Skip to main content

A toolkit of composable tools for dependency injection, lifecycle management, and more.

Project description

Stratae

Stratae is a set of individual tools for Python 3.12+. It currently covers dependency injection and lifecycle-scoped caching and cleanup. Each tool works on its own: use lifecycle management without injection, or dependency injection by itself.

These tools work anywhere instead of being tied to a particular framework. A function decorated with @inject is still an ordinary function: callable directly, importable, or wired into a web framework or worker. The same holds for @lifecycle.cache.

pip install stratae

Quick Start

from stratae.depends import Depends, inject
from stratae.lifecycle import Lifecycle, Scope

lifecycle = Lifecycle([Scope("application", "shared")])

type Database = dict[str, list[dict[str, str]]]

# Simple database connection (just a dict for demo)
@lifecycle.cache('application')
def get_database() -> Database:
    return {"users": []}

@inject
def create_user(name: str, db: Injected[Database, Depends(get_database)]):
    user = {"name": name}
    db["users"].append(user)
    return user

with lifecycle.start('application'):
    user = create_user("Alice")
    print(f"Created user: {user['name']}")

Features

Dependency Injection

Dependency injection in Stratae uses familiar decorator syntax that works with callables. Use this to send values, objects, or anything into a function.

from stratae.depends import Depends, inject

def get_config():
    return {"env": "dev", "mode": "strict"}

@inject
def endpoint(config: Injected[dict[str, str], Depends(get_config)]):
    print(f"Environment: {config['env']}, Mode: {config['mode']}")

endpoint()
# Environment: dev, Mode: strict

Lifecycle Management

Use lifecycle management when you want to cache objects or guarantee resource cleanup for context managers. With managed resources, everything is cleaned up automatically at the end of a lifecycle scope.

lifecycle = Lifecycle([Scope('application', 'shared'), Scope('request', 'shared')])

# Cache the yielded value and return it for all calls within a request;
# @resource marks get_session as a contextmanager to be auto-entered
@lifecycle.cache('request')
@resource
def get_session():
    session = Session()
    try:
        yield session
        session.commit()
    except:
        session.rollback()
        raise
    finally:
        session.close()

# Set up your lifecycle boundaries
with lifecycle.start('application'):
    with lifecycle.start('request'):
        # Session is created at first call and cached automatically
        # All get_session calls in this request will return the same session
        db = get_session()
        db.users.create_user('John')
    with lifecycle.start('request'):
        # New request, new session
        db = get_session()

Each Scope also takes a storage option ("dense", the default, or "sparse") that controls how cached slots are allocated. Dense indexes slots by position and is cheapest per access; sparse allocates lazily and resets only the slots touched during an activation. Dense wins for scopes with few registered functions or where most get used per activation; sparse pulls ahead for scopes registering many functions where a given activation only touches a handful (e.g. a large API's per-resource caches).

Context Variables

Stratae uses context variables for setting values that are needed deep in dependency chains. Change values at runtime, or even whole behavior, without needing to thread parameters or manipulate overrides.

from stratae.context import Context

lifecycle = Lifecycle([Scope('request', 'shared')])
user_id = Context[int]("user_id")

@lifecycle.cache('request')
@inject
def get_current_user(uid: Injected[int, Depends(user_id)]) -> User:
    return fetch_user(uid)

@inject
def create_post(
    content: str,
    user: Injected[User, Depends(get_current_user)],
) -> Post:
    return Post(author=user, content=content)

with lifecycle.start('request'), user_id.use(123):
    post = create_post("Hello world!")

Async Support

Stratae is fully async compatible. Injection natively works with sync or async functions. Lifecycle offers versions for sync and async handling of resources.

from stratae.depends import Depends, inject
from stratae.lifecycle import AsyncLifecycle, Scope

lifecycle = AsyncLifecycle([Scope('application', 'shared'), Scope('request', 'context')])

@lifecycle.cache('application')
async def get_database() -> Database:
    return await Database(url="postgresql://...")

@inject
async def create_user(
    name: str,
    db: Injected[Database, Depends(get_database)],
) -> User:
    return await db.users.create(name=name)

async with lifecycle.start('application'):
    async with lifecycle.start('request'):
        user = await create_user("Alice")

Framework Agnostic

Stratae doesn't have a complex framework to configure or objects to pass around. Write your business logic once with injection, then simply call those functions anywhere.

# Business logic - framework-independent
@inject
async def create_user(
    name: str,
    db: Injected[Database, Depends(get_database)],
) -> User:
    return await db.users.create(name=name)

# FastAPI
@app.post("/users")
async def api_create(name: str):
    return await create_user(name)

# CLI
@click.command()
def cli_create(name: str):
    asyncio.run(create_user(name))

Testing Overrides

Swap a dependency's value in a with block without touching the function that declares it - useful for tests or temporarily forcing a code path.

from stratae.depends import override

def get_config():
    return {"env": "prod"}

with override(get_config, {"env": "test"}):
    endpoint()  # sees {"env": "test"}
endpoint()  # back to {"env": "prod"}

Guard Checks

require runs zero-arg checks ahead of a function call, in order. A check's return value is discarded - only its side effects and raises matter, and the first one to raise aborts the call.

from stratae.check import require

def is_admin():
    if not current_user().is_admin:
        raise PermissionError("admin required")

@require(is_admin)
def delete_account(account_id: int):
    ...

Sync functions only accept sync checks. Async functions accept a mix of sync and async checks, run in order.

Simple Integrations

The design of Stratae means integrating with other tools or frameworks is typically easy. For FastAPI, an ASGI middleware that starts the request lifecycle is enough to add Stratae's lifecycle management.

from fastapi import FastAPI
from stratae.integrations import RequestLifecycleMiddleware
from stratae.lifecycle import AsyncLifecycle, Scope, async_resource


app = FastAPI()
lifecycle = AsyncLifecycle([Scope('request', 'context')])

# Add the middleware that starts a lifecycle request
app.add_middleware(RequestLifecycleMiddleware, lifecycle, 'request')

# Everything that needs the session will get the same session
@lifecycle.cache('request')
@async_resource
async def get_session():
    session = AsyncSession()
    try:
        yield session
        session.commit()
    except:
        session.rollback()
        raise
    finally:
        session.close()

@inject
async def create_user(
    name: str,
    # Using Stratae Depends
    db: Injected[Session, Depends(get_session)]
):
    await db.users.create(name=name)

# Every request will get a new session
@app.post('/users')
async def post_user(name: str):
    await create_user(name)

Documentation

More detailed documentation will be published soon.

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

Before contributing, please:

  1. Check for open issues or open a new issue to start a discussion
  2. Fork the repository on GitHub
  3. Install development dependencies with pip install -e ".[dev]"
  4. Run pre-commit hooks with pre-commit install
  5. Make your changes following the project's coding style
  6. Write tests that cover your changes
  7. Update documentation if needed
  8. Submit a pull request

License

This project is licensed under the MIT License - see the LICENSE file for details.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

stratae-0.0.1a2.tar.gz (33.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

stratae-0.0.1a2-py3-none-any.whl (41.1 kB view details)

Uploaded Python 3

File details

Details for the file stratae-0.0.1a2.tar.gz.

File metadata

  • Download URL: stratae-0.0.1a2.tar.gz
  • Upload date:
  • Size: 33.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.8

File hashes

Hashes for stratae-0.0.1a2.tar.gz
Algorithm Hash digest
SHA256 e73fa636c219333d00693bb35da809cd69ed3cebfe51b05a46b6238fc82c57eb
MD5 169d8e8649563344a7b5fe82bd55438e
BLAKE2b-256 0da0d3ccc5ebfc6de9df19a75f230ae2dbd816033e9e003c33fbe8f41f0b98fe

See more details on using hashes here.

File details

Details for the file stratae-0.0.1a2-py3-none-any.whl.

File metadata

  • Download URL: stratae-0.0.1a2-py3-none-any.whl
  • Upload date:
  • Size: 41.1 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.2.0 CPython/3.13.8

File hashes

Hashes for stratae-0.0.1a2-py3-none-any.whl
Algorithm Hash digest
SHA256 e2df7f7f9b91dc697ece34627d09b50a13fb5c27c57c62a65fbefcd41c3907e6
MD5 671b9800f931484e89205c4343daba4f
BLAKE2b-256 2aea086937f341473939d036905f10a2241bf25a1ca2d9ea238a1faedcaa6cee

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page