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-1.8.1.tar.gz (36.1 kB view details)

Uploaded Source

Built Distribution

iterpy-1.8.1-py3-none-any.whl (9.4 kB view details)

Uploaded Python 3

File details

Details for the file iterpy-1.8.1.tar.gz.

File metadata

  • Download URL: iterpy-1.8.1.tar.gz
  • Upload date:
  • Size: 36.1 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for iterpy-1.8.1.tar.gz
Algorithm Hash digest
SHA256 c368b45b573c7cbc1eac5a6ca51745fe41576a1a6ac343b3672972f3e20745ac
MD5 14f73d8962cc0aee57fba5af6402843e
BLAKE2b-256 05c292cafa2781dc59e3f5164a997684edde0312d2e588b4d2e2608e2d09762f

See more details on using hashes here.

File details

Details for the file iterpy-1.8.1-py3-none-any.whl.

File metadata

  • Download URL: iterpy-1.8.1-py3-none-any.whl
  • Upload date:
  • Size: 9.4 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? Yes
  • Uploaded via: twine/4.0.2 CPython/3.11.8

File hashes

Hashes for iterpy-1.8.1-py3-none-any.whl
Algorithm Hash digest
SHA256 de6a60f32d33b64798063ffed944f20676e7289d18ee361177d7388e2dfa6d28
MD5 57dd1bff723f7af24a47773ce0b45d2b
BLAKE2b-256 2e17fed344881bbb9d0d427f42399e40b22fd8df26e6db09352e5df7188bf651

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