The Fediverse Sharing Button is a tool that allows users to share content from their site to Fediverse platforms. It supports various Fediverse software, lets users choose text to share, and remembers the last Fediverse domain used. You can get the code or add it to WordPress. It's open source, and feedback is encouraged on its GitHub page.
Shows a logo of supported Fediverse software to users.
Allows users to share selected text from a webpage.
Remembers the last Fediverse domain used for sharing.
Provides a WordPress plugin option for easy integration.
A tool to encode or decode URLs quickly and efficiently.
Generates secure and random passwords based on specific criteria set by the user.
An experiment that lets users draw sketches which are converted into 'sketchy' lines to give them a draw-by-hand appearance.
A tool for network engineers to calculate various aspects of subnets, like network and broadcast addresses.
A collection of CSS cursor styles that users can browse and easily implement in their websites.
Creates QR codes from text input, making it easy for users to generate and download QR codes.
Allows users to encode text into Base64 format with ease.
Provides statistical analysis of a block of text, including word count, sentence count, and readability scores.
Compute the MD5 hash of a given text input.
Creates random filler text (Lorem Ipsum) for use in design mockups.
Translates English text into Pig Latin and vice versa.
Allows users to share content with the fediverse.
Generates HTML buttons for sharing to Facebook, Twitter, and other social networks.
Allows users to display unlocked Zwift achievements on their blogs or websites. Provides HTML and JSON code to showcase their achievements.
The site offers instructions for hosting the achievements showcase on different platforms like Neocities and Glitch.
Generates domain names from public domain books using a Python script, making it easier to use by integrating it into a website.
Tracks the use of alt text in social media posts, highlighting exceptional examples.
Provides information and tips on writing better image descriptions to promote accessibility.
The project is accessible through its website and a Fediverse account.
Allows users to search through dialogue lines in public domain movies. Provides links to Archive.org where users can watch or download the films.
Helps users find voice samples in movies by searching subtitles. Users can potentially extract spoken words with external tools, especially if music is present.
Allows you to use generative art as placeholders in images, providing visual interest without being mistaken for the final design.
Provides link and instructions for distributing free Fight Fascism stickers, inspired by Angus Johnston’s campaign.
Originally linked to R. Luke DuBois' adaptation of Umberto Eco’s essay Ur-Fascism, offering educational resources.
Hosted on Glitch, allowing users to create personal versions of the project for spreading the message.
Formats a list of URLs into HTML or Markdown code by dynamically loading the title of each page.
Optionally adds the domain name after each link for easy identification.
Allows the links to be formatted within bullet lists for organized presentation.
Create responsive and customizable sharing buttons that fit your website's style.
The sharing buttons do not collect any user data, ensuring privacy.
Generate code that includes sharing options for different social networks.
A map created using Felt to display locations of subway artists in NYC.
Option to download data related to NYC subway artists.
Uploaded list of performers and their locations for each subway station.
These bots tweet and toot random datasets from NYC OpenData. They select data that contain location information, such as latitude and longitude, to create maps.
The bot looks through datasets on NYC OpenData using the Socrata Discovery API. It uses the 'data.cityofnewyork.us' as the dataSource and searches through datasets of datatype 'datasets'.
The bot uses Mapbox to generate maps from datasets containing location information. Due to limitations, it uses a randomly selected subset of 100 datapoints.
Instructions are provided for users to create their own version of the bot for their city using OpenData networks.