# PyMongo: the official MongoDB Python driver, and what it actually commits you to

> PyMongo is MongoDB's own Python driver, distributed as pymongo with bundled bson and gridfs packages. It is the default choice for talking to MongoDB from Python, and it also ties your application to MongoDB's release and support cycle.

**mongodb/mongo-python-driver** — PyMongo - the Official MongoDB Python driver

- Repository: https://github.com/mongodb/mongo-python-driver
- Website: https://www.mongodb.com/docs/languages/python/pymongo-driver/current/
- Stars: 4,357 · Forks: 1,160
- Language: Python
- License: Apache-2.0
- Published: 2026-09-23 · Updated: 2026-09-23 · Language: en
- Canonical page: https://hysenlabs.com/projects/mongodb-mongo-python-driver

## What PyMongo solves, and who it is written for

MongoDB speaks a binary wire protocol, not SQL. Something has to encode your Python dictionaries into BSON, open and pool TCP connections, route reads and writes to the right server in a replica set, retry the operations that are safe to retry, and decode what comes back. PyMongo is that layer, maintained by MongoDB itself rather than by a third party.

The distribution is three packages in one install. bson implements the BSON format for Python. pymongo is the driver, offering both synchronous and asynchronous APIs. gridfs implements the GridFS specification on top of pymongo for storing files that exceed the BSON document size limit. If you are writing a Python service that persists documents to MongoDB, this is the intended path.

Who it is not for: anyone who wants to swap databases later without touching application code. PyMongo exposes MongoDB's model directly, including collection-level operations and MongoDB-specific concepts. That directness is the point, but it is also the commitment.

## How the driver is structured: client, database, collection

The README's example shows the object model in a few lines. A MongoClient holds the connection pool and topology state. Indexing into it gives you a Database, and indexing into that gives you a Collection. Reads and writes go through the collection.

The README example also shows the shape of a result. insert_one returns an object whose inserted_id attribute carries the generated ObjectId. find_one returns a plain dict with the _id field included. find returns a cursor, and the README iterates it with a for loop, then demonstrates sort, limit and skip chained on the same cursor before iteration.

One detail worth noticing: the README calls create_index("x") and the return value is the string 'x_1', the generated index name. Index creation is an explicit operation in PyMongo, not something inferred from your query patterns. If your application queries on a field, you create that index yourself, in application code or in a migration step. Nothing in the driver does it for you.

Because the driver ships both a synchronous and an asynchronous API, the architecture decision that matters most is which one you pick. That choice propagates through your entire data access layer and is expensive to reverse later.

## Installing PyMongo and running a first query

The README gives one installation command for the common case. Run it in the environment where your application will import pymongo:

```bash
python -m pip install pymongo
```

The README is explicit about one trap here: do not install the bson package from PyPI. PyMongo ships its own bson package, and the README states that installing bson separately pulls in a third-party package that is incompatible with PyMongo. If bson appears in your dependency tree from another source, that is worth resolving before you debug anything else.

Optional features are gated behind extras. The README lists them individually, and also gives a single command that installs all of them together:

```bash
python -m pip install "pymongo[gssapi,aws,ocsp,snappy,zstd,encryption]"
```

Each extra maps to a specific capability: GSSAPI authentication, MONGODB-AWS authentication, OCSP certificate checking, snappy and zstd wire protocol compression, and client-side field level encryption. Install the extras you actually use rather than the full set, since each one adds third-party dependencies to your image.

For a first query, the README's own example connects to a local server and inserts documents. This is the shortest path to confirming the driver works against your deployment:

```python
import pymongo

client = pymongo.MongoClient("localhost", 27017)
db = client.test
collection = db.my_collection
collection.insert_one({"x": 10})
print(collection.find_one())
```

The README shows that find_one() returns a dict containing the inserted value plus a generated _id of type ObjectId. Seeing that _id in the output confirms the round trip through BSON encoding and decoding worked. Note that the README's example uses a bare host and port; a connection string with mongodb+srv:// requires dnspython, which is the single entry in requirements.txt.

## The version matrix is the real constraint

PyMongo supports MongoDB 4.4, 5.0, 6.0, 7.0, 8.0 and 9.0, and requires CPython 3.9 or newer. Those two ranges are the first thing to check before adopting it, because they define what you can run on both ends.

The Python side is the tighter squeeze in practice. The package metadata in pyproject.toml declares requires-python = ">=3.9" and lists classifiers through Python 3.15, so the floor is 3.9 and newer interpreters are accounted for. PyPy support is a different story: the README states that PyPy3.9+ is supported but that PyPy support is deprecated and will be removed in a future release. If you run PyPy for its interpreter characteristics, that is a migration you will eventually have to plan, and the README does not say when the removal lands.

The server side matters for a subtler reason. A driver that supports a range of server versions is not the same as a driver that supports every feature on every server version. The README states the supported server versions but does not document which driver features require which server version. That mapping lives in the linked documentation and changelog, not in the README. If you are pinned to an older server and planning to use a newer feature, check the changelog rather than assuming the version range covers you.

## Where PyMongo is the wrong tool

PyMongo is a driver. It does not map Python classes to collections, does not manage schema migrations, and does not give you a query language that abstracts over backends. If your team's expectation is an ORM, PyMongo will feel like it is missing a layer, because it is.

There is a second, sharper limitation. The README's support section routes issues to MongoDB's support channels and to StackOverflow under the mongodb tag, and directs bug reports to the PYTHON project in MongoDB's JIRA. There is no mention of a community forum run by the project, and the README explicitly asks users not to email the PyMongo developers directly. For a team that wants an informal escalation path, that is a real difference from a smaller community project where maintainers answer in a chat channel.

Finally, consider the failure mode around optional dependencies. Authentication mechanisms, compression and encryption are not in the base install. A deployment that works in development and fails in production with an authentication error is often a missing extra rather than a configuration mistake. The README lists the extras but does not document the error you get when one is absent, so the diagnostic path runs through the traceback rather than the documentation.

## PyMongo versus an ODM such as Beanie or MongoEngine

The closest alternatives in Python are object-document mappers, which sit on top of a driver and add a model layer. Beanie is built on the asynchronous Motor lineage and targets Pydantic-style models; MongoEngine takes a declarative document-class approach closer to Django's ORM. The difference in approach is where validation and structure live.

With PyMongo, your documents are dicts and your types are whatever you put in them. Validation is your code's job. With an ODM, you declare a document class, and the mapper handles serialization, field validation and often index declaration from that class. You get structure and less boilerplate, at the cost of an extra dependency, an extra abstraction to debug through, and a mapper that has to track the driver's own releases.

There is a concrete reason to prefer PyMongo for a first project. The README's example is complete and runnable in a handful of lines, and the driver is the thing the ODM itself calls. Debugging a query that returns nothing is easier when there is no mapper between your code and the server. The trade-off reverses once your document shapes stabilize and you find yourself writing the same validation by hand in several places. That is the point at which an ODM starts paying for itself, and not before.

## Maintenance cost, release cadence and the Apache-2.0 licence

The repository was last pushed on 2026-09-22 and is not archived. Recent releases are 4.18.1 on 2026-09-10, 4.18.0 on 2026-09-03, and 4.17.0 on 2026-04-20. The README states that PyMongo follows semantic versioning, which gives you a usable rule: patch releases should be safe to take, minor releases can add behavior, and major releases are where breaking changes are allowed to land.

Upgrading has one specific hazard documented in the repository. setup.py no longer builds the package; it raises a RuntimeError whose message states that PyMongo 4.8 and later cannot be built via setup.py and directs you to python -m pip install <path/to/pymongo>, adding that editable installs require pip 21.3 or newer. Any build script or Dockerfile still invoking setup.py directly will fail hard rather than degrade. That is a deliberate choice, and it is easy to miss because the failure appears at build time, not install time.

The licence is Apache-2.0, declared in pyproject.toml with license-files pointing at LICENSE. Apache-2.0 is permissive and includes an explicit patent grant, which is generally the reason projects pick it over MIT. It carries attribution and notice obligations, and the repository ships a THIRD-PARTY-NOTICES file plus an sbom.json, so if you redistribute PyMongo you have concrete artifacts to inspect. This is a description of what the repository contains, not legal advice; your own counsel should review redistribution questions.

## Conclusion

Adopt PyMongo when your data already lives in MongoDB and you want the vendor's own driver rather than a community wrapper: it ships bson and gridfs in the same distribution, supports CPython 3.9+ with both synchronous and asynchronous APIs, and targets MongoDB 4.4 through 9.0. Do not adopt it if you need a database-agnostic layer or an ORM-style mapper; PyMongo is a driver, not an abstraction over storage engines. Before committing, verify three things against your own environment: that your MongoDB server version is in the supported range, that your Python interpreter is 3.9 or newer (PyPy support is deprecated and will be removed in a future release), and whether your connection string uses mongodb+srv://, which requires the dnspython dependency declared in requirements.txt. If you need Kerberos, AWS, OCSP, snappy or zstd compression, or client-side field level encryption, install the matching extra rather than the bare package, because those code paths have separate dependencies.

## FAQ

### What is the Python driver for MongoDB?

It is PyMongo, the official MongoDB driver for Python, distributed as the pymongo package with the bson and gridfs packages included. It offers both synchronous and asynchronous APIs for interacting with a MongoDB deployment from Python.

### What is the purpose of MongoDB drivers?

A driver translates between your application's native types and MongoDB's BSON wire protocol, handling operations such as inserting documents, running queries and creating indexes. In PyMongo's case the bson package implements the BSON format for Python and pymongo provides the driver itself.

### Is MongoDB part of Python?

No. MongoDB is a separate database server, and PyMongo is the official Python driver for talking to it. The driver is installed separately with pip and supports MongoDB server versions 4.4 through 9.0.

## Sources

- [License: Apache-2.0](https://github.com/mongodb/mongo-python-driver/blob/main/LICENSE)
- [mongodb/mongo-python-driver on GitHub](https://github.com/mongodb/mongo-python-driver)
- [Project website](https://www.mongodb.com/docs/languages/python/pymongo-driver/current/)
- [README](https://github.com/mongodb/mongo-python-driver/blob/main/README.md)
- [Releases](https://github.com/mongodb/mongo-python-driver/releases)

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Hysen Labs editorial analysis, written from the project's own repository and release notes. Cite the canonical page: https://hysenlabs.com/projects/mongodb-mongo-python-driver