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Discover Twitter Spaces is an open-source SvelteKit tool for finding Twitter Spaces via Twitter API data, with its own searchable API endpoint.
Discover Twitter Spaces is an open-source SvelteKit web application that helps users find live Twitter Spaces using data from the Twitter API, exposing both a search UI and a public JSON API endpoint. The project is built by Navneet Sharma and released under the MIT License, and it is deployed on Vercel as a serverless application.
Discover Twitter Spaces is a tool for discovering Twitter Spaces by querying Twitter's API. It takes a search term as input, for example bitcoin, and returns matching Spaces data through a web interface or via the /api/spaces endpoint with a query parameter such as /api/spaces?search=bitcoin. The application is built with SvelteKit and Svelte, written in TypeScript, and styled with Tailwind CSS and PostCSS. Redis and serverless functions are part of the stack, and the SvelteKit Vercel adapter handles deployment.
The project setup is straightforward: clone the repository from GitHub, install dependencies with yarn, copy the .env.example file to .env and fill in the required Twitter and Redis keys, then run yarn run dev for local development. To deploy, use yarn run build:vercel and then yarn run preview. The Twitter API route is implemented in src/routes/api/spaces/index.ts.
Yes, the project is open-source and released under the MIT License, so the code is free to use, modify, and distribute. You will need your own Twitter API credentials to run the application.
The API endpoint is /api/spaces on the deployed application, and it accepts a search query parameter, for example /api/spaces?search=bitcoin, to return relevant Spaces data.
The application uses SvelteKit and Svelte, TypeScript, Tailwind CSS, PostCSS, the Twitter API, Redis, serverless functions, and the SvelteKit Vercel adapter.
The project was created by Navneet Sharma and is copyrighted as of 2021. It is inspired by the find-twitter-space project by Rakhisharma.
Clone the repository, install dependencies with yarn install, set up the .env file based on .env.example, and run yarn run dev. For a production-style build, run yarn run build:vercel and then yarn run preview.
