| Name | mongomock JSON |
| Version |
4.2.0.post1
JSON |
| download |
| home_page | None |
| Summary | Fake pymongo stub for testing simple MongoDB-dependent code |
| upload_time | 2024-09-11 14:30:58 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | None |
| license | ISC License
Copyright (c) 2024, Monogomock Contributors
Permission to use, copy, modify, and/or distribute this software for any
purpose with or without fee is hereby granted, provided that the above
copyright notice and this permission notice appear in all copies.
THE SOFTWARE IS PROVIDED "AS IS" AND THE AUTHOR DISCLAIMS ALL WARRANTIES WITH
REGARD TO THIS SOFTWARE INCLUDING ALL IMPLIED WARRANTIES OF MERCHANTABILITY
AND FITNESS. IN NO EVENT SHALL THE AUTHOR BE LIABLE FOR ANY SPECIAL, DIRECT,
INDIRECT, OR CONSEQUENTIAL DAMAGES OR ANY DAMAGES WHATSOEVER RESULTING FROM
LOSS OF USE, DATA OR PROFITS, WHETHER IN AN ACTION OF CONTRACT, NEGLIGENCE OR
OTHER TORTIOUS ACTION, ARISING OUT OF OR IN CONNECTION WITH THE USE OR
PERFORMANCE OF THIS SOFTWARE. |
| keywords |
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
|
| coveralls test coverage |
No coveralls.
|
.. image:: https://img.shields.io/pypi/v/mongomock.svg?style=flat-square
:target: https://pypi.python.org/pypi/mongomock
.. image:: https://img.shields.io/github/actions/workflow/status/mongomock/mongomock/lint-and-test.yml?branch=develop&style=flat-square
:target: https://github.com/mongomock/mongomock/actions?query=workflow%3Alint-and-test
.. image:: https://img.shields.io/pypi/l/mongomock.svg?style=flat-square
:target: https://pypi.python.org/pypi/mongomock
.. image:: https://img.shields.io/codecov/c/github/mongomock/mongomock.svg?style=flat-square
:target: https://codecov.io/gh/mongomock/mongomock
What is this?
-------------
Mongomock is a small library to help testing Python code that interacts with MongoDB via Pymongo.
To understand what it's useful for, we can take the following code:
.. code-block:: python
def increase_votes(collection):
for document in collection.find():
collection.update_one(document, {'$set': {'votes': document['votes'] + 1}})
The above code can be tested in several ways:
1. It can be tested against a real mongodb instance with pymongo.
2. It can receive a record-replay style mock as an argument. In this manner we record the
expected calls (find, and then a series of updates), and replay them later.
3. It can receive a carefully hand-crafted mock responding to find() and update() appropriately.
Option number 1 is obviously the best approach here, since we are testing against a real mongodb
instance. However, a mongodb instance needs to be set up for this, and cleaned before/after the
test. You might want to run your tests in continuous integration servers, on your laptop, or
other bizarre platforms - which makes the mongodb requirement a liability.
We are left with #2 and #3. Unfortunately they are very high maintenance in real scenarios,
since they replicate the series of calls made in the code, violating the DRY rule. Let's see
#2 in action - we might write our test like so:
.. code-block:: python
def test_increase_votes():
objects = [dict(...), dict(...), ...]
collection_mock = my_favorite_mock_library.create_mock(Collection)
record()
collection_mock.find().AndReturn(objects)
for obj in objects:
collection_mock.update_one(obj, {'$set': {'votes': obj['votes']}})
replay()
increase_votes(collection_mock)
verify()
Let's assume the code changes one day, because the author just learned about the '$inc' instruction:
.. code-block:: python
def increase_votes(collection):
collection.update_many({}, {'$inc': {'votes': 1}})
This breaks the test, although the end result being tested is just the same. The test also repeats
large portions of the code we already wrote.
We are left, therefore, with option #3 -- you want something to behave like a mongodb database
collection, without being one. This is exactly what this library aims to provide. With mongomock,
the test simply becomes:
.. code-block:: python
def test_increase_votes():
collection = mongomock.MongoClient().db.collection
objects = [dict(votes=1), dict(votes=2), ...]
for obj in objects:
obj['_id'] = collection.insert_one(obj).inserted_id
increase_votes(collection)
for obj in objects:
stored_obj = collection.find_one({'_id': obj['_id']})
stored_obj['votes'] -= 1
assert stored_obj == obj # by comparing all fields we make sure only votes changed
This code checks *increase_votes* with respect to its functionality, not syntax or algorithm, and
therefore is much more robust as a test.
If the code to be tested is creating the connection itself with pymongo, you can use
mongomock.patch (NOTE: you should use :code:`pymongo.MongoClient(...)` rather than
:code:`from pymongo import MongoClient`, as shown below):
.. code-block:: python
@mongomock.patch(servers=(('server.example.com', 27017),))
def test_increate_votes_endpoint():
objects = [dict(votes=1), dict(votes=2), ...]
client = pymongo.MongoClient('server.example.com')
client.db.collection.insert_many(objects)
call_endpoint('/votes')
... verify client.db.collection
Important Note About Project Status & Development
-------------------------------------------------
MongoDB is complex. This library aims at a reasonably complete mock of MongoDB for testing purposes,
not a perfect replica. This means some features are not likely to make it in any time soon.
Also, since many corner cases are encountered along the way, our goal is to try and TDD our way into
completeness. This means that every time we encounter a missing or broken (incompatible) feature,
we write a test for it and fix it. There are probably lots of such issues hiding around lurking,
so feel free to open issues and/or pull requests and help the project out!
**NOTE**: We don't include pymongo functionality as "stubs" or "placeholders". Since this library is
used to validate production code, it is unacceptable to behave differently than the real pymongo
implementation. In such cases it is better to throw `NotImplementedError` than implement a modified
version of the original behavior.
Upgrading to Pymongo v4
-----------------------
The major version 4 of Pymongo changed the API quite a bit. The Mongomock library has evolved to
help you ease the migration:
1. Upgrade to Mongomock v4 or above: if your tests are running with Pymongo installed, Mongomock
will adapt its own API to the version of Pymongo installed.
2. Upgrade to Pymongo v4 or above: your tests using Mongomock will fail exactly where your code
would fail in production, so that you can fix it before releasing.
Contributing
------------
When submitting a PR, please make sure that:
1. You include tests for the feature you are adding or bug you are fixing. Preferably, the test
should compare against the real MongoDB engine (see `examples in tests`_ for reference).
2. No existing test got deleted or unintentionally castrated
3. The build passes on your PR.
To download, setup and perfom tests, run the following commands on Mac / Linux:
.. code-block:: console
$ git clone git@github.com:mongomock/mongomock.git
$ pipx install hatch
$ cd mongomock
$ hatch test
Alternatively, docker-compose can be used to simplify dependency management for local development:
.. code-block:: console
$ git clone git@github.com:mongomock/mongomock.git
$ cd mongomock
$ docker compose build
$ docker compose run --rm mongomock
If you want to run ``hatch`` against a specific environment in the container:
.. code-block:: console
$ docker compose run --rm mongomock hatch test -py=3.11 -i pymongo=4
If you'd like to run only one test, you can also add the test name at the end of your command:
.. code-block:: console
$ docker compose run --rm mongomock hatch test -py=3.12 -i pymongo=4 tests/test__mongomock.py::MongoClientCollectionTest::test__insert
NOTE: If the MongoDB image was updated, or you want to try a different MongoDB version in
``docker-compose``, you'll have to issue a ``docker compose down`` before you do anything else to
ensure you're running against the intended version.
utcnow
~~~~~~
When developing features that need to make use of "now," please use the libraries :code:`utcnow`
helper method in the following way:
.. code-block:: python
import mongomock
# Awesome code!
now_reference = mongomock.utcnow()
This provides users a consistent way to mock the notion of "now" in mongomock if they so choose.
Please see `utcnow docstring for more details <mongomock/helpers.py#L52>`_.
Branching model
~~~~~~~~~~~~~~~
The branching model used for this project follows the `gitflow workflow`_. This means that pull
requests should be issued against the `develop` branch and *not* the `master` branch. If you want
to contribute to the legacy 2.x branch then your pull request should go into the `support/2.x`
branch.
Releasing
~~~~~~~~~
When ready for a release, tag the `develop` branch with a new tag (please keep semver names) and
push your tags to GitHub. The CI should do the rest.
To add release notes, create a release in GitHub's `Releases Page <https://github.com/mongomock/mongomock/releases>`_
then generate the release notes locally with:
.. code-block:: bash
python -c "from pbr import git; git.write_git_changelog()"
Then you can get the relevant section in the generated `Changelog` file.
Acknowledgements
----------------
Mongomock has originally been developed by `Rotem Yaari <https://github.com/vmalloc/>`_, then by
`Martin Domke <https://github.com/mdomke>`_. It is currently being developed and maintained by
`Pascal Corpet <https://github.com/pcorpet>`_ .
Also, many thanks go to the following people for helping out, contributing pull requests and fixing
bugs:
* Alec Perkins
* Alexandre Viau
* Austin W Ellis
* Andrey Ovchinnikov
* Arthur Hirata
* Baruch Oxman
* Corey Downing
* Craig Hobbs
* Daniel Murray
* David Fischer
* Diego Garcia
* Dmitriy Kostochko
* Drew Winstel
* Eddie Linder
* Edward D'Souza
* Emily Rosengren
* Eugene Chernyshov
* Grigoriy Osadchenko
* Israel Teixeira
* Jacob Perkins
* Jason Burchfield
* Jason Sommer
* Jeff Browning
* Jeff McGee
* Joël Franusic
* `Jonathan Hedén <https://github.com/jheden/>`_
* Julian Hille
* Krzysztof Płocharz
* Lyon Zhang
* `Lucas Rangel Cezimbra <https://github.com/Lrcezimbra/>`_
* Marc Prewitt
* Marcin Barczynski
* Marian Galik
* Michał Albrycht
* Mike Ho
* Nigel Choi
* Omer Gertel
* Omer Katz
* Papp Győző
* Paul Glass
* Scott Sexton
* Srinivas Reddy Thatiparthy
* Taras Boiko
* Todd Tomkinson
* `Xinyan Lu <https://github.com/lxy1992/>`_
* Zachary Carter
* catty (ca77y _at_ live.com)
* emosenkis
* hthieu1110
* יppetlinskiy
* pacud
* tipok
* waskew (waskew _at_ narrativescience.com)
* jmsantorum (jmsantorum [at] gmail [dot] com)
* lidongyong
* `Juan Gutierrez <https://github.com/juannyg/>`_
.. _examples in tests: https://github.com/mongomock/mongomock/blob/develop/tests/test__mongomock.py
.. _gitflow workflow: https://www.atlassian.com/git/tutorials/comparing-workflows/gitflow-workflow
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"description": ".. image:: https://img.shields.io/pypi/v/mongomock.svg?style=flat-square\n :target: https://pypi.python.org/pypi/mongomock\n.. image:: https://img.shields.io/github/actions/workflow/status/mongomock/mongomock/lint-and-test.yml?branch=develop&style=flat-square\n :target: https://github.com/mongomock/mongomock/actions?query=workflow%3Alint-and-test\n.. image:: https://img.shields.io/pypi/l/mongomock.svg?style=flat-square\n :target: https://pypi.python.org/pypi/mongomock\n.. image:: https://img.shields.io/codecov/c/github/mongomock/mongomock.svg?style=flat-square\n :target: https://codecov.io/gh/mongomock/mongomock\n\n\nWhat is this?\n-------------\nMongomock is a small library to help testing Python code that interacts with MongoDB via Pymongo.\n\nTo understand what it's useful for, we can take the following code:\n\n.. code-block:: python\n\n def increase_votes(collection):\n for document in collection.find():\n collection.update_one(document, {'$set': {'votes': document['votes'] + 1}})\n\nThe above code can be tested in several ways:\n\n1. It can be tested against a real mongodb instance with pymongo.\n2. It can receive a record-replay style mock as an argument. In this manner we record the\n expected calls (find, and then a series of updates), and replay them later.\n3. It can receive a carefully hand-crafted mock responding to find() and update() appropriately.\n\nOption number 1 is obviously the best approach here, since we are testing against a real mongodb\ninstance. However, a mongodb instance needs to be set up for this, and cleaned before/after the\ntest. You might want to run your tests in continuous integration servers, on your laptop, or\nother bizarre platforms - which makes the mongodb requirement a liability.\n\nWe are left with #2 and #3. Unfortunately they are very high maintenance in real scenarios,\nsince they replicate the series of calls made in the code, violating the DRY rule. Let's see\n#2 in action - we might write our test like so:\n\n.. code-block:: python\n\n def test_increase_votes():\n objects = [dict(...), dict(...), ...]\n collection_mock = my_favorite_mock_library.create_mock(Collection)\n record()\n collection_mock.find().AndReturn(objects)\n for obj in objects:\n collection_mock.update_one(obj, {'$set': {'votes': obj['votes']}})\n replay()\n increase_votes(collection_mock)\n verify()\n\nLet's assume the code changes one day, because the author just learned about the '$inc' instruction:\n\n.. code-block:: python\n\n def increase_votes(collection):\n collection.update_many({}, {'$inc': {'votes': 1}})\n\nThis breaks the test, although the end result being tested is just the same. The test also repeats\nlarge portions of the code we already wrote.\n\nWe are left, therefore, with option #3 -- you want something to behave like a mongodb database\ncollection, without being one. This is exactly what this library aims to provide. With mongomock,\nthe test simply becomes:\n\n.. code-block:: python\n\n def test_increase_votes():\n collection = mongomock.MongoClient().db.collection\n objects = [dict(votes=1), dict(votes=2), ...]\n for obj in objects:\n obj['_id'] = collection.insert_one(obj).inserted_id\n increase_votes(collection)\n for obj in objects:\n stored_obj = collection.find_one({'_id': obj['_id']})\n stored_obj['votes'] -= 1\n assert stored_obj == obj # by comparing all fields we make sure only votes changed\n\nThis code checks *increase_votes* with respect to its functionality, not syntax or algorithm, and\ntherefore is much more robust as a test.\n\nIf the code to be tested is creating the connection itself with pymongo, you can use\nmongomock.patch (NOTE: you should use :code:`pymongo.MongoClient(...)` rather than\n:code:`from pymongo import MongoClient`, as shown below):\n\n.. code-block:: python\n\n @mongomock.patch(servers=(('server.example.com', 27017),))\n def test_increate_votes_endpoint():\n objects = [dict(votes=1), dict(votes=2), ...]\n client = pymongo.MongoClient('server.example.com')\n client.db.collection.insert_many(objects)\n call_endpoint('/votes')\n ... verify client.db.collection\n\n\nImportant Note About Project Status & Development\n-------------------------------------------------\n\nMongoDB is complex. This library aims at a reasonably complete mock of MongoDB for testing purposes,\nnot a perfect replica. This means some features are not likely to make it in any time soon.\n\nAlso, since many corner cases are encountered along the way, our goal is to try and TDD our way into\ncompleteness. This means that every time we encounter a missing or broken (incompatible) feature,\nwe write a test for it and fix it. There are probably lots of such issues hiding around lurking,\nso feel free to open issues and/or pull requests and help the project out!\n\n**NOTE**: We don't include pymongo functionality as \"stubs\" or \"placeholders\". Since this library is\nused to validate production code, it is unacceptable to behave differently than the real pymongo\nimplementation. In such cases it is better to throw `NotImplementedError` than implement a modified\nversion of the original behavior.\n\nUpgrading to Pymongo v4\n-----------------------\n\nThe major version 4 of Pymongo changed the API quite a bit. The Mongomock library has evolved to\nhelp you ease the migration:\n\n1. Upgrade to Mongomock v4 or above: if your tests are running with Pymongo installed, Mongomock\n will adapt its own API to the version of Pymongo installed.\n2. Upgrade to Pymongo v4 or above: your tests using Mongomock will fail exactly where your code\n would fail in production, so that you can fix it before releasing.\n\nContributing\n------------\n\nWhen submitting a PR, please make sure that:\n\n1. You include tests for the feature you are adding or bug you are fixing. Preferably, the test\n should compare against the real MongoDB engine (see `examples in tests`_ for reference).\n2. No existing test got deleted or unintentionally castrated\n3. The build passes on your PR.\n\nTo download, setup and perfom tests, run the following commands on Mac / Linux:\n\n.. code-block:: console\n\n $ git clone git@github.com:mongomock/mongomock.git\n $ pipx install hatch\n $ cd mongomock\n $ hatch test\n\nAlternatively, docker-compose can be used to simplify dependency management for local development:\n\n.. code-block:: console\n\n $ git clone git@github.com:mongomock/mongomock.git\n $ cd mongomock\n $ docker compose build\n $ docker compose run --rm mongomock\n\nIf you want to run ``hatch`` against a specific environment in the container:\n\n.. code-block:: console\n\n $ docker compose run --rm mongomock hatch test -py=3.11 -i pymongo=4\n\nIf you'd like to run only one test, you can also add the test name at the end of your command:\n\n.. code-block:: console\n\n $ docker compose run --rm mongomock hatch test -py=3.12 -i pymongo=4 tests/test__mongomock.py::MongoClientCollectionTest::test__insert\n\nNOTE: If the MongoDB image was updated, or you want to try a different MongoDB version in\n``docker-compose``, you'll have to issue a ``docker compose down`` before you do anything else to\nensure you're running against the intended version.\n\nutcnow\n~~~~~~\n\nWhen developing features that need to make use of \"now,\" please use the libraries :code:`utcnow`\nhelper method in the following way:\n\n.. code-block:: python\n\n import mongomock\n # Awesome code!\n now_reference = mongomock.utcnow()\n\nThis provides users a consistent way to mock the notion of \"now\" in mongomock if they so choose.\nPlease see `utcnow docstring for more details <mongomock/helpers.py#L52>`_.\n\nBranching model\n~~~~~~~~~~~~~~~\n\nThe branching model used for this project follows the `gitflow workflow`_. This means that pull\nrequests should be issued against the `develop` branch and *not* the `master` branch. If you want\nto contribute to the legacy 2.x branch then your pull request should go into the `support/2.x`\nbranch.\n\nReleasing\n~~~~~~~~~\n\nWhen ready for a release, tag the `develop` branch with a new tag (please keep semver names) and\npush your tags to GitHub. The CI should do the rest.\n\nTo add release notes, create a release in GitHub's `Releases Page <https://github.com/mongomock/mongomock/releases>`_\nthen generate the release notes locally with:\n\n.. code-block:: bash\n\n python -c \"from pbr import git; git.write_git_changelog()\"\n\nThen you can get the relevant section in the generated `Changelog` file.\n\nAcknowledgements\n----------------\n\nMongomock has originally been developed by `Rotem Yaari <https://github.com/vmalloc/>`_, then by\n`Martin Domke <https://github.com/mdomke>`_. It is currently being developed and maintained by\n`Pascal Corpet <https://github.com/pcorpet>`_ .\n\nAlso, many thanks go to the following people for helping out, contributing pull requests and fixing\nbugs:\n\n* Alec Perkins\n* Alexandre Viau\n* Austin W Ellis\n* Andrey Ovchinnikov\n* Arthur Hirata\n* Baruch Oxman\n* Corey Downing\n* Craig Hobbs\n* Daniel Murray\n* David Fischer\n* Diego Garcia\n* Dmitriy Kostochko\n* Drew Winstel\n* Eddie Linder\n* Edward D'Souza\n* Emily Rosengren\n* Eugene Chernyshov\n* Grigoriy Osadchenko\n* Israel Teixeira\n* Jacob Perkins\n* Jason Burchfield\n* Jason Sommer\n* Jeff Browning\n* Jeff McGee\n* Jo\u00ebl Franusic\n* `Jonathan Hed\u00e9n <https://github.com/jheden/>`_\n* Julian Hille\n* Krzysztof P\u0142ocharz\n* Lyon Zhang\n* `Lucas Rangel Cezimbra <https://github.com/Lrcezimbra/>`_\n* Marc Prewitt\n* Marcin Barczynski\n* Marian Galik\n* Micha\u0142 Albrycht\n* Mike Ho\n* Nigel Choi\n* Omer Gertel\n* Omer Katz\n* Papp Gy\u0151z\u0151\n* Paul Glass\n* Scott Sexton\n* Srinivas Reddy Thatiparthy\n* Taras Boiko\n* Todd Tomkinson\n* `Xinyan Lu <https://github.com/lxy1992/>`_\n* Zachary Carter\n* catty (ca77y _at_ live.com)\n* emosenkis\n* hthieu1110\n* \u05d9ppetlinskiy\n* pacud\n* tipok\n* waskew (waskew _at_ narrativescience.com)\n* jmsantorum (jmsantorum [at] gmail [dot] com)\n* lidongyong\n* `Juan Gutierrez <https://github.com/juannyg/>`_\n\n.. _examples in tests: https://github.com/mongomock/mongomock/blob/develop/tests/test__mongomock.py\n.. _gitflow workflow: https://www.atlassian.com/git/tutorials/comparing-workflows/gitflow-workflow\n",
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