# PyMongoArrow
[](https://pypi.org/project/pymongoarrow)
[](https://pypi.org/project/pymongoarrow)
[](https://pepy.tech/project/pymongoarrow)
[](http://mongo-arrow.readthedocs.io/en/stable/?badge=stable)
**PyMongoArrow** is a companion library to PyMongo that contains tools
for loading MongoDB query result sets as Apache Arrow tables, Pandas
DataFrames or NumPy arrays.
```pycon
>>> from pymongoarrow.monkey import patch_all
... patch_all()
... from pymongoarrow.api import Schema
... schema = Schema({"_id": int, "qty": float})
... from pymongo import MongoClient
... client = MongoClient()
... client.db.data.insert_many(
... [{"_id": 1, "qty": 25.4}, {"_id": 2, "qty": 16.9}, {"_id": 3, "qty": 2.3}]
... )
... data_frame = client.db.test.find_pandas_all({}, schema=schema)
... data_frame
_id qty
0 1 25.4
1 2 16.9
2 3 2.3
... arrow_table = client.db.test.find_arrow_all({}, schema=schema)
# The schema may also be omitted
... arrow_table = client.db.test.find_arrow_all({})
... arrow_table
pyarrow.Table
_id: int64
qty: double
... ndarrays = client.db.test.find_numpy_all({}, schema=schema)
... ndarrays
{'_id': array([1, 2, 3]), 'qty': array([25.4, 16.9, 2.3])}
```
**PyMongoArrow** is the recommended way to materialize MongoDB query
result sets as contiguous-in-memory, typed arrays suited for in-memory
analytical processing applications.
## Installing PyMongoArrow
PyMongoArrow is available on PyPI:
```bash
python -m pip install pymongoarrow
```
To use PyMongoArrow with MongoDB Atlas' `mongodb+srv://` URIs, you will
need to also install PyMongo with the `srv` extra:
```bash
python -m pip install 'pymongo[srv]' pymongoarrow
```
To use PyMongoArrow APIs that return query result sets as pandas
DataFrame instances, you will also need to have the `pandas` package
installed:
```bash
python -m pip install pandas
```
Note: `pymongoarrow` is not supported or tested on big-endian systems
(e.g. Linux s390x).
## Development Install
See the instructions in the [Contributing Guide][./CONTRIBUTING.md]
## Documentation
Full documentation is available on [Read the
Docs](https://mongo-arrow.readthedocs.io/en/latest).
Raw data
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"description": "# PyMongoArrow\n\n[](https://pypi.org/project/pymongoarrow)\n[](https://pypi.org/project/pymongoarrow)\n[](https://pepy.tech/project/pymongoarrow)\n[](http://mongo-arrow.readthedocs.io/en/stable/?badge=stable)\n\n**PyMongoArrow** is a companion library to PyMongo that contains tools\nfor loading MongoDB query result sets as Apache Arrow tables, Pandas\nDataFrames or NumPy arrays.\n\n```pycon\n>>> from pymongoarrow.monkey import patch_all\n... patch_all()\n... from pymongoarrow.api import Schema\n... schema = Schema({\"_id\": int, \"qty\": float})\n... from pymongo import MongoClient\n... client = MongoClient()\n... client.db.data.insert_many(\n... [{\"_id\": 1, \"qty\": 25.4}, {\"_id\": 2, \"qty\": 16.9}, {\"_id\": 3, \"qty\": 2.3}]\n... )\n... data_frame = client.db.test.find_pandas_all({}, schema=schema)\n... data_frame\n _id qty\n0 1 25.4\n1 2 16.9\n2 3 2.3\n... arrow_table = client.db.test.find_arrow_all({}, schema=schema)\n# The schema may also be omitted\n... arrow_table = client.db.test.find_arrow_all({})\n... arrow_table\npyarrow.Table\n_id: int64\nqty: double\n... ndarrays = client.db.test.find_numpy_all({}, schema=schema)\n... ndarrays\n{'_id': array([1, 2, 3]), 'qty': array([25.4, 16.9, 2.3])}\n```\n\n**PyMongoArrow** is the recommended way to materialize MongoDB query\nresult sets as contiguous-in-memory, typed arrays suited for in-memory\nanalytical processing applications.\n\n## Installing PyMongoArrow\n\nPyMongoArrow is available on PyPI:\n\n```bash\npython -m pip install pymongoarrow\n```\n\nTo use PyMongoArrow with MongoDB Atlas' `mongodb+srv://` URIs, you will\nneed to also install PyMongo with the `srv` extra:\n\n```bash\npython -m pip install 'pymongo[srv]' pymongoarrow\n```\n\nTo use PyMongoArrow APIs that return query result sets as pandas\nDataFrame instances, you will also need to have the `pandas` package\ninstalled:\n\n```bash\npython -m pip install pandas\n```\n\nNote: `pymongoarrow` is not supported or tested on big-endian systems\n(e.g. Linux s390x).\n\n## Development Install\n\nSee the instructions in the [Contributing Guide][./CONTRIBUTING.md]\n\n## Documentation\n\nFull documentation is available on [Read the\nDocs](https://mongo-arrow.readthedocs.io/en/latest).\n",
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