Tools for using NumPy, Pandas, Polars, and PyArrow with MongoDB

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PyMongoArrow

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.

>>> 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:

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:

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:

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.

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1.6.0

Nov 4, 2024

This version

1.5.2

Sep 23, 2024

1.5.1

Aug 12, 2024

1.5.0

Aug 7, 2024

1.4.0

Jun 5, 2024

1.3.0

Feb 6, 2024

1.2.0

Dec 12, 2023

1.1.0

Oct 18, 2023

1.0.2

Jul 17, 2023

1.0.1

Jun 22, 2023

1.0.0

Jun 21, 2023

0.7.0

Jan 30, 2023

0.6.3

Dec 14, 2022

0.6.2

Nov 16, 2022

0.5.1

Aug 31, 2022

0.5.0

Aug 18, 2022

0.4.0

Apr 27, 2022

0.4.0.dev0 pre-release

Apr 26, 2022

0.3.0

Mar 2, 2022

0.2.0

Jan 6, 2022

0.1.1

Apr 27, 2021

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