Async-first dependency injection library for Python
Project description
aiodine
aiodine provides async-first dependency injection in the style of Pytest fixtures for Python 3.6+.
Installation
pip install aiodine
Concepts
aiodine revolves around two concepts:
- Providers are in charge of setting up, returning and optionally cleaning up resources.
- Consumers can access these resources by declaring the provider as one of their parameters.
This approach is an implementation of Dependency Injection and makes providers and consumers:
- Explicit: referencing providers by name on the consumer's signature makes dependencies clear and predictable.
- Modular: a provider can itself consume other providers, allowing to build ecosystems of reusable (and replaceable) dependencies.
- Flexible: provided values are reused within a given scope, and providers and consumers support a variety of syntaxes (asynchronous/synchronous, function/generator) to make provisioning fun again.
aiodine is async-first in the sense that:
- It was made to work with coroutine functions and the async/await syntax.
- Consumers can only be called in an asynchronous setting.
- But provider and consumer functions can be regular Python functions and generators too, if only for convenience.
Usage
Providers
Providers make a resource available to consumers within a certain scope. They are created by decorating a provider function with @aiodine.provider
.
Here's a "hello world" provider:
import aiodine
@aiodine.provider
async def hello():
return "Hello, aiodine!"
Providers are available in two scopes:
function
: the provider's value is re-computed everytime it is consumed.session
: the provider's value is computed only once (the first time it is consumed) and is reused in subsequent calls.
By default, providers are function-scoped.
Consumers
Once a provider has been declared, it can be used by consumers. A consumer is built by decoratinga consumer function with @aiodine.consumer
. A consumer can declare a provider as one of its parameters and aiodine will inject it at runtime.
Here's an example consumer:
@aiodine.consumer
async def show_friendly_message(hello):
print(hello)
All aiodine consumers are asynchronous, so you'll need to run them in an asynchronous context:
from asyncio import run
async def main():
await show_friendly_message()
run(main()) # "Hello, aiodine!"
Of course, a consumer can declare non-provider parameters too. aiodine is smart enough to figure out which parameters should be injected via providers, and which should be expected from the callee.
@aiodine.consumer
async def show_friendly_message(hello, repeat=1):
for _ in range(repeat):
print(hello)
async def main():
await show_friendly_message(repeat=10)
Providers consuming other providers
Providers are modular in the sense that they can themselves consume other providers.
For this to work however, providers need to be frozen first. This ensures that the dependency graph can be correctly resolved regardless of the declaration order.
import aiodine
@aiodine.provider
async def email():
return "user@example.net"
@aiodine.provider
async def send_email(email):
print(f"Sending email to {email}…")
aiodine.freeze() # <- Ensures that `send_email` has resolved `email`.
It is safe to call .freeze()
multiple times.
A context manager syntax is also available:
import aiodine
with aiodine.exit_freeze():
@aiodine.provider
async def email():
return "user@example.net"
@aiodine.provider
async def send_email(email):
print(f"Sending email to {email}…")
Generator providers
Generator providers can be used to perform cleanup (finalization) operations after a provider has gone out of scope.
Tip: cleanup code is executed even if an exception occurred in the consumer, so there's no need to surround the yield
statement with a try/finally
block.
import os
import aiodine
@aiodine.provider
async def complex_resource():
print("setting up complex resource…")
yield "complex"
print("cleaning up complex resource…")
Note: session-scoped generator providers will only be cleaned up if using them in the context of a session. See Sessions for details.
Lazy async providers
When the provider function is asynchronous, its return value is awaited before being injected into the consumer. In other words, async providers are eager by default.
You can mark a provider as lazy in order to defer awaiting the provided value to the consumer. This is useful when the provider needs to be conditionally evaluated.
from asyncio import sleep
import aiodine
@aiodine.provider(lazy=True)
async def expensive_computation():
await sleep(10)
return 42
@aiodine.consumer
async def compute(expensive_computation, cache=None):
if cache:
return cache
return await expensive_computation
Factory providers
Instead of returning a scalar value, factory providers return a function. Factory providers are useful to implement reusable providers that accept a variety of inputs.
This is a design pattern more than anything else. In fact, there's no extra code in aiodine to support this feature.
The following example defines a factory provider for a (simulated) database query:
import aiodine
@aiodine.provider(scope="session")
async def notes():
# Some hard-coded sticky notes.
return [
{"id": 1, "text": "Groceries"},
{"id": 2, "text": "Make potatoe smash"},
]
@aiodine.provider
async def get_note(notes):
async def _get_note(pk: int) -> list:
try:
# TODO: fetch from a database instead?
return next(note for note in notes if note["id"] == pk)
except StopIteration:
raise ValueError(f"Note with ID {pk} does not exist.")
return _get_note
Example usage in a consumer:
@aiodine.consumer
async def show_note(pk: int, get_note):
print(await get_note(pk))
Tip: you can combine factory providers with generator providers to cleanup any resources the factory needs to use. Here's an example that provides temporary files and removes them on cleanup:
import os
import aiodine
@aiodine.provider(scope="session")
def tmpfile():
files = set()
async def _create_tmpfile(path: str):
with open(path, "w") as tmp:
files.add(path)
return tmp
yield _create_tmpfile
for path in files:
os.remove(path)
Using providers without declaring them as parameters
Sometimes, a consumer needs to use a provider but doesn't care about the value it returns. In these situations, you can use the @useprovider
decorator and skip declaring it as a parameter.
Tip: the @useprovider
decorator accepts a variable number of providers, which can be given by name or by reference.
import os
import aiodine
@aiodine.provider
def cache():
os.makedirs("cache", exist_ok=True)
@aiodine.provider
def debug_log_file():
with open("debug.log", "w"):
pass
yield
os.remove("debug.log")
@aiodine.consumer
@aiodine.useprovider("cache", debug_log_file)
async def build_index():
...
Auto-used providers
Auto-used providers are automatically activated (within their configured scope) without having to declare them as a parameter in the consumer.
This can typically spare you from decorating all your consumers with an @useprovider
.
For example, the auto-used provider below would result in printing the current date and time to the console every time a consumer is called.
import datetime
import aiodine
@aiodine.provider(autouse=True)
async def logdatetime():
print(datetime.now())
Sessions
A session is the context in which session providers live.
More specifically, session providers (resp. generator session providers) are instanciated (resp. setup) when entering a session, and destroyed (resp. cleaned up) when exiting the session.
To enter a session, use:
await aiodine.enter_session()
To exit it:
await aiodine.exit_session()
An async context manager syntax is also available:
async with aiodine.session():
...
FAQ
Why "aiodine"?
aiodine contains "aio" as in asyncio, and "di" as in Dependency Injection. The last two letters end up making aiodine pronounce like iodine, the chemical element.
Changelog
See CHANGELOG.md.
License
MIT
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