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Markdown parser that works with most awesome lists #4

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Ly0n opened this issue Nov 24, 2021 · 2 comments
Open

Markdown parser that works with most awesome lists #4

Ly0n opened this issue Nov 24, 2021 · 2 comments
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@Ly0n
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Ly0n commented Nov 24, 2021

We need a better more robust parser to work with all awesome lists that get tested by the linter.

@tjarkdoering tjarkdoering self-assigned this Dec 3, 2021
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I feel like doing this.
What are our requirements for this? We have some in the other issues already (#5 , #2 , maybe #7 ).

What I am currently thinking about:
This should work as a GitHub-Action that creates, then updates one or multiple csv files that can then be used further by AwesomeCure.

@Ly0n Ly0n changed the title Better parser that works with all awesome list Markdown parser that works with all awesome list Dec 3, 2021
@Ly0n Ly0n changed the title Markdown parser that works with all awesome list Markdown parser that works with all awesome lists Dec 3, 2021
@Ly0n Ly0n changed the title Markdown parser that works with all awesome lists Markdown parser that works with most awesome lists Dec 3, 2021
@Ly0n
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Ly0n commented Dec 3, 2021

This is the library that we use at the moment:
https://github.com/protontypes/AwesomeCure/blob/main/awesomecure/awesome2py.py
It was developed by @kikass13, it works perfectly for OpenSustain.tech.

What are our requirements for this?
To make this project work with the most awesome list we have to create a much more generic version because you do not want to lose the context information of the list like the rubric and the oneliner. A simple solution would be to use this package here:
https://pypi.org/project/urlextract/
In this case, we would lose the context information like the onliner.

You could also have a look at the linter itself because this could also needs to parse the markdown to lint the single enties.
https://github.com/sindresorhus/awesome-lint

Another solution could be found here but the code is not under an open-source license:
https://github.com/lee212/md2dict

This should work as a GitHub-Action that creates, then updates one or multiple csv files that can then be used further by AwesomeCure.

That would be a good solution. When we refactor AwesomeCure as a real python package we can separate it into different modules.

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