Test benefits of pandas parallelization libraries
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ideas
- Dominant language
- Python
- Stars
- 23
- Forks
- 9
- Avg merge
- 5d 12h
- Merged PRs (30d)
- 4
Description
Libraries such as
- https://github.com/jmcarpenter2/swifter
- https://modin.readthedocs.io/en/stable/getting_started/quickstart.html
promise big speedups to dataframe operations, so we'll want to test their potential to accelerate prx. https://modin.readthedocs.io/en/stable/getting_started/quickstart.html seems especially promising, as it looks like they try to completely emulate the pandas API.
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Start by locating the pandas dataframe operations in prx and review how they are currently executed. Evaluate swifter and Modin against representative operations, then document whether either library provides meaningful speedups without breaking the pandas API expectations.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- pandas, python
- Domain
- data, performance
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100