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Next Steps #49

@ntninja

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@ntninja

Since #1 is clogged with all the many comments I open a new issue here. Feel free to continue the discussion below and I'll keep the following updated as things develop. Also feel free to create separate issues / repos to coordinate and I'll add the relevant links below.

Next steps (networking, stalled – please see the “storage” section below):

Next steps (storage, simpler):

  1. Port https://github.com/ipfs/py-datastore to Python 3
    (Suggestion: Use Python's lib2to3 and just drop Python 2 entirely.)
  2. Convert datastore to use async/await using some library (maybe https://pypi.org/project/aiofiles/ ?) for file access The trio framework is used for async I/O now
  3. Implement a https://github.com/ipfs/go-ds-flatfs compatible backend for the above library
  4. Write a minimal py-ipfs “implementation” that can fetch blocks from the local $IPFS_PATH directory and expose them with an API similar to what https://github.com/ipfs/py-ipfs-http-client currently offers (goal here is to eventually have a drop-in replacement)
    • In progress by @Alexander255 (no public code yet, most work happens in py-datastore)
  5. Implement a simple Python HTTP server that emulates the block/{get,put,rm,stat} API that serves blocks from the local $IPFS_PATH directory
  6. (Stretch goal) Implement a badgerds compatible backend for py-datastore
    • There is an issue requesting Python bindings for the Go library, but no work has been done yet:
      dgraph-io/badger#984
  7. Beyond: Start integrating IPLD to expose the UnixFS files stored in those raw blocks…

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