fsspec / fsspec/filesystem_spec
Towards a roadmap
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- Python
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Description
Following a get-together of a few contributors, we have some thoughts on topics that could be part of a mid-term roadmap for fsspec. Here I will list them, with the intention that they be linked to issues discussing each in depth, when there is enough momentum to try to tackle them.
This issue might become a doc page for better visibility. Edits and comments are welcome.
- organisation structure of fsspec
- possible move to a separate github org with a fully-fleshed identity (coherent docs, logo). Can include repos currently in various places (e.g., dask, intake, dvc, ...)
- feedback and conversation options for users, better than GH issues. GH discussions maybe the easiest starter.
- test-specific repo
- regular (e.g., nightly) testing of all implementations
- a clear path to register new implementations and an expected interface for them to participate
- dashboard or alert system to surface problems before release
- obvious place for benchmarking
- push for performance on a number of fronts
- (optional) threaded operations for non-async filesystem batch operations
- move to better backend libraries (e.g., ditch paramiko)
- benchmark-specific cases, ideally with some transparent feedback metric
- directory and path utilities
- make multiple pluggable dircache implementations, including persistence
- iter / gen / pagable listings
- generalised string and maybe Path utilities in concrete location with better testing
- module of functions operating on URLs, dispatching to filesystems
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
This issue is a broad roadmap covering organization, testing infrastructure, performance, and directory/path utilities, with no specific files or tests named. Start by reviewing the listed topics and any follow-up issues that discuss them in depth. Done would require selecting one topic and turning it into a concrete, scoped piece of work or documentation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- developer-experience, documentation, performance, testing
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100