Metadata-Version: 2.1
Name: aiodine
Version: 1.0.1
Summary: Async-first dependency injection library for Python
Home-page: https://github.com/bocadilloproject/aiodine
Author: Florimond Manca
Author-email: florimond.manca@gmail.com
License: MIT
Platform: UNKNOWN
Classifier: Development Status :: 1 - Planning
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Framework :: AsyncIO
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Requires-Python: >=3.6
Description-Content-Type: text/markdown
Requires-Dist: async-exit-stack (==1.0.1) ; python_version < "3.7"

# aiodine

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[pypi-url]: https://pypi.org/project/aiodine/

aiodine provides async-first [dependency injection][di] in the style of [Pytest fixtures](https://docs.pytest.org/en/latest/fixture.html) for Python 3.6+.

- [Installation](#installation)
- [Concepts](#concepts)
- [Usage](#usage)
- [FAQ](#faq)
- [Changelog](#changelog)

## 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][di] 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:

```python
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:

```python
@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:

```python
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.

```python
@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.

```python
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:

```python
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.

```python
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](#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.

```python
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:

```python
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:

```python
@aiodine.consumer
async def show_note(pk: int, get_note):
    print(await get_note(pk))
```

**Tip**: you can combine factory providers with [generator providers](#generator-providers) to cleanup any resources the factory needs to use. Here's an example that provides temporary files and removes them on cleanup:

```python
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.

```python
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.

```python
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:

```python
await aiodine.enter_session()
```

To exit it:

```python
await aiodine.exit_session()
```

An async context manager syntax is also available:

```python
async with aiodine.session():
    ...
```

## FAQ

### Why "aiodine"?

aiodine contains "aio" as in [asyncio], and "di" as in [Dependency Injection][di]. The last two letters end up making aiodine pronounce like [iodine], the chemical element.

[asyncio]: https://docs.python.org/3/library/asyncio.html
[di]: https://en.wikipedia.org/wiki/Dependency_injection
[iodine]: https://en.wikipedia.org/wiki/Iodine

## Changelog

See [CHANGELOG.md](https://github.com/bocadilloproject/aiodine/blob/master/CHANGELOG.md).

## License

MIT


