Metadata-Version: 2.1
Name: beavers
Version: 0.7.0
Summary: Python stream processing
Home-page: https://github.com/tradewelltech/beavers
License: Apache-2.0
Keywords: apache-arrow,streaming,data
Author: Tradewell Tech
Author-email: engineering@tradewelltech.co
Maintainer: 0x26res
Maintainer-email: 0x26res@gmail.com
Requires-Python: >=3.10,<3.13
Classifier: Development Status :: 5 - Production/Stable
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Provides-Extra: confluent-kafka
Provides-Extra: pyarrow
Requires-Dist: confluent_kafka (>=2.1.1) ; extra == "confluent-kafka"
Requires-Dist: pandas (>1.4.0)
Requires-Dist: pyarrow (>=12.0) ; extra == "pyarrow"
Project-URL: Documentation, https://beavers.readthedocs.io/en/latest/
Project-URL: Repository, https://github.com/tradewelltech/beavers
Description-Content-Type: text/markdown


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![Beavers Logo][5]

# Beavers

[Documentation][6] / [Installation][7] / [Repository][1] / [PyPI][8]

[Beavers][1] is a python library for stream processing, optimized for analytics.

It is used at [Tradewell Technologies][2],
to calculate analytics and serve model predictions,
for both realtime and batch jobs.

## Key Features

- Works in **real time** (eg: reading from Kafka) and **replay mode** (eg: reading from Parquet files).
- Optimized for analytics, using micro-batches (instead of processing records one by one).
- Similar to [incremental][3], it updates nodes in a dag incrementally.
- Taking inspiration from [kafka streams][4], there are two types of nodes in the dag:
    - **Stream**: ephemeral micro-batches of events (cleared after every cycle).
    - **State**: durable state derived from streams.
- Clear separation between the business logic and the IO.
  So the same dag can be used in real time mode, replay mode or can be easily tested.
- Functional interface: no inheritance or decorator required.
- Support for complicated joins, not just "linear" data flow.

## Limitations

- No concurrency support.
  To speed up calculation use libraries like pandas, pyarrow or polars.
- No async code.
  To speed up IO use kafka driver native thread or parquet IO thread pool.
- No support for persistent state.
  Instead of saving state, replay historic data from kafka to prime stateful nodes.

## Talks

- [Unified batch and stream processing in python | PyData Global 2023][9]

[1]: https://github.com/tradewelltech/beavers
[2]: https://www.tradewelltech.co/
[3]: https://github.com/janestreet/incremental
[4]: https://www.confluent.io/blog/kafka-streams-tables-part-1-event-streaming/
[5]: https://raw.githubusercontent.com/tradewelltech/beavers/master/docs/static/icons/beavers/logo.svg
[6]: https://beavers.readthedocs.io/en/latest/
[7]: https://beavers.readthedocs.io/en/latest/install/
[8]: https://pypi.org/project/beavers/
[9]: https://www.youtube.com/watch?v=8pUwsGA8SQM

[pypi-image]: https://img.shields.io/pypi/v/beavers
[pypi-url]: https://pypi.org/project/beavers/
[build-image]: https://github.com/tradewelltech/beavers/actions/workflows/ci.yaml/badge.svg
[build-url]: https://github.com/tradewelltech/beavers/actions/workflows/ci.yaml
[stars-image]: https://img.shields.io/github/stars/tradewelltech/beavers
[stars-url]: https://github.com/tradewelltech/beavers
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[versions-url]: https://pypi.org/project/beavers/
[doc-image]: https://readthedocs.org/projects/beavers/badge/?version=latest
[doc-url]: https://beavers.readthedocs.io/en/latest/?badge=latest
[license-image]: http://img.shields.io/:license-Apache%202-blue.svg
[license-url]: https://github.com/tradewelltech/beavers/blob/main/LICENSE
[codecov-image]: https://codecov.io/gh/tradewelltech/beavers/branch/main/graph/badge.svg?token=GY6KL7NT1Q
[codecov-url]: https://codecov.io/gh/tradewelltech/beavers
[downloads-image]: https://pepy.tech/badge/beavers
[downloads-url]: https://static.pepy.tech/badge/beavers
[downloads-month-image]: https://pepy.tech/badge/beavers/month
[downloads-month-url]: https://static.pepy.tech/badge/beavers/month
[codestyle-image]: https://img.shields.io/badge/code%20style-black-000000.svg
[codestyle-url]: https://github.com/ambv/black
[snyk-image]: https://snyk.io/advisor/python/beavers/badge.svg
[snyk-url]: https://snyk.io/advisor/python/beavers

