Gist 842ac39b24599fe93d18a0c536f0ea69

100%

Gist 842ac39b24599fe93d18a0c536f0ea69

✓ Published0🌍 Public

Last edited Aug 24, 2017

Created on Aug 24, 2017

This example demonstrates a Node.js script that sends a base64-encoded image file to the TrueFace API’s face-detection endpoint, then logs the returned JSON response. It reads a local JPEG, converts it to base64, and posts it via the `superagent` HTTP client with `superagent-bluebird-promise` for promise support. The request uses the `x-api-key` header for authentication and targets `https://api.chui.ai/v1/facedetect`. The visualization shows the raw API output, not a graphical chart, highlighting a simple request–response workflow.

AI-generated description

Similar vizzes

Loading thumbnail…

Gist 5c673a7db6d8612eda9dee50ff2e4b80

This example demonstrates asynchronous file reading and HTTP request handling in Node.js. It shows how to extract the first line from a local file and retrieve the HTTP status code from a remote URL using two separate promise-based functions. The code uses Bluebird’s `Promise` constructor, Node’s `fs.readFile` API, and the `request` library for network requests. Each function returns a promise that resolves with the extracted data or rejects on error, illustrating a modular approach to handling I/O operations with promise chaining.

MMailnickko

61% match

Loading thumbnail…

Gist 1a03bf15beee9f72953b414669e44576

This example demonstrates a Node.js utility that asynchronously fetches the HTTP status code for a given URL. It first reads a text file using the `fs.readFile` method to extract a domain or URL from its first line, then passes that address to the `request` library’s `getStatusCodeAsync` function, which returns the server’s response code. The visualization shows how file I/O and network requests are chained through callbacks, highlighting the flow of data from local storage to remote servers without any graphical rendering.

MMailnickko

59% match

Loading thumbnail…

Gist fdfeb2b6c1c7c936cff968552d66277f

This example visualizes the flow of a failed HTTP request within a Node.js application, tracking the error from its initial 403 response through the complete async call stack. The visualization uses a structured log-and-trace rendering approach, where each line of the stack trace is displayed as a sequential node in a vertical flow diagram. The code relies on axios for making the POST request to the `/api/v1/Challenges` endpoint and Node’s built-in async/await pattern to propagate the error through layers like `ChallengeClient`, `ChallengeController`, and `AccountController`. The screenshot shows the raw error object with its nested `config` and `requestId` metadata.

HHoffmannP

57% match

Loading thumbnail…

Let's Make a Face Part I

This interactive visualization constructs a human face from a network of nodes and edges, using a physics-based layout to organize the features into a recognizable profile. The SVG scene is rendered with D3.js, and the arrangement is driven by a force-directed simulation, likely `d3.forceSimulation`, which positions the nodes based on attractive and repulsive forces. The face emerges as the system settles into a stable configuration, with nodes representing key facial landmarks like the eyes, nose, and mouth. The static HTML page loads the D3 library and a separate `bundle.js` script to execute the layout algorithm, producing a stylized, abstract portrait from raw graph data.

RRambo-chan

56% match

Loading thumbnail…

post-google-forms-nodejs

This example demonstrates how to submit form data directly to a Google Form using Node.js, bypassing the need for a browser interface. It shows a programmatic POST request that populates a form with fields such as size, email, delivery method, and address. The code uses the `superagent` library to send URL-encoded form data to the `/formResponse` endpoint of Google Forms. It explicitly maps each form field’s entry ID, like `entry.1721541334`, and includes both regular and "other" response options. The script logs the server response or any errors encountered during submission.

55un

56% match

Loading thumbnail…

Face

This interactive face is rendered as an SVG whose geometry is driven by D3’s force simulation, with nodes representing facial features. The visualization uses a custom D3 v5 force layout to position circles for eyes, a nose, and a mouth, demonstrating how force-directed algorithms can create structured, expressive shapes. The entire scene is drawn using D3’s selection and data-join methods within a React framework, while the HTML page loads D3 from a CDN and logs it to the console for verification. No external data source is used, as the node positions emerge purely from simulation physics.

MMuhammad Aboidrees Altraife

55% match

Loading thumbnail…

Smiley face Part I

This example displays a blank page intended to become a smiley face visualization. The code fetches a CSV file from a GitHub gist using JavaScript’s `fetch` API and logs its contents to the console. It uses vanilla HTML, CSS, and JavaScript without any external visualization libraries. The data source is a remote `.scv` file (likely a typo for `.csv`) containing the shape’s coordinates. The visualization itself is not yet rendered, only the data retrieval step is demonstrated.

Eelcr3ator

55% match

Loading thumbnail…

Let's make a face with D3.js!

A face drawn from a network graph animates as force-directed simulation moves its nodes. The D3.js code uses `d3.forceSimulation` with `forceX`, `forceY`, `forceCollide`, `forceManyBody`, and `forceLink` forces to arrange vertices from a JSON data file. The Canvas rendering updates on each tick, drawing edges with `drawEdge` and circular nodes with `drawNode` to form the face’s features.

Hhhhheeee

55% match