# RxPY **Repository Path**: mirrors_ReactiveX/RxPY ## Basic Information - **Project Name**: RxPY - **Description**: ReactiveX for Python - **Primary Language**: Unknown - **License**: MIT - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-08-18 - **Last Updated**: 2026-06-27 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README =============================== The ReactiveX for Python (RxPY) =============================== .. image:: https://github.com/ReactiveX/RxPY/workflows/Python%20package/badge.svg :target: https://github.com/ReactiveX/RxPY/actions :alt: Build Status .. image:: https://img.shields.io/coveralls/ReactiveX/RxPY.svg :target: https://coveralls.io/github/ReactiveX/RxPY :alt: Coverage Status .. image:: https://img.shields.io/pypi/v/reactivex.svg :target: https://pypi.org/project/reactivex/ :alt: PyPY Package Version .. image:: https://img.shields.io/readthedocs/rxpy.svg :target: https://readthedocs.org/projects/rxpy/builds/ :alt: Documentation Status *A library for composing asynchronous and event-based programs using observable collections and query operator functions in Python* ReactiveX for Python v5 ----------------------- For v3.X please go to the `v3 branch `_. ReactiveX for Python v4.x runs on `Python `_ 3.9 or above. To install: .. code:: console pip3 install reactivex About ReactiveX --------------- ReactiveX for Python (RxPY) is a library for composing asynchronous and event-based programs using observable sequences and pipable query operators in Python. Using Rx, developers represent asynchronous data streams with Observables, query asynchronous data streams using operators, and parameterize concurrency in data/event streams using Schedulers. .. code:: python import reactivex as rx from reactivex import operators as ops source = rx.of("Alpha", "Beta", "Gamma", "Delta", "Epsilon") composed = source.pipe( ops.map(lambda s: len(s)), ops.filter(lambda i: i >= 5) ) composed.subscribe(lambda value: print("Received {0}".format(value))) Fluent and Functional Syntax ----------------------------- RxPY supports both **fluent** (method chaining) and **functional** (pipe-based) syntax, giving you the flexibility to choose the style that works best for your codebase: **Fluent style** - Method chaining for a more Pythonic feel: .. code:: python import reactivex as rx result = (rx.of(1, 2, 3, 4, 5) .map(lambda x: x * 2) .filter(lambda x: x > 5) .reduce(lambda acc, x: acc + x, 0) ) result.subscribe(print) # Output: 24 **Functional style** - Pipe-based for functional composition: .. code:: python import reactivex as rx from reactivex import operators as ops result = rx.of(1, 2, 3, 4, 5).pipe( ops.map(lambda x: x * 2), ops.filter(lambda x: x > 5), ops.reduce(lambda acc, x: acc + x, 0) ) result.subscribe(print) # Output: 24 Both styles are **fully supported** and can even be mixed in the same pipeline. Choose the style that best fits your team's preferences and coding standards. Learning ReactiveX ------------------ Read the `documentation `_ to learn the principles of ReactiveX and get the complete reference of the available operators. If you need to migrate code from RxPY v1.x or v3.x, read the `migration `_ section. There is also a list of third party documentation available `here `_. Community ---------- Join the conversation on GitHub `Discussions `_! if you have any questions or suggestions. Differences from .NET and RxJS ------------------------------ ReactiveX for Python is a fairly complete implementation of `Rx `_ with more than `120 operators `_, and over `1300 passing unit-tests `_. RxPY is mostly a direct port of RxJS, but also borrows a bit from Rx.NET and RxJava in terms of threading and blocking operators. ReactiveX for Python follows `PEP 8 `_, so all function and method names are ``snake_cased`` i.e lowercase with words separated by underscores as necessary to improve readability. Thus .NET code such as: .. code:: c# var group = source.GroupBy(i => i % 3); need to be written with an ``_`` in Python: .. code:: python # Functional style group = source.pipe(ops.group_by(lambda i: i % 3)) # Or fluent style group = source.group_by(lambda i: i % 3) With ReactiveX for Python you should use `named keyword arguments `_ instead of positional arguments when an operator has multiple optional arguments. RxPY will not try to detect which arguments you are giving to the operator (or not). Development ----------- This project is managed using `uv `_. Code is formatted using `Ruff `_. Code is statically type checked using `pyright `_. After cloning the repository, install dependencies: .. code:: console uv sync Run unit tests: .. code:: console uv run pytest Run type checking: .. code:: console uv run pyright Run code checks (manually): .. code:: console uv run pre-commit run --all-files