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.coveragerc Normal file
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[run]
include = dependency_injector/*
omit = tests/*

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version = 1
test_patterns = ["tests/**/test_*.py"]
exclude_patterns = ["docs/**"]
[[analyzers]]
name = "python"
enabled = true
[analyzers.meta]
runtime_version = "3.x.x"

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github: rmk135

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name: Publishing
on:
workflow_dispatch:
push:
tags:
- '*'
jobs:
tests:
name: Run tests
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: 3.13
- run: pip install tox
- run: tox
env:
TOXENV: 3.13
linters:
name: Run linters
runs-on: ubuntu-24.04
strategy:
matrix:
toxenv: [flake8, pydocstyle, mypy, pylint]
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: 3.13
- run: pip install tox
- run: tox
env:
TOXENV: ${{ matrix.toxenv }}
build-sdist:
name: Build source tarball
needs: [tests, linters]
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: 3.13
- run: |
python -m pip install --upgrade build
python -m build --sdist
- uses: actions/upload-artifact@v4
with:
name: cibw-sdist
path: ./dist/*
build-wheels:
name: Build wheels
needs: [tests, linters]
runs-on: ${{ matrix.os }}
strategy:
matrix:
os: [ubuntu-24.04, ubuntu-24.04-arm, windows-2019, macos-14]
env:
CIBW_SKIP: cp27-*
steps:
- uses: actions/checkout@v3
- name: Build wheels
uses: pypa/cibuildwheel@v2.20.0
- uses: actions/upload-artifact@v4
with:
name: cibw-wheels-x86-${{ matrix.os }}-${{ strategy.job-index }}
path: ./wheelhouse/*.whl
publish:
name: Publish on PyPI
needs: [build-sdist, build-wheels]
runs-on: ubuntu-24.04
steps:
- uses: actions/download-artifact@v4
with:
pattern: cibw-*
path: dist
merge-multiple: true
- uses: pypa/gh-action-pypi-publish@release/v1
with:
user: __token__
password: ${{ secrets.PYPI_API_TOKEN }}
# For publishing to Test PyPI, uncomment next two lines:
# password: ${{ secrets.TEST_PYPI_API_TOKEN }}
# repository_url: https://test.pypi.org/legacy/
publish-docs:
name: Publish docs
needs: [publish]
runs-on: ubuntu-24.04
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: 3.13
- run: pip install awscli
- run: pip install -r requirements-doc.txt
- run: pip install -e .
- run: (cd docs && make clean html)
- run: |
aws s3 sync docs/_build/html s3://python-dependency-injector-docs --delete
aws cloudfront create-invalidation --distribution-id ${{ secrets.AWS_CLOUDFRONT_DISTRIBUTION_ID }} --path "/*" > /dev/null
echo "Cache invalidation triggered"
env:
AWS_ACCESS_KEY_ID: ${{ secrets.AWS_ACCESS_KEY_ID }}
AWS_SECRET_ACCESS_KEY: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
AWS_DEFAULT_REGION: ${{ secrets.AWS_DEFAULT_REGION }}

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name: Tests and linters
on: [push, pull_request, workflow_dispatch]
jobs:
tests-on-legacy-versions:
name: Run tests on legacy versions
runs-on: ubuntu-20.04
strategy:
matrix:
python-version: [3.7]
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- run: pip install tox
- run: tox
env:
TOXENV: ${{ matrix.python-version }}
test-on-different-versions:
name: Run tests
runs-on: ubuntu-latest
strategy:
matrix:
python-version: [3.8, 3.9, "3.10", 3.11, 3.12, 3.13]
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: ${{ matrix.python-version }}
- run: pip install tox
- run: tox
env:
TOXENV: ${{ matrix.python-version }}
test-different-pydantic-versions:
name: Run tests with different pydantic versions
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: "3.12"
- run: pip install tox
- run: tox -e pydantic-v1,pydantic-v2
test-coverage:
name: Run tests with coverage
runs-on: ubuntu-latest
env:
DEPENDENCY_INJECTOR_DEBUG_MODE: 1
PIP_VERBOSE: 1
COVERALLS_REPO_TOKEN: ${{ secrets.COVERALLS_REPO_TOKEN }}
GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: 3.12
- run: pip install tox 'cython>=3,<4'
- run: tox -vv
env:
TOXENV: coveralls
linters:
name: Run linters
runs-on: ubuntu-latest
strategy:
matrix:
toxenv: [flake8, pydocstyle, mypy, pylint]
steps:
- uses: actions/checkout@v3
- uses: actions/setup-python@v4
with:
python-version: 3.13
- run: pip install tox
- run: tox
env:
TOXENV: ${{ matrix.toxenv }}

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.gitignore vendored
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__pycache__/
*.py[cod]
# C extensions
*.so
# Distribution / packaging
.Python
env/
@ -30,13 +33,12 @@ pip-log.txt
pip-delete-this-directory.txt
# Unit test / coverage reports
reports/
htmlcov/
.tox/
.coverage
.cache
nosetests.xml
coverage.xml
.hypothesis/
# Translations
*.mo
@ -55,21 +57,13 @@ target/
.idea/
# Virtualenv
venv*/
venv/
# SQLite
*.db
# JointJS Experiments
jointjs/
# Vim Rope
.ropeproject/
# Cython artifacts
src/**/*.c
src/**/*.h
src/**/*.so
src/**/*.html
# Workspace for samples
.workspace/
.vscode/

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.pylintrc Normal file
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[MASTER]
# Add <file or directory> to the black list. It should be a base name, not a
# path. You may set this option multiple times.
ignore=utils,test
[MESSAGES CONTROL]
# Disable the message(s) with the given id(s).
# disable-msg=
[SIMILARITIES]
# Minimum lines number of a similarity.
min-similarity-lines=5
[TYPECHECK]
ignore-mixin-members=yes
# ignored-classes=
zope=no
# generated-members=providedBy,implementedBy,rawDataReceived
[DESIGN]
# Maximum number of arguments for function / method
max-args=10
# Maximum number of locals for function / method body
max-locals=20
# Maximum number of return / yield for function / method body
max-returns=10
# Maximum number of branch for function / method body
max-branchs=10
# Maximum number of statements in function / method body
max-statements=60
# Maximum number of parents for a class (see R0901).
max-parents=10
# Maximum number of attributes for a class (see R0902).
max-attributes=30
# Minimum number of public methods for a class (see R0903).
min-public-methods=0
# Maximum number of public methods for a class (see R0904).
max-public-methods=30

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.travis.yml Normal file
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sudo: false
language: python
install: pip install tox
script: tox
python:
- 3.5
env:
- TOXENV=coveralls
- TOXENV=pylint
- TOXENV=flake8
- TOXENV=pep257
- TOXENV=py26
- TOXENV=py27
- TOXENV=py33
- TOXENV=py34
- TOXENV=py35
- TOXENV=pypy
- TOXENV=pypy3

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Dependency Injector Contributors
================================
+ Roman Mogylatov (rmk135)
+ Konstantin vz'One Enchant (sirkonst)
+ Terrence Brannon (metaperl)
+ Stanislav Lobanov (asyncee)
+ James Lafa (jameslafa)
+ Vlad Ghita (vlad-ghita)
+ Jeroen Rietveld (jeroenrietveld)
+ Dmitry Kuzmin (xotonic)
+ supakeen (supakeen)
+ Bruno P. Kinoshita (kinow)
+ RobinsonMa (RobinsonMa)
+ Rüdiger Busche (JarnoRFB)
+ Dmitry Rassoshenko (rda-dev)
+ Fotis Koutoupas (kootoopas)
+ Shubhendra Singh Chauhan (withshubh)
+ sonthonaxrk (sonthonaxrk)
+ Ngo Thanh Loi (Leonn) (loingo95)
+ Thiago Hiromi (thiromi)
+ Felipe Rubio (krouw)
+ Anton Petrov (anton-petrov)
+ ZipFile (ZipFile)
+ Roman Mogilatov

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Copyright (c) 2024, Roman Mogylatov
Copyright (c) 2015, ETS Labs
All rights reserved.
Redistribution and use in source and binary forms, with or without

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recursive-include src/dependency_injector *.py* *.c
recursive-include tests *.py
include dependency_injector/*
include README.rst
include CONTRIBUTORS.rst
include LICENSE.rst
include requirements.txt
include setup.py
include tox.ini
include py.typed

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VERSION := $(shell python setup.py --version)
export COVERAGE_RCFILE := pyproject.toml
clean:
# Clean sources
find src -name '*.py[cod]' -delete
find src -name '__pycache__' -delete
find src -name '*.c' -delete
find src -name '*.h' -delete
find src -name '*.so' -delete
find src -name '*.html' -delete
# Clean tests
find tests -name '*.py[co]' -delete
find tests -name '__pycache__' -delete
# Clean examples
find examples -name '*.py[co]' -delete
find examples -name '__pycache__' -delete
build: clean
# Compile C extensions
python setup.py build_ext --inplace
# Move all Cython html reports
mkdir -p reports/cython/
find src -name '*.html' -exec mv {} reports/cython/ \;
docs-live:
sphinx-autobuild docs docs/_build/html
install: uninstall clean build
pip install -ve .
uninstall:
- pip uninstall -y -q dependency-injector 2> /dev/null
test:
# Unit tests with coverage report
coverage erase
coverage run -m pytest -c tests/.configs/pytest.ini
coverage report
coverage html
check:
flake8 src/dependency_injector/
flake8 examples/
pydocstyle src/dependency_injector/
pydocstyle examples/
mypy tests/typing
test-publish: build
# Create distributions
python -m build --sdist
# Upload distributions to PyPI
twine upload --repository testpypi dist/dependency-injector-$(VERSION)*
publish:
# Merge release to master branch
git checkout master
git merge --no-ff release/$(VERSION) -m "Merge branch 'release/$(VERSION)' into master"
git push origin master
# Create and upload tag
git tag -a $(VERSION) -m 'version $(VERSION)'
git push --tags

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.. figure:: https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/logo.svg
:target: https://github.com/ets-labs/python-dependency-injector
Dependency Injector
===================
|
*Dependency Injector* is a Python dependency injection framework. It was
designed to be unified, developer's friendly tool for managing any kind
of Python objects and their dependencies in formal, pretty way.
.. image:: https://img.shields.io/pypi/v/dependency_injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: Latest Version
.. image:: https://img.shields.io/pypi/l/dependency_injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: License
Below is a list of some key features and points of *Dependency Injector*:
.. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: Supported Python versions
.. image:: https://img.shields.io/pypi/implementation/dependency_injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: Supported Python implementations
- Easy, smart, pythonic style.
- Obvious, clear structure.
- Memory efficiency.
- Thread safety.
- Semantic versioning.
.. image:: https://pepy.tech/badge/dependency-injector
:target: https://pepy.tech/project/dependency-injector
:alt: Downloads
Main idea of *Dependency Injector* is to keep dependencies under control.
.. image:: https://pepy.tech/badge/dependency-injector/month
:target: https://pepy.tech/project/dependency-injector
:alt: Downloads
Status
------
.. image:: https://pepy.tech/badge/dependency-injector/week
:target: https://pepy.tech/project/dependency-injector
:alt: Downloads
.. image:: https://img.shields.io/pypi/wheel/dependency-injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: Wheel
.. image:: https://img.shields.io/github/actions/workflow/status/ets-labs/python-dependency-injector/tests-and-linters.yml?branch=master
:target: https://github.com/ets-labs/python-dependency-injector/actions
:alt: Build Status
.. image:: https://coveralls.io/repos/github/ets-labs/python-dependency-injector/badge.svg?branch=master
:target: https://coveralls.io/github/ets-labs/python-dependency-injector?branch=master
:alt: Coverage Status
What is ``Dependency Injector``?
================================
``Dependency Injector`` is a dependency injection framework for Python.
It helps implement the dependency injection principle.
Key features of the ``Dependency Injector``:
- **Providers**. Provides ``Factory``, ``Singleton``, ``Callable``, ``Coroutine``, ``Object``,
``List``, ``Dict``, ``Configuration``, ``Resource``, ``Dependency``, and ``Selector`` providers
that help assemble your objects.
See `Providers <https://python-dependency-injector.ets-labs.org/providers/index.html>`_.
- **Overriding**. Can override any provider by another provider on the fly. This helps in testing
and configuring dev/stage environment to replace API clients with stubs etc. See
`Provider overriding <https://python-dependency-injector.ets-labs.org/providers/overriding.html>`_.
- **Configuration**. Reads configuration from ``yaml``, ``ini``, and ``json`` files, ``pydantic`` settings,
environment variables, and dictionaries.
See `Configuration provider <https://python-dependency-injector.ets-labs.org/providers/configuration.html>`_.
- **Resources**. Helps with initialization and configuring of logging, event loop, thread
or process pool, etc. Can be used for per-function execution scope in tandem with wiring.
See `Resource provider <https://python-dependency-injector.ets-labs.org/providers/resource.html>`_.
- **Containers**. Provides declarative and dynamic containers.
See `Containers <https://python-dependency-injector.ets-labs.org/containers/index.html>`_.
- **Wiring**. Injects dependencies into functions and methods. Helps integrate with
other frameworks: Django, Flask, Aiohttp, Sanic, FastAPI, etc.
See `Wiring <https://python-dependency-injector.ets-labs.org/wiring.html>`_.
- **Asynchronous**. Supports asynchronous injections.
See `Asynchronous injections <https://python-dependency-injector.ets-labs.org/providers/async.html>`_.
- **Typing**. Provides typing stubs, ``mypy``-friendly.
See `Typing and mypy <https://python-dependency-injector.ets-labs.org/providers/typing_mypy.html>`_.
- **Performance**. Fast. Written in ``Cython``.
- **Maturity**. Mature and production-ready. Well-tested, documented, and supported.
.. code-block:: python
from dependency_injector import containers, providers
from dependency_injector.wiring import Provide, inject
class Container(containers.DeclarativeContainer):
config = providers.Configuration()
api_client = providers.Singleton(
ApiClient,
api_key=config.api_key,
timeout=config.timeout,
)
service = providers.Factory(
Service,
api_client=api_client,
)
@inject
def main(service: Service = Provide[Container.service]) -> None:
...
if __name__ == "__main__":
container = Container()
container.config.api_key.from_env("API_KEY", required=True)
container.config.timeout.from_env("TIMEOUT", as_=int, default=5)
container.wire(modules=[__name__])
main() # <-- dependency is injected automatically
with container.api_client.override(mock.Mock()):
main() # <-- overridden dependency is injected automatically
When you call the ``main()`` function the ``Service`` dependency is assembled and injected automatically.
When you do testing, you call the ``container.api_client.override()`` method to replace the real API
client with a mock. When you call ``main()``, the mock is injected.
You can override any provider with another provider.
It also helps you in a re-configuring project for different environments: replace an API client
with a stub on the dev or stage.
With the ``Dependency Injector``, object assembling is consolidated in a container. Dependency injections are defined explicitly.
This makes it easier to understand and change how an application works.
.. figure:: https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/di-readme.svg
:target: https://github.com/ets-labs/python-dependency-injector
Visit the docs to know more about the
`Dependency injection and inversion of control in Python <https://python-dependency-injector.ets-labs.org/introduction/di_in_python.html>`_.
+---------------------------------------+---------------------------------------------------------------------------------+
| *PyPi* | .. image:: https://img.shields.io/pypi/v/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Latest Version |
| | .. image:: https://img.shields.io/pypi/dm/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Downloads |
| | .. image:: https://img.shields.io/pypi/l/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: License |
+---------------------------------------+---------------------------------------------------------------------------------+
| *Python versions and implementations* | .. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Supported Python versions |
| | .. image:: https://img.shields.io/pypi/implementation/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Supported Python implementations |
+---------------------------------------+---------------------------------------------------------------------------------+
| *Builds and tests coverage* | .. image:: https://travis-ci.org/ets-labs/dependency_injector.svg?branch=master |
| | :target: https://travis-ci.org/ets-labs/dependency_injector |
| | :alt: Build Status |
| | .. image:: https://coveralls.io/repos/ets-labs/dependency_injector/badge.svg |
| | :target: https://coveralls.io/r/ets-labs/dependency_injector |
| | :alt: Coverage Status |
+---------------------------------------+---------------------------------------------------------------------------------+
Installation
------------
The package is available on the `PyPi`_::
*Dependency Injector* library is available on PyPi_::
pip install dependency-injector
pip install dependency_injector
Documentation
-------------
The documentation is available `here <https://python-dependency-injector.ets-labs.org/>`_.
*Dependency Injector* documentation is hosted on ReadTheDocs:
- `User's guide`_
- `API docs`_
Examples
--------
Choose one of the following:
.. code-block:: python
- `Application example (single container) <https://python-dependency-injector.ets-labs.org/examples/application-single-container.html>`_
- `Application example (multiple containers) <https://python-dependency-injector.ets-labs.org/examples/application-multiple-containers.html>`_
- `Decoupled packages example (multiple containers) <https://python-dependency-injector.ets-labs.org/examples/decoupled-packages.html>`_
- `Boto3 example <https://python-dependency-injector.ets-labs.org/examples/boto3.html>`_
- `Django example <https://python-dependency-injector.ets-labs.org/examples/django.html>`_
- `Flask example <https://python-dependency-injector.ets-labs.org/examples/flask.html>`_
- `Aiohttp example <https://python-dependency-injector.ets-labs.org/examples/aiohttp.html>`_
- `Sanic example <https://python-dependency-injector.ets-labs.org/examples/sanic.html>`_
- `FastAPI example <https://python-dependency-injector.ets-labs.org/examples/fastapi.html>`_
- `FastAPI + Redis example <https://python-dependency-injector.ets-labs.org/examples/fastapi-redis.html>`_
- `FastAPI + SQLAlchemy example <https://python-dependency-injector.ets-labs.org/examples/fastapi-sqlalchemy.html>`_
"""Concept example of `Dependency Injector`."""
Tutorials
---------
import sqlite3
Choose one of the following:
from dependency_injector import catalogs
from dependency_injector import providers
from dependency_injector import injections
- `Flask web application tutorial <https://python-dependency-injector.ets-labs.org/tutorials/flask.html>`_
- `Aiohttp REST API tutorial <https://python-dependency-injector.ets-labs.org/tutorials/aiohttp.html>`_
- `Asyncio monitoring daemon tutorial <https://python-dependency-injector.ets-labs.org/tutorials/asyncio-daemon.html>`_
- `CLI application tutorial <https://python-dependency-injector.ets-labs.org/tutorials/cli.html>`_
Concept
-------
class UsersService(object):
"""Users service, that has dependency on database."""
The framework stands on the `PEP20 (The Zen of Python) <https://www.python.org/dev/peps/pep-0020/>`_ principle:
def __init__(self, db):
"""Initializer."""
self.db = db
.. code-block:: bash
Explicit is better than implicit
class AuthService(object):
"""Auth service, that has dependencies on users service and database."""
You need to specify how to assemble and where to inject the dependencies explicitly.
def __init__(self, db, users_service):
"""Initializer."""
self.db = db
self.users_service = users_service
The power of the framework is in its simplicity.
``Dependency Injector`` is a simple tool for the powerful concept.
Frequently asked questions
--------------------------
class Services(catalogs.DeclarativeCatalog):
"""Catalog of service providers."""
What is dependency injection?
- dependency injection is a principle that decreases coupling and increases cohesion
database = providers.Singleton(sqlite3.connect, ':memory:')
""":type: providers.Provider -> sqlite3.Connection"""
Why should I do the dependency injection?
- your code becomes more flexible, testable, and clear 😎
users = providers.Factory(UsersService,
db=database)
""":type: providers.Provider -> UsersService"""
How do I start applying the dependency injection?
- you start writing the code following the dependency injection principle
- you register all of your application components and their dependencies in the container
- when you need a component, you specify where to inject it or get it from the container
auth = providers.Factory(AuthService,
db=database,
users_service=users)
""":type: providers.Provider -> AuthService"""
What price do I pay and what do I get?
- you need to explicitly specify the dependencies
- it will be extra work in the beginning
- it will payoff as project grows
Have a question?
- Open a `Github Issue <https://github.com/ets-labs/python-dependency-injector/issues>`_
# Retrieving catalog providers:
users_service = Services.users()
auth_service = Services.auth()
Found a bug?
- Open a `Github Issue <https://github.com/ets-labs/python-dependency-injector/issues>`_
# Making some asserts:
assert users_service.db is auth_service.db is Services.database()
assert isinstance(auth_service.users_service, UsersService)
assert users_service is not Services.users()
assert auth_service is not Services.auth()
Want to help?
- |star| Star the ``Dependency Injector`` on the `Github <https://github.com/ets-labs/python-dependency-injector/>`_
- |new| Start a new project with the ``Dependency Injector``
- |tell| Tell your friend about the ``Dependency Injector``
Want to contribute?
- |fork| Fork the project
- |pull| Open a pull request to the ``develop`` branch
# Making some "inline" injections:
@injections.inject(users_service=Services.users)
@injections.inject(auth_service=Services.auth)
@injections.inject(database=Services.database)
def example(users_service, auth_service, database):
"""Example callback."""
assert users_service.db is auth_service.db
assert auth_service.db is database
assert database is Services.database()
.. _PyPi: https://pypi.org/project/dependency-injector/
.. |star| unicode:: U+2B50 U+FE0F .. star sign1
.. |new| unicode:: U+1F195 .. new sign
.. |tell| unicode:: U+1F4AC .. tell sign
.. |fork| unicode:: U+1F500 .. fork sign
.. |pull| unicode:: U+2B05 U+FE0F .. pull sign
# Making a call of decorated callback:
example()
# Overriding auth service provider and making some asserts:
class ExtendedAuthService(AuthService):
"""Extended version of auth service."""
def __init__(self, db, users_service, ttl):
"""Initializer."""
self.ttl = ttl
super(ExtendedAuthService, self).__init__(db=db,
users_service=users_service)
Services.auth.override(providers.Factory(ExtendedAuthService,
db=Services.database,
users_service=Services.users,
ttl=3600))
auth_service = Services.auth()
assert isinstance(auth_service, ExtendedAuthService)
You can get more *Dependency Injector* examples in ``/examples`` directory on
GitHub:
https://github.com/ets-labs/dependency_injector
Feedback
--------
Feel free to post questions, bugs, feature requests, proposals etc. on
*Dependency Injector* GitHub Issues:
https://github.com/ets-labs/dependency_injector/issues
Your feedback is quite important!
.. _PyPi: https://pypi.python.org/pypi/dependency_injector
.. _User's guide: http://dependency_injector.readthedocs.org/en/stable/
.. _API docs: http://dependency-injector.readthedocs.org/en/stable/api/
.. _SLOC: http://en.wikipedia.org/wiki/Source_lines_of_code
.. _SOLID: http://en.wikipedia.org/wiki/SOLID_%28object-oriented_design%29
.. _IoC: http://en.wikipedia.org/wiki/Inversion_of_control
.. _dependency injection: http://en.wikipedia.org/wiki/Dependency_injection

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@ -0,0 +1,116 @@
"""Dependency injector."""
from .catalogs import DeclarativeCatalog
from .catalogs import AbstractCatalog
from .catalogs import DynamicCatalog
from .catalogs import CatalogBundle
from .catalogs import override
from .providers import Provider
from .providers import Delegate
from .providers import Callable
from .providers import DelegatedCallable
from .providers import Factory
from .providers import DelegatedFactory
from .providers import Singleton
from .providers import DelegatedSingleton
from .providers import ExternalDependency
from .providers import StaticProvider
from .providers import Class
from .providers import Object
from .providers import Function
from .providers import Value
from .providers import Config
from .injections import Injection
from .injections import Arg
from .injections import KwArg
from .injections import Attribute
from .injections import Method
from .injections import inject
from .utils import is_provider
from .utils import ensure_is_provider
from .utils import is_delegated_provider
from .utils import is_injection
from .utils import ensure_is_injection
from .utils import is_arg_injection
from .utils import is_kwarg_injection
from .utils import is_attribute_injection
from .utils import is_method_injection
from .utils import is_catalog
from .utils import is_dynamic_catalog
from .utils import is_declarative_catalog
from .utils import is_catalog_bundle
from .utils import ensure_is_catalog_bundle
from .errors import Error
from .errors import UndefinedProviderError
# Backward compatibility for versions < 0.11.*
from . import catalogs
catalog = catalogs
VERSION = '1.14.2'
"""Version number that follows semantic versioning.
:type: str
"""
__all__ = (
# Catalogs
'DeclarativeCatalog',
'AbstractCatalog',
'DynamicCatalog',
'CatalogBundle',
'override',
# Providers
'Provider',
'Delegate',
'Callable',
'DelegatedCallable',
'Factory',
'DelegatedFactory',
'Singleton',
'DelegatedSingleton',
'ExternalDependency',
'StaticProvider',
'Class',
'Object',
'Function',
'Value',
'Config',
# Injections
'Injection',
'Arg',
'KwArg',
'Attribute',
'Method',
'inject',
# Utils
'is_provider',
'ensure_is_provider',
'is_delegated_provider',
'is_injection',
'ensure_is_injection',
'is_arg_injection',
'is_kwarg_injection',
'is_attribute_injection',
'is_method_injection',
'is_catalog',
'is_dynamic_catalog',
'is_declarative_catalog',
'is_catalog_bundle',
'ensure_is_catalog_bundle',
# Errors
'Error',
'UndefinedProviderError',
# Version
'VERSION'
)

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@ -0,0 +1,891 @@
"""Catalogs module."""
import six
from .errors import Error
from .errors import UndefinedProviderError
from .utils import is_provider
from .utils import is_catalog
from .utils import is_declarative_catalog
from .utils import ensure_is_provider
from .utils import ensure_is_catalog_bundle
@six.python_2_unicode_compatible
class CatalogBundle(object):
"""Bundle of catalog providers.
:py:class:`CatalogBundle` is a frozen, limited collection of catalog
providers. While catalog could be used as a centralized place for
particular providers group, such bundles of catalog providers can be used
for creating several frozen, limited scopes that could be passed to
different subsystems.
:py:class:`CatalogBundle` has API's parity with catalogs
(:py:class:`DeclarativeCatalog` or :py:class:`DynamicCatalog`) in terms of
retrieving the providers, but it is "frozen" in terms of modification
provider's list.
:py:class:`CatalogBundle` is considered to be dependable on catalogs
(:py:class:`DeclarativeCatalog` or :py:class:`DynamicCatalog`) entity by
its design.
.. py:attribute:: catalog
Bundle's catalog.
:type: :py:class:`DeclarativeCatalog` | :py:class:`DynamicCatalog`
.. py:attribute:: providers
Dictionary of all providers.
:type: dict[str, :py:class:`dependency_injector.providers.Provider`]
"""
catalog = None
__IS_CATALOG_BUNDLE__ = True
__slots__ = ('providers', '__dict__')
@classmethod
def sub_cls_factory(cls, catalog):
"""Create bundle subclass for catalog.
:return: Subclass of :py:class:`CatalogBundle`.
:rtype: :py:class:`CatalogBundle`
"""
return type('BundleSubclass', (cls,), dict(catalog=catalog))
def __init__(self, *providers):
"""Initializer.
:param providers: Tuple of catalog's bundle providers.
:type providers: tuple[
:py:class:`dependency_injector.providers.Provider`]
"""
self.providers = dict((self.catalog.get_provider_bind_name(provider),
provider)
for provider in providers)
self.__dict__.update(self.providers)
super(CatalogBundle, self).__init__()
def get_provider(self, name):
"""Return provider with specified name or raise an error.
:param name: Provider's name.
:type name: str
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
:return: Provider with specified name.
:rtype: :py:class:`dependency_injector.providers.Provider`
"""
try:
return self.providers[name]
except KeyError:
raise Error('Provider "{0}" is not a part of {1}'.format(name,
self))
def has_provider(self, name):
"""Check if there is provider with certain name.
:param name: Provider's name.
:type name: str
:rtype: bool
"""
return name in self.providers
def __getattr__(self, item):
"""Return provider with specified name or raise en error.
:param name: Attribute's name.
:type name: str
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
"""
if item.startswith('__') and item.endswith('__'):
return super(CatalogBundle, self).__getattr__(item)
raise UndefinedProviderError('Provider "{0}" is not a part '
'of {1}'.format(item, self))
def __repr__(self):
"""Return string representation of catalog's bundle.
:rtype: str
"""
return '<{0}.Bundle({1})>'.format(
self.catalog.name, ', '.join(six.iterkeys(self.providers)))
__str__ = __repr__
@six.python_2_unicode_compatible
class DynamicCatalog(object):
"""Dynamic catalog of providers.
:py:class:`DynamicCatalog` is a catalog of providers that could be created
in application's runtime. It should cover most of the cases when list of
providers that would be included in catalog is non-deterministic in terms
of apllication code (catalog's structure could be determined just after
application will be started and will do some initial work, like parsing
list of catalog's providers from the configuration).
.. code-block:: python
services = DynamicCatalog(auth=providers.Factory(AuthService),
users=providers.Factory(UsersService))
users_service = services.users()
.. py:attribute:: Bundle
Catalog's bundle class.
:type: :py:class:`CatalogBundle`
.. py:attribute:: name
Catalog's name.
By default, it is catalog's module + catalog's class name.
:type: str
.. py:attribute:: providers
Dictionary of all providers.
:type: dict[str, :py:class:`dependency_injector.providers.Provider`]
.. py:attribute:: overridden_by
Tuple of overriding catalogs.
:type: tuple[
:py:class:`DeclarativeCatalog` | :py:class:`DynamicCatalog`]
.. py:attribute:: provider_type
If provider type is defined, :py:class:`DynamicCatalog` checks that
all of its providers are instances of
:py:attr:`DynamicCatalog.provider_type`.
:type: type | None
"""
provider_type = None
__IS_CATALOG__ = True
__slots__ = ('name', 'providers', 'provider_names', 'overridden_by',
'Bundle')
def __init__(self, **providers):
"""Initializer.
:param providers: Dictionary of catalog providers.
:type providers:
dict[str, :py:class:`dependency_injector.providers.Provider`]
"""
self.Bundle = CatalogBundle.sub_cls_factory(self)
self.name = '.'.join((self.__class__.__module__,
self.__class__.__name__))
self.providers = dict()
self.provider_names = dict()
self.overridden_by = tuple()
self.bind_providers(providers)
super(DynamicCatalog, self).__init__()
def is_bundle_owner(self, bundle):
"""Check if catalog is bundle owner.
:param bundle: Catalog's bundle instance.
:type bundle: :py:class:`CatalogBundle`
:rtype: bool
"""
return ensure_is_catalog_bundle(bundle) and bundle.catalog is self
def get_provider_bind_name(self, provider):
"""Return provider's name in catalog.
:param provider: Provider instance.
:type provider: :py:class:`dependency_injector.providers.Provider`
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
:return: Provider's name.
:rtype: str
"""
if not self.is_provider_bound(provider):
raise Error('Can not find bind name for {0} in catalog {1}'.format(
provider, self))
return self.provider_names[provider]
def is_provider_bound(self, provider):
"""Check if provider is bound to the catalog.
:param provider: Provider instance.
:type provider: :py:class:`dependency_injector.providers.Provider`
:rtype: bool
"""
return provider in self.provider_names
def filter(self, provider_type):
"""Return dictionary of providers, that are instance of provided type.
:param provider_type: Provider's type.
:type provider_type: :py:class:`dependency_injector.providers.Provider`
:rtype: dict[str, :py:class:`dependency_injector.providers.Provider`]
"""
return dict((name, provider)
for name, provider in six.iteritems(self.providers)
if isinstance(provider, provider_type))
@property
def is_overridden(self):
"""Read-only property that is set to ``True`` if catalog is overridden.
:rtype: bool
"""
return bool(self.overridden_by)
@property
def last_overriding(self):
"""Read-only reference to the last overriding catalog, if any.
:type: :py:class:`DeclarativeCatalog` | :py:class:`DynamicCatalog` |
None
"""
return self.overridden_by[-1] if self.overridden_by else None
def override(self, overriding):
"""Override current catalog providers by overriding catalog providers.
:param overriding: Overriding catalog.
:type overriding: :py:class:`DeclarativeCatalog` |
:py:class:`DynamicCatalog`
:raise: :py:exc:`dependency_injector.errors.Error` if trying to
override catalog by itself
:rtype: None
"""
if overriding is self:
raise Error('Catalog {0} could not be overridden '
'with itself'.format(self))
self.overridden_by += (overriding,)
for name, provider in six.iteritems(overriding.providers):
self.get_provider(name).override(provider)
def reset_last_overriding(self):
"""Reset last overriding catalog.
:rtype: None
"""
if not self.is_overridden:
raise Error('Catalog {0} is not overridden'.format(self))
self.overridden_by = self.overridden_by[:-1]
for provider in six.itervalues(self.providers):
provider.reset_last_overriding()
def reset_override(self):
"""Reset all overridings for all catalog providers.
:rtype: None
"""
self.overridden_by = tuple()
for provider in six.itervalues(self.providers):
provider.reset_override()
def get_provider(self, name):
"""Return provider with specified name or raise an error.
:param name: Provider's name.
:type name: str
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
:return: Provider with specified name.
:rtype: :py:class:`dependency_injector.providers.Provider`
"""
try:
return self.providers[name]
except KeyError:
raise UndefinedProviderError('{0} has no provider with such '
'name - {1}'.format(self, name))
def bind_provider(self, name, provider):
"""Bind provider to catalog with specified name.
:param name: Name of the provider.
:type name: str
:param provider: Provider instance.
:type provider: :py:class:`dependency_injector.providers.Provider`
:raise: :py:exc:`dependency_injector.errors.Error`
:rtype: None
"""
provider = ensure_is_provider(provider)
if (self.__class__.provider_type and
not isinstance(provider, self.__class__.provider_type)):
raise Error('{0} can contain only {1} instances'.format(
self, self.__class__.provider_type))
if name in self.providers:
raise Error('Catalog {0} already has provider with '
'such name - {1}'.format(self, name))
if provider in self.provider_names:
raise Error('Catalog {0} already has such provider '
'instance - {1}'.format(self, provider))
self.providers[name] = provider
self.provider_names[provider] = name
def bind_providers(self, providers):
"""Bind providers dictionary to catalog.
:param providers: Dictionary of providers, where key is a name
and value is a provider.
:type providers:
dict[str, :py:class:`dependency_injector.providers.Provider`]
:raise: :py:exc:`dependency_injector.errors.Error`
:rtype: None
"""
for name, provider in six.iteritems(providers):
self.bind_provider(name, provider)
def has_provider(self, name):
"""Check if there is provider with certain name.
:param name: Provider's name.
:type name: str
:rtype: bool
"""
return name in self.providers
def unbind_provider(self, name):
"""Remove provider binding.
:param name: Provider's name.
:type name: str
:rtype: None
"""
provider = self.get_provider(name)
del self.providers[name]
del self.provider_names[provider]
def __getattr__(self, name):
"""Return provider with specified name or raise en error.
:param name: Attribute's name.
:type name: str
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
"""
return self.get_provider(name)
def __setattr__(self, name, value):
"""Handle setting of catalog attributes.
Setting of attributes works as usual, but if value of attribute is
provider, this provider will be bound to catalog.
:param name: Attribute's name.
:type name: str
:param value: Attribute's value.
:type value: :py:class:`dependency_injector.providers.Provider` |
object
:rtype: None
"""
if is_provider(value):
return self.bind_provider(name, value)
return super(DynamicCatalog, self).__setattr__(name, value)
def __delattr__(self, name):
"""Handle deleting of catalog attibute.
Deleting of attributes works as usual, but if value of attribute is
provider, this provider will be unbound from catalog.
:param name: Attribute's name.
:type name: str
:rtype: None
"""
self.unbind_provider(name)
def __repr__(self):
"""Return Python representation of catalog.
:rtype: str
"""
return '<{0}({1})>'.format(self.name,
', '.join(six.iterkeys(self.providers)))
__str__ = __repr__
@six.python_2_unicode_compatible
class DeclarativeCatalogMetaClass(type):
"""Declarative catalog meta class."""
def __new__(mcs, class_name, bases, attributes):
"""Declarative catalog class factory."""
cls_providers = tuple((name, provider)
for name, provider in six.iteritems(attributes)
if is_provider(provider))
inherited_providers = tuple((name, provider)
for base in bases if is_catalog(base)
for name, provider in six.iteritems(
base.providers))
providers = cls_providers + inherited_providers
cls = type.__new__(mcs, class_name, bases, attributes)
if cls.provider_type:
cls._catalog = type('DynamicCatalog',
(DynamicCatalog,),
dict(provider_type=cls.provider_type))()
else:
cls._catalog = DynamicCatalog()
cls._catalog.name = '.'.join((cls.__module__, cls.__name__))
cls._catalog.bind_providers(dict(providers))
cls.cls_providers = dict(cls_providers)
cls.inherited_providers = dict(inherited_providers)
cls.Bundle = cls._catalog.Bundle
return cls
@property
def name(cls):
"""Read-only property that represents catalog's name.
Catalog's name is catalog's module + catalog's class name.
:type: str
"""
return cls._catalog.name
@property
def providers(cls):
"""Read-only dictionary of all providers.
:type: dict[str, :py:class:`dependency_injector.providers.Provider`]
"""
return cls._catalog.providers
@property
def overridden_by(cls):
"""Tuple of overriding catalogs.
:type: tuple[
:py:class:`DeclarativeCatalog` |
:py:class:`DynamicCatalog`]
"""
return cls._catalog.overridden_by
@property
def is_overridden(cls):
"""Read-only property that is set to ``True`` if catalog is overridden.
:rtype: bool
"""
return cls._catalog.is_overridden
@property
def last_overriding(cls):
"""Read-only reference to the last overriding catalog, if any.
:type: :py:class:`DeclarativeCatalog` | :py:class:`DynamicCatalog` |
None
"""
return cls._catalog.last_overriding
def __getattr__(cls, name):
"""Return provider with specified name or raise en error.
:param name: Attribute's name.
:type name: str
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
"""
raise UndefinedProviderError('There is no provider "{0}" in '
'catalog {1}'.format(name, cls))
def __setattr__(cls, name, value):
"""Handle setting of catalog attributes.
Setting of attributes works as usual, but if value of attribute is
provider, this provider will be bound to catalog.
:param name: Attribute's name.
:type name: str
:param value: Attribute's value.
:type value: :py:class:`dependency_injector.providers.Provider` |
object
:rtype: None
"""
if is_provider(value):
setattr(cls._catalog, name, value)
return super(DeclarativeCatalogMetaClass, cls).__setattr__(name, value)
def __delattr__(cls, name):
"""Handle deleting of catalog attibute.
Deleting of attributes works as usual, but if value of attribute is
provider, this provider will be unbound from catalog.
:param name: Attribute's name.
:type name: str
:rtype: None
"""
if is_provider(getattr(cls, name)):
delattr(cls._catalog, name)
return super(DeclarativeCatalogMetaClass, cls).__delattr__(name)
def __repr__(cls):
"""Return string representation of the catalog.
:rtype: str
"""
return '<{0}({1})>'.format(cls.name,
', '.join(six.iterkeys(cls.providers)))
__str__ = __repr__
@six.add_metaclass(DeclarativeCatalogMetaClass)
class DeclarativeCatalog(object):
"""Declarative catalog of providers.
:py:class:`DeclarativeCatalog` is a catalog of providers that could be
defined in declarative manner. It should cover most of the cases when list
of providers that would be included in catalog is deterministic (catalog
will not change its structure in runtime).
.. code-block:: python
class Services(DeclarativeCatalog):
auth = providers.Factory(AuthService)
users = providers.Factory(UsersService)
users_service = Services.users()
.. py:attribute:: Bundle
Catalog's bundle class.
:type: :py:class:`CatalogBundle`
.. py:attribute:: name
Read-only property that represents catalog's name.
Catalog's name is catalog's module + catalog's class name.
:type: str
.. py:attribute:: cls_providers
Read-only dictionary of current catalog providers.
:type: dict[str, :py:class:`dependency_injector.providers.Provider`]
.. py:attribute:: inherited_providers
Read-only dictionary of inherited providers.
:type: dict[str, :py:class:`dependency_injector.providers.Provider`]
.. py:attribute:: providers
Read-only dictionary of all providers.
:type: dict[str, :py:class:`dependency_injector.providers.Provider`]
.. py:attribute:: overridden_by
Tuple of overriding catalogs.
:type: tuple[:py:class:`DeclarativeCatalog` |
:py:class:`DynamicCatalog`]
.. py:attribute:: is_overridden
Read-only property that is set to ``True`` if catalog is overridden.
:type: bool
.. py:attribute:: is_overridden
Read-only reference to the last overriding catalog, if any.
:type: :py:class:`DeclarativeCatalog` | :py:class:`DynamicCatalog` |
None
.. py:attribute:: provider_type
If provider type is defined, :py:class:`DeclarativeCatalog` checks that
all of its providers are instances of
:py:attr:`DeclarativeCatalog.provider_type`.
:type: type | None
"""
Bundle = CatalogBundle
name = str()
cls_providers = dict()
inherited_providers = dict()
providers = dict()
overridden_by = tuple()
is_overridden = bool
last_overriding = None
provider_type = None
_catalog = DynamicCatalog
__IS_CATALOG__ = True
@classmethod
def is_bundle_owner(cls, bundle):
"""Check if catalog is bundle owner.
:param bundle: Catalog's bundle instance.
:type bundle: :py:class:`CatalogBundle`
:rtype: bool
"""
return cls._catalog.is_bundle_owner(bundle)
@classmethod
def get_provider_bind_name(cls, provider):
"""Return provider's name in catalog.
:param provider: Provider instance.
:type provider: :py:class:`dependency_injector.providers.Provider`
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
:return: Provider's name.
:rtype: str
"""
return cls._catalog.get_provider_bind_name(provider)
@classmethod
def is_provider_bound(cls, provider):
"""Check if provider is bound to the catalog.
:param provider: Provider instance.
:type provider: :py:class:`dependency_injector.providers.Provider`
:rtype: bool
"""
return cls._catalog.is_provider_bound(provider)
@classmethod
def filter(cls, provider_type):
"""Return dictionary of providers, that are instance of provided type.
:param provider_type: Provider's type.
:type provider_type: :py:class:`dependency_injector.providers.Provider`
:rtype: dict[str, :py:class:`dependency_injector.providers.Provider`]
"""
return cls._catalog.filter(provider_type)
@classmethod
def override(cls, overriding):
"""Override current catalog providers by overriding catalog providers.
:param overriding: Overriding catalog.
:type overriding: :py:class:`DeclarativeCatalog` |
:py:class:`DynamicCatalog`
:raise: :py:exc:`dependency_injector.errors.Error` if trying to
override catalog by itself or its subclasses
:rtype: None
"""
if is_declarative_catalog(overriding) and issubclass(cls, overriding):
raise Error('Catalog {0} could not be overridden '
'with itself or its subclasses'.format(cls))
return cls._catalog.override(overriding)
@classmethod
def reset_last_overriding(cls):
"""Reset last overriding catalog.
:rtype: None
"""
cls._catalog.reset_last_overriding()
@classmethod
def reset_override(cls):
"""Reset all overridings for all catalog providers.
:rtype: None
"""
cls._catalog.reset_override()
@classmethod
def get_provider(cls, name):
"""Return provider with specified name or raise an error.
:param name: Provider's name.
:type name: str
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
:return: Provider with specified name.
:rtype: :py:class:`dependency_injector.providers.Provider`
"""
return cls._catalog.get_provider(name)
get = get_provider # Backward compatibility for versions < 0.11.*
@classmethod
def bind_provider(cls, name, provider):
"""Bind provider to catalog with specified name.
:param name: Name of the provider.
:type name: str
:param provider: Provider instance.
:type provider: :py:class:`dependency_injector.providers.Provider`
:raise: :py:exc:`dependency_injector.errors.Error`
:rtype: None
"""
setattr(cls, name, provider)
@classmethod
def bind_providers(cls, providers):
"""Bind providers dictionary to catalog.
:param providers: Dictionary of providers, where key is a name
and value is a provider.
:type providers:
dict[str, :py:class:`dependency_injector.providers.Provider`]
:raise: :py:exc:`dependency_injector.errors.Error`
:rtype: None
"""
for name, provider in six.iteritems(providers):
setattr(cls, name, provider)
@classmethod
def has_provider(cls, name):
"""Check if there is provider with certain name.
:param name: Provider's name.
:type name: str
:rtype: bool
"""
return hasattr(cls, name)
has = has_provider # Backward compatibility for versions < 0.11.*
@classmethod
def unbind_provider(cls, name):
"""Remove provider binding.
:param name: Provider's name.
:type name: str
:rtype: None
"""
delattr(cls, name)
@classmethod
def __getattr__(cls, name): # pragma: no cover
"""Return provider with specified name or raise en error.
:param name: Attribute's name.
:type name: str
:raise: :py:exc:`dependency_injector.errors.UndefinedProviderError`
"""
raise NotImplementedError('Implementated in metaclass')
@classmethod
def __setattr__(cls, name, value): # pragma: no cover
"""Handle setting of catalog attributes.
Setting of attributes works as usual, but if value of attribute is
provider, this provider will be bound to catalog.
:param name: Attribute's name.
:type name: str
:param value: Attribute's value.
:type value: :py:class:`dependency_injector.providers.Provider` |
object
:rtype: None
"""
raise NotImplementedError('Implementated in metaclass')
@classmethod
def __delattr__(cls, name): # pragma: no cover
"""Handle deleting of catalog attibute.
Deleting of attributes works as usual, but if value of attribute is
provider, this provider will be unbound from catalog.
:param name: Attribute's name.
:type name: str
:rtype: None
"""
raise NotImplementedError('Implementated in metaclass')
# Backward compatibility for versions < 0.11.*
AbstractCatalog = DeclarativeCatalog
def override(catalog):
""":py:class:`DeclarativeCatalog` overriding decorator.
:param catalog: Catalog that should be overridden by decorated catalog.
:type catalog: :py:class:`DeclarativeCatalog` | :py:class:`DynamicCatalog`
:return: Declarative catalog's overriding decorator.
:rtype: callable(:py:class:`DeclarativeCatalog`)
"""
def decorator(overriding_catalog):
"""Overriding decorator."""
catalog.override(overriding_catalog)
return overriding_catalog
return decorator

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"""Errors module."""
class Error(Exception):
"""Base error.
All dependency injector errors extend this error class.
"""
class UndefinedProviderError(Error, AttributeError):
"""Undefined provider error.
This error is used when provider could not be defined, for example:
- provider with certain name could not be defined
- catalog's name of the certain provider could not be defined
- etc...
Also this error extends standard :py:class:`AttributeError`. This gives
possibility to use it correctly with ``__getattr__()``.
"""

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"""Injections module."""
import sys
import itertools
import six
from .utils import is_provider
from .utils import is_delegated_provider
from .utils import is_injection
from .utils import is_arg_injection
from .utils import is_kwarg_injection
from .errors import Error
_IS_PYPY = '__pypy__' in sys.builtin_module_names
if _IS_PYPY or six.PY3: # pragma: no cover
_OBJECT_INIT = six.get_unbound_function(object.__init__)
else: # pragma: no cover
_OBJECT_INIT = None
@six.python_2_unicode_compatible
class Injection(object):
"""Base injection class.
All injections extend this class.
.. py:attribute:: injectable
Injectable value, could be provider or any other object.
:type: object | :py:class:`dependency_injector.providers.Provider`
.. py:attribute:: call_injectable
Flag that is set to ``True`` if it is needed to call injectable.
Injectable needs to be called if it is not delegated provider.
:type: bool
"""
__IS_INJECTION__ = True
__slots__ = ('injectable', 'call_injectable')
def __init__(self, injectable):
"""Initializer.
:param injectable: Injectable value, could be provider or any
other object.
:type injectable: object |
:py:class:`dependency_injector.providers.Provider`
"""
self.injectable = injectable
self.call_injectable = (is_provider(injectable) and
not is_delegated_provider(injectable))
super(Injection, self).__init__()
@property
def value(self):
"""Read-only property that represents injectable value.
Injectable values and delegated providers are provided "as is".
Other providers will be called every time, when injection needs to
be done.
:rtype: object
"""
if self.call_injectable:
return self.injectable()
return self.injectable
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return '<{injection}({injectable}) at {address}>'.format(
injection='.'.join((self.__class__.__module__,
self.__class__.__name__)),
injectable=repr(self.injectable),
address=hex(id(self)))
__repr__ = __str__
class Arg(Injection):
"""Positional argument injection."""
__IS_ARG_INJECTION__ = True
@six.python_2_unicode_compatible
class _NamedInjection(Injection):
"""Base class of named injections.
.. py:attribute:: name
Injection target's name (keyword argument, attribute, method).
:type: str
"""
__slots__ = ('name',)
def __init__(self, name, injectable):
"""Initializer.
:param name: Injection target's name.
:type name: str
:param injectable: Injectable value, could be provider or any
other object.
:type injectable: object |
:py:class:`dependency_injector.providers.Provider`
"""
self.name = name
super(_NamedInjection, self).__init__(injectable)
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return '<{injection}({name}, {injectable}) at {address}>'.format(
name=repr(self.name),
injection='.'.join((self.__class__.__module__,
self.__class__.__name__)),
injectable=repr(self.injectable),
address=hex(id(self)))
__repr__ = __str__
class KwArg(_NamedInjection):
"""Keyword argument injection.
.. py:attribute:: name
Keyword argument's name.
:type: str
"""
__IS_KWARG_INJECTION__ = True
class Attribute(_NamedInjection):
"""Attribute injection.
.. py:attribute:: name
Attribute's name.
:type: str
"""
__IS_ATTRIBUTE_INJECTION__ = True
class Method(_NamedInjection):
"""Method injection.
.. py:attribute:: name
Method's name.
:type: str
"""
__IS_METHOD_INJECTION__ = True
def inject(*args, **kwargs):
"""Dependency injection decorator.
:py:func:`inject` decorator can be used for making inline dependency
injections. It patches decorated callable in such way that dependency
injection will be done during every call of decorated callable.
:py:func:`inject` decorator supports different syntaxes of passing
injections:
.. code-block:: python
# Positional arguments injections (simplified syntax):
@inject(1, 2)
def some_function(arg1, arg2):
pass
# Keyword arguments injections (simplified syntax):
@inject(arg1=1)
@inject(arg2=2)
def some_function(arg1, arg2):
pass
# Keyword arguments injections (extended (full) syntax):
@inject(KwArg('arg1', 1))
@inject(KwArg('arg2', 2))
def some_function(arg1, arg2):
pass
# Keyword arguments injections into class init (simplified syntax):
@inject(arg1=1)
@inject(arg2=2)
class SomeClass(object):
def __init__(self, arg1, arg2):
pass
:param args: Tuple of context positional arguments.
:type args: tuple[object]
:param kwargs: Dictionary of context keyword arguments.
:type kwargs: dict[str, object]
:return: Class / callable decorator
:rtype: (callable) -> (type | callable)
"""
arg_injections = _parse_args_injections(args)
kwarg_injections = _parse_kwargs_injections(args, kwargs)
def decorator(callback_or_cls):
"""Dependency injection decorator."""
if isinstance(callback_or_cls, six.class_types):
cls = callback_or_cls
try:
cls_init = six.get_unbound_function(cls.__init__)
assert cls_init is not _OBJECT_INIT
except (AttributeError, AssertionError):
raise Error(
'Class {0}.{1} has no __init__() '.format(cls.__module__,
cls.__name__) +
'method and could not be decorated with @inject decorator')
cls.__init__ = decorator(cls_init)
return cls
callback = callback_or_cls
if hasattr(callback, 'injections'):
callback.args += arg_injections
callback.kwargs += kwarg_injections
callback.injections += arg_injections + kwarg_injections
return callback
@six.wraps(callback)
def decorated(*args, **kwargs):
"""Decorated with dependency injection callback."""
return callback(*_get_injectable_args(args, decorated.args),
**_get_injectable_kwargs(kwargs, decorated.kwargs))
decorated.args = arg_injections
decorated.kwargs = kwarg_injections
decorated.injections = arg_injections + kwarg_injections
return decorated
return decorator
def _parse_args_injections(args):
"""Parse positional argument injections according to current syntax."""
return tuple(Arg(arg) if not is_injection(arg) else arg
for arg in args
if not is_injection(arg) or is_arg_injection(arg))
def _parse_kwargs_injections(args, kwargs):
"""Parse keyword argument injections according to current syntax."""
kwarg_injections = tuple(injection
for injection in args
if is_kwarg_injection(injection))
if kwargs:
kwarg_injections += tuple(KwArg(name, value)
for name, value in six.iteritems(kwargs))
return kwarg_injections
def _get_injectable_args(context_args, arg_injections):
"""Return tuple of positional arguments, patched with injections."""
return itertools.chain((arg.value for arg in arg_injections), context_args)
def _get_injectable_kwargs(context_kwargs, kwarg_injections):
"""Return dictionary of keyword arguments, patched with injections."""
injectable_kwargs = dict((kwarg.name, kwarg.value)
for kwarg in kwarg_injections)
injectable_kwargs.update(context_kwargs)
return injectable_kwargs

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"""Providers module."""
import six
from .injections import _parse_args_injections
from .injections import _parse_kwargs_injections
from .injections import _get_injectable_args
from .injections import _get_injectable_kwargs
from .utils import ensure_is_provider
from .utils import is_attribute_injection
from .utils import is_method_injection
from .utils import represent_provider
from .utils import GLOBAL_LOCK
from .errors import Error
@six.python_2_unicode_compatible
class Provider(object):
"""Base provider class.
:py:class:`Provider` is callable (implements ``__call__`` method). Every
call to provider object returns provided result, according to the providing
strategy of particular provider. This ``callable`` functionality is a
regular part of providers API and it should be the same for all provider's
subclasses.
Implementation of particular providing strategy should be done in
:py:meth:`Provider._provide` of :py:class:`Provider` subclass. Current
method is called every time when not overridden provider is called.
:py:class:`Provider` implements provider overriding logic that should be
also common for all providers:
.. code-block:: python
provider1 = Factory(SomeClass)
provider2 = Factory(ChildSomeClass)
provider1.override(provider2)
some_instance = provider1()
assert isinstance(some_instance, ChildSomeClass)
Also :py:class:`Provider` implements helper function for creating its
delegates:
.. code-block:: python
provider = Factory(object)
delegate = provider.delegate()
delegated = delegate()
assert provider is delegated
All providers should extend this class.
.. py:attribute:: overridden_by
Tuple of overriding providers, if any.
:type: tuple[:py:class:`Provider`] | None
"""
__IS_PROVIDER__ = True
__slots__ = ('overridden_by',)
def __init__(self):
"""Initializer."""
self.overridden_by = None
super(Provider, self).__init__()
def __call__(self, *args, **kwargs):
"""Return provided instance.
Implementation of current method adds ``callable`` functionality for
providers API and it should be common for all provider's subclasses.
Also this method implements provider overriding logic that is also
common for all providers. Implementation of particular providing
strategy should be done in :py:meth:`Provider._provide` of
:py:class:`Provider` subclass.
"""
if self.overridden_by:
return self.last_overriding(*args, **kwargs)
return self._provide(*args, **kwargs)
def _provide(self, *args, **kwargs):
"""Providing strategy implementation.
Abstract protected method that implements providing strategy of
particular provider. Current method is called every time when not
overridden provider is called. Need to be overridden in subclasses.
"""
raise NotImplementedError()
@property
def is_overridden(self):
"""Read-only property that is set to ``True`` if provider is overridden.
:rtype: bool
"""
return bool(self.overridden_by)
@property
def last_overriding(self):
"""Read-only reference to the last overriding provider, if any.
:type: :py:class:`Provider` | None
"""
return self.overridden_by[-1] if self.overridden_by else None
def override(self, provider):
"""Override provider with another provider.
:param provider: Overriding provider.
:type provider: :py:class:`Provider`
:raise: :py:exc:`dependency_injector.errors.Error`
"""
if provider is self:
raise Error('Provider {0} could not be overridden '
'with itself'.format(self))
if not self.is_overridden:
self.overridden_by = (ensure_is_provider(provider),)
else:
self.overridden_by += (ensure_is_provider(provider),)
def reset_last_overriding(self):
"""Reset last overriding provider.
:raise: :py:exc:`dependency_injector.errors.Error` if provider is not
overridden.
:rtype: None
"""
if not self.overridden_by:
raise Error('Provider {0} is not overridden'.format(str(self)))
self.overridden_by = self.overridden_by[:-1]
def reset_override(self):
"""Reset all overriding providers.
:rtype: None
"""
self.overridden_by = None
def delegate(self):
"""Return provider's delegate.
:rtype: :py:class:`Delegate`
"""
return Delegate(self)
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return represent_provider(provider=self, provides=None)
__repr__ = __str__
@six.python_2_unicode_compatible
class Delegate(Provider):
""":py:class:`Delegate` provider delegates another provider.
.. code-block:: python
provider = Factory(object)
delegate = Delegate(provider)
delegated = delegate()
assert provider is delegated
.. py:attribute:: delegated
Delegated provider.
:type: :py:class:`Provider`
"""
__slots__ = ('delegated',)
def __init__(self, delegated):
"""Initializer.
:provider delegated: Delegated provider.
:type delegated: :py:class:`Provider`
"""
self.delegated = ensure_is_provider(delegated)
super(Delegate, self).__init__()
def _provide(self, *args, **kwargs):
"""Return provided instance.
:param args: Tuple of context positional arguments.
:type args: tuple[object]
:param kwargs: Dictionary of context keyword arguments.
:type kwargs: dict[str, object]
:rtype: object
"""
return self.delegated
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return represent_provider(provider=self, provides=self.delegated)
__repr__ = __str__
@six.python_2_unicode_compatible
class Callable(Provider):
""":py:class:`Callable` provider calls wrapped callable on every call.
:py:class:`Callable` provider provides callable that is called on every
provider call with some predefined dependency injections.
:py:class:`Callable` syntax of passing injections is the same like
:py:class:`Factory` one:
.. code-block:: python
# simplified syntax for passing positional and keyword argument
# injections:
some_function = Callable(some_function, 'arg1', 'arg2', arg3=3, arg4=4)
# extended (full) syntax for passing positional and keyword argument
# injections:
some_function = Callable(some_function,
injections.Arg(1),
injections.Arg(2),
injections.KwArg('some_arg', 3),
injections.KwArg('other_arg', 4))
.. py:attribute:: provides
Provided callable.
:type: callable
.. py:attribute:: args
Tuple of positional argument injections.
:type: tuple[:py:class:`dependency_injector.injections.Arg`]
.. py:attribute:: kwargs
Tuple of keyword argument injections.
:type: tuple[:py:class:`dependency_injector.injections.KwArg`]
"""
__slots__ = ('provides', 'args', 'kwargs')
def __init__(self, provides, *args, **kwargs):
"""Initializer.
:param provides: Wrapped callable.
:type provides: callable
:param args: Tuple of injections.
:type args: tuple
:param kwargs: Dictionary of injections.
:type kwargs: dict
"""
if not callable(provides):
raise Error('Provider{0} expected to get callable, '
'got {0}'.format('.'.join((self.__class__.__module__,
self.__class__.__name__)),
provides))
self.provides = provides
self.args = _parse_args_injections(args)
self.kwargs = _parse_kwargs_injections(args, kwargs)
super(Callable, self).__init__()
@property
def injections(self):
"""Read-only tuple of all injections.
:rtype: tuple[:py:class:`dependency_injector.injections.Injection`]
"""
return self.args + self.kwargs
def _provide(self, *args, **kwargs):
"""Return provided instance.
:param args: Tuple of context positional arguments.
:type args: tuple[object]
:param kwargs: Dictionary of context keyword arguments.
:type kwargs: dict[str, object]
:rtype: object
"""
return self.provides(*_get_injectable_args(args, self.args),
**_get_injectable_kwargs(kwargs, self.kwargs))
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return represent_provider(provider=self, provides=self.provides)
__repr__ = __str__
class DelegatedCallable(Callable):
""":py:class:`DelegatedCallable` is a delegated :py:class:`Callable`.
:py:class:`DelegatedCallable` is a :py:class:`Callable`, that is injected
"as is".
.. py:attribute:: provides
Provided callable.
:type: callable
.. py:attribute:: args
Tuple of positional argument injections.
:type: tuple[:py:class:`dependency_injector.injections.Arg`]
.. py:attribute:: kwargs
Tuple of keyword argument injections.
:type: tuple[:py:class:`dependency_injector.injections.KwArg`]
"""
__IS_DELEGATED__ = True
class Factory(Callable):
""":py:class:`Factory` provider creates new instance on every call.
:py:class:`Factory` supports different syntaxes of passing injections:
.. code-block:: python
# simplified syntax for passing positional and keyword argument
# injections only:
factory = Factory(SomeClass, 'arg1', 'arg2', arg3=3, arg4=4)
# extended (full) syntax for passing any type of injections:
factory = Factory(SomeClass,
injections.Arg(1),
injections.Arg(2),
injections.KwArg('some_arg', 3),
injections.KwArg('other_arg', 4),
injections.Attribute('some_attribute', 5))
Retrieving of provided instance can be performed via calling
:py:class:`Factory` object:
.. code-block:: python
factory = Factory(SomeClass,
some_arg1=1,
some_arg2=2)
some_object = factory()
.. py:attribute:: provided_type
If provided type is defined, :py:class:`Factory` checks that
:py:attr:`Factory.provides` is subclass of
:py:attr:`Factory.provided_type`.
:type: type | None
.. py:attribute:: provides
Class or other callable that provides object.
:type: type | callable
.. py:attribute:: args
Tuple of positional argument injections.
:type: tuple[:py:class:`dependency_injector.injections.Arg`]
.. py:attribute:: kwargs
Tuple of keyword argument injections.
:type: tuple[:py:class:`dependency_injector.injections.KwArg`]
.. py:attribute:: attributes
Tuple of attribute injections.
:type: tuple[:py:class:`dependency_injector.injections.Attribute`]
.. py:attribute:: methods
Tuple of method injections.
:type: tuple[:py:class:`dependency_injector.injections.Method`]
"""
provided_type = None
__slots__ = ('attributes', 'methods')
def __init__(self, provides, *args, **kwargs):
"""Initializer.
:param provides: Class or other callable that provides object
for creation.
:type provides: type | callable
:param args: Tuple of injections.
:type args: tuple
:param kwargs: Dictionary of injections.
:type kwargs: dict
"""
if (self.__class__.provided_type and
not issubclass(provides, self.__class__.provided_type)):
raise Error('{0} can provide only {1} instances'.format(
self.__class__, self.__class__.provided_type))
self.attributes = tuple(injection
for injection in args
if is_attribute_injection(injection))
self.methods = tuple(injection
for injection in args
if is_method_injection(injection))
super(Factory, self).__init__(provides, *args, **kwargs)
@property
def injections(self):
"""Read-only tuple of all injections.
:rtype: tuple[:py:class:`dependency_injector.injections.Injection`]
"""
return self.args + self.kwargs + self.attributes + self.methods
def _provide(self, *args, **kwargs):
"""Return provided instance.
:param args: Tuple of context positional arguments.
:type args: tuple[object]
:param kwargs: Dictionary of context keyword arguments.
:type kwargs: dict[str, object]
:rtype: object
"""
instance = super(Factory, self)._provide(*args, **kwargs)
for attribute in self.attributes:
setattr(instance, attribute.name, attribute.value)
for method in self.methods:
getattr(instance, method.name)(method.value)
return instance
class DelegatedFactory(Factory):
""":py:class:`DelegatedFactory` is a delegated :py:class:`Factory`.
:py:class:`DelegatedFactory` is a :py:class:`Factory`, that is injected
"as is".
.. py:attribute:: provided_type
If provided type is defined, :py:class:`Factory` checks that
:py:attr:`Factory.provides` is subclass of
:py:attr:`Factory.provided_type`.
:type: type | None
.. py:attribute:: provides
Class or other callable that provides object.
:type: type | callable
.. py:attribute:: args
Tuple of positional argument injections.
:type: tuple[:py:class:`dependency_injector.injections.Arg`]
.. py:attribute:: kwargs
Tuple of keyword argument injections.
:type: tuple[:py:class:`dependency_injector.injections.KwArg`]
.. py:attribute:: attributes
Tuple of attribute injections.
:type: tuple[:py:class:`dependency_injector.injections.Attribute`]
.. py:attribute:: methods
Tuple of method injections.
:type: tuple[:py:class:`dependency_injector.injections.Method`]
"""
__IS_DELEGATED__ = True
class Singleton(Factory):
""":py:class:`Singleton` provider returns same instance on every call.
:py:class:`Singleton` provider creates instance once and return it on every
call. :py:class:`Singleton` extends :py:class:`Factory`, so, please follow
:py:class:`Factory` documentation to go inside with injections syntax.
:py:class:`Singleton` is thread-safe and could be used in multithreading
environment without any negative impact.
Retrieving of provided instance can be performed via calling
:py:class:`Singleton` object:
.. code-block:: python
singleton = Singleton(SomeClass,
some_arg1=1,
some_arg2=2)
some_object = singleton()
.. py:attribute:: provided_type
If provided type is defined, :py:class:`Factory` checks that
:py:attr:`Factory.provides` is subclass of
:py:attr:`Factory.provided_type`.
:type: type | None
.. py:attribute:: instance
Read-only reference to singleton's instance.
:type: object
.. py:attribute:: provides
Class or other callable that provides object.
:type: type | callable
.. py:attribute:: args
Tuple of positional argument injections.
:type: tuple[:py:class:`dependency_injector.injections.Arg`]
.. py:attribute:: kwargs
Tuple of keyword argument injections.
:type: tuple[:py:class:`dependency_injector.injections.KwArg`]
.. py:attribute:: attributes
Tuple of attribute injections.
:type: tuple[:py:class:`dependency_injector.injections.Attribute`]
.. py:attribute:: methods
Tuple of method injections.
:type: tuple[:py:class:`dependency_injector.injections.Method`]
"""
__slots__ = ('instance',)
def __init__(self, provides, *args, **kwargs):
"""Initializer.
:param provides: Class or other callable that provides object
for creation.
:type provides: type | callable
:param args: Tuple of injections.
:type args: tuple
:param kwargs: Dictionary of injections.
:type kwargs: dict
"""
self.instance = None
super(Singleton, self).__init__(provides, *args, **kwargs)
def reset(self):
"""Reset cached instance, if any.
:rtype: None
"""
self.instance = None
def _provide(self, *args, **kwargs):
"""Return provided instance.
:param args: Tuple of context positional arguments.
:type args: tuple[object]
:param kwargs: Dictionary of context keyword arguments.
:type kwargs: dict[str, object]
:rtype: object
"""
with GLOBAL_LOCK:
if not self.instance:
self.instance = super(Singleton, self)._provide(*args,
**kwargs)
return self.instance
class DelegatedSingleton(Singleton):
""":py:class:`DelegatedSingleton` is a delegated :py:class:`Singleton`.
:py:class:`DelegatedSingleton` is a :py:class:`Singleton`, that is injected
"as is".
.. py:attribute:: provided_type
If provided type is defined, :py:class:`Factory` checks that
:py:attr:`Factory.provides` is subclass of
:py:attr:`Factory.provided_type`.
:type: type | None
.. py:attribute:: instance
Read-only reference to singleton's instance.
:type: object
.. py:attribute:: provides
Class or other callable that provides object.
:type: type | callable
.. py:attribute:: args
Tuple of positional argument injections.
:type: tuple[:py:class:`dependency_injector.injections.Arg`]
.. py:attribute:: kwargs
Tuple of keyword argument injections.
:type: tuple[:py:class:`dependency_injector.injections.KwArg`]
.. py:attribute:: attributes
Tuple of attribute injections.
:type: tuple[:py:class:`dependency_injector.injections.Attribute`]
.. py:attribute:: methods
Tuple of method injections.
:type: tuple[:py:class:`dependency_injector.injections.Method`]
"""
__IS_DELEGATED__ = True
@six.python_2_unicode_compatible
class ExternalDependency(Provider):
""":py:class:`ExternalDependency` provider describes dependency interface.
This provider is used for description of dependency interface. That might
be useful when dependency could be provided in the client's code only,
but it's interface is known. Such situations could happen when required
dependency has non-determenistic list of dependencies itself.
.. code-block:: python
database_provider = ExternalDependency(sqlite3.dbapi2.Connection)
database_provider.override(Factory(sqlite3.connect, ':memory:'))
database = database_provider()
.. py:attribute:: instance_of
Class of required dependency.
:type: type
"""
__slots__ = ('instance_of',)
def __init__(self, instance_of):
"""Initializer."""
if not isinstance(instance_of, six.class_types):
raise Error('ExternalDependency provider expects to get class, ' +
'got {0} instead'.format(str(instance_of)))
self.instance_of = instance_of
super(ExternalDependency, self).__init__()
def __call__(self, *args, **kwargs):
"""Return provided instance.
:param args: Tuple of context positional arguments.
:type args: tuple[object]
:param kwargs: Dictionary of context keyword arguments.
:type kwargs: dict[str, object]
:raise: :py:exc:`dependency_injector.errors.Error`
:rtype: object
"""
if not self.is_overridden:
raise Error('Dependency is not defined')
instance = self.last_overriding(*args, **kwargs)
if not isinstance(instance, self.instance_of):
raise Error('{0} is not an '.format(instance) +
'instance of {0}'.format(self.instance_of))
return instance
def provided_by(self, provider):
"""Set external dependency provider.
:param provider: Provider that provides required dependency.
:type provider: :py:class:`Provider`
:rtype: None
"""
return self.override(provider)
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return represent_provider(provider=self, provides=self.instance_of)
__repr__ = __str__
@six.python_2_unicode_compatible
class Static(Provider):
""":py:class:`Static` provider returns provided instance "as is".
:py:class:`Static` provider is base implementation that provides exactly
the same as it got on input.
.. py:attribute:: provides
Value that have to be provided.
:type: object
"""
__slots__ = ('provides',)
def __init__(self, provides):
"""Initializer.
:param provides: Value that have to be provided.
:type provides: object
"""
self.provides = provides
super(Static, self).__init__()
def _provide(self, *args, **kwargs):
"""Return provided instance.
:param args: Tuple of context positional arguments.
:type args: tuple[object]
:param kwargs: Dictionary of context keyword arguments.
:type kwargs: dict[str, object]
:rtype: object
"""
return self.provides
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return represent_provider(provider=self, provides=self.provides)
__repr__ = __str__
StaticProvider = Static
# Backward compatibility for versions < 1.11.1
class Class(Static):
""":py:class:`Class` returns provided class "as is".
.. code-block:: python
cls_provider = Class(object)
object_cls = cls_provider()
"""
class Object(Static):
""":py:class:`Object` returns provided object "as is".
.. code-block:: python
object_provider = Object(object())
object_instance = object_provider()
"""
class Function(Static):
""":py:class:`Function` returns provided function "as is".
.. code-block:: python
function_provider = Function(len)
len_function = function_provider()
"""
class Value(Static):
""":py:class:`Value` returns provided value "as is".
.. code-block:: python
value_provider = Value(31337)
value = value_provider()
"""
@six.python_2_unicode_compatible
class Config(Provider):
""":py:class:`Config` provider provide dict values.
:py:class:`Config` provider creates :py:class:`ChildConfig` objects for all
undefined attribute calls. It makes possible to create deferred config
value providers. It might be useful in cases where it is needed to
define / pass some configuration in declarative manner, while
configuration values will be loaded / updated in application's runtime.
"""
__slots__ = ('value',)
def __init__(self, value=None):
"""Initializer.
:param value: Configuration dictionary.
:type value: dict[str, object]
"""
if not value:
value = dict()
self.value = value
super(Config, self).__init__()
def __getattr__(self, item):
"""Return instance of deferred config.
:param item: Name of configuration option or section.
:type item: str
:rtype: :py:class:`ChildConfig`
"""
return ChildConfig(parents=(item,), root_config=self)
def _provide(self, paths=None):
"""Return provided instance.
:param paths: Tuple of pieces of configuration option / section path.
:type args: tuple[str]
:rtype: object
"""
value = self.value
if paths:
for path in paths:
try:
value = value[path]
except KeyError:
raise Error('Config key '
'"{0}" is undefined'.format('.'.join(paths)))
return value
def update_from(self, value):
"""Update current value from another one.
:param value: Configuration dictionary.
:type value: dict[str, object]
:rtype: None
"""
self.value.update(value)
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return represent_provider(provider=self, provides=self.value)
__repr__ = __str__
@six.python_2_unicode_compatible
class ChildConfig(Provider):
""":py:class:`ChildConfig` provider provides value from :py:class:`Config`.
:py:class:`ChildConfig` provides value from the root config object
according to the current path in the config tree.
"""
__slots__ = ('parents', 'root_config')
def __init__(self, parents, root_config):
"""Initializer.
:param parents: Tuple of pieces of configuration option / section
parent path.
:type parents: tuple[str]
:param root_config: Root configuration object.
:type root_config: :py:class:`Config`
"""
self.parents = parents
self.root_config = root_config
super(ChildConfig, self).__init__()
def __getattr__(self, item):
"""Return instance of deferred config.
:param item: Name of configuration option or section.
:type item: str
:rtype: :py:class:`ChildConfig`
"""
return ChildConfig(parents=self.parents + (item,),
root_config=self.root_config)
def _provide(self, *args, **kwargs):
"""Return provided instance.
:param args: Tuple of context positional arguments.
:type args: tuple[object]
:param kwargs: Dictionary of context keyword arguments.
:type kwargs: dict[str, object]
:rtype: object
"""
return self.root_config(self.parents)
def __str__(self):
"""Return string representation of provider.
:rtype: str
"""
return represent_provider(provider=self,
provides='.'.join(self.parents))
__repr__ = __str__

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@ -0,0 +1,222 @@
"""Utils module."""
import threading
import six
from .errors import Error
GLOBAL_LOCK = threading.RLock()
"""Dependency injector global reentrant lock.
:type: :py:class:`threading.RLock`
"""
def is_provider(instance):
"""Check if instance is provider instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (not isinstance(instance, six.class_types) and
hasattr(instance, '__IS_PROVIDER__') and
getattr(instance, '__IS_PROVIDER__') is True)
def ensure_is_provider(instance):
"""Check if instance is provider instance and return it.
:param instance: Instance to be checked.
:type instance: object
:raise: :py:exc:`dependency_injector.errors.Error` if provided instance is
not provider.
:rtype: :py:class:`dependency_injector.providers.Provider`
"""
if not is_provider(instance):
raise Error('Expected provider instance, '
'got {0}'.format(str(instance)))
return instance
def is_delegated_provider(instance):
"""Check if instance is delegated provider instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (is_provider(instance) and
hasattr(instance, '__IS_DELEGATED__') and
getattr(instance, '__IS_DELEGATED__') is True)
def is_injection(instance):
"""Check if instance is injection instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (not isinstance(instance, six.class_types) and
hasattr(instance, '__IS_INJECTION__') and
getattr(instance, '__IS_INJECTION__') is True)
def ensure_is_injection(instance):
"""Check if instance is injection instance and return it.
:param instance: Instance to be checked.
:type instance: object
:raise: :py:exc:`dependency_injector.errors.Error` if provided instance is
not injection.
:rtype: :py:class:`dependency_injector.injections.Injection`
"""
if not is_injection(instance):
raise Error('Expected injection instance, '
'got {0}'.format(str(instance)))
return instance
def is_arg_injection(instance):
"""Check if instance is positional argument injection instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (not isinstance(instance, six.class_types) and
hasattr(instance, '__IS_ARG_INJECTION__') and
getattr(instance, '__IS_ARG_INJECTION__', False) is True)
def is_kwarg_injection(instance):
"""Check if instance is keyword argument injection instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (not isinstance(instance, six.class_types) and
hasattr(instance, '__IS_KWARG_INJECTION__') and
getattr(instance, '__IS_KWARG_INJECTION__', False) is True)
def is_attribute_injection(instance):
"""Check if instance is attribute injection instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (not isinstance(instance, six.class_types) and
hasattr(instance, '__IS_ATTRIBUTE_INJECTION__') and
getattr(instance, '__IS_ATTRIBUTE_INJECTION__', False) is True)
def is_method_injection(instance):
"""Check if instance is method injection instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (not isinstance(instance, six.class_types) and
hasattr(instance, '__IS_METHOD_INJECTION__') and
getattr(instance, '__IS_METHOD_INJECTION__', False) is True)
def is_catalog(instance):
"""Check if instance is catalog instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (hasattr(instance, '__IS_CATALOG__') and
getattr(instance, '__IS_CATALOG__', False) is True)
def is_dynamic_catalog(instance):
"""Check if instance is dynamic catalog instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (not isinstance(instance, six.class_types) and is_catalog(instance))
def is_declarative_catalog(instance):
"""Check if instance is declarative catalog instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (isinstance(instance, six.class_types) and is_catalog(instance))
def is_catalog_bundle(instance):
"""Check if instance is catalog bundle instance.
:param instance: Instance to be checked.
:type instance: object
:rtype: bool
"""
return (not isinstance(instance, six.class_types) and
hasattr(instance, '__IS_CATALOG_BUNDLE__') and
getattr(instance, '__IS_CATALOG_BUNDLE__', False) is True)
def ensure_is_catalog_bundle(instance):
"""Check if instance is catalog bundle instance and return it.
:param instance: Instance to be checked.
:type instance: object
:raise: :py:exc:`dependency_injector.errors.Error` if provided instance
is not catalog bundle.
:rtype: :py:class:`dependency_injector.catalogs.CatalogBundle`
"""
if not is_catalog_bundle(instance):
raise Error('Expected catalog bundle instance, '
'got {0}'.format(str(instance)))
return instance
def represent_provider(provider, provides):
"""Return string representation of provider.
:param provider: Provider object
:type provider: :py:class:`dependency_injector.providers.Provider`
:param provides: Object that provider provides
:type provider: object
:return: String representation of provider
:rtype: str
"""
return '<{provider}({provides}) at {address}>'.format(
provider='.'.join((provider.__class__.__module__,
provider.__class__.__name__)),
provides=repr(provides) if provides is not None else '',
address=hex(id(provider)))

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@ -1,9 +0,0 @@
.no-border {
border: 0 !important;
box-shadow: none !important;
-webkit-box-shadow: none !important;
}
.no-border td {
border: 0px !important;
padding: 0px 10px 0px 0px !important;
}

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<iframe src="https://github.com/sponsors/rmk135/button" title="Sponsor Dependency Injector" height="32" width="114" style="border: 0; border-radius: 6px;"></iframe>

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Advanced usage
==============
Current section of documentation describes advanced usage of
*Dependency Injector*.
@inject decorator
-----------------
.. currentmodule:: dependency_injector.injections
:py:func:`inject` decorator is a part of
:py:mod:`dependency_injector.injections` module.
:py:func:`inject` decorator can be used for making *inline* dependency
injections. It *patches* decorated callable in such way that dependency
injection will be done during every call of decorated callable.
:py:func:`inject` takes a various number of positional and keyword arguments
that are used as decorated callable injections. Every time, when
:py:func:`inject` is called, positional and keyword argument injections would
be passed as an callable arguments.
Such behaviour is very similar to the standard Python ``functools.partial``
object, except of one thing: all injectable values are provided
*"as is"*, except of providers (subclasses of
:py:class:`dependency_injector.providers.Provider`). Providers
will be called every time, when injection needs to be done. For example,
if injectable value of injection is a
:py:class:`dependency_injector.providers.Factory`, it will provide new one
instance (as a result of its call) every time, when injection needs to be done.
:py:func:`inject` behaviour with context positional and keyword arguments is
very like a standard Python ``functools.partial``:
- Positional context arguments will be appended after :py:func:`inject`
positional injections.
- Keyword context arguments have priority on :py:func:`inject` keyword
injections and will be merged over them.
Example:
.. literalinclude:: ../../examples/advanced_usage/inject_simple.py
:language: python
Example of usage :py:func:`inject` decorator with Flask:
.. literalinclude:: ../../examples/advanced_usage/inject_flask.py
:language: python
@inject decorator with classes
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
:py:func:`inject` could be applied for classes. In such case, it will look for
class ``__init__()`` method and pass injection to it. If decorated class has
no ``__init__()`` method, appropriate
:py:exc:`dependency_injector.errors.Error` will be raised.
Example of usage :py:func:`inject` with Flask class-based view:
.. literalinclude:: ../../examples/advanced_usage/inject_flask_class_based.py
:language: python

6
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@ -0,0 +1,6 @@
``dependency_injector.catalogs``
--------------------------------
.. automodule:: dependency_injector.catalogs
:members:
:special-members:

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@ -1,9 +0,0 @@
dependency_injector.containers
==============================
.. automodule:: dependency_injector.containers
:members:
:inherited-members:
:show-inheritance:
.. disqus::

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@ -1,8 +1,5 @@
dependency_injector.errors
==========================
``dependency_injector.errors``
------------------------------
.. automodule:: dependency_injector.errors
:members:
.. disqus::

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@ -4,8 +4,9 @@ API Documentation
.. toctree::
:maxdepth: 2
top-level
providers
containers
wiring
errors
top_level
providers
injections
catalogs
utils
errors

6
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@ -0,0 +1,6 @@
``dependency_injector.injections``
----------------------------------
.. automodule:: dependency_injector.injections
:members:
:inherited-members:

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@ -1,10 +1,7 @@
dependency_injector.providers
=============================
``dependency_injector.providers``
---------------------------------
.. automodule:: dependency_injector.providers
:members:
:inherited-members:
:show-inheritance:
.. disqus::

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@ -1,8 +0,0 @@
dependency_injector
===================
.. automodule:: dependency_injector
:members: __version__
.. disqus::

5
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@ -0,0 +1,5 @@
``dependency_injector``
-----------------------
.. automodule:: dependency_injector
:members: VERSION

5
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@ -0,0 +1,5 @@
``dependency_injector.utils``
-----------------------------
.. automodule:: dependency_injector.utils
:members:

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@ -1,7 +0,0 @@
dependency_injector.wiring
=============================
.. automodule:: dependency_injector.wiring
:members:
.. disqus::

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@ -0,0 +1,60 @@
Catalog provider bundles
------------------------
.. currentmodule:: dependency_injector.catalogs
:py:class:`CatalogBundle` is a frozen, limited collection of catalog
providers. While catalog could be used as a centralized place for
particular providers group, such bundles of catalog providers can be used
for creating several frozen, limited scopes that could be passed to different
subsystems.
:py:class:`CatalogBundle` has API's parity with catalogs
(:py:class:`DeclarativeCatalog` or :py:class:`DynamicCatalog`) in terms of
retrieving the providers, but it is "frozen" in terms of modification
provider's list.
:py:class:`CatalogBundle` is considered to be dependable on catalogs
(:py:class:`DeclarativeCatalog` or :py:class:`DynamicCatalog`) entity by
its design.
Each catalog (:py:class:`DeclarativeCatalog` or :py:class:`DynamicCatalog`)
has a reference to its bundle class - :py:attr:`DeclarativeCatalog.Bundle`
(or :py:attr:`DynamicCatalog.Bundle` consequently). For example, subclass of
:py:class:`CatalogBundle` for some concrete declarative catalog
``SomeCatalog`` could be reached as ``SomeCatalog.Bundle``.
:py:class:`CatalogBundle` expects to get the list of its catalog providers
as positional arguments and will limit the scope of created bundle to this
list.
.. note::
Some notes about :py:class:`CatalogBundle` design.
Design and syntax of :py:class:`CatalogBundle` was developed with the idea
of keeping full functionalities of type-hinting and introspection of
modern IDE's. This design came from some practical experience of using
:py:class:`CatalogBundle` and considered to be the most comfortable for
developer.
Example:
.. image:: /images/catalogs/bundles.png
:width: 100%
:align: center
Listing of `services.py`:
.. literalinclude:: ../../examples/catalogs/bundles/services.py
:language: python
Listing of `views.py`:
.. literalinclude:: ../../examples/catalogs/bundles/views.py
:language: python
Listing of `catalogs.py`:
.. literalinclude:: ../../examples/catalogs/bundles/catalogs.py
:language: python

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@ -0,0 +1,61 @@
Declarative catalogs
--------------------
.. currentmodule:: dependency_injector.catalogs
:py:class:`DeclarativeCatalog` is a catalog of providers that could be
defined in declarative manner. It should cover most of the cases when list
of providers that would be included in catalog is deterministic (catalog
will not change its structure in runtime).
Declarative catalogs have to extend base declarative catalog class -
:py:class:`dependency_injector.catalogs.DeclarativeCatalog`.
Declarative catalog's providers have to be defined like catalog's class
attributes. Every provider in catalog has name. This name should follow
``some_provider`` convention, that is standard naming convention for
attribute names in Python.
.. note::
Declarative catalogs have several features that could be useful
for some kind of operations on catalog's providers, please visit API
documentation for getting full list of features -
:py:class:`dependency_injector.catalogs.DeclarativeCatalog`.
.. note::
It might be useful to add such
``""":type: dependency_injector.providers.Provider -> Object1"""``
docstrings just on the next line after provider's definition. It will
help code analyzing tools and IDE's to understand that variable above
contains some callable object, that returns particular instance as a
result of its call.
Here is an simple example of defining declarative catalog with several
factories:
.. image:: /images/catalogs/declarative.png
:width: 85%
:align: center
.. literalinclude:: ../../examples/catalogs/declarative.py
:language: python
Example of declarative catalogs inheritance:
.. image:: /images/catalogs/declarative_inheritance.png
:width: 100%
:align: center
.. literalinclude:: ../../examples/catalogs/declarative_inheritance.py
:language: python
Example of declarative catalog's provider injections:
.. image:: /images/catalogs/declarative_injections.png
:width: 100%
:align: center
.. literalinclude:: ../../examples/catalogs/declarative_injections.py
:language: python

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@ -0,0 +1,29 @@
Dynamic catalogs
----------------
.. currentmodule:: dependency_injector.catalogs
:py:class:`DynamicCatalog` is a catalog of providers that could be created in
application's runtime. It should cover most of the cases when list of
providers that would be included in catalog is non-deterministic in terms of
apllication code (catalog's structure could be determined just after
application will be started and will do some initial work, like parsing list
of catalog's providers from the configuration).
:py:class:`DeclarativeCatalog` and :py:class:`DynamicCatalog` have
100% API parity.
Main difference between :py:class:`DeclarativeCatalog` and
:py:class:`DynamicCatalog` is that :py:class:`DeclarativeCatalog` acts on
class-level, while :py:class:`DynamicCatalog` do the same on
instance-level.
Here is an simple example of defining dynamic catalog with several factories:
.. literalinclude:: ../../examples/catalogs/dynamic.py
:language: python
Next one example demonstrates creation and runtime filling of dynamic catalog:
.. literalinclude:: ../../examples/catalogs/dynamic_runtime_creation.py
:language: python

28
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@ -0,0 +1,28 @@
Catalogs
========
Catalogs are collections of providers. Main purpose of catalogs is to group
providers.
There are, actually, several popular cases of catalogs usage:
- Grouping of providers from the same architectural layer (for example,
``Services``, ``Models`` and ``Forms`` catalogs).
- Grouping of providers from the same functional groups (for example,
catalog ``Users``, that contains all functional parts of ``Users``
component).
Also, for both of these and some other cases, it might be useful to attach
some init / shutdown functionality or something else, that deals with group
of providers.
Catalogs module API docs - :py:mod:`dependency_injector.catalogs`.
.. toctree::
:maxdepth: 2
declarative
dynamic
bundles
specialization
overriding

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@ -0,0 +1,49 @@
Overriding of catalogs
----------------------
.. currentmodule:: dependency_injector.catalogs
Catalogs can be overridden by other catalogs. This, actually, means that
all of the providers from overriding catalog will override providers with the
same names in overridden catalog.
There are two ways to override :py:class:`DeclarativeCatalog` with another
catalog:
- Use :py:meth:`DeclarativeCatalog.override` method.
- Use :py:func:`override` class decorator.
Example of overriding catalog using :py:meth:`DeclarativeCatalog.override`
method:
.. literalinclude:: ../../examples/catalogs/override_declarative.py
:language: python
Example of overriding catalog using :py:func:`override` decorator:
.. literalinclude:: ../../examples/catalogs/override_declarative_decorator.py
:language: python
Also there are several useful :py:class:`DeclarativeCatalog` methods and
properties that help to work with catalog overridings:
- :py:attr:`DeclarativeCatalog.is_overridden` - read-only property that is set
to ``True`` if catalog is overridden.
- :py:attr:`DeclarativeCatalog.last_overriding` - read-only reference to
the last overriding catalog, if any.
- :py:attr:`DeclarativeCatalog.overridden_by` - tuple of all overriding
catalogs.
- :py:meth:`DeclarativeCatalog.reset_last_overriding()` - reset last
overriding catalog.
- :py:meth:`DeclarativeCatalog.reset_override()` - reset all overridings for
all catalog providers.
:py:class:`DynamicCatalog` has exactly the same functionality, except of
:py:func:`override` decorator. Also :py:class:`DynamicCatalog` can override
:py:class:`DeclarativeCatalog` and vise versa.
Example of overriding :py:class:`DeclarativeCatalog` by
:py:class:`DynamicCatalog`:
.. literalinclude:: ../../examples/catalogs/override_declarative_by_dynamic.py
:language: python

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@ -0,0 +1,41 @@
Specialization of catalogs
--------------------------
.. currentmodule:: dependency_injector.catalogs
:py:class:`DeclarativeCatalog` and :py:class:`DynamicCatalog` could be
specialized for any kind of needs via declaring its subclasses.
One of such `builtin` features is a limitation to
:py:class:`DeclarativeCatalog` (and :py:class:`DynamicCatalog`) provider type.
Next example shows usage of this feature with :py:class:`DeclarativeCatalog`
in couple with feature of :py:class:`dependency_injector.providers.Factory`
for limitation of its provided type:
Listing of `services.py`:
.. literalinclude:: ../../examples/catalogs/declarative_provider_type/services.py
:language: python
Listing of `catalog.py`:
.. literalinclude:: ../../examples/catalogs/declarative_provider_type/catalog.py
:language: python
Limitation to provider type could be used with :py:class:`DynamicCatalog`
as well.
Next example does the same that previous one, but use
:py:class:`DynamicCatalog` instead of :py:class:`DeclarativeCatalog`:
Listing of `services.py`:
.. literalinclude:: ../../examples/catalogs/dynamic_provider_type/services.py
:language: python
Listing of `catalog.py`:
.. literalinclude:: ../../examples/catalogs/dynamic_provider_type/catalog.py
:language: python

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@ -15,54 +15,49 @@
import os
import re
import sys
import alabaster
# If extensions (or modules to document with autodoc) are in another directory,
# add these directories to sys.path here. If the directory is relative to the
# documentation root, use os.path.abspath to make it absolute, like shown here.
sys.path.insert(0, os.path.abspath(".."))
sys.path.insert(0, os.path.abspath('..'))
# -- General configuration ------------------------------------------------
# If your documentation needs a minimal Sphinx version, state it here.
#needs_sphinx = "1.0"
#needs_sphinx = '1.0'
# Add any Sphinx extension module names here, as strings. They can be
# extensions coming with Sphinx (named "sphinx.ext.*") or your custom
# extensions coming with Sphinx (named 'sphinx.ext.*') or your custom
# ones.
extensions = [
"alabaster",
"sphinx.ext.autodoc",
"sphinx_disqus.disqus",
]
extensions = ['sphinx.ext.autodoc']
# Add any paths that contain templates here, relative to this directory.
templates_path = ["_templates"]
templates_path = ['_templates']
# The suffix(es) of source filenames.
# You can specify multiple suffix as a list of string:
# source_suffix = [".rst", ".md"]
source_suffix = ".rst"
# source_suffix = ['.rst', '.md']
source_suffix = '.rst'
# The encoding of source files.
#source_encoding = "utf-8-sig"
#source_encoding = 'utf-8-sig'
# The master toctree document.
master_doc = "index"
master_doc = 'index'
# General information about the project.
project = "Dependency Injector"
copyright = "2024, Roman Mogylatov"
author = "Roman Mogylatov"
project = u'Dependency Injector'
copyright = u'2016, ETS Labs'
author = u'ETS Labs'
# The version info for the project you"re documenting, acts as replacement for
# The version info for the project you're documenting, acts as replacement for
# |version| and |release|, also used in various other places throughout the
# built documents.
#
# The short X.Y version.
# Getting version:
with open("../src/dependency_injector/__init__.py") as init_file:
version = re.search("__version__ = \"(.*?)\"", init_file.read()).group(1)
with open('../dependency_injector/__init__.py') as init_file:
version = re.search('VERSION = \'(.*?)\'', init_file.read()).group(1)
# The full version, including alpha/beta/rc tags.
release = version
@ -76,19 +71,19 @@ language = None
# There are two options for replacing |today|: either, you set today to some
# non-false value, then it is used:
#today = ""
#today = ''
# Else, today_fmt is used as the format for a strftime call.
#today_fmt = "%B %d, %Y"
#today_fmt = '%B %d, %Y'
# List of patterns, relative to source directory, that match files and
# directories to ignore when looking for source files.
exclude_patterns = ["_build"]
exclude_patterns = ['_build']
# The reST default role (used for this markup: `text`) to use for all
# documents.
#default_role = None
# If true, "()" will be appended to :func: etc. cross-reference text.
# If true, '()' will be appended to :func: etc. cross-reference text.
#add_function_parentheses = True
# If true, the current module name will be prepended to all description
@ -100,7 +95,7 @@ exclude_patterns = ["_build"]
#show_authors = False
# The name of the Pygments (syntax highlighting) style to use.
pygments_style = "sphinx"
pygments_style = 'sphinx'
# A list of ignored prefixes for module index sorting.
#modindex_common_prefix = []
@ -116,16 +111,15 @@ todo_include_todos = False
# The theme to use for HTML and HTML Help pages. See the documentation for
# a list of builtin themes.
# html_theme = "sphinx_rtd_theme"
html_theme = "alabaster"
html_theme = 'default'
# Theme options are theme-specific and customize the look and feel of a theme
# further. For a list of options available for each theme, see the
# documentation.
# html_context = {}
#html_theme_options = {}
# Add any paths that contain custom themes here, relative to this directory.
html_theme_path = [alabaster.get_path()]
#html_theme_path = []
# The name for this set of Sphinx documents. If None, it defaults to
# "<project> v<release> documentation".
@ -141,24 +135,21 @@ html_theme_path = [alabaster.get_path()]
# The name of an image file (within the static path) to use as favicon of the
# docs. This file should be a Windows icon file (.ico) being 16x16 or 32x32
# pixels large.
html_favicon = "favicon.ico"
#html_favicon = None
# Add any paths that contain custom static files (such as style sheets) here,
# relative to this directory. They are copied after the builtin static files,
# so a file named "default.css" will overwrite the builtin "default.css".
html_static_path = ["_static"]
html_css_files = [
"custom.css",
]
html_static_path = []
# Add any extra paths that contain custom files (such as robots.txt or
# .htaccess) here, relative to this directory. These files are copied
# directly to the root of the documentation.
#html_extra_path = []
# If not "", a "Last updated on:" timestamp is inserted at every page bottom,
# If not '', a 'Last updated on:' timestamp is inserted at every page bottom,
# using the given strftime format.
#html_last_updated_fmt = "%b %d, %Y"
#html_last_updated_fmt = '%b %d, %Y'
# If true, SmartyPants will be used to convert quotes and dashes to
# typographically correct entities.
@ -192,50 +183,61 @@ html_css_files = [
# If true, an OpenSearch description file will be output, and all pages will
# contain a <link> tag referring to it. The value of this option must be the
# base URL from which the finished HTML is served.
#html_use_opensearch = ""
#html_use_opensearch = ''
# This is the file name suffix for HTML files (e.g. ".xhtml").
#html_file_suffix = None
# Language to be used for generating the HTML full-text search index.
# Sphinx supports the following languages:
# "da", "de", "en", "es", "fi", "fr", "hu", "it", "ja"
# "nl", "no", "pt", "ro", "ru", "sv", "tr"
#html_search_language = "en"
# 'da', 'de', 'en', 'es', 'fi', 'fr', 'hu', 'it', 'ja'
# 'nl', 'no', 'pt', 'ro', 'ru', 'sv', 'tr'
#html_search_language = 'en'
# A dictionary with options for the search language support, empty by default.
# Now only "ja" uses this config value
#html_search_options = {"type": "default"}
# Now only 'ja' uses this config value
#html_search_options = {'type': 'default'}
# The name of a javascript file (relative to the configuration directory) that
# implements a search results scorer. If empty, the default will be used.
#html_search_scorer = "scorer.js"
#html_search_scorer = 'scorer.js'
# Output file base name for HTML help builder.
htmlhelp_basename = "dependency_injectordoc"
htmlhelp_basename = 'dependency_injectordoc'
# on_rtd is whether we are on readthedocs.org, this line of code grabbed from
# docs.readthedocs.org
on_rtd = os.environ.get('READTHEDOCS', None) == 'True'
if not on_rtd: # only import and set the theme if we're building docs locally
import sphinx_rtd_theme
html_theme = 'sphinx_rtd_theme'
html_theme_path = [sphinx_rtd_theme.get_html_theme_path()]
# otherwise, readthedocs.org uses their theme by default, so no need to
# specify it
# -- Options for LaTeX output ---------------------------------------------
latex_elements = {
# The paper size ("letterpaper" or "a4paper").
#"papersize": "letterpaper",
# The paper size ('letterpaper' or 'a4paper').
#'papersize': 'letterpaper',
# The font size ("10pt", "11pt" or "12pt").
#"pointsize": "10pt",
# The font size ('10pt', '11pt' or '12pt').
#'pointsize': '10pt',
# Additional stuff for the LaTeX preamble.
#"preamble": "",
#'preamble': '',
# Latex figure (float) alignment
#"figure_align": "htbp",
#'figure_align': 'htbp',
}
# Grouping the document tree into LaTeX files. List of tuples
# (source start file, target name, title,
# author, documentclass [howto, manual, or own class]).
latex_documents = [
(master_doc, "dependency_injector.tex", u"Dependency Injector Documentation",
u"Roman Mogylatov", "manual"),
(master_doc, 'dependency_injector.tex', u'Dependency Injector Documentation',
u'ETS Labs', 'manual'),
]
# The name of an image file (relative to this directory) to place at the top of
@ -264,7 +266,7 @@ latex_documents = [
# One entry per manual page. List of tuples
# (source start file, name, description, authors, manual section).
man_pages = [
(master_doc, "Dependency Injector", u"Dependency Injector Documentation",
(master_doc, 'Dependency Injector', u'Dependency Injector Documentation',
[author], 1)
]
@ -278,9 +280,9 @@ man_pages = [
# (source start file, target name, title, author,
# dir menu entry, description, category)
texinfo_documents = [
(master_doc, "Dependency Injector", u"Dependency Injector Documentation",
author, "Dependency Injector", "Dependency injection microframework for Python",
"Miscellaneous"),
(master_doc, 'Dependency Injector', u'Dependency Injector Documentation',
author, 'Dependency Injector', 'Python dependency injection framework',
'Miscellaneous'),
]
# Documents to append as an appendix to all manuals.
@ -289,25 +291,10 @@ texinfo_documents = [
# If false, no module index is generated.
#texinfo_domain_indices = True
# How to display URL addresses: "footnote", "no", or "inline".
#texinfo_show_urls = "footnote"
# How to display URL addresses: 'footnote', 'no', or 'inline'.
#texinfo_show_urls = 'footnote'
# If true, do not generate a @detailmenu in the "Top" node"s menu.
# If true, do not generate a @detailmenu in the "Top" node's menu.
#texinfo_no_detailmenu = False
autodoc_member_order = "bysource"
disqus_shortname = "python-dependency-injector"
html_theme_options = {
"github_user": "ets-labs",
"github_repo": "python-dependency-injector",
"github_type": "star",
"github_button": True,
"github_banner": True,
"logo": "logo.svg",
"description": "Dependency injection framework for Python by Roman Mogylatov",
"code_font_size": "10pt",
"analytics_id": "UA-67012059-1",
"donate_url": "https://github.com/sponsors/rmk135",
}
autodoc_member_order = 'bysource'

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@ -1,18 +0,0 @@
.. _check-container-dependencies:
Check container dependencies
----------------------------
To check container dependencies use method ``.check_dependencies()``.
.. literalinclude:: ../../examples/containers/check_dependencies.py
:language: python
:lines: 3-
:emphasize-lines: 12
Method ``.check_dependencies()`` raises an error if container has any undefined dependencies.
If all dependencies are provided or have defaults, no error is raised.
See also: :ref:`dependency-provider`.
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@ -1,23 +0,0 @@
Container copying
-----------------
You can create declarative container copies using ``@containers.copy()`` decorator.
.. literalinclude:: ../../examples/containers/declarative_copy_decorator1.py
:language: python
:lines: 3-
:emphasize-lines: 18-22
Decorator ``@containers.copy()`` copies providers from source container to destination container.
Destination container provider will replace source provider, if names match.
Decorator ``@containers.copy()`` helps you when you create derived declarative containers
from the base one. Base container often keeps default dependencies while derived containers define
overriding providers. Without ``@containers.copy()`` decorator, overridden providers are available
in the derived container, but base class dependencies continue to be bound to the base class providers.
.. literalinclude:: ../../examples/containers/declarative_copy_decorator2.py
:language: python
:lines: 11-
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Declarative container
---------------------
.. currentmodule:: dependency_injector.containers
:py:class:`DeclarativeContainer` is a class-based style of the providers definition.
You create the declarative container subclass, put the providers as attributes and create the
container instance.
.. literalinclude:: ../../examples/containers/declarative.py
:language: python
:lines: 3-
The declarative container providers should only be used when you have the container instance.
Working with the providers of the container on the class level will influence all further
instances.
The declarative container can not have any methods or any other attributes then providers.
The container class provides next attributes:
- ``providers`` - the dictionary of all the container providers
- ``cls_providers`` - the dictionary of the container providers of the current container
- ``inherited_providers`` - the dictionary of all the inherited container providers
.. literalinclude:: ../../examples/containers/declarative_inheritance.py
:language: python
:lines: 3-
Injections in the declarative container are done the usual way:
.. literalinclude:: ../../examples/containers/declarative_injections.py
:language: python
:lines: 3-
You can override container providers while creating a container instance:
.. literalinclude:: ../../examples/containers/declarative_override_providers.py
:language: python
:lines: 3-
:emphasize-lines: 13
Alternatively, you can call ``container.override_providers()`` method when the container instance
already exists:
.. code-block:: python
:emphasize-lines: 3
container = Container()
container.override_providers(foo=mock.Mock(Foo), bar=mock.Mock(Bar))
assert isinstance(container.foo(), mock.Mock)
assert isinstance(container.bar(), mock.Mock)
You can also use ``container.override_providers()`` with a context manager to reset
provided overriding after the context is closed:
.. code-block:: python
:emphasize-lines: 3
container = Container()
with container.override_providers(foo=mock.Mock(Foo), bar=mock.Mock(Bar)):
assert isinstance(container.foo(), mock.Mock)
assert isinstance(container.bar(), mock.Mock)
assert isinstance(container.foo(), Foo)
assert isinstance(container.bar(), Bar)
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Dynamic container
-----------------
.. currentmodule:: dependency_injector.containers
:py:class:`DynamicContainer` is a collection of the providers defined in the runtime.
You create the dynamic container instance and put the providers as attributes.
.. literalinclude:: ../../examples/containers/dynamic.py
:language: python
:lines: 3-
The dynamic container is good for the case when your application structure depends on the
configuration file or some other source that you can reach only after application is already
running (database, api, etc).
In this example we use the configuration to fill in the dynamic container with the providers:
.. literalinclude:: ../../examples/containers/dynamic_runtime_creation.py
:language: python
:lines: 3-
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.. _containers:
Containers
==========
Containers are collections of the providers.
There are several use cases how you can use containers:
+ Keeping all the providers in a single container (most common).
+ Grouping of the providers from the same architectural layer (for example,
``Services``, ``Models`` and ``Forms`` containers).
+ Grouping of providers from the same functional groups (for example,
container ``Users``, that contains all functional parts of the ``users``
package).
Containers module API docs - :py:mod:`dependency_injector.containers`.
.. toctree::
:maxdepth: 2
declarative
dynamic
specialization
overriding
copying
reset_singletons
check_dependencies
traversal

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@ -1,40 +0,0 @@
Container overriding
--------------------
.. currentmodule:: dependency_injector.containers
The container can be overridden by the other container. All of the providers from the overriding
container will override the providers with the same names in the overridden container.
.. literalinclude:: ../../examples/containers/override.py
:language: python
:lines: 3-
It helps in a testing. Also you can use it for configuring project for the different
environments: replace an API client with a stub on the dev or stage.
The container also has:
- ``container.overridden`` - tuple of all overriding containers.
- ``container.reset_last_overriding()`` - reset last overriding for each provider in the container.
- ``container.reset_override()`` - reset all overriding in the container.
:py:class:`DynamicContainer` has the same functionality.
Another possible way to override container providers on declarative level is
``@containers.override()`` decorator:
.. literalinclude:: ../../examples/containers/declarative_override_decorator.py
:language: python
:lines: 3-
:emphasize-lines: 12-16
Decorator ``@containers.override()`` takes a container for overriding as an argument.
This container providers will be overridden by the providers with the same names from
the decorated container.
It helps to change the behaviour of application by importing extension modules but not a code change.
Imported module can override providers in main container. While the code uses main container as
before, the overridden providers provide components defined in the extension module.
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.. _reset-container-singletons:
Reset container singletons
--------------------------
To reset all container singletons use method ``.reset_singletons()``.
.. literalinclude:: ../../examples/containers/reset_singletons.py
:language: python
:lines: 3-
:emphasize-lines: 16
Method ``.reset_singletons()`` also resets singletons in sub-containers: ``providers.Container`` and
``providers.DependenciesContainer.``
.. literalinclude:: ../../examples/containers/reset_singletons_subcontainers.py
:language: python
:lines: 3-
:emphasize-lines: 21
You can use ``.reset_singletons()`` method with a context manager. Singletons will be reset on
both entering and exiting a context.
.. literalinclude:: ../../examples/containers/reset_singletons_with.py
:language: python
:lines: 3-
:emphasize-lines: 14-15
See also: :ref:`singleton-provider`.
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Specialization of the container provider type
---------------------------------------------
.. currentmodule:: dependency_injector.containers
You can make a restriction of the :py:class:`DeclarativeContainer` provider type:
.. literalinclude:: ../../examples/containers/declarative_provider_type.py
:language: python
:lines: 3-
:emphasize-lines: 29-31
The emphasized lines will cause an error because ``other_provider`` is not a subtype of the
``ServiceProvider``. This helps to control the content of the container.
The same works for the :py:class:`DynamicContainer`:
.. literalinclude:: ../../examples/containers/dynamic_provider_type.py
:language: python
:lines: 3-
:emphasize-lines: 23
The emphasized line will also cause an error.
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Container providers traversal
-----------------------------
To traverse container providers use method ``.traverse()``.
.. literalinclude:: ../../examples/containers/traverse.py
:language: python
:lines: 3-
:emphasize-lines: 38
Method ``.traverse()`` returns a generator. Traversal generator visits all container providers.
This includes nested providers even if they are not present on the root level of the container.
Traversal generator guarantees that each container provider will be visited only once.
It can traverse cyclic provider graphs.
Traversal generator does not guarantee traversal order.
You can use ``types=[...]`` argument to filter providers. Traversal generator will only return
providers matching specified types.
.. code-block:: python
:emphasize-lines: 3
container = Container()
for provider in container.traverse(types=[providers.Resource]):
print(provider)
# <dependency_injector.providers.Resource(<function init_database at 0x10bd2cb80>) at 0x10d346b40>
# <dependency_injector.providers.Resource(<function init_cache at 0x10be373a0>) at 0x10d346bc0>
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Chained Factories pattern
=========================
This example demonstrates "Chained Factories" pattern.
The idea of the pattern is in wrapping ``Factory`` into another ``Factory`` that adds
additional arguments.
.. code-block:: python
base_factory = providers.Factory(
SomeClass,
base_argument=1,
)
concrete_factory = providers.Factory(
base_factory,
extra_argument=2,
)
if __name__ == "__main__":
instance = concrete_factory()
# Same as: # instance = SomeClass(base_argument=1, extra_argument=2)
Sample code
-----------
Listing of the pattern example:
.. literalinclude:: ../../examples/miniapps/factory-patterns/chained_factories.py
:language: python
Arguments priority
------------------
Passing of the arguments works the same way like for any other :ref:`factory-provider`.
.. code-block:: python
# 1. Keyword arguments of upper level factory are added to lower level factory
chained_dict_factory = providers.Factory(
providers.Factory(dict, arg1=1),
arg2=2,
)
print(chained_dict_factory()) # prints: {"arg1": 1, "arg2": 2}
# 2. Keyword arguments of upper level factory have priority
chained_dict_factory = providers.Factory(
providers.Factory(dict, arg1=1),
arg1=2,
)
print(chained_dict_factory()) # prints: {"arg1": 2}
# 3. Keyword arguments provided from context have the most priority
chained_dict_factory = providers.Factory(
providers.Factory(dict, arg1=1),
arg1=2,
)
print(chained_dict_factory(arg1=3)) # prints: {"arg1": 3}
Credits
-------
The "Chained Factories" pattern was suggested by the ``Dependency Injector`` users.
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Factory of Factories pattern
============================
This example demonstrates "Factory of Factories" pattern.
The idea of the pattern is in creating a ``Factory`` that creates another ``Factory`` and adds
additional arguments.
.. code-block:: python
base_factory = providers.Factory(
providers.Factory
SomeClass,
base_argument=1,
)
concrete_factory = providers.Factory(
OtherClass,
instance=base_factory(extra_argument=1),
)
if __name__ == "__main__":
instance = concrete_factory()
# Same as: # instance = SomeClass(base_argument=1, extra_argument=2)
Sample code
-----------
Listing of the pattern example:
.. literalinclude:: ../../examples/miniapps/factory-patterns/factory_of_factories.py
:language: python
Arguments priority
------------------
Passing of the arguments works the same way like for any other :ref:`factory-provider`.
.. code-block:: python
# 1. Keyword arguments of upper level factory are added to lower level factory
factory_of_dict_factories = providers.Factory(
providers.Factory,
dict,
arg1=1,
)
dict_factory = factory_of_dict_factories(arg2=2)
print(dict_factory()) # prints: {"arg1": 1, "arg2": 2}
# 2. Keyword arguments of upper level factory have priority
factory_of_dict_factories = providers.Factory(
providers.Factory,
dict,
arg1=1,
)
dict_factory = factory_of_dict_factories(arg1=2)
print(dict_factory()) # prints: {"arg1": 2}
# 3. Keyword arguments provided from context have the most priority
factory_of_dict_factories = providers.Factory(
providers.Factory,
dict,
arg1=1,
)
dict_factory = factory_of_dict_factories(arg1=2)
print(dict_factory(arg1=3)) # prints: {"arg1": 3}
Credits
-------
The "Factory of Factories" pattern was suggested by the ``Dependency Injector`` users.
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@ -1,17 +0,0 @@
Other examples
==============
.. meta::
:keywords: Python,Dependency Injection,Inversion of Control,Container,Example,Application,
Framework
:description: This sections contains assorted Dependency Injector examples.
This sections contains assorted ``Dependency Injector`` examples.
.. toctree::
:maxdepth: 2
use-cases
password-hashing
chained-factories
factory-of-factories

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Password hashing example
========================
.. meta::
:keywords: Python,Dependency Injection,Inversion of Control,Container,Example,Application,
Framework,Callable
:description: This example demonstrates a usage of the Callable provider.
This example demonstrates an injection of the ``Callable`` provider.
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/password-hashing>`_.
Sample code
-----------
Listing of the pattern example:
.. literalinclude:: ../../examples/miniapps/password-hashing/example.py
:language: python
Run the example
---------------
Instructions for running:
.. code-block:: bash
python example.py
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Use cases example
=================
.. meta::
:keywords: Python,Dependency Injection,Inversion of Control,Container,Example,Application,
Framework,DependenciesContainer
:description: This example demonstrates a usage of the DependenciesContainer provider.
This example demonstrates a usage of the ``DependenciesContainer`` provider.
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/decoupled-packages>`_.
Application structure
---------------------
Example application has next structure:
.. code-block:: bash
./
└── example/
├── __init__.py
├── __main__.py
├── adapters.py
├── containers.py
└── usecases.py
Containers
----------
Listing of the ``example/containers.py``:
.. literalinclude:: ../../examples/miniapps/use-cases/example/containers.py
:language: python
Main module
-----------
Listing of the ``example/__main__.py``:
.. literalinclude:: ../../examples/miniapps/use-cases/example/__main__.py
:language: python
Run the application
-------------------
Instructions for running in the "test" mode:
.. code-block:: bash
python run.py test example@example.com
Instructions for running in the "prod" mode:
.. code-block:: bash
python run.py prod example@example.com
Adapters and use cases
----------------------
Listing of the ``example/adapters.py``:
.. literalinclude:: ../../examples/miniapps/use-cases/example/adapters.py
:language: python
Listing of the ``example/usecases.py``:
.. literalinclude:: ../../examples/miniapps/use-cases/example/usecases.py
:language: python
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.. _aiohttp-example:
Aiohttp example
===============
.. meta::
:keywords: Python,Dependency Injection,Aiohttp,Example
:description: This example demonstrates a usage of the Aiohttp and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `Aiohttp <https://docs.aiohttp.org/>`_.
The example application is a REST API that searches for funny GIFs on the `Giphy <https://giphy.com/>`_.
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/aiohttp>`_.
:ref:`aiohttp-tutorial` demonstrates how to build this application step-by-step.
Application structure
---------------------
Application has next structure:
.. code-block:: bash
./
├── giphynavigator/
│ ├── __init__.py
│ ├── application.py
│ ├── containers.py
│ ├── giphy.py
│ ├── handlers.py
│ ├── services.py
│ └── tests.py
├── config.yml
└── requirements.txt
Container
---------
Declarative container is defined in ``giphynavigator/containers.py``:
.. literalinclude:: ../../examples/miniapps/aiohttp/giphynavigator/containers.py
:language: python
Handlers
--------
Handler has dependencies on search service and some config options. The dependencies are injected
using :ref:`wiring` feature.
Listing of ``giphynavigator/handlers.py``:
.. literalinclude:: ../../examples/miniapps/aiohttp/giphynavigator/handlers.py
:language: python
Application factory
-------------------
Application factory creates container, wires it with the ``handlers`` module, creates
``Aiohttp`` app and setup routes.
Listing of ``giphynavigator/application.py``:
.. literalinclude:: ../../examples/miniapps/aiohttp/giphynavigator/application.py
:language: python
Tests
-----
Tests use :ref:`provider-overriding` feature to replace giphy client with a mock ``giphynavigator/tests.py``:
.. literalinclude:: ../../examples/miniapps/aiohttp/giphynavigator/tests.py
:language: python
:emphasize-lines: 32,59,73
Sources
-------
Explore the sources on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/aiohttp>`_.
.. include:: ../sponsor.rst
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.. _application-multiple-containers:
Application example (multiple containers)
=========================================
.. meta::
:keywords: Python,Dependency Injection,Inversion of Control,Container,Example,Application,
Framework,AWS,boto3,client
:description: This example shows how you can create an application using multiple declarative
containers. We build an example Python micro application following the dependency
injection principle. It consists from several services with a domain logic that
have dependencies on database & AWS S3.
This example shows how you can create an application using multiple declarative containers. Using
multiple declarative containers is a good choice for a large application. For
building a moderate or a small size application refer to :ref:`application-single-container`.
We build an example micro application following the dependency injection principle. It consists
of several services with a domain logic. The services have dependencies on database & AWS S3.
.. image:: images/application.png
:width: 100%
:align: center
Start from the scratch or jump to the section:
.. contents::
:local:
:backlinks: none
You can find the source code and instructions for running on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/application-multiple-containers>`_.
Application structure
---------------------
Application consists of an ``example`` package, a configuration file and a ``requirements.txt``
file.
.. code-block:: bash
./
├── example/
│ ├── __init__.py
│ ├── __main__.py
│ ├── containers.py
│ └── services.py
├── config.yml
└── requirements.txt
Containers
----------
Listing of the ``example/containers.py``:
.. literalinclude:: ../../examples/miniapps/application-multiple-containers/example/containers.py
:language: python
Main module
-----------
Listing of the ``example/__main__.py``:
.. literalinclude:: ../../examples/miniapps/application-multiple-containers/example/__main__.py
:language: python
Services
--------
Listing of the ``example/services.py``:
.. literalinclude:: ../../examples/miniapps/application-multiple-containers/example/services.py
:language: python
Configuration
-------------
Listing of the ``config.yml``:
.. literalinclude:: ../../examples/miniapps/application-multiple-containers/config.yml
:language: yaml
Run the application
-------------------
You can find the source code and instructions for running on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/application-multiple-containers>`_.
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.. _application-single-container:
Application example (single container)
======================================
.. meta::
:keywords: Python,Dependency Injection,Inversion of Control,Container,Example,Application,
Framework,AWS,boto3,client
:description: This example shows how you can create an application using a single declarative
container. We build an example Python micro application following the dependency
injection principle. It consists from several services with a domain logic that
have dependencies on database & AWS S3.
This example shows how you can create an application using a single declarative container. Using
a single declarative container is a good choice for small or moderate size application. For
building a large application refer to :ref:`application-multiple-containers`.
We build an example micro application following the dependency injection principle. It consists
of several services with a domain logic. The services have dependencies on database & AWS S3.
.. image:: images/application.png
:width: 100%
:align: center
Start from the scratch or jump to the section:
.. contents::
:local:
:backlinks: none
You can find the source code and instructions for running on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/application-single-container>`_.
Application structure
---------------------
Application consists of an ``example`` package, several configuration files and a
``requirements.txt`` file.
.. code-block:: bash
./
├── example/
│ ├── __init__.py
│ ├── __main__.py
│ ├── containers.py
│ └── services.py
├── config.ini
├── logging.ini
└── requirements.txt
Container
---------
Listing of the ``example/containers.py``:
.. literalinclude:: ../../examples/miniapps/application-single-container/example/containers.py
:language: python
Main module
-----------
Listing of the ``example/__main__.py``:
.. literalinclude:: ../../examples/miniapps/application-single-container/example/__main__.py
:language: python
Services
--------
Listing of the ``example/services.py``:
.. literalinclude:: ../../examples/miniapps/application-single-container/example/services.py
:language: python
Configuration
-------------
Listing of the ``config.ini``:
.. literalinclude:: ../../examples/miniapps/application-single-container/config.ini
:language: ini
Listing of the ``logging.ini``:
.. literalinclude:: ../../examples/miniapps/application-single-container/logging.ini
:language: ini
Run the application
-------------------
You can find the source code and instructions for running on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/application-single-container>`_.
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.. _boto3-example:
Boto3 example
=============
.. meta::
:keywords: Python,Dependency Injection,Boto3,AWS,Amazon Web Services,S3,SQS,Rout53,EC2,Lambda,Example
:description: This example demonstrates a usage of Boto3 AWS client and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `Boto3 <https://github.com/boto/boto3>`_.
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/boto3-session>`_.
Listing of ``boto3_session_example.py``:
.. literalinclude:: ../../examples/miniapps/boto3-session/boto3_session_example.py
:language: python
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.. _decoupled-packages:
Decoupled packages example (multiple containers)
================================================
.. meta::
:keywords: Python,Dependency Injection,Inversion of Control,Container,Example,Application,
Framework,AWS,boto3,client
:description: This example shows how to use Dependency Injector to create Python decoupled packages.
To achieve a decoupling each package has a container with the components. When
a component needs a dependency from the outside of the package scope we use the
Dependency provider. The package container has no knowledge on where the
dependencies come from. It states a need that the dependencies must be provided.
This helps to decouple a package from the 3rd party dependencies and other
packages.
This example shows how to use ``Dependency Injector`` to create decoupled packages.
To achieve a decoupling each package has a container with the components. When a component needs a
dependency from the outside of the package scope we use the ``Dependency`` provider. The package
container has no knowledge on where the dependencies come from. It states a need that the
dependencies must be provided. This helps to decouple a package from the 3rd party dependencies
and other packages.
To wire the packages we use an application container. Application container has all 3rd party
dependencies and package containers. It wires the packages and dependencies to create a
complete application.
We build an example micro application that consists of 3 packages:
- ``user`` - a package with user domain logic, depends on a database
- ``photo`` - a package with photo domain logic, depends on a database and AWS S3
- ``analytics`` - a package with analytics domain logic, depends on the ``user`` and ``photo``
package components
.. image:: images/decoupled-packages.png
:width: 100%
:align: center
Start from the scratch or jump to the section:
.. contents::
:local:
:backlinks: none
You can find the source code and instructions for running on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/decoupled-packages>`_.
Application structure
---------------------
Application consists of an ``example`` package, a configuration file and a ``requirements.txt``
file.
.. code-block:: bash
./
├── example/
│ ├── analytics/
│ │ ├── __init__.py
│ │ ├── containers.py
│ │ └── services.py
│ ├── photo/
│ │ ├── __init__.py
│ │ ├── containers.py
│ │ ├── entities.py
│ │ └── repositories.py
│ ├── user/
│ │ ├── __init__.py
│ │ ├── containers.py
│ │ ├── entities.py
│ │ └── repositories.py
│ ├── __init__.py
│ ├── __main__.py
│ └── containers.py
├── config.ini
└── requirements.txt
Package containers
------------------
Listing of the ``example/user/containers.py``:
.. literalinclude:: ../../examples/miniapps/decoupled-packages/example/user/containers.py
:language: python
Listing of the ``example/photo/containers.py``:
.. literalinclude:: ../../examples/miniapps/decoupled-packages/example/photo/containers.py
:language: python
Listing of the ``example/analytics/containers.py``:
.. literalinclude:: ../../examples/miniapps/decoupled-packages/example/analytics/containers.py
:language: python
Application container
---------------------
Application container consists of all packages and 3rd party dependencies. Its role is to wire
everything together in a complete application.
Listing of the ``example/containers.py``:
.. literalinclude:: ../../examples/miniapps/decoupled-packages/example/containers.py
:language: python
.. note::
Package ``analytics`` has dependencies on the repositories from the ``user`` and
``photo`` packages. This is an example of how you can pass the dependencies from one package
to another.
Main module
-----------
Listing of the ``example/__main__.py``:
.. literalinclude:: ../../examples/miniapps/decoupled-packages/example/__main__.py
:language: python
Configuration
-------------
Listing of the ``config.ini``:
.. literalinclude:: ../../examples/miniapps/decoupled-packages/config.ini
:language: ini
Run the application
-------------------
You can find the source code and instructions for running on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/decoupled-packages>`_.
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.. _django-example:
Django example
==============
.. meta::
:keywords: Python,Dependency Injection,Django,Example
:description: This example demonstrates a usage of the Django and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `Django <https://www.djangoproject.com/>`_.
The example application helps to search for repositories on the Github.
.. image:: images/django.png
:width: 100%
:align: center
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/django>`_.
Application structure
---------------------
Application has standard Django project structure. It consists of ``githubnavigator`` project package and
``web`` application package:
.. code-block:: bash
./
├── githubnavigator/
│ ├── __init__.py
│ ├── asgi.py
│ ├── containers.py
│ ├── services.py
│ ├── settings.py
│ ├── urls.py
│ └── wsgi.py
├── web/
│ ├── templates/
│ │ ├── base.html
│ │ └── index.html
│ ├── __init__.py
│ ├── apps.py
│ ├── tests.py
│ ├── urls.py
│ └── views.py
├── manage.py
└── requirements.txt
Container
---------
Declarative container is defined in ``githubnavigator/containers.py``:
.. literalinclude:: ../../examples/miniapps/django/githubnavigator/containers.py
:language: python
Container instance is created in ``githubnavigator/__init__.py``:
.. literalinclude:: ../../examples/miniapps/django/githubnavigator/__init__.py
:language: python
Views
-----
View has dependencies on search service and some config options. The dependencies are injected
using :ref:`wiring` feature.
Listing of ``web/views.py``:
.. literalinclude:: ../../examples/miniapps/django/web/views.py
:language: python
App config
----------
Container is wired to the ``views`` module in the app config ``web/apps.py``:
.. literalinclude:: ../../examples/miniapps/django/web/apps.py
:language: python
:emphasize-lines: 13
Tests
-----
Tests use :ref:`provider-overriding` feature to replace github client with a mock ``web/tests.py``:
.. literalinclude:: ../../examples/miniapps/django/web/tests.py
:language: python
:emphasize-lines: 39,60
Sources
-------
Explore the sources on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/django>`_.
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.. _fastapi-redis-example:
FastAPI + Redis example
=======================
.. meta::
:keywords: Python,Dependency Injection,FastAPI,Redis,Example
:description: This example demonstrates a usage of the FastAPI, Redis, and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `FastAPI <https://fastapi.tiangolo.com/>`_ and
`Redis <https://redis.io/>`_.
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/fastapi-redis>`_.
See also:
- Provider :ref:`async-injections`
- Resource provider :ref:`resource-async-initializers`
- Wiring :ref:`async-injections-wiring`
Application structure
---------------------
Application has next structure:
.. code-block:: bash
./
├── fastapiredis/
│ ├── __init__.py
│ ├── application.py
│ ├── containers.py
│ ├── redis.py
│ ├── services.py
│ └── tests.py
├── docker-compose.yml
├── Dockerfile
└── requirements.txt
Redis
-----
Module ``redis`` defines Redis connection pool initialization and shutdown. See ``fastapiredis/redis.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-redis/fastapiredis/redis.py
:language: python
Service
-------
Module ``services`` contains example service. Service has a dependency on Redis connection pool.
It uses it for getting and setting a key asynchronously. Real life service will do something more meaningful.
See ``fastapiredis/services.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-redis/fastapiredis/services.py
:language: python
Container
---------
Declarative container wires example service with Redis connection pool. See ``fastapiredis/containers.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-redis/fastapiredis/containers.py
:language: python
Application
-----------
Module ``application`` creates ``FastAPI`` app, setup endpoint, and init container.
Endpoint ``index`` has a dependency on example service. The dependency is injected using :ref:`wiring` feature.
Listing of ``fastapiredis/application.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-redis/fastapiredis/application.py
:language: python
Tests
-----
Tests use :ref:`provider-overriding` feature to replace example service with a mock. See ``fastapiredis/tests.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-redis/fastapiredis/tests.py
:language: python
:emphasize-lines: 24
Sources
-------
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/fastapi-redis>`_.
See also:
- Provider :ref:`async-injections`
- Resource provider :ref:`resource-async-initializers`
- Wiring :ref:`async-injections-wiring`
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.. _fastapi-sqlalchemy-example:
FastAPI + SQLAlchemy example
============================
.. meta::
:keywords: Python,Dependency Injection,FastAPI,SQLAlchemy,Example
:description: This example demonstrates a usage of the FastAPI, SQLAlchemy, and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `FastAPI <https://fastapi.tiangolo.com/>`_ and
`SQLAlchemy <https://www.sqlalchemy.org/>`_.
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/fastapi-sqlalchemy>`_.
Thanks to `@ShvetsovYura <https://github.com/ShvetsovYura>`_ for providing initial example:
`FastAPI_DI_SqlAlchemy <https://github.com/ShvetsovYura/FastAPI_DI_SqlAlchemy>`_.
Application structure
---------------------
Application has next structure:
.. code-block:: bash
./
├── webapp/
│ ├── __init__.py
│ ├── application.py
│ ├── containers.py
│ ├── database.py
│ ├── endpoints.py
│ ├── models.py
│ ├── repositories.py
│ ├── services.py
│ └── tests.py
├── config.yml
├── docker-compose.yml
├── Dockerfile
└── requirements.txt
Application factory
-------------------
Application factory creates container, wires it with the ``endpoints`` module, creates
``FastAPI`` app, and setup routes.
Application factory also creates database if it does not exist.
Listing of ``webapp/application.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-sqlalchemy/webapp/application.py
:language: python
Endpoints
---------
Module ``endpoints`` contains example endpoints. Endpoints have a dependency on user service.
User service is injected using :ref:`wiring` feature. See ``webapp/endpoints.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-sqlalchemy/webapp/endpoints.py
:language: python
Container
---------
Declarative container wires example user service, user repository, and utility database class.
See ``webapp/containers.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-sqlalchemy/webapp/containers.py
:language: python
Services
--------
Module ``services`` contains example user service. See ``webapp/services.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-sqlalchemy/webapp/services.py
:language: python
Repositories
------------
Module ``repositories`` contains example user repository. See ``webapp/repositories.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-sqlalchemy/webapp/repositories.py
:language: python
Models
------
Module ``models`` contains example SQLAlchemy user model. See ``webapp/models.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-sqlalchemy/webapp/models.py
:language: python
Database
--------
Module ``database`` defines declarative base and utility class with engine and session factory.
See ``webapp/database.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-sqlalchemy/webapp/database.py
:language: python
Tests
-----
Tests use :ref:`provider-overriding` feature to replace repository with a mock. See ``webapp/tests.py``:
.. literalinclude:: ../../examples/miniapps/fastapi-sqlalchemy/webapp/tests.py
:language: python
:emphasize-lines: 25, 45, 58, 74, 86, 97
Sources
-------
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/fastapi-sqlalchemy>`_.
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.. _fastapi-example:
FastAPI example
===============
.. meta::
:keywords: Python,Dependency Injection,FastAPI,Example
:description: This example demonstrates a usage of the FastAPI and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `FastAPI <https://fastapi.tiangolo.com/>`_.
The example application is a REST API that searches for funny GIFs on the `Giphy <https://giphy.com/>`_.
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/fastapi>`_.
Application structure
---------------------
Application has next structure:
.. code-block:: bash
./
├── giphynavigator/
│ ├── __init__.py
│ ├── application.py
│ ├── containers.py
│ ├── endpoints.py
│ ├── giphy.py
│ ├── services.py
│ └── tests.py
├── config.yml
└── requirements.txt
Container
---------
Declarative container is defined in ``giphynavigator/containers.py``:
.. literalinclude:: ../../examples/miniapps/fastapi/giphynavigator/containers.py
:language: python
Endpoints
---------
Endpoint has a dependency on search service. There are also some config options that are used as default values.
The dependencies are injected using :ref:`wiring` feature.
Listing of ``giphynavigator/endpoints.py``:
.. literalinclude:: ../../examples/miniapps/fastapi/giphynavigator/endpoints.py
:language: python
Application factory
-------------------
Application factory creates container, wires it with the ``endpoints`` module, creates
``FastAPI`` app, and setup routes.
Listing of ``giphynavigator/application.py``:
.. literalinclude:: ../../examples/miniapps/fastapi/giphynavigator/application.py
:language: python
Tests
-----
Tests use :ref:`provider-overriding` feature to replace giphy client with a mock ``giphynavigator/tests.py``:
.. literalinclude:: ../../examples/miniapps/fastapi/giphynavigator/tests.py
:language: python
:emphasize-lines: 29,57,72
Sources
-------
Explore the sources on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/fastapi>`_.
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.. _flask-blueprints-example:
Flask blueprints example
========================
.. meta::
:keywords: Python,Dependency Injection,Flask,Blueprints,Example
:description: This example demonstrates a usage of the Flask Blueprints and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `Flask <https://flask.palletsprojects.com/en/1.1.x/>`_
blueprints.
The example application helps to search for repositories on the Github.
.. image:: images/flask.png
:width: 100%
:align: center
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/flask-blueprints>`_.
Application structure
---------------------
Application has next structure:
.. code-block:: bash
./
├── githubnavigator/
│ ├── blueprints
│ │ ├── __init__.py
│ │ └── example.py
│ ├── templates
│ │ ├── base.html
│ │ └── index.py
│ ├── __init__.py
│ ├── application.py
│ ├── containers.py
│ ├── services.py
│ └── tests.py
├── config.yml
└── requirements.txt
Container
---------
Declarative container is defined in ``githubnavigator/containers.py``:
.. literalinclude:: ../../examples/miniapps/flask-blueprints/githubnavigator/containers.py
:language: python
Blueprints
----------
Blueprint's view has dependencies on search service and some config options. The dependencies are injected
using :ref:`wiring` feature.
Listing of ``githubnavigator/blueprints/example.py``:
.. literalinclude:: ../../examples/miniapps/flask-blueprints/githubnavigator/blueprints/example.py
:language: python
Application factory
-------------------
Application factory creates container, wires it with the blueprints, creates
``Flask`` app, and setup routes.
Listing of ``githubnavigator/application.py``:
.. literalinclude:: ../../examples/miniapps/flask-blueprints/githubnavigator/application.py
:language: python
Tests
-----
Tests use :ref:`provider-overriding` feature to replace github client with a mock ``githubnavigator/tests.py``:
.. literalinclude:: ../../examples/miniapps/flask-blueprints/githubnavigator/tests.py
:language: python
:emphasize-lines: 44,67
Sources
-------
Explore the sources on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/flask-blueprints>`_.
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.. _flask-example:
Flask example
=============
.. meta::
:keywords: Python,Dependency Injection,Flask,Example
:description: This example demonstrates a usage of the Flask and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `Flask <https://flask.palletsprojects.com/en/1.1.x/>`_.
The example application helps to search for repositories on the Github.
.. image:: images/flask.png
:width: 100%
:align: center
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/flask>`_.
:ref:`flask-tutorial` demonstrates how to build this application step-by-step.
Application structure
---------------------
Application has next structure:
.. code-block:: bash
./
├── githubnavigator/
│ ├── templates
│ │ ├── base.html
│ │ └── index.py
│ ├── __init__.py
│ ├── application.py
│ ├── containers.py
│ ├── services.py
│ ├── tests.py
│ └── views.py
├── config.yml
└── requirements.txt
Container
---------
Declarative container is defined in ``githubnavigator/containers.py``:
.. literalinclude:: ../../examples/miniapps/flask/githubnavigator/containers.py
:language: python
Views
-----
View has dependencies on search service and some config options. The dependencies are injected
using :ref:`wiring` feature.
Listing of ``githubnavigator/views.py``:
.. literalinclude:: ../../examples/miniapps/flask/githubnavigator/views.py
:language: python
Application factory
-------------------
Application factory creates container, wires it with the ``views`` module, creates
``Flask`` app and setup routes.
Listing of ``githubnavigator/application.py``:
.. literalinclude:: ../../examples/miniapps/flask/githubnavigator/application.py
:language: python
Tests
-----
Tests use :ref:`provider-overriding` feature to replace github client with a mock ``githubnavigator/tests.py``:
.. literalinclude:: ../../examples/miniapps/flask/githubnavigator/tests.py
:language: python
:emphasize-lines: 44,67
Sources
-------
Explore the sources on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/flask>`_.
.. include:: ../sponsor.rst
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Examples
========
.. meta::
:keywords: Python,DI,Dependency injection,IoC,Inversion of Control,Example
:description: Python dependency injection examples.
Explore the examples to see the ``Dependency Injector`` in action.
.. toctree::
:maxdepth: 2
application-single-container
application-multiple-containers
decoupled-packages
boto3
django
flask
flask-blueprints
aiohttp
sanic
fastapi
fastapi-redis
fastapi-sqlalchemy
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.. _sanic-example:
Sanic example
==============
.. meta::
:keywords: Python,Dependency Injection,Sanic,Example
:description: This example demonstrates a usage of the Sanic and Dependency Injector.
This example shows how to use ``Dependency Injector`` with `Sanic <https://sanic.readthedocs.io/en/latest/>`_.
The example application is a REST API that searches for funny GIFs on the `Giphy <https://giphy.com/>`_.
The source code is available on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/sanic>`_.
Application structure
---------------------
Application has next structure:
.. code-block:: bash
./
├── giphynavigator/
│ ├── __init__.py
│ ├── __main__.py
│ ├── application.py
│ ├── containers.py
│ ├── giphy.py
│ ├── handlers.py
│ ├── services.py
│ └── tests.py
├── config.yml
└── requirements.txt
Container
---------
Declarative container is defined in ``giphynavigator/containers.py``:
.. literalinclude:: ../../examples/miniapps/sanic/giphynavigator/containers.py
:language: python
Handlers
--------
Handler has dependencies on search service and some config options. The dependencies are injected
using :ref:`wiring` feature.
Listing of ``giphynavigator/handlers.py``:
.. literalinclude:: ../../examples/miniapps/sanic/giphynavigator/handlers.py
:language: python
Application factory
-------------------
Application factory creates container, wires it with the ``handlers`` module, creates
``Sanic`` app and setup routes.
Listing of ``giphynavigator/application.py``:
.. literalinclude:: ../../examples/miniapps/sanic/giphynavigator/application.py
:language: python
Tests
-----
Tests use :ref:`provider-overriding` feature to replace giphy client with a mock ``giphynavigator/tests.py``:
.. literalinclude:: ../../examples/miniapps/sanic/giphynavigator/tests.py
:language: python
:emphasize-lines: 34,61,75
Sources
-------
Explore the sources on the `Github <https://github.com/ets-labs/python-dependency-injector/tree/master/examples/miniapps/sanic>`_.
.. include:: ../sponsor.rst
.. disqus::

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=================================================================
Dependency Injector --- Dependency injection framework for Python
=================================================================
Dependency Injector
===================
.. meta::
:google-site-verification: V1hlKfpgL3AARAElwFcqP4qW1Smsx5bKSRU8O86i20Y
:keywords: Python,Dependency injection,DI,Inversion of Control,IoC,
IoC Container,Factory, Singleton, Design Patterns
:description: Dependency Injector is a dependency injection framework
for Python. It helps to maintain you application structure.
It was designed to be unified, developer-friendly
tool that helps to implement dependency injection design
pattern in formal, pretty, Pythonic way. Dependency Injector
provides implementations of such popular design patterns
like IoC container, Factory and Singleton. Dependency
Injector providers are implemented as C extension types
using Cython.
:description: Python dependency injection framework
:keywords: Python, Dependency injection, Dependency injection framework,
Dependency injection container, Dependency injector,
Dependency management, DI, DI Container, Inversion of Control,
Inversion of Control container, IoC, IoC container
.. _index:
*Dependency Injector* is a Python dependency injection framework. It was
designed to be unified, developer's friendly tool for managing any kind
of Python objects and their dependencies in formal, pretty way.
.. image:: https://img.shields.io/pypi/v/dependency_injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: Latest Version
Below is a list of some key features and points of *Dependency Injector*:
.. image:: https://img.shields.io/pypi/l/dependency_injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: License
- Easy, smart, pythonic style.
- Obvious, clear structure.
- Memory efficiency.
- Thread safety.
- Semantic versioning.
.. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: Supported Python versions
Main idea of *Dependency Injector* is to keep dependencies under control.
.. image:: https://img.shields.io/pypi/implementation/dependency_injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: Supported Python implementations
Status
------
.. image:: https://static.pepy.tech/badge/dependency-injector
:target: https://pepy.tech/project/dependency-injector
:alt: Downloads
.. image:: https://static.pepy.tech/badge/dependency-injector/month
:target: https://pepy.tech/project/dependency-injector
:alt: Downloads
.. image:: https://static.pepy.tech/badge/dependency-injector/week
:target: https://pepy.tech/project/dependency-injector
:alt: Downloads
.. image:: https://img.shields.io/pypi/wheel/dependency-injector.svg
:target: https://pypi.org/project/dependency-injector/
:alt: Wheel
.. image:: https://img.shields.io/github/actions/workflow/status/ets-labs/python-dependency-injector/tests-and-linters.yml?branch=master
:target: https://github.com/ets-labs/python-dependency-injector/actions
:alt: Build Status
.. image:: https://coveralls.io/repos/github/ets-labs/python-dependency-injector/badge.svg?branch=master
:target: https://coveralls.io/github/ets-labs/python-dependency-injector?branch=master
:alt: Coverage Status
``Dependency Injector`` is a dependency injection framework for Python.
It helps implementing the dependency injection principle.
Key features of the ``Dependency Injector``:
- **Providers**. Provides ``Factory``, ``Singleton``, ``Callable``, ``Coroutine``, ``Object``,
``List``, ``Dict``, ``Configuration``, ``Resource``, ``Dependency``, and ``Selector`` providers
that help assemble your objects. See :ref:`providers`.
- **Overriding**. Can override any provider by another provider on the fly. This helps in testing
and configuring dev/stage environment to replace API clients with stubs etc. See
:ref:`provider-overriding`.
- **Configuration**. Reads configuration from ``yaml``, ``ini``, and ``json`` files, ``pydantic`` settings,
environment variables, and dictionaries. See :ref:`configuration-provider`.
- **Resources**. Helps with initialization and configuring of logging, event loop, thread
or process pool, etc. Can be used for per-function execution scope in tandem with wiring.
See :ref:`resource-provider`.
- **Containers**. Provides declarative and dynamic containers. See :ref:`containers`.
- **Wiring**. Injects dependencies into functions and methods. Helps integrate with
other frameworks: Django, Flask, Aiohttp, Sanic, FastAPI, etc. See :ref:`wiring`.
- **Asynchronous**. Supports asynchronous injections. See :ref:`async-injections`.
- **Typing**. Provides typing stubs, ``mypy``-friendly. See :ref:`provider-typing`.
- **Performance**. Fast. Written in ``Cython``.
- **Maturity**. Mature and production-ready. Well-tested, documented, and supported.
.. code-block:: python
from dependency_injector import containers, providers
from dependency_injector.wiring import Provide, inject
class Container(containers.DeclarativeContainer):
config = providers.Configuration()
api_client = providers.Singleton(
ApiClient,
api_key=config.api_key,
timeout=config.timeout,
)
service = providers.Factory(
Service,
api_client=api_client,
)
@inject
def main(service: Service = Provide[Container.service]) -> None:
...
if __name__ == "__main__":
container = Container()
container.config.api_key.from_env("API_KEY", required=True)
container.config.timeout.from_env("TIMEOUT", as_=int, default=5)
container.wire(modules=[__name__])
main() # <-- dependency is injected automatically
with container.api_client.override(mock.Mock()):
main() # <-- overridden dependency is injected automatically
With the ``Dependency Injector``, object assembling is consolidated in the container.
Dependency injections are defined explicitly.
This makes it easier to understand and change how the application works.
.. figure:: https://raw.githubusercontent.com/wiki/ets-labs/python-dependency-injector/img/di-readme.svg
:target: https://github.com/ets-labs/python-dependency-injector
Explore the documentation to know more about the ``Dependency Injector``.
.. _contents:
+---------------------------------------+---------------------------------------------------------------------------------+
| *PyPi* | .. image:: https://img.shields.io/pypi/v/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Latest Version |
| | .. image:: https://img.shields.io/pypi/dm/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Downloads |
| | .. image:: https://img.shields.io/pypi/l/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: License |
+---------------------------------------+---------------------------------------------------------------------------------+
| *Python versions and implementations* | .. image:: https://img.shields.io/pypi/pyversions/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Supported Python versions |
| | .. image:: https://img.shields.io/pypi/implementation/dependency_injector.svg |
| | :target: https://pypi.python.org/pypi/dependency_injector/ |
| | :alt: Supported Python implementations |
+---------------------------------------+---------------------------------------------------------------------------------+
| *Builds and tests coverage* | .. image:: https://travis-ci.org/ets-labs/dependency_injector.svg?branch=master |
| | :target: https://travis-ci.org/ets-labs/dependency_injector |
| | :alt: Build Status |
| | .. image:: https://coveralls.io/repos/ets-labs/dependency_injector/badge.svg |
| | :target: https://coveralls.io/r/ets-labs/dependency_injector |
| | :alt: Coverage Status |
+---------------------------------------+---------------------------------------------------------------------------------+
Contents
--------
.. toctree::
:maxdepth: 2
.. toctree::
:maxdepth: 2
main/introduction
main/installation
providers/index
catalogs/index
advanced_usage/index
api/index
main/feedback
main/changelog
introduction/index
examples/index
tutorials/index
providers/index
containers/index
wiring
examples-other/index
api/index
main/feedback
main/changelog

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@ -1,315 +0,0 @@
Dependency injection and inversion of control in Python
=======================================================
.. meta::
:keywords: Python,DI,Dependency injection,IoC,Inversion of Control,Example
:description: This page describes a usage of the dependency injection and inversion of control
in Python. It contains Python examples that show how to implement dependency
injection. It demonstrates a usage of the dependency injection framework
Dependency Injector, its container, Factory, Singleton and Configuration
providers. The example show how to use Dependency Injector providers overriding
feature for testing or configuring project in different environments and explains
why it's better than monkey-patching.
Originally dependency injection pattern got popular in languages with static typing like Java.
Dependency injection is a principle that helps to achieve an inversion of control. A
dependency injection framework can significantly improve the flexibility of a language
with static typing. Implementation of a dependency injection framework for a language
with static typing is not something that one can do quickly. It will be a quite complex thing
to be done well. And will take time.
Python is an interpreted language with dynamic typing. There is an opinion that dependency
injection doesn't work for it as well as it does for Java. A lot of the flexibility is already
built-in. Also, there is an opinion that a dependency injection framework is something that
Python developer rarely needs. Python developers say that dependency injection can be implemented
easily using language fundamentals.
This page describes the advantages of applying dependency injection in Python. It
contains Python examples that show how to implement dependency injection. It demonstrates the usage
of the ``Dependency Injector`` framework, its container, ``Factory``, ``Singleton``,
and ``Configuration`` providers. The example shows how to use providers' overriding feature
of ``Dependency Injector`` for testing or re-configuring a project in different environments and
explains why it's better than monkey-patching.
What is dependency injection?
-----------------------------
Let's see what the dependency injection is.
Dependency injection is a principle that helps to decrease coupling and increase cohesion.
.. image:: images/coupling-cohesion.png
What is coupling and cohesion?
Coupling and cohesion are about how tough the components are tied.
- **High coupling**. If the coupling is high it's like using superglue or welding. No easy way
to disassemble.
- **High cohesion**. High cohesion is like using screws. Quite easy to disassemble and
re-assemble in a different way. It is an opposite to high coupling.
Cohesion often correlates with coupling. Higher cohesion usually leads to lower coupling and vice versa.
Low coupling brings flexibility. Your code becomes easier to change and test.
How to implement the dependency injection?
Objects do not create each other anymore. They provide a way to inject the dependencies instead.
Before:
.. code-block:: python
import os
class ApiClient:
def __init__(self) -> None:
self.api_key = os.getenv("API_KEY") # <-- dependency
self.timeout = int(os.getenv("TIMEOUT")) # <-- dependency
class Service:
def __init__(self) -> None:
self.api_client = ApiClient() # <-- dependency
def main() -> None:
service = Service() # <-- dependency
...
if __name__ == "__main__":
main()
After:
.. code-block:: python
import os
class ApiClient:
def __init__(self, api_key: str, timeout: int) -> None:
self.api_key = api_key # <-- dependency is injected
self.timeout = timeout # <-- dependency is injected
class Service:
def __init__(self, api_client: ApiClient) -> None:
self.api_client = api_client # <-- dependency is injected
def main(service: Service) -> None: # <-- dependency is injected
...
if __name__ == "__main__":
main(
service=Service(
api_client=ApiClient(
api_key=os.getenv("API_KEY"),
timeout=int(os.getenv("TIMEOUT")),
),
),
)
``ApiClient`` is decoupled from knowing where the options come from. You can read a key and a
timeout from a configuration file or even get them from a database.
``Service`` is decoupled from the ``ApiClient``. It does not create it anymore. You can provide a
stub or other compatible object.
Function ``main()`` is decoupled from ``Service``. It receives it as an argument.
Flexibility comes with a price.
Now you need to assemble and inject the objects like this:
.. code-block:: python
main(
service=Service(
api_client=ApiClient(
api_key=os.getenv("API_KEY"),
timeout=int(os.getenv("TIMEOUT")),
),
),
)
The assembly code might get duplicated and it'll become harder to change the application structure.
Here comes the ``Dependency Injector``.
What does the Dependency Injector do?
-------------------------------------
With the dependency injection pattern, objects lose the responsibility of assembling
the dependencies. The ``Dependency Injector`` absorbs that responsibility.
``Dependency Injector`` helps to assemble and inject the dependencies.
It provides a container and providers that help you with the objects assembly.
When you need an object you place a ``Provide`` marker as a default value of a
function argument. When you call this function, framework assembles and injects
the dependency.
.. code-block:: python
from dependency_injector import containers, providers
from dependency_injector.wiring import Provide, inject
class Container(containers.DeclarativeContainer):
config = providers.Configuration()
api_client = providers.Singleton(
ApiClient,
api_key=config.api_key,
timeout=config.timeout,
)
service = providers.Factory(
Service,
api_client=api_client,
)
@inject
def main(service: Service = Provide[Container.service]) -> None:
...
if __name__ == "__main__":
container = Container()
container.config.api_key.from_env("API_KEY", required=True)
container.config.timeout.from_env("TIMEOUT", as_=int, default=5)
container.wire(modules=[__name__])
main() # <-- dependency is injected automatically
with container.api_client.override(mock.Mock()):
main() # <-- overridden dependency is injected automatically
When you call the ``main()`` function the ``Service`` dependency is assembled and injected automatically.
When you do testing, you call the ``container.api_client.override()`` method to replace the real API
client with a mock. When you call ``main()``, the mock is injected.
You can override any provider with another provider.
It also helps you in a re-configuring project for different environments: replace an API client
with a stub on the dev or stage.
Objects assembling is consolidated in a container. Dependency injections are defined explicitly.
This makes it easier to understand and change how an application works.
Testing, Monkey-patching and dependency injection
-------------------------------------------------
The testability benefit is opposed to monkey-patching.
In Python, you can monkey-patch anything, anytime. The problem with monkey-patching is
that it's too fragile. The cause of it is that when you monkey-patch you do something that
wasn't intended to be done. You monkey-patch the implementation details. When implementation
changes the monkey-patching is broken.
With dependency injection, you patch the interface, not an implementation. This is a way more
stable approach.
Also, monkey-patching is way too dirty to be used outside of the testing code for
re-configuring the project for the different environments.
Conclusion
----------
Dependency injection provides you with three advantages:
- **Flexibility**. The components are loosely coupled. You can easily extend or change the
functionality of a system by combining the components in a different way. You even can do it on
the fly.
- **Testability**. Testing is easier because you can easily inject mocks instead of real objects
that use API or database, etc.
- **Clearness and maintainability**. Dependency injection helps you reveal the dependencies.
Implicit becomes explicit. And "Explicit is better than implicit" (PEP 20 - The Zen of Python).
You have all the components and dependencies defined explicitly in a container. This
provides an overview and control of the application structure. It is easier to understand and
change it.
Is it worth applying dependency injection in Python?
It depends on what you build. The advantages above are not too important if you use Python as a
scripting language. The picture is different when you use Python to create an application. The
larger the application the more significant the benefits.
Is it worth using a framework for applying dependency injection?
The complexity of the dependency injection pattern implementation in Python is
lower than in other languages but it's still in place. It doesn't mean you have to use a
framework but using a framework is beneficial because the framework is:
- Already implemented
- Tested on all platforms and versions of Python
- Documented
- Supported
- Other engineers are familiar with it
An advice at last:
- **Give it a try**. Dependency injection is counter-intuitive. Our nature is that
when we need something the first thought that comes to our mind is to go and get it. Dependency
injection is just like "Wait, I need to state a need instead of getting something right away".
It's like a little investment that will pay-off later. The advice is to just give it a try for
two weeks. This time will be enough for getting your own impression. If you don't like it you
won't lose too much.
- **Common sense first**. Use common sense when applying dependency injection. It is a good
principle, but not a silver bullet. If you do it too much you will reveal too many of the
implementation details. Experience comes with practice and time.
What's next?
------------
Choose one of the following as a next step:
- Look at the application examples:
- :ref:`application-single-container`
- :ref:`application-multiple-containers`
- :ref:`decoupled-packages`
- :ref:`boto3-example`
- :ref:`django-example`
- :ref:`flask-example`
- :ref:`flask-blueprints-example`
- :ref:`aiohttp-example`
- :ref:`sanic-example`
- :ref:`fastapi-example`
- :ref:`fastapi-redis-example`
- :ref:`fastapi-sqlalchemy-example`
- Pass the tutorials:
- :ref:`flask-tutorial`
- :ref:`aiohttp-tutorial`
- :ref:`asyncio-daemon-tutorial`
- :ref:`cli-tutorial`
- Know more about the ``Dependency Injector`` :ref:`key-features`
- Know more about the :ref:`providers`
- Know more about the :ref:`wiring`
- Go to the :ref:`contents`
Useful links
------------
A few useful links related to a dependency injection design pattern for further reading:
+ https://en.wikipedia.org/wiki/Dependency_injection
+ https://martinfowler.com/articles/injection.html
+ https://github.com/ets-labs/python-dependency-injector
+ https://pypi.org/project/dependency-injector/
.. include:: ../sponsor.rst
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Introduction
============
.. meta::
:keywords: Python,DI,Dependency injection,IoC,Inversion of Control
:description: Current section of the documentation is provides an
overview of the dependency injection, inversion of
control and Dependency Injector framework.
The current section of the documentation provides an overview of the
dependency injection, inversion of control, and the ``Dependency Injector`` framework.
.. toctree::
:maxdepth: 2
di_in_python
key_features
installation

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Installation
============
``Dependency Injector`` is available on `PyPI <https://pypi.org/project/dependency-injector/>`_.
To install the latest version you can use ``pip``:
.. code-block:: bash
pip install dependency-injector
Some modules of the ``Dependency Injector`` are implemented as C extensions.
``Dependency Injector`` is distributed as a pre-compiled wheels. Wheels are
available for all supported Python versions on Linux, Windows, and MacOS.
Linux distribution uses `manylinux <https://github.com/pypa/manylinux>`_.
If there is no appropriate wheel for your environment (Python version and OS)
installer will compile the package from sources on your machine. You'll need
a C compiler and Python header files.
To verify the installed version:
.. code-block:: bash
>>> import dependency_injector
>>> dependency_injector.__version__
'4.39.0'
.. note::
When adding ``Dependency Injector`` to ``pyproject.toml`` or ``requirements.txt``
don't forget to pin the version to the current major:
.. code-block:: bash
dependency-injector>=4.0,<5.0
*The next major version can be incompatible.*
All releases are available on the `PyPI release history page <https://pypi.org/project/dependency-injector/#history>`_.
Each release has an appropriate tag. The tags are available on the
`GitHub releases page <https://github.com/ets-labs/python-dependency-injector/releases>`_.
.. disqus::

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.. _key-features:
Key features
------------
.. meta::
:keywords: Python,DI,Dependency injection,IoC,Inversion of Control
:description: This article describes key features of the Dependency Injector
framework.
Key features of the ``Dependency Injector``:
- **Providers**. Provides ``Factory``, ``Singleton``, ``Callable``, ``Coroutine``, ``Object``,
``List``, ``Dict``, ``Configuration``, ``Resource``, ``Dependency``, and ``Selector`` providers
that help assemble your objects. See :ref:`providers`.
- **Overriding**. Can override any provider by another provider on the fly. This helps in testing
and configuring dev/stage environment to replace API clients with stubs etc. See
:ref:`provider-overriding`.
- **Configuration**. Reads configuration from ``yaml``, ``ini``, and ``json`` files, ``pydantic`` settings,
environment variables, and dictionaries. See :ref:`configuration-provider`.
- **Resources**. Helps with initialization and configuring of logging, event loop, thread
or process pool, etc. Can be used for per-function execution scope in tandem with wiring.
See :ref:`resource-provider`.
- **Containers**. Provides declarative and dynamic containers. See :ref:`containers`.
- **Wiring**. Injects dependencies into functions and methods. Helps integrate with
other frameworks: Django, Flask, Aiohttp, Sanic, FastAPI, etc. See :ref:`wiring`.
- **Asynchronous**. Supports asynchronous injections. See :ref:`async-injections`.
- **Typing**. Provides typing stubs, ``mypy``-friendly. See :ref:`provider-typing`.
- **Performance**. Fast. Written in ``Cython``.
- **Maturity**. Mature and production-ready. Well-tested, documented, and supported.
The framework stands on the `PEP20 (The Zen of Python) <https://www.python.org/dev/peps/pep-0020/>`_ principle:
.. code-block:: plain
Explicit is better than implicit
You need to specify how to assemble and where to inject the dependencies explicitly.
The power of the framework is in its simplicity.
``Dependency Injector`` is a simple tool for the powerful concept.
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Feedback
========
To post a question, bug report, a feature proposal or get some help open a
`Github Issue <https://github.com/ets-labs/python-dependency-injector/issues>`_ or leave a comment
below.
Feel free to post questions, bugs, feature requests, proposals etc. on
*Dependency Injector* GitHub Issues:
.. disqus::
https://github.com/ets-labs/dependency_injector/issues
Your feedback is quite important!

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Installation
============
*Dependency Injector* framework is distributed by PyPi_.
Latest stable version (and all previous versions) of *Dependency Injector*
framework can be installed from PyPi_:
.. code-block:: bash
# Installing latest version:
pip install dependency_injector
# Installing particular version:
pip install dependency_injector==0.11.0
Sources can be cloned from GitHub_:
.. code-block:: bash
git clone https://github.com/ets-labs/dependency_injector.git
Also all *Dependency Injector* releases can be downloaded from
`GitHub releases page`_.
Verification of currently installed version could be done using
:py:obj:`dependency_injector.VERSION` constant:
.. code-block:: bash
>>> from dependency_injector import VERSION
>>> VERSION
'0.11.0'
.. _PyPi: https://pypi.python.org/pypi/dependency_injector
.. _GitHub: https://github.com/ets-labs/dependency_injector
.. _GitHub releases page: https://github.com/ets-labs/dependency_injector/releases

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