campfire transcript export

Gist 5ea363dfe112d08281a8c89a3f31bcff

This example scrapes trail data from a website, extracting features, overview, and description sections into a structured hash. It uses Nokogiri to parse the HTML and XPath queries to locate the relevant headings and their adjacent content, cleaning the text by removing line breaks. The code demonstrates a straightforward scraping pattern for capturing semantic sections, though it does not include visualization logic or rendering libraries. The data source is a single trail page URL, and the output is a formatted description ready for further processing or display.

53% match

Tributary inlet

This example visualizes a chat log by loading it as CSV data and plotting each message’s timestamp on a simple SVG canvas. The code uses D3.js to parse the CSV file and displays the data points, with a custom date-reformatting function converting the timestamps into a standardized format. The visualization shows the distribution of messages over time, though the specific rendering of points or marks is not implemented beyond loading and logging the data. The configuration specifies a 280×400 pixel SVG display with animation settings, but the actual drawing logic remains minimal. The example relies on D3’s CSV parsing and time formatting APIs to handle the input data.

CCBasis

53% match

Gist f72a3553521c158f0eb0dccbe774455e

This example demonstrates a web scraper that extracts detailed trail information from a hiking website. It shows how structured data can be programmatically retrieved from HTML pages, specifically pulling out features, overview, and description sections. The code uses the Nokogiri library to parse the document and XPath queries to locate the relevant heading elements. After extracting each section, it cleans the text by removing newlines and excess whitespace. The scraper returns a hash containing the three descriptive fields, making the data readily accessible for further processing or visualization.

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<title>Oral History Transcript

This visualization parses an oral history transcript encoded in TEI XML, displaying the dialogue between two speakers as a series of connected text blocks. It shows the conversational flow, with each speech act rendered as a separate node and the speaker identified by color-coded labels. The code uses D3.js’s `d3.forceSimulation` for layout and `d3.select` with data binding to manage the nodes and links, while the raw XML is loaded via `d3.xml` and traversed with DOM methods to extract speaker turns and text. The visualization highlights gaps in speech (e.g., `<gap n="00:00:28"/>`) by adding time-stamped ellipses, making the transcript’s pacing and pauses explicit.

CCliffordAnderson

Gist 182083

This example visualizes the output of a shell script that forcibly reinstalls Ruby Version Manager (RVM), capturing the terminal session as a log. The data is a sequence of command prompts and system responses, shown as text. The visualization would likely render this as a timeline or list of terminal output, highlighting the progression of commands, the confirmation prompt, and the cascade of permission errors during the uninstall. It emphasizes the iterative nature of the process and the repeated permission failures, turning a mundane system log into a visual narrative about software management and error handling.

DDylanFM

Gist 7e49fbcdf09b9db1d220cd51c4d7ecd3

The example visualizes a command-line trail-finder application built with Ruby, using the HikingProject API as its data source. It shows a list of trails near a specific latitude and longitude, displaying each trail's name, length in miles, and summary. The code defines a `list_trails` method that calls `HikingProject::Scraper.get_trails_from_api` to fetch trail hashes, then creates trail objects via `HikingProject::Trail.create_from_collection`. It iterates through `HikingProject::Trail.all` to print each entry with an index, separated by dashed lines, before returning to the menu. No graphical rendering is involved; the visualization relies solely on text output and the standard Ruby API.

Gist d6a23c33db14aba44cb192c90ce81142

This example demonstrates a data-visualization pattern for displaying trail information retrieved from an API, using Ruby to structure the data before rendering. It shows a collection of three trails, each with a name, length, and summary, formatted as a list of hashes. The code explicitly constructs dummy trail data, representing what would be fetched from an external service, and organizes it into an array for further processing. While no specific visualization library is used in the provided snippet, the structure suggests a preparation step for a charting tool such as D3.js or a mapping library that would consume the trail metadata. The rendering approach is not shown, only the data assembly phase.