{"id":13449726,"url":"https://github.com/streamlet-dev/tributary","last_synced_at":"2025-04-10T06:17:36.022Z","repository":{"id":32999241,"uuid":"147895712","full_name":"streamlet-dev/tributary","owner":"streamlet-dev","description":"Streaming reactive and dataflow graphs in Python","archived":false,"fork":false,"pushed_at":"2024-11-19T17:03:01.000Z","size":10754,"stargazers_count":451,"open_issues_count":12,"forks_count":36,"subscribers_count":13,"default_branch":"main","last_synced_at":"2025-04-03T03:52:33.342Z","etag":null,"topics":["asynchronous","data-pipeline","kafka","lazy-evaluation","python","python-data-streams","python3","reactive-data-streams","stream","streaming","websockets"],"latest_commit_sha":null,"homepage":"","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"apache-2.0","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/streamlet-dev.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":".github/CODE_OF_CONDUCT.md","threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2018-09-08T02:58:57.000Z","updated_at":"2025-03-28T09:46:06.000Z","dependencies_parsed_at":"2025-01-08T09:00:43.486Z","dependency_job_id":"f84048b0-dba0-446a-95dc-e14fe06f86ee","html_url":"https://github.com/streamlet-dev/tributary","commit_stats":null,"previous_names":[],"tags_count":17,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/streamlet-dev%2Ftributary","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/streamlet-dev%2Ftributary/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/streamlet-dev%2Ftributary/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/streamlet-dev%2Ftributary/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/streamlet-dev","download_url":"https://codeload.github.com/streamlet-dev/tributary/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":248166858,"owners_count":21058481,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["asynchronous","data-pipeline","kafka","lazy-evaluation","python","python-data-streams","python3","reactive-data-streams","stream","streaming","websockets"],"created_at":"2024-07-31T06:00:52.523Z","updated_at":"2025-04-10T06:17:35.997Z","avatar_url":"https://github.com/streamlet-dev.png","language":"Python","readme":"# \u003cimg src=\"https://raw.githubusercontent.com/streamlet-dev/tributary/main/docs/img/icon.png\" width=\"300\"\u003e\nPython Data Streams\n\n[![Build Status](https://github.com/streamlet-dev/tributary/workflows/Build%20Status/badge.svg?branch=main)](https://github.com/streamlet-dev/tributary/actions?query=workflow%3A%22Build+Status%22)\n[![Coverage](https://codecov.io/gh/streamlet-dev/tributary/branch/main/graph/badge.svg)](https://codecov.io/gh/streamlet-dev/tributary)\n[![PyPI](https://img.shields.io/pypi/l/tributary.svg)](https://pypi.python.org/pypi/tributary)\n[![PyPI](https://img.shields.io/pypi/v/tributary.svg)](https://pypi.python.org/pypi/tributary)\n[![Binder](https://mybinder.org/badge_logo.svg)](https://mybinder.org/v2/gh/streamlet-dev/tributary/main?urlpath=lab)\n\n\nTributary is a library for constructing dataflow graphs in python. Unlike many other DAG libraries in python ([airflow](https://airflow.apache.org), [luigi](https://luigi.readthedocs.io/en/stable/), [prefect](https://docs.prefect.io), [dagster](https://docs.dagster.io), [dask](https://dask.org), [kedro](https://github.com/quantumblacklabs/kedro), etc), tributary is not designed with data/etl pipelines or scheduling in mind. Instead, tributary is more similar to libraries like [mdf](https://github.com/man-group/mdf), [loman](https://github.com/janushendersonassetallocation/loman), [pyungo](https://github.com/cedricleroy/pyungo), [streamz](https://streamz.readthedocs.io/en/latest/), or [pyfunctional](https://github.com/EntilZha/PyFunctional), in that it is designed to be used as the implementation for a data model. One such example is the [greeks](https://github.com/streamlet-dev/greeks) library, which leverages tributary to build data models for [options pricing](https://www.investopedia.com/articles/optioninvestor/07/options_beat_market.asp). \n\n![](https://raw.githubusercontent.com/streamlet-dev/tributary/main/docs/img/example.gif)\n\n\n# Installation\nInstall with pip:\n\n`pip install tributary`\n\nor with conda:\n\n`conda install -c conda-forge tributary`\n\nor from source:\n\n`python setup.py install`\n\nNote: If installing from source or with pip, you'll also need [Graphviz itself](https://www.graphviz.org/download/) if you want to visualize the graph using the `.graphviz()` method.\n\n# Stream Types\nTributary offers several kinds of streams:\n\n## Streaming\nThese are synchronous, reactive data streams, built using asynchronous python generators. They are designed to mimic complex event processors in terms of event ordering.\n\n## Functional\nThese are functional streams, built by currying python functions (callbacks). \n\n## Lazy\nThese are lazily-evaluated python streams, where outputs are propogated only as inputs change. They are implemented as directed acyclic graphs.\n\n# Examples\n- [Streaming](docs/examples/streaming/streaming.md): In this example, we construct a variety of forward propogating reactive graphs.\n- [Lazy](docs/examples/lazy/lazy.md): In this example, we construct a variety of lazily-evaluated directed acyclic computation graphs. \n- [Automatic Differentiation](docs/examples/autodiff/autodiff.md): In this example, we use `tributary` to perform automatic differentiation on both lazy and streaming graphs.\n\n# Graph Visualization\nYou can visualize the graph with Graphviz. All streaming and lazy nodes support a `graphviz` method.\n\nStreaming and lazy nodes also support [ipydagred3](https://github.com/timkpaine/ipydagred3) for live update monitoring.\n\n## Streaming\n![](https://raw.githubusercontent.com/streamlet-dev/tributary/main/docs/img/streaming/dagred3.gif)\n\nHere green indicates executing, yellow indicates stalled for backpressure, and red indicates that `StreamEnd` has been propogated (e.g. stream has ended).\n\n## Lazy\n![](https://raw.githubusercontent.com/streamlet-dev/tributary/main/docs/img/lazy/dagred3.gif)\n\nHere green indicates executing, and red indicates that the node is dirty. Note the the determination if a node is dirty is also done lazily (we can check with `isDirty` whcih will update the node's graph state.\n\n## Catalog\nSee the [CATALOG](CATALOG.md) for a full list of functions, transforms, sources, and sinks.\n\n## Support / Contributors\nThanks to the following organizations for providing code or financial support.\n\n\n\u003ca href=\"https://nemoulous.com\"\u003e\u003cimg src=\"https://raw.githubusercontent.com/streamlet-dev/tributary/main/docs/img/nem.png\" width=\"50\"\u003e\u003c/a\u003e\n\n\u003ca href=\"https://nemoulous.com\"\u003eNemoulous\u003c/a\u003e\n\n## License\nThis software is licensed under the Apache 2.0 license. See the [LICENSE](LICENSE) file for details.\n\n## Alternatives\nHere is an incomplete list of libraries which implement similar/overlapping functionality\n\n- [man-group/mdf](https://github.com/man-group/mdf)\n- [janushendersonassetallocation/loman](https://github.com/janushendersonassetallocation/loman)\n- [cedricleroy/pyungo](https://github.com/cedricleroy/pyungo)\n- [python-streamz/streamz](https://github.com/python-streamz/streamz)\n- [EntilZha/pyfunctional](https://github.com/EntilZha/PyFunctional)\n- [stitchfix/hamilton](https://github.com/stitchfix/hamilton)\n","funding_links":[],"categories":["Graph Computation","Python","Interactive Widgets \u0026 Visualization"],"sub_categories":["Cryptocurrencies"],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstreamlet-dev%2Ftributary","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fstreamlet-dev%2Ftributary","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fstreamlet-dev%2Ftributary/lists"}