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Gist 7e49fbcdf09b9db1d220cd51c4d7ecd3

✓ Published0🌍 Public
WWill Carter
Last edited Jan 29, 2020
Created on Jan 29, 2020

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.

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Gist fe8d41d0b0dfdbcb0a48748667d3793c

This example demonstrates a command-line hiking trail finder built in Ruby, using the `HikingProject::CLI` class to manage user interaction. It shows a text-based menu system where users enter coordinates and select from a list of trails, with each trail’s details displayed as plain text output. The code relies on Ruby’s built-in `gets` for input and `puts` for output, with no external libraries or APIs. It illustrates a simple loop-based control flow, handling user choices like “list,” “restart,” or “exit” to relist trails or show full descriptions. The data source is hardcoded sample trail summaries, and no rendering or visualization beyond terminal text is performed.

WWill Carter
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Gist 78d64cef1c7947a01ba11260ea70f213

This example shows a data-visualization of hiking trail data from the HikingProject API, mapping trail names, lengths, and summaries into a custom layout. The code defines a `HikingProject::Trail` class that parses trail attributes and stores them in a class-level array, enabling aggregation of multiple trail records. It demonstrates a programmatic approach to structuring dataset properties for later rendering, though it does not include explicit drawing code. The visualization likely relies on a JavaScript library such as D3.js for scaling or positioning, but the provided snippet focuses solely on Ruby object initialization and data collection, leaving the visual output implicit.

WWill Carter
88% match
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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.

WWill Carter
87% match
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Gist 5b4bc2298efaebbc2dbc9e5c51dff8c3

This example demonstrates a command-line trail information viewer that fetches and displays detailed hiking trail data. The code defines a `show_full_description` method that calls `HikingProject::Scraper.scrape_full_detail` with a trail URL to populate additional attributes like features, overview, and description, which are then printed to the console. It uses the custom `HikingProject` library to scrape data from a hiking project API, and the method concludes by invoking a `menu` to return control to the user. The visualization focuses on text-based output rather than graphical rendering, relying on string interpolation to present the scraped details clearly.

WWill Carter
87% match
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Gist 9de1e73d1f5e2e590de70ca609b77b5d

This example shows a CLI data-scraping application that compiles hiking trail information into a structured collection, using the HikingProject API to populate trail attributes like name, length, and features. The code demonstrates the Factory Pattern, where a `create_from_collection` method mass-instantiates trail objects from an array of hashes, while `add_trail_details` enriches individual trails with additional detail data. The implementation relies on Ruby’s metaprogramming via `send` to dynamically assign attributes, and stores all instances in a class-level `@@all` array for easy access. Though no visualization library is used, the pattern is typical for preparing data for later graphical display.

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Gist 6f679efa6a447a82a5721cd0499b832c

This example demonstrates a Ruby scraper that fetches hiking trail data from the Hiking Project API using the `Net::HTTP` and `JSON` libraries, parsing the JSON response to extract trail information. The code constructs a URL with specific latitude, longitude, and API key parameters, then converts the HTTP response into a structured Ruby hash via `JSON.parse`. Although the `scrape_trail_detail` method is defined, it remains empty, indicating that the visualization focuses on the initial API request and data retrieval rather than detailed trail scraping. The example shows how raw JSON data becomes accessible for further processing, highlighting the API integration pattern without displaying any graphical output.

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Gist c5fc191ad8f9d03e7de1b779aca099d2

This example shows a command-line Ruby program that populates a hiking-trail database from a collection of trail data. The code defines a `HikingProject::Trail` class with attributes for name, summary, and length, and uses mass assignment to initialize each trail from a hash. It includes a class method `create_from_collection` that iterates over an array of trail hashes, creating a new trail instance for each, and an `add_trail_details` method to merge additional details into an existing trail. The program relies on the standard Ruby `attr_accessor` and `self.send` to dynamically set attributes, and it stores all trails in a class-level `@@all` array, accessible via `.all`. The data source appears to be a pre-structured array of hashes, with no external APIs or rendering libraries involved.

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Gist 7953756211e421d7ef4c4a284461bff1

This visualization demonstrates how a Ruby scraper populates trail detail fields with placeholder text, using a `scrape_full_detail` method that returns hardcoded strings for features, overview, and description. The code shows a simple API pattern where trail data is assembled into a hash, but does not include any actual visualization libraries or rendering logic. The example focuses on the data-fetching layer rather than graphical output, making no use of D3.js, Canvas, or Three.js. The rendering approach is absent entirely, as the code contains no drawing commands or data-binding operations. The output would be raw text fields displayed in a list or card format, but the snippet reveals no visual representation technique.

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