update or add sessions to a JSON file. The module uses the lockfile, fs, and path modules, as well as a custom ../Core module, to perform its operations.

The getSessions function retrieves available sessions for a given client, filtering out inactive sessions based on the lastActive timestamp. It uses a multi-step process to verify sessions, including loading sessions, filtering, mapping, running promises, and deduplicating results.

This code imports necessary modules, sets variables, and defines two primary functions: addPlugins and verifySession. The addPlugins function attaches event listeners to a client object and locks/unlocks promises to update or add session data, while the verifySession function verifies a session by setting the session ID, adding plugins, and interacting with the client object's promise chain.

This code checks if two variables, client and $, are defined, and if so, it creates a new Webdriver client instance and sends the result to the $ function. The code also catches any errors that occur during client creation and sends them to the $ function for handling.

The code checks if client and $ are defined, and if so, executes a block of code. It also contains functions to execute an asynchronous method and handle client window handles, including sending results or errors through the $ object.

This JavaScript code checks if a client object exists and, if so, closes all connections to it by calling the endAll() method. If the client object does not exist, the code does nothing.

you earned it

This code automates interactions on a "YouEarnedIt" website, including logging in and simulating "High-Five" button clicks. It uses functions to handle each step of the process, making it modular and reusable.

The runHighFiver function uses Selenium WebDriver to execute a predefined automation script, likely for interacting with the "YouEarnedIt" website. It simplifies the process of running this automation by abstracting away the Selenium setup and execution details.

The JavaScript code snippet initiates an asynchronous operation with $.async() and handles the result or error using the .then() and .catch() methods, passing the result to $.sendResult() or the error to $.sendError().

The code starts with $.async() to initiate an asynchronous operation and continues with a promise resolution and error handling using .then() and .catch(). The result or error is then passed to specific functions within a framework or library, indicated by the $.$ namespace.

Introduction

Untitled

This Python code snippet 1 + 1 represents a simple arithmetic expression that adds two numbers together, resulting in 2. The expression is executed using the + symbol to denote the addition operation.

Untitled1

Utilities

active directory

bash

The command displays the names of the 10 largest files in the current directory, including their sizes, by using a pipeline of Unix utilities (du, sort, and head). The command includes file counting, numerical sorting, and reversing the order to show the largest files first.

These commands navigate to a specific directory, install a browser automation library, and create three new directories: Collections, searches, and screenshots. The directory creation commands include error handling to ensure the execution continues even if a directory already exists or cannot be created.

To install Node.js version 9.x on a Linux system, execute the installation script with the command curl -sL https://deb.nodesource.com/setup_9.x | sudo -E bash - and then update the package index with sudo apt-get update -qqy.

This code clones a Git repository (jupyter_ops) from Bitbucket and installs its dependencies using npm, chaining the commands together with && for a seamless execution. The cloning process creates a new directory named jupytangular in the current working directory, and then changes to that directory to install the dependencies.

This shell script configures systemd services on a Linux system by copying service files to /etc/systemd/system and enabling them to start at boot time. It reloads the systemd daemon, enables and starts services for Jupyter Notebook and Selenium, ensuring they run automatically when the system boots up.

This shell command sets up and starts a LaunchAgent on macOS by copying a plist file, loading it, enabling it, and starting it. The command assumes the plist file is in the correct format and the user has necessary permissions to modify their LaunchAgents directory.

These shell commands perform the following actions: create a directory and execute a command if it doesn't exist, copy files using Secure Copy (SCP) from a local directory to a remote EC2 instance, using private key authentication. The commands copy different patterns of files using SCP, including https_www_googleapis, client_secret, and aws-sdk files.

This Bash script continuously runs an npm command using an infinite loop, executing the import script with the argument "create export cache". The loop structure follows a standard Bash while loop syntax, with do for the code block and done to mark the end of the loop.

bitbuffer

The JavaScript BitView class provides a similar interface to DataView with support for bit-level reads and writes, allowing for manipulation of single bits within a specified byte offset. It offers methods to set a single bit, read a specified number of bits, and private properties for internal use, with dependencies on ArrayBuffer or Buffer objects and the DataView class.

child process

The code utilizes the child_process and importer modules to execute external Bash commands and handle errors, with functions such as bashToExec and execCmd to prepare and run the commands. The execCmd function creates a promise that resolves with the output of the executed command and logs the command and its output if not in quiet mode.

The code combines asynchronous operations with error handling in Node.js, initiating a test suite, executing a shell command, and handling the result or error through custom functions.

However, for brevity I could remove the Node.js and shell command execution to just convey that it's asynchronous and has error-handling in one sentence.

The code is asynchronous, with error handling and uses a test suite.

The bashToOne function maps Bash shell script code to a single executable command, handling platform-specific line endings and command separators. It does this by splitting, modifying, and joining the input code according to the detected platform (Windows or Unix-like).

cied2000

The CIEDE2000 color difference calculation function is a C++ function that determines the color difference between two colors by converting their coordinates to a new chromaticity space and then calculating the deltaLPrime, deltaCPrime, and deltahPrime values. The function returns the CIEDE2000 color difference value based on these calculated values.

This code provides functions for color space conversions, including RGBtoXYZ, XYZtoLab, and rgb2lab, which transform RGB values into Lab* color space according to CIE XYZ and Lab specifications. The code uses C programming language and assumes RGB values are in the range [0, 255] and XYZ values are in the range [0, 1].

The testCIED2000 function calculates the CIEDE2000 color difference between two colors, "red" and "darkred", using the rgb2labRet and CIEDE2000 functions, and logs and asserts the result. The function is designed to test the accuracy of the color difference calculation, and returns the calculated value.

compress

LZString is a JavaScript library that provides efficient compression and decompression functionality using the LZ77 algorithm, supporting various output formats like Base64, UTF-16, and URL-encoded strings.

The LZString library is a JavaScript implementation of the LZ77 compression algorithm, providing methods for compressing and decompressing strings using Base64 and UTF16 encoding schemes. It offers functions for converting strings to and from compressed formats, including compressing to and decompressing from Base64, as well as retrieving character indices in a given alphabet.

This code uses the iltorb library to synchronously compress data in Node.js, handling potential errors during the process.

dates

This code identifies and lists all Tuesdays in the remaining months of 2017 that occur on or after the 26th of the month. It does this by calculating the first Tuesday of each month and iterating through subsequent Tuesdays until the next month begins.

This code provides a function ISODateString that converts a Date object into a standardized ISO 8601 formatted string, ensuring consistent date and time representation. It utilizes helper functions and UTC methods to achieve this conversion.

This code calculates the total duration of a list of events in minutes, handling cases where end times are missing. It iterates through the events, calculates the duration of each event, and sums them up to provide the total duration in minutes.

The filterDistant function takes a list of events and a time threshold, returning a new list containing only events that are within the specified time window from the previous event.

This code snippet uses the D3.js library to generate a line graph visualizing time-series data from an array of events. It sets up scales, defines a line generator, creates an SVG element, binds data, and renders axes to display the graph.

diff

This code snippet compares two code snippets, calculates their differences, and presents the results as a visually highlighted HTML diff using Prism.js for syntax highlighting.

This code imports modules and variables, interprets functions, sets a project directory, and reads/displaying code. It uses various functions from the importer module to find and compare code snippets, and displays the differences using a custom $.html function.

dylib

This Node.js module exports a function enumWindows that enumerates the titles of visible windows on the system, filters out certain programs, and returns an array of window titles. The function uses Foreign Function Interface (FFI) bindings to a dynamic library sog to interact with the system's window management API.

The code defines a function signature using the define function and uses the resulting object to call functions and verify their correctness. It includes the sum and atoi functions, which are called with test arguments and validated against expected results using the equal function.

This Node.js module exports a moveMouse function that moves the mouse cursor to a specified position (x, y) by interacting with a dynamic library file. The module determines the platform-specific path to the dynamic library file and loads a SetMousePosition function from it, which is then called with the provided coordinates.

The testEdge function loads a dynamic library (005.dll) using node-api-dotnet and creates an instance of the Rosetta.Euler class from it, then calls its Main method. The function is exported as a module, making it available for use in other parts of the application.

The moveMouse function moves the mouse cursor to the specified coordinates (x, y) asynchronously, returning a promise that resolves when the move is complete. It requires an importer object and the mouse control c module, and is exported as a module.

The getParameters function is an asynchronous function that extracts data from a provided C++ code string using the select function from the antlr tree package. It imports the select function using an importer object and returns the extracted data, which is then exported as a module.

The getExports function extracts function definitions from C++ code by parsing the input code and returning an array of function definitions as strings. It uses the select function from the antlr and tree modules to implement this functionality.

The getTypes function is an asynchronous function that retrieves function types from a given C++ code snippet, optionally specifying a function name to retrieve the type for. It uses an XPath expression to parse the code and extract the function types, and is exported as a module for use in other parts of the application.

The typeToDataType function takes in parameters returnLength, returnType, and dataType and returns an object compatible with the ffi-rs library, handling different data types through switch statements.

The code imports required modules and defines constants, then uses the buildDylib function to compile a dynamic library, extract environment variables, and recompile if necessary, assuming the library is written in C, C++, or Objective-C.

Or in two sentences:

The code imports necessary modules and defines constants for a build process. The buildDylib function compiles a dynamic library, extracts environment variables, and recompiles if necessary, assuming the library is written in C, C++, or Objective-C.

heartbeat

This code defines a function thump that asynchronously executes Node.js scripts, allowing for parameter passing, output logging, and error handling.

This code uses a Google Calendar to trigger the execution of Node.js scripts by parsing event descriptions and extracting parameters to run.

levenshtein

This code calculates the Levenshtein distance between two strings, which represents the minimum number of edits (insertions, deletions, or substitutions) needed to transform one string into the other. It uses a dynamic programming approach to efficiently compute this distance.

The levSort function sorts an array of objects based on how similar their strings are to a given search string, using the Levenshtein distance as the similarity measure.

This code implements a fuzzy search function, levSearch, that finds objects in a dataset based on the closest match to a given search term using Levenshtein distance.

mono

This Dockerfile instruction sets the base image for a new Docker image to be the latest version of the official Mono runtime environment.

This shell script configures a NuGet package source, restores packages in a.NET project, and builds the project using MSBuild. The script creates a configuration file, sets up symbolic links, updates the NuGet package source, and builds a specific project.

This Dockerfile builds two types of images: one based on Mono for running a.NET application, and another based on ASP.NET Core 1.1 for running an ASP.NET Core application. The images install necessary dependencies, copy files, set the working directory, and define entry points to run the applications using respective runtimes.

nmap

The nmap command nmap --script=smb-brute.nse localhost performs an SMB brute-force attack against the local machine using the smb-brute.nse script. This command is used to test the security of the local machine's SMB protocol by attempting to brute-force login credentials.

openssl

This code sets up a root Certificate Authority (CA) using OpenSSL, configuring directories, files, and policies for issuing and managing digital certificates.

This shell script creates a self-signed intermediate Certificate Authority (CA) using OpenSSL, generating a private key, CSR, and certificate, and creating a certificate chain with the root CA's certificate.

This shell script creates a self-signed intermediate Certificate Authority (CA) using OpenSSL by generating a private key, CSR, and certificate. The script then creates a certificate chain by concatenating the intermediate CA's certificate and the root CA's certificate.

This code generates a client certificate and its corresponding private key, signs it using a self-signed intermediate CA, and then verifies the signed certificate.

packages

This code defines a JSON object with various commands that execute specific tasks using Node.js, including import, execution, interpretation, SSH connections, and Git automation. It utilizes Node.js variables and npm run to execute scripts and separate commands from arguments.

parse

This code snippet offers two JavaScript utility functions: flatten for simplifying nested arrays and escapeRegExp for preparing strings for use in regular expressions.

polyfills

This code defines a httpRequest function that makes HTTP requests using either the request module (if available) or a custom implementation based on the http and https modules.

qr codes

This code generates a QR code image containing contact information encoded as a vCard and displays it using a custom framework or library.

raspberry pi

This C code snippet is a driver for MaxDetect series sensors using the wiringPi library, providing two functions to wait for pin transitions and read bytes from the MaxDetect bus. The code is licensed under the LGPL version 3 or later and is specific to the MaxDetect series sensors and wiringPi library.

The rht03.c C program is a driver for the MaxDetect series RHT03 sensor, designed to run on a Raspberry Pi device, and it continuously reads and displays temperature and humidity values from the sensor. The program is distributed under the GNU Lesser General Public License (LGPL) version 3 or later, written by Gordon Henderson and part of the wiringPi project.

robot

The screenshotMonitor function captures a screenshot of a specified monitor, resizes it, and returns it as a PNG buffer, using the screenshot-desktop and sharp modules to handle image processing and capture.

The code requires the node-screenshots library and exports a single function, screenshotWindow, which takes a window argument and returns a PNG screenshot of the corresponding desktop application window. The function identifies and captures the window, converts the image to PNG format, and returns it as the result.

The getScreenSize function is used to retrieve the current size of the screen, and it can be accessed from other JavaScript files by importing the module. The module is exported using module.exports = getScreenSize.

The moveMouse function moves the mouse cursor to a specified position on the primary monitor by scaling the input coordinates and using the mouse-controller library. It requires the node-screenshots library to get the list of monitors.

The clickMouse function uses the node-screenshots and mouse-controller modules to simulate a left mouse click at a specified position (x, y) on the primary monitor. This function is exported as a module, making it available for use in other scripts.

The keySend function is designed to simulate typing a string on the keyboard with optional special key presses, using the robotjs library to interact with the mouse and keyboard. The function takes a string to be typed and an array of special keys to be pressed, and uses a loop to simulate typing the string with realistic timing and modifier key presses.

This code simulates mouse events using Core Graphics and Core Foundation frameworks, allowing for functions to set the mouse position, simulate mouse button clicks, and retrieve the current mouse position. It uses a combination of C-style includes and C++ code, suggesting it may be a wrapper around C code, to create a comprehensive mouse simulation tool.

scraping

This JavaScript code imports various modules and sets constants for a project directory, then defines two functions, getLocations and getLocation, which respectively retrieve a list of locations and extract specific data from each location's webpage. The getLocation function makes a GET request to a URL, extracts XPath expressions for elements containing day names, times, and deals, and then maps the results to an object with dotw, time, and deals properties.

This code uses Selenium to scrape location names and descriptions from Google Maps search results, handling pagination to retrieve all available data. It then prepares the data for further processing or storage, likely in JSON format.

The code imports necessary modules and functions, sets environment variables, and defines two main functions: loadLocations() and getAllLocationsData(). These functions interact with file systems, Google Maps, and Selenium to load and update locations data, which is then written to a JSON file.

shell-parse

The code is a parser for a Bash-like shell scripting language, using regular expressions to tokenize the input string and apply specific parsing rules for quoting and syntax. The parser handles various syntax elements, including single and double quotes, control characters and keywords, and backslashes and dollar signs, to correctly interpret the input string.

usage

The systemUsage function monitors system CPU usage and memory usage over time, calculating and returning the average percentage usage in an object format. It measures CPU usage at regular intervals, calculates the average CPU usage, and stores memory usage data in an object.

The code uses the D3.js library to create a graph that displays system usage data over time, with the option to use a fallback data source if the primary data is missing. The graph is customized with a color palette and axis labels, and it displays a line for each group in the data.

The code requires dependencies on fs, path, os, and child_process to interact with the file system, work with file paths, and execute system commands. The systemBuffer function generates a graph usage PNG image from a given data parameter, writing and converting an SVG to a PNG before returning the PNG image as a buffer.

uuid

This code provides a set of functions for generating, converting, and manipulating UUIDs, including support for SHA-1 hashing.

vnc

This code snippet configures a Linux desktop for remote access using VNC by launching a window manager and starting a VNC server on port 5900. This allows another computer to connect and control the Linux machine remotely.

This shell command executes a script (../novnc/utils/launch.sh) with VNC functionality enabled (--vnc) and connects to the VNC server at localhost:5900.

This command runs a script with VNC functionality enabled. The script is launched remotely using the VNC server at localhost:5900.

This code sets up a local copy of the noVNC project by creating a directory, checking if a "master" branch already exists, and cloning the repository from GitHub if necessary. It then lists the contents of the "novnc" directory and displays the current working directory.

This code installs the live-server package globally and then starts a local web server serving the "novnc" project, typically opening a browser window to display the project's content.

This Dockerfile configures a container to run a VNC server with a customized resolution, scaling, and user account.

This script automates the setup of a Selenium testing environment on a Linux machine by installing required dependencies, configuring the system, and setting up the Selenium server and ChromeDriver.

This Bash script sets up a headless environment with a virtual display, starts Selenium, a window manager, and a VNC server for remote Selenium testing.

This code prepares a directory and generates a VNC entry point script for a Jupyter/Angular project using an npm script.

This code sets up and starts a Selenium VNC server for a Jupyter/Angular project by navigating to the project directory and executing npm scripts to start the server and install necessary dependencies.

wget

The provided wget command downloads a website's contents with various options to customize the download process, including speed limits, downloading linked pages, and converting file references. The command options include settings for download speed, user agent, recursive downloading, and ignoring the robots.txt file to access the website's contents.

The wget command is used to download a website, specifically excluding directories /forums, /files, /images, /gallery, /nc, and /diane. The command uses options --mirror, --convert-links, -nc, and -r to retrieve the site recursively and handle links and failed downloads.

This code uses the wget command to download a website's documentation section, including its dependencies, using a recursive approach to download only the required files. The code includes numerous options to customize the download process, such as avoiding overwrites and waiting between downloads to avoid overwhelming the server.

window enum

This macOS code retrieves a list of open windows and their titles, storing them in global variables and using two functions: enumWindows to get the list of windows and getTitle to retrieve the title of each window. The main function iterates over the list of windows, calling getTitle to print each title to the console.

The getTitle(int i) function retrieves the title of a window with the specified layer index i by searching through an array of window dictionaries and constructing a string with the window's layer index and owner name.

The getTitle(int i) function searches for a window with a matching layer index i in an array of window dictionaries.
If found, it constructs a string with the window's layer index and owner name, and returns a duplicate of this string as a C-style string.

windows

The code defines a static class ProgramExtensions in the window_tracker namespace, which imports various Windows API functions from the user32.dll library and provides methods to retrieve window text, find windows, and retrieve the foreground window. The class includes a delegate EnumWindowsProc to filter which windows to include and uses various attributes and classes to handle the imported functions and their return types.

The C# code, located within the window_tracker namespace, retrieves a list of windows that meet certain conditions (e.g., non-zero height, non-empty title, matching process title) using the FindWindows method from the ProgramExtensions class. The filtered window details, including their titles, process names, and foreground status, are then printed to the console.

The.NET project file is a Visual Studio solution file in XML format that declares the project, imports external files, sets project properties, and specifies references and compilation settings.

The.NET project file is a XML-based file that outlines the project's properties, references, and compilation settings. It includes sections for project declaration, importing external files, project properties, debug and release properties, references, and compilation items, providing a comprehensive description of the project's configuration.

A Microsoft Visual Studio solution file, specifically a .sln file, contains metadata and configuration information for a Visual Studio solution, including project references, solution configurations, and extensibility settings. The file is divided into several sections, including global information, project references, and extensibility settings.

This is a command line instruction to build a project using MSBuild, with the executable file located at C:\Program Files (x86)\MSBuild\14.0\bin\amd64\msbuild.exe and the project file being "window tracker.csproj".

demo

The code imports a module named Core from the current directory and uses it to import the node express.ipynb module from the Frameworks directory, assigning it to the variable express. It then calls a sendResult function on an object, passing the express module as an argument, likely to serve the results of executing the node express.ipynb file.

Code Breakdown

The code imports a module named Core and calls its evalNotebook method to evaluate a Jupyter Notebook file named file system.ipynb, passing a custom argument 'memory-fs' || 1.

This code imports the Core module, invokes its interpret function with a list of keywords, and assigns the result to a variable. The result is then passed to a function named sendResult on a global object $, but the purpose of this function is unclear without more context.

This code provides automatic language detection and flexible code structure, allowing for simplicity and clarity without requiring explicit language specification.

The manage_server function is a basic server management function that connects to a server, retrieves recent activity logs, costs explorer data, and instance information, and returns this data as a dictionary. It includes error handling to catch and print any exceptions that may occur during server management.

The code snippet highlights the importance of choosing the right method for handling multiple asynchronous operations in JavaScript. While Promise.all works, the recommended approach using runAllPromises likely offers more efficient and flexible management of asynchronous tasks.

This code defines a function import that returns another function, but the returned function is immediately invoked, making the entire block importable as a module.

This code enables exposing functions and search services as an Express HTTP service, allowing them to be accessed via HTTP requests, making API endpoints available for external usage.

To start a Docker Selenium Grid in AWS, follow these steps:

Pull the official Selenium Docker image, then run a container with the necessary port mapping and shared memory allocation. Alternatively, create an ECS cluster and service using Docker Compose and start the service with the AWS CLI.

To incorporate Angular components, identify the necessary components for your project and integrate them into your existing codebase, ensuring proper configuration and setup. Once integrated, test the components to ensure they function as expected and meet your UI/UX requirements.

The code utilizes various tools and features to enhance development, including automatic GitHub branching, real-time deployment, and monitoring of external file changes. It generates word clouds for import and require statements, as well as notebooks, and focuses on documentation detailing tools and features used.

This code sets up a development environment for a Jupyter project by installing necessary packages, configuring Git, and initializing a repository. It then pulls the latest code from a remote repository and builds the project.

This code updates a Jupyter project by pulling the latest changes from a remote repository, resetting the local branch, and reinstalling project dependencies.