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I have ~4k start in 2 Python libraries. Both help fetch live news articles. Links below.
These were my first libraries.
I took the approach of promoting them as any other product. You have to "sell" your code. Even if it's 100% free.
In my opinion, the most important thing is DEMO. Just make a GIF where you showcase what your software does:
* 80% of engineers won't even bother to read the description
No one will spend their precious time trying to get through your code.
[0] https://github.com/kotartemiy/newscatcher Programmatically collect normalized news from (almost) any website.
[1] https://github.com/kotartemiy/pygooglenews If Google News had a Python library
I have ~4k start in 2 Python libraries. Both help fetch live news articles. Links below.
These were my first libraries.
I took the approach of promoting them as any other product. You have to "sell" your code. Even if it's 100% free.
In my opinion, the most important thing is DEMO. Just make a GIF where you showcase what your software does:
* 80% of engineers won't even bother to read the description
No one will spend their precious time trying to get through your code.
[0] https://github.com/kotartemiy/newscatcher Programmatically collect normalized news from (almost) any website.
[1] https://github.com/kotartemiy/pygooglenews If Google News had a Python library
These are impressive! The use of screenshots and figures really helps. I've also always thought Groue's GRDB is an example of great documentation and readme combination[1].
[1] https://github.com/groue/GRDB.swift
Maybe a story from a maintainer would help. To contextualize, the main SheetJS open source project https://github.com/SheetJS/sheetjs has over 28K stars.
tl;dr: the project involves "crowdsourced research" which benefits from popularity.
The main social goal with the project is data preservation and integrity. Large-scale economic and political decisions are made from data and analyses in spreadsheets. For example, last year in the UK, COVID cases were underreported thanks to Excel minutiae https://www.bbc.com/news/technology-54423988
Due to various corporate stratagems, the older data representations were intentionally obfuscated. To support Excel, many developers poked around at Excel files and guessed at the structures.
In this environment, the biggest challenge is finding worksheets with random corner cases. These types of files are not easy to create and fuzzing has limited effectiveness. This is where open source and popularity come into play. The open source and JS nature of the project helps reduce testing friction (https://oss.sheetjs.com/ runs in the web browser, no need to install anything) and encourage bug reports with test cases.
There will always be "entitled users" and "low quality bug reports" but that comes with the territory. There are also meaningful issues and code contributions. Efforts at trying to prevent the low quality contributions also discourage higher quality contributions.
I agree with you. Most my packages are around ~100 stars, and I'm met with a lot of respect and appreciatio.n[1][2]
My library for Correlation-IDs in Django[3] got implemented by AWX, which also was a nice experience![4] I maintain a lot of small packages, and maybe it is the Django/FastAPI community, but "you'll get a load of entitled users" is straight up not true in my experience.
[1] https://github.com/Intility/fastapi-azure-auth/issues/24
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