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iterpy

Project description

iterpy

Open in Dev Container PyPI Python Version Tests Roadmap

ALPHA: APIs can change dramatically without notice.

Python has implemented map, filter etc. as functions, rather than methods on a sequence. This makes the result harder to read and iterators less used than they could be. iterpy exists to change that.

You get this 🔥:

from iterpy import Iter

result = Iter([1,2,3]).map(multiply_by_2).filter(is_even)

Instead of this:

sequence = [1,2,3]
multiplied = [multiply_by_2(x) for x in sequence]
result = [x for x in multiplied if is_even(x)]

Or this:

result = filter(is_even, map(multiply_by_2, [1,2,3]))

Install

pip install iterpy

Usage

from iterpy import Iter

result = (Iter([1, 2])
            .filter(lambda x: x % 2 == 0)
            .map(lambda x: x * 2)
            .to_list()
)
assert result == [4]

Prior art

iterpy stands on the shoulders of Scala, Rust etc.

Other Python projects have had similar ideas:

  • PyFunctional has existed for 7+ years with a comprehensive feature set. It is performant, with built-in lineage and caching. Unfortunately, this makes typing non-trivial, with a 4+ year ongoing effort to add types.
  • flupy is highly similar, well typed, and mature. I had some issues with .flatten() not being type-hinted correctly, but but your mileage may vary.
  • Your library here? Feel free to make an issue if you have a good alternative!

Contributing

Conventions

Philosophy

  • Make it work: Concise syntax borrowed from Scala, Rust etc.
  • Make it right: Fully typed, no exceptions
  • Make it fast:
    • Concurrency through .pmap
    • (Future): Caching
    • (Future): Refactor operations to use generators
  • Keep it simple: No dependencies

API design

As a heuristic, we follow the APIs of:

In cases where this conflicts with typical python implementations, the API should be as predictable as possible for Python users.

Devcontainer

  1. Install Orbstack or Docker Desktop. Make sure to complete the full install process before continuing.
  2. If not installed, install VSCode
  3. Press this link
  4. Complete the setup process
  5. Done! Easy as that.

💬 Where to ask questions

Type
🚨 Bug Reports GitHub Issue Tracker
🎁 Feature Requests & Ideas GitHub Issue Tracker
👩‍💻 Usage Questions GitHub Discussions
🗯 General Discussion GitHub Discussions

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