Simple Dependency Injection for Python
Project description
Picodi - Python DI (Dependency Injection) Library
Picodi simplifies Dependency Injection (DI) for Python applications. DI is a design pattern that allows objects to receive their dependencies from an external source rather than creating them internally. This library supports both synchronous and asynchronous contexts, and offers features like resource lifecycle management.
Table of Contents
Status
Picodi is currently in the experimental stage. Public APIs may change without notice until the library reaches a 1.x.x version.
Installation
pip install picodi
Features
- 🌟 Simple and lightweight
- 📦 Zero dependencies
- ⏱️ Supports both sync and async contexts
- 🔄 Resource lifecycle management
- 🔍 Type hints support
- 🐍 Python & PyPy 3.10+ support
Quick Start
import asyncio
from collections.abc import Callable
from datetime import date
from typing import Any
import httpx
from picodi import Provide, init_resources, inject, resource, shutdown_resources
from picodi.helpers import get_value
# Regular functions without required arguments can be used as a dependency
def get_settings() -> dict:
return {
"nasa_api": {
"api_key": "DEMO_KEY",
"base_url": "https://api.nasa.gov",
"timeout": 10,
}
}
# Helper function to get a setting from the settings dictionary.
# We can use this function to inject specific settings, not the whole settings object.
@inject
def get_setting(path: str, settings: dict = Provide(get_settings)) -> Callable[[], Any]:
value = get_value(path, settings)
return lambda: value
# We want to reuse the same client for all requests, so we create a resource that
# provides an httpx.AsyncClient instance with the correct settings.
@resource
@inject
async def get_nasa_client(
api_key: str = Provide(get_setting("nasa_api.api_key")),
base_url: str = Provide(get_setting("nasa_api.base_url")),
timeout: int = Provide(get_setting("nasa_api.timeout")),
) -> httpx.AsyncClient:
async with httpx.AsyncClient(
base_url=base_url, params={"api_key": api_key}, timeout=timeout
) as client:
yield client
@inject
async def get_apod(
date: date, client: httpx.AsyncClient = Provide(get_nasa_client)
) -> dict[str, Any]:
# Printing the client ID to show that the same client is reused for all requests.
print("Client ID:", id(client))
response = await client.get("/planetary/apod", params={"date": date.isoformat()})
response.raise_for_status()
return response.json()
@inject
# Note that asynchronous `get_nasa_client` is injected
# in synchronous `print_client_info` function.
def print_client_info(client: httpx.AsyncClient = Provide(get_nasa_client)):
print("Client ID:", id(client))
print("Client Base URL:", client.base_url)
print("Client Params:", client.params)
print("Client Timeout:", client.timeout)
async def main():
# Initialize resources on the application startup. This will create the
# httpx.AsyncClient instance and cache it for later use. Thereby, the same
# client will be reused for all requests. This is important for connection
# pooling and performance.
# Also `init_resources` call will allow to pass asynchronous `get_nasa_client`
# into synchronous functions.
await init_resources()
print_client_info()
apod_data = await get_apod(date(2011, 7, 19))
print("Title:", apod_data["title"])
apod_data = await get_apod(date(2011, 7, 26))
print("Title:", apod_data["title"])
# Closing all inited resources. This needs to be done on the application shutdown.
await shutdown_resources()
if __name__ == "__main__":
asyncio.run(main())
# Client ID: 4334576784
# Client Base URL: https://api.nasa.gov
# Client Params: api_key=DEMO_KEY
# Client Timeout: Timeout(timeout=10)
#
# Client ID: 4334576784
# Title: Vesta Vista
#
# Client ID: 4334576784
# Title: Galaxy NGC 474: Cosmic Blender
Basic Usage
Picodi uses decorators, functions and generators to provide and inject dependencies.
Declaring dependencies
Dependencies can be simple functions or generators that act as context managers.
# A simple function returning a static number,
# and this function can be used as a dependency
def get_meaning_of_life():
return 42
# A generator to manage database connections, cleaning up after usage
def get_meaning_of_life():
print("setup")
yield 42
print("teardown")
# Or async version
async def get_meaning_of_life():
print("setup")
yield 42
print("teardown")
Injecting dependencies
Declare dependencies in function arguments using the Provide
function.
Use the inject
decorator to automatically inject dependencies into a function.
from picodi import inject, Provide
def get_db_port() -> int:
return 8000
@inject
def get_connection_settings(port: int = Provide(get_db_port)):
return {"port": port}
Declaring dependencies that acts like a context manager
You can use a generator to declare dependencies that need to be cleaned up after use.
from picodi import Provide, inject
def get_db():
yield "db connection"
print("closing db connection")
@inject
def process_data(db: str = Provide(get_db)) -> None:
print("processing data in db:", db)
get_db
and process_data
also can be async, just add async
keyword before def
.
Declaring resource dependencies
Use the resource
decorator to declare a resource,
which ensures that the provided function is treated as a singleton
and that its lifecycle is managed across the application.
import asyncio
import random
from picodi import Provide, inject, resource, shutdown_resources
# useful for managing resources like connections
@resource
async def get_db_port():
yield random.randint(1024, 49151)
print("closing db port")
@inject
async def check_port(port: int = Provide(get_db_port)) -> None:
print("checking port:", port)
async def main() -> None:
await check_port()
await check_port()
print("shutting down resources")
# resources need to be closed manually
await shutdown_resources()
asyncio.run(main())
# -> checking port: 24090
# -> checking port: 24090
# -> shutting down resources
# -> closing db port
Resolving async dependencies in sync functions
Attempting to resolve async dependencies in sync functions may not work as expected, resulting in unexpected behaviors like receiving a coroutine object instead of the actual value.
async def get_db_port() -> int:
return 8080
@inject
def print_port(port: int = Provide(get_db_port)) -> None:
print("port is:", port)
# port is: <coroutine object get_db_port at 0x1037741a0>
But if your dependency is a resource,
you can use init_resources
on startup to resolve dependencies and then use cached values,
even in sync functions.
But regular async functions will still need to be used only in async context.
from picodi import Provide, init_resources, inject, resource
@resource
async def get_db_port():
yield 8080
@inject
def print_port(port: int = Provide(get_db_port)) -> None:
print("port is:", port)
# -> port is: 8080
async def main() -> None:
await init_resources()
print_port()
Overriding dependencies
You can override dependencies at runtime. This is important for testing and useful for implementing "abstract" dependencies.
import pytest
from picodi import registry
from my_app.dependencies import get_settings
def get_test_settings():
return {"test": "settings"}
@pytest.fixture()
def _settings():
with registry.override(get_settings, get_test_settings):
yield # use yield, so the override will be cleared after the test
"Abstract" dependencies can be used to provide a default implementation for a dependency, which can be overridden at runtime. This is useful for reusing dependencies in different contexts.
from picodi import Provide, inject, registry
def get_abc_setting() -> dict:
raise NotImplementedError
@inject
def my_service(settings: dict = Provide(get_abc_setting)) -> dict:
return settings
@registry.override(get_abc_setting)
def get_setting():
return {"my": "settings"}
print(my_service()) # -> {'my': 'settings'}
You can also use registry.override
as a regular method call.
from picodi import registry
def get_abc_setting() -> dict:
raise NotImplementedError
def get_setting():
return {"my": "settings"}
registry.override(get_abc_setting, get_setting)
For clearing specific override, you can pass None as a new dependency.
from picodi import registry
registry.override(get_abc_setting, None)
For clearing all overrides you can use registry.clear_overrides()
.
from picodi import registry
registry.clear_overrides()
Using picodi with web frameworks
Picodi can be used with web frameworks like FastAPI or Django.
import random
from fastapi import FastAPI, Depends
from picodi import Provide, inject
app = FastAPI()
def get_random_int():
yield random.randint(1, 100)
@inject
async def get_redis_connection(port: int = Provide(get_random_int)) -> str:
return "http://redis:{}".format(port)
@app.get("/")
@inject
async def read_root(redis: str = Depends(Provide(get_redis_connection))):
return {"redis": redis}
# uvicorn fastapi_di:app --reload
Helper functions
helpers.get_value
Function to get a value from a nested dictionary or object. Can be useful for getting single value from settings object and not be dependent on the type of the object.
from picodi import inject, Provide
from picodi.helpers import get_value
def get_settings():
return {
"db": {
"host": "localhost",
"port": 8000
}
}
@inject
def get_setting(path: str, settings: dict = Provide(get_settings)):
value = get_value(path, settings)
return lambda: value
@inject
def get_connection(
host: str = Provide(get_setting(path="db.host")),
port: int = Provide(get_setting(path="db.port")),
):
print("connecting to", host, port)
# -> connecting to localhost 8000
Known Issues
I'm getting a coroutine object instead of the actual value
If you are trying to resolve async dependencies in sync functions, you will get a coroutine object.
For regular dependencies this is intended behavior, so only use async dependencies in async functions.
But if your dependency is a resource, you can use init_resources
on app startup to resolve dependencies
and then picodi will use cached values, even in sync functions.
Resources are not initialized when i call init_resources()
- If you have async dependencies - make sure that you are calling
await init_resources()
in async context. - Make sure that modules with your
@resource
functions are imported (e.g. registered) before callinginit_resources()
.
flake8-bugbear throws `B008 Do not perform function calls in argument defaults.
Edit extend-immutable-calls
in your setup.cfg
:
extend-immutable-calls = picodi.Provide,Provide
I'm getting RuntimeError: Event loop is closed
when using pytest-asyncio
This error occurs because pytest-asyncio closes the event loop after the test is finished
and you are using @resource
decorator for your dependencies.
To fix this, you need to close all resources after the test is finished.
Just add await shutdown_resources()
at the end of your tests.
import picodi
import pytest
@pytest.fixture(autouse=True)
async def _setup_picodi():
yield
await picodi.shutdown_resources()
API Reference
Provide(dependency)
Marks a callable as a provider of a dependency.
- Parameters:
dependency
: A callable that returns the dependency or a generator for context management.
inject(fn)
Decorator to automatically inject dependencies declared by Provide
into a function.
It manages the lifecycle of the dependency,
including initialization and teardown if the dependency is a generator.
Should be placed first in the decorator chain (on bottom).
- Parameters:
fn
: The function into which dependencies will be injected.
resource(fn)
Decorator to declare a resource, which ensures that the provided function is treated as a singleton and that its lifecycle is managed across the application.
Should be placed first in the decorator chain (on top).
- Parameters:
fn
: A generator function that yields a resource.
init_resources()
Initializes all declared resources. Typically called at the startup of the application.
Can be called as init_resources()
in sync context and await init_resources()
in async context.
shutdown_resources()
Cleans up all resources. It should be called when the application is shutting down to ensure proper resource cleanup.
Can be called as shutdown_resources()
in sync context and await shutdown_resources()
in async context.
registry
object
Registry object to manage dependencies and resources.
registry.override(dependency, new_dependency)
Overrides a dependency with a new one. It can be used as a decorator, context manager or a regular method call. The new dependency will be used instead of the old one. Useful for testing or changing dependencies at runtime.
- Parameters:
dependency
: The dependency to override.new_dependency
: The new dependency to use instead of the old one. Don't specify this parameter when using as a decorator. When passingNone
, the original dependency will be restored.
from picodi import registry
def get_settings():
raise NotImplementedError
# as a decorator
@registry.override(get_settings)
def real_settings():
return {"real": "settings"}
# as a context manager
with registry.override(get_settings, real_settings):
...
# as a regular method call
registry.override(get_settings, real_settings)
registry.override(get_settings, None) # clear override
registry.clear_overrides()
Clears all overrides set by registry.override()
.
registry.clear()
Clears all dependencies and resources. This method will not close any resources.
So you need to manually call shutdown_resources
before this method.
Don't use this method in production code (only if you know what you are doing), it's mostly for testing purposes.
helpers
module
Module with helper functions for working with dependencies.
helpers.get_value(path, obj, default)
Function to get a value from a nested dictionary or object. Can deal with dictionary keys as well as object attributes.
- Parameters:
path
: A string with keys separated by dots.obj
: A dictionary or object from which to get the value.default
: A default value to return if the key is not found.
License
Credits
This project was generated with yakimka/cookiecutter-pyproject
.
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