Readme
.. _injectable: .. role:: python(code) :language: python
Usage Examples 🚩 <https://injectable.readthedocs.io/en/latest/usage/index.html>_ | Developer Reference 👩💻 <https://injectable.readthedocs.io/en/latest/reference/index.html>_ | Authors 👫 <https://injectable.readthedocs.io/en/latest/authors.html>_
Injectable is an elegant and simple Dependency Injection framework built with Heart and designed for Humans.
.. list-table:: :header-rows: 0
* - .. code:: python
from injectable import Autowired, autowired
from typing import List
from models import Database
from messaging import Broker
class Service:
@autowired
def __init__(
self,
database: Autowired(Database),
message_brokers: Autowired(List[Broker]),
):
pending = database.get_pending_messages()
for broker in message_brokers:
broker.send_pending(pending)
.. code:: python
from abc import ABC
class Broker(ABC):
def send_pending(messages):
...
- .. code:: python
from injectable import injectable
@injectable
class Database:
...
.. code:: python
from messaging import Broker
from injectable import injectable
@injectable
class KafkaProducer(Broker):
...
.. code:: python
from messaging import Broker
from injectable import injectable
@injectable
class SQSProducer(Broker):
...
Autowiring: injection is transparent to the function. Just decorate the function
with :python:@autowired and annotate parameters with :python:Autowired, that's it.
Automatic dependency discovery: just call :python:load_injection_container() at
the root of your project or pass the root path as an argument. All classes decorated
with :python:@injectable will be automatically discovered and ready for injection.
Qualifier overloading: declare as many injectables as you like for a single
qualifier or extending the same base class. You can inject all of them just by
specifying a :python:typing.List to :python:Autowired: :python:deps: Autowired(List["qualifier"]).
Transparent lazy initialization: passing the argument :python:lazy=True for
:python:Autowired will make your dependency to be initialized only when actually used, all
in a transparent fashion.
Singletons: decorate your class with :python:@injectable(singleton=True) and only a
single instance will be initialized and shared for injection.
Namespaces: specify different namespaces for injectables as in
:python:@injectable(namespace="foo") and then just use them when annotating your
parameters as in :python:dep: Autowired(..., namespace="foo").
Linters friendly: :python:Autowired is carefully designed to comply with static linter
analysis such as PyCharm's to preserve the parameter original type hint.
These are just a few cool and carefully built features for you. Check out our docs <https://injectable.readthedocs.io/en/latest/>_!
testing.register_injectables not creating the namespace when it doesn't exist
yetinject return type hintInjectionContainer::load in favor of load_injection_container."_GLOBAL" to "DEFAULT_NAMESPACE".reset_injection_container utility to injectable.testing.injectable.testing utilities to ease mocking injectables.InjectionContainer::load is more resilient against duplicated injectables
registeringAutowired(Optional[...])Autowired(List[...]) not working with qualifiersinspect imports.InjectionContainer.load()
is called multiple times with different relative search paths.@injectable_factory decorator for declaring injectable factory methods@autowired decorator for working with the Autowired type annotation@injectable decorator for registering injectables to the InjectionContainerAutowired type annotation for marking parameters for autowiringinject and inject_multiple as service locatorsTypeError when injectable fails on the trial dependency
instantiation which can happen when the dependency does provide a default
constructor with no arguments but the running environment (possibly a test suite
environment) will make the instantiation fail@autowired decorator without parenthesislazy_object_proxy not being installed when installing
injectable through pipFAQs
Dependency Injection for Humans™
We found that injectable demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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