# GraphFrames Python Package
  
<img src=https://raw.githubusercontent.com/graphframes/graphframes/refs/heads/master/docs/img/GraphFrames-Logo-Large.png width=500>
https://graphframes.io/
The is the officila [graphframes-py PyPI package](https://pypi.org/project/graphframes-py/), which is a Python wrapper for the Scala GraphFrames library.
This package is maintained by the GraphFrames project and is available on PyPI.
For instructions on GraphFrames, check the project [README.md](https://github.com/graphframes/graphframes?tab=readme-ov-file#graphframes-dataframe-based-graphs).
See [Installation and Quick-Start](https://github.com/graphframes/graphframes?tab=readme-ov-file#installation-and-quick-start) for the best way to install and use GraphFrames.
## Installation
```bash
pip install graphframes-py
```
**NOTE!** *Python distribution does not include JVM-core. You need to add it to your cluster or Spark-Connect server!*
## Running `graphframes-py`
You should use GraphFrames via the `--packages` argument to `pyspark` or `spark-submit`, but this package is helpful in development environments.
```bash
# Interactive Python, Spark 3.5.x
$ pyspark --packages io.graphframes:graphframes-spark3_2.12:0.9.2
# Interactive Python, Spark 4.0.x
$ pyspark --packages io.graphframes:graphframes-spark4_2.13:0.9.2
```
## Documentation
- [API Reference](https://graphframes.io/api/python/index.html)
## Spark-Connect Note
GraphFrames PySpark is choosing connect or classic implementation implicitly based on the result of `is_remote()`.
To enforce usage of connect-based implementation, you may export this variable `SPARK_CONNECT_MODE_ENABLED=1`
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"description": "# GraphFrames Python Package\n\n  \n\n<img src=https://raw.githubusercontent.com/graphframes/graphframes/refs/heads/master/docs/img/GraphFrames-Logo-Large.png width=500>\n\nhttps://graphframes.io/\n\nThe is the officila [graphframes-py PyPI package](https://pypi.org/project/graphframes-py/), which is a Python wrapper for the Scala GraphFrames library.\nThis package is maintained by the GraphFrames project and is available on PyPI.\n\nFor instructions on GraphFrames, check the project [README.md](https://github.com/graphframes/graphframes?tab=readme-ov-file#graphframes-dataframe-based-graphs).\n\nSee [Installation and Quick-Start](https://github.com/graphframes/graphframes?tab=readme-ov-file#installation-and-quick-start) for the best way to install and use GraphFrames.\n\n## Installation\n\n```bash\npip install graphframes-py\n```\n\n**NOTE!** *Python distribution does not include JVM-core. You need to add it to your cluster or Spark-Connect server!*\n\n## Running `graphframes-py`\n\nYou should use GraphFrames via the `--packages` argument to `pyspark` or `spark-submit`, but this package is helpful in development environments.\n\n```bash\n# Interactive Python, Spark 3.5.x\n$ pyspark --packages io.graphframes:graphframes-spark3_2.12:0.9.2\n\n# Interactive Python, Spark 4.0.x\n$ pyspark --packages io.graphframes:graphframes-spark4_2.13:0.9.2\n```\n\n## Documentation\n\n- [API Reference](https://graphframes.io/api/python/index.html)\n\n## Spark-Connect Note\n\nGraphFrames PySpark is choosing connect or classic implementation implicitly based on the result of `is_remote()`.\nTo enforce usage of connect-based implementation, you may export this variable `SPARK_CONNECT_MODE_ENABLED=1`\n\n",
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