microsoft / microsoft/typeagent-py
Code Quality & Cleanup (from TODO.md)
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- Dominant language
- Python
- Stars
- 884
- Forks
- 75
- Avg merge
- 3h 2m
- Merged PRs (30d)
- 2
Description
In this issue we track possible Code Quality & Cleanup Items from TODO.md
Code Quality & Cleanup
P1 - High Priority
- - [P1, large] Make coding style more uniform (e.g. docstrings)
- - [P1, large] Reduce code size
P2 - Medium Priority
- - [P2, small] Avoid most inline imports: fixed #113
- - [P2, medium] Break cycles by moving things to their own file if necessary fixed #113
- - [P2, medium] Unify or align or refactor
VectorBaseandEmbeddingIndex - - [P2, medium] Address
TODOcomments (too numerous) - - [P2, medium] Address
raise NotImplementedError("TODO")(five found) -- implement it
P3 - Low Priority
- - [P3, medium] Change inconsistent module names (Claude uses different naming style)
- - [P3, medium] Rewrite podcast parsing without regexes
- - [P3, medium] Switch from Protocol to ABC
- - [P3, medium] Reduce duplication between ingest_vtt.py and typeagent/transcripts/
- - [P3, small] Rename
kplib.pyto something ending in_schema.py
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 with TODO.md and choose a single unchecked cleanup item; the issue names VectorBase, EmbeddingIndex, ingest_vtt.py, typeagent/transcripts/, and kplib.py as investigation points. Define the selected item's scope and completion checks before changing code, then verify that the corresponding cleanup is complete without expanding into the other listed tasks.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- tooling
- Issue type
- Refactor
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Quiet
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100