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Process images, audio, video, and structured data at any scale.\n\n* **Native multimodal processing:** Process images, audio, video, and embeddings alongside structured data in a single framework\n* **Built-in AI operations:** Run LLM prompts, generate embeddings, and classify data at scale using OpenAI, Transformers, or custom models\n* **Python-native, Rust-powered:** Skip the JVM complexity with Python at its core and Rust under the hood for blazing performance\n* **Seamless scaling:** Start local, scale to distributed clusters on `Ray \u003chttps://docs.daft.ai/en/stable/distributed/ray/\u003e`_, `Kubernetes \u003chttps://docs.daft.ai/en/stable/distributed/kubernetes/\u003e`_\n* **Universal connectivity:** Access data anywhere (S3, GCS, Iceberg, Delta Lake, Hugging Face, Unity Catalog)\n* **Out-of-box reliability:** Intelligent memory management and sensible defaults eliminate configuration headaches\n\nGetting Started\n---------------\n\nInstallation\n^^^^^^^^^^^^\n\nInstall Daft with ``pip install daft``. Requires Python 3.10 or higher.\n\nFor more advanced installations (e.g. installing from source or with extra dependencies such as Ray and AWS utilities), please see our `Installation Guide \u003chttps://docs.daft.ai/en/stable/install/\u003e`_\n\nQuickstart\n^^^^^^^^^^\n\nGet started in minutes with our `Quickstart \u003chttps://docs.daft.ai/en/stable/quickstart/\u003e`_ - load a real-world e-commerce dataset, process product images, and run AI inference at scale.\n\n\nMore Resources\n^^^^^^^^^^^^^^\n\n* `Examples \u003chttps://docs.daft.ai/en/stable/examples/\u003e`_ - see Daft in action with use cases across text, images, audio, and more\n* `User Guide \u003chttps://docs.daft.ai/en/stable/\u003e`_ - take a deep-dive into each topic within Daft\n* `API Reference \u003chttps://docs.daft.ai/en/stable/api/\u003e`_ - API reference for public classes/functions of Daft\n\nBenchmarks\n----------\n|Benchmark Image|\n\nTo see the full benchmarks, detailed setup, and logs, check out our `benchmarking page. \u003chttps://docs.daft.ai/en/stable/benchmarks\u003e`_\n\nContributing\n------------\n\nWe ❤️ developers! To start contributing to Daft, please read `CONTRIBUTING.md \u003chttps://github.com/Eventual-Inc/Daft/blob/main/CONTRIBUTING.md\u003e`_. This document describes the development lifecycle and toolchain for working on Daft. It also details how to add new functionality to the core engine and expose it through a Python API.\n\nHere's a list of `good first issues \u003chttps://github.com/Eventual-Inc/Daft/issues?q=is%3Aopen+is%3Aissue+label%3A%22good+first+issue%22\u003e`_ to get yourself warmed up with Daft. Comment in the issue to pick it up, and feel free to ask any questions!\n\nTelemetry\n---------\n\nTo help improve Daft, we collect non-identifiable data via Scarf (https://scarf.sh).\n\nTo disable this behavior, set the environment variable ``DO_NOT_TRACK=true``.\n\nThe data that we collect is:\n\n1. **Non-identifiable:** No session IDs or user identifiers are collected\n2. **Metadata-only:** We do not collect any of our users’ proprietary code or data\n3. **For development only:** We do not buy or sell any user data\n\nPlease see our `documentation \u003chttps://docs.daft.ai/en/stable/telemetry/\u003e`_ for more details.\n\n.. image:: https://static.scarf.sh/a.png?x-pxid=31f8d5ba-7e09-4d75-8895-5252bbf06cf6\n\nRelated Projects\n----------------\n\n+---------------------------------------------------+-----------------+---------------+-------------+-----------------+-----------------------------+-------------+\n| Engine                                            | Query Optimizer | Multimodal    | Distributed | Arrow Backed    | Vectorized Execution Engine | Out-of-core |\n+===================================================+=================+===============+=============+=================+=============================+=============+\n| Daft                                              | Yes             | Yes           | Yes         | Yes             | Yes                         | Yes         |\n+---------------------------------------------------+-----------------+---------------+-------------+-----------------+-----------------------------+-------------+\n| `Pandas \u003chttps://github.com/pandas-dev/pandas\u003e`_  | No              | Python object | No          | optional \u003e= 2.0 | Some(Numpy)                 | No          |\n+---------------------------------------------------+-----------------+---------------+-------------+-----------------+-----------------------------+-------------+\n| `Polars \u003chttps://github.com/pola-rs/polars\u003e`_     | Yes             | Python object | No          | Yes             | Yes                         | Yes         |\n+---------------------------------------------------+-----------------+---------------+-------------+-----------------+-----------------------------+-------------+\n| `Modin \u003chttps://github.com/modin-project/modin\u003e`_ | Yes             | Python object | Yes         | No              | Some(Pandas)                | Yes         |\n+---------------------------------------------------+-----------------+---------------+-------------+-----------------+-----------------------------+-------------+\n| `Ray Data \u003chttps://github.com/ray-project/ray\u003e`_  | No              | Yes           | Yes         | Yes             | Some(PyArrow)               | Yes         |\n+---------------------------------------------------+-----------------+---------------+-------------+-----------------+-----------------------------+-------------+\n| `PySpark \u003chttps://github.com/apache/spark\u003e`_      | Yes             | No            | Yes         | Pandas UDF/IO   | Pandas UDF                  | Yes         |\n+---------------------------------------------------+-----------------+---------------+-------------+-----------------+-----------------------------+-------------+\n| `Dask DF \u003chttps://github.com/dask/dask\u003e`_         | No              | Python object | Yes         | No              | Some(Pandas)                | Yes         |\n+---------------------------------------------------+-----------------+---------------+-------------+-----------------+-----------------------------+-------------+\n\nLicense\n-------\n\nDaft has an Apache 2.0 license - please see the LICENSE file.\n\n.. |Quickstart Image| image:: https://github.com/Eventual-Inc/Daft/assets/17691182/dea2f515-9739-4f3e-ac58-cd96d51e44a8\n   :alt: Dataframe code to load a folder of images from AWS S3 and create thumbnails\n   :height: 256\n\n.. |Benchmark Image| image:: https://raw.githubusercontent.com/Eventual-Inc/Daft/refs/heads/main/assets/benchmark.png\n   :alt: AI Benchmarks\n\n.. |Banner| image:: https://daft.ai/images/diagram.png\n   :target: https://www.daft.ai\n   :alt: Daft dataframes can load any data such as PDF documents, images, protobufs, csv, parquet and audio files into a table dataframe structure for easy querying\n\n.. |CI| image:: https://github.com/Eventual-Inc/Daft/actions/workflows/pr-test-suite.yml/badge.svg\n   :target: https://github.com/Eventual-Inc/Daft/actions/workflows/pr-test-suite.yml?query=branch:main\n   :alt: GitHub Actions tests\n\n.. |PyPI| image:: https://img.shields.io/pypi/v/daft.svg?label=pip\u0026logo=PyPI\u0026logoColor=white\n   :target: https://pypi.org/project/daft\n   :alt: PyPI\n\n.. |Latest Tag| image:: https://img.shields.io/github/v/tag/Eventual-Inc/Daft?label=latest\u0026logo=GitHub\n   :target: https://github.com/Eventual-Inc/Daft/tags\n   :alt: latest tag\n\n.. |Coverage| image:: https://codecov.io/gh/Eventual-Inc/Daft/branch/main/graph/badge.svg?token=J430QVFE89\n   :target: https://codecov.io/gh/Eventual-Inc/Daft\n   :alt: Coverage\n\n.. |Slack| image:: https://img.shields.io/badge/slack-@distdata-purple.svg?logo=slack\n   :target: https://join.slack.com/t/dist-data/shared_invite/zt-3rh9jr9iv-tmmTNOlQpfvhEy2NTMWS_w\n   :alt: slack community\n\n.. |TrendShift| image:: https://trendshift.io/api/badge/repositories/8239\n   :target: https://trendshift.io/repositories/8239\n   :alt: Eventual-Inc/Daft | Trendshift\n   :width: 250px\n   :height: 55px\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feventual-inc%2Fdaft","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Feventual-inc%2Fdaft","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Feventual-inc%2Fdaft/lists"}