public-apis VS public-api-lists

For inspirations on what type of agents I should build, I turned to the Public APIs GitHub repository which has a curated lists of free APIs. I narrowed my search for an API that does not require sign-up or an API key and returns useful information. I ultimately decided to use the Free Currency Exchange Rates API, which seemed promising upon some basic testing.

✅ public-apis/public-apis : https://github.com/public-apis/public-apis

Public-Apis Github Repo — A list of free public APIs.

Interesting thread at https://github.com/public-apis/public-apis/issues/3104

Use curl to access a free public API and get a random joke, cat fact, or whatever.

I remember the forking of https://github.com/public-apis/public-apis and the long git issue discussions. The company owning the repository stopped maintaining it but didn't give up control either. Over the years you've put in a lot of work in publicapis.dev and that is much appreciated.

Also, that isn't really a list of "contributors", but of "organisations with the most stars". Those are different things.

For example "public-apis"[1] didn't "contribute" anything as that's not a person, and looking at GitHub[2] there are a bunch of substantial contributors (the person who created the organisation/repo only has 12 commits by the way);

[1]: https://opensource-heroes.com/o/public-apis

[2]: https://github.com/public-apis/public-apis/graphs/contributo...

I have a few e2e projects, if that might help. While they can be deployed to AWS via the included terraform file (costs money) you can run them locally with docker. I list the projects from simplest to more complicated 1. I’d recommend starting at https://www.startdataengineering.com/post/data-engineering-project-to-impress-hiring-managers/ this is the simplest. 2. Once you have it running, and get an overview of the components( docker, ec2, Postgres), then I’d recommend looking at this article https://www.startdataengineering.com/post/data-engineering-projects-with-free-template/ to understand how the components work together. 3. Try out the pipeline with a data source if your choosing. I use https://github.com/public-api-lists/public-api-lists to get some data API. 4. Once you get a good understanding of how data is pulled and loaded along with how it’s scheduled, then I’d recommend looking at this airflow project https://www.startdataengineering.com/post/data-engineering-project-for-beginners-batch-edition/ I posted about this a while back https://www.reddit.com/r/dataengineering/comments/ygieh8/data\_engineering\_projects\_with\_template\_airflow/ Hope this helps. LMK if you have any questions.

And then try out the pipeline with a data source if your choosing. I use https://github.com/public-api-lists/public-api-lists to get some data API.

Suggest to take a look through https://github.com/public-api-lists/public-api-lists

Sounds like you're stuck in tutorial purgatory. It's time to drop the training wheels and apply the knowledge you've learned to some personal projects. Pickup pygame, or build a web scraper. Here's a list of free public api's. This might get you started. https://github.com/public-api-lists/public-api-lists

Public-api-lists (fork of original one I linked)

public-api-lists Another great repository to find good APIs for development. It has more than 4K stars on GitHub. These APIs are more inclined towards the development side. It is also organized into suitable categories.