Skip to main content

iterpy

Project description

iterpy

Open in Dev Container PyPI Python Version Roadmap

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

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

iterpy-1.8.0.tar.gz (35.8 kB view details)

Uploaded Source

Built Distribution

iterpy-1.8.0-py3-none-any.whl (9.3 kB view details)

Uploaded Python 3

File details

Details for the file iterpy-1.8.0.tar.gz.

File metadata

  • Download URL: iterpy-1.8.0.tar.gz
  • Upload date:
  • Size: 35.8 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for iterpy-1.8.0.tar.gz
Algorithm Hash digest
SHA256 46fe56776f8fde949127f0e0a7f7f9cb67f63fc3b3b061dc526fa07b0bb3e341
MD5 abc2415586800e0c7ba9f1c1aea66df5
BLAKE2b-256 627dc3e53956ef3de1d56a1b8bf6b955d997f089230a7f0eb37b4c2e424578da

See more details on using hashes here.

File details

Details for the file iterpy-1.8.0-py3-none-any.whl.

File metadata

  • Download URL: iterpy-1.8.0-py3-none-any.whl
  • Upload date:
  • Size: 9.3 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for iterpy-1.8.0-py3-none-any.whl
Algorithm Hash digest
SHA256 83551a4d0db1ac04102fcc54377682b060f45f4128a1aef5dc9d171446d5f58f
MD5 3373f790bb3e312b8723ba91681c0e5c
BLAKE2b-256 f246fdffbe1583c256e304b38e3869af7f34fca884537b79e382884f3c06e2cf

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page