matloff / matloff/R-vs.-Python-for-Data-Science
Different Python versions
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- Stars
- 448
- Forks
- 40
- PR merge metrics
- No merged PRs in 30d
Description
I'm a CRAN package developer and I have had many people call for a Python implementation of one of my packages. I got a student to create this and we have it all working in base Python but I wanted to take advantage of the same C code that the R package uses.
This is when I ran into Python problems. I've tried several recommended ways of interfacing existing C code to Python but for each way there are Python installs that cannot download and use my package! You have to be using the "right" version of Python in order to be able to use the package. This is just my understanding so please do correct me if i'm wrong on this.
This, to me, is a huge downside of Python right now. Why should a user have to change their software to run my package? I can see an argument for forcing users to upgrade, but most Python packages that run on 2.7 don't run on 2.6 or 3.0. At least with R packages get checked and removed if authors don't update them.
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First steps
- Read the whole issue, then the project's contributing guide.
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- Open a pull request that references the issue number.
Research direction
The issue names no files, tests, or entry points. Start by clarifying the requested Python/C interface and supported Python versions; done would require an agreed compatibility target and evidence that the package installs on it.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- c, python, r
- Domain
- developer-experience
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100