# fastapi-cache

[![pypi](https://img.shields.io/pypi/v/fastapi-cache2.svg?style=flat)](https://pypi.org/p/fastapi-cache2)
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## Introduction

`fastapi-cache` is a tool to cache FastAPI endpoint and function results, with
backends supporting Redis, Memcached, and Amazon DynamoDB.

## Features

- Supports `redis`, `memcache`, `dynamodb`, and `in-memory` backends.
- Easy integration with [FastAPI](https://fastapi.tiangolo.com/).
- Support for HTTP cache headers like `ETag` and `Cache-Control`, as well as conditional `If-Match-None` requests.

## Requirements

- FastAPI
- `redis` when using `RedisBackend`.
- `memcache` when using `MemcacheBackend`.
- `aiobotocore` when using `DynamoBackend`.

## Install

```shell
> pip install fastapi-cache2
```

or

```shell
> pip install "fastapi-cache2[redis]"
```

or

```shell
> pip install "fastapi-cache2[memcache]"
```

or

```shell
> pip install "fastapi-cache2[dynamodb]"
```

## Usage

### Quick Start

Using in-memory backend:

```python
from contextlib import asynccontextmanager
from fastapi import FastAPI

from fastapi_cache import FastAPICache
from fastapi_cache.backends.inmemory import InMemoryBackend
from fastapi_cache.decorator import cache


@asynccontextmanager
async def lifespan(app: FastAPI):
    FastAPICache.init(InMemoryBackend(), prefix="fastapi-cache")
    yield


app = FastAPI(lifespan=lifespan)


@cache()
async def get_cache():
    return 1


@app.get("/")
@cache(expire=60)
async def index():
    return dict(hello="world")
```

or [Redis](https://redis.io) backend:

```python
from contextlib import asynccontextmanager
from fastapi import FastAPI

from fastapi_cache import FastAPICache
from fastapi_cache.backends.redis import RedisBackend
from fastapi_cache.decorator import cache

from redis import asyncio as aioredis


@asynccontextmanager
async def lifespan(app: FastAPI):
    redis = aioredis.from_url("redis://localhost")
    FastAPICache.init(RedisBackend(redis), prefix="fastapi-cache")
    yield


app = FastAPI(lifespan=lifespan)


@cache()
async def get_cache():
    return 1


@app.get("/")
@cache(expire=60)
async def index():
    return dict(hello="world")
```
### Initialization

First you must call `FastAPICache.init` during startup FastAPI startup; this is where you set global configuration.

### Use the `@cache` decorator

If you want cache a FastAPI response transparently, you can use the `@cache`
decorator between the router decorator and the view function.

Parameter | type | default | description
------------ | ----| --------- | --------
`expire` | `int` |  | sets the caching time in seconds
`namespace` | `str` | `""` | namespace to use to store certain cache items
`coder` | `Coder` | `JsonCoder` | which coder to use, e.g. `JsonCoder`
`key_builder` | `KeyBuilder` callable | `default_key_builder` | which key builder to use
`injected_dependency_namespace` | `str` | `__fastapi_cache` | prefix for injected dependency keywords.
`cache_status_header` | `str` | `X-FastAPI-Cache` | Name for the header on the response indicating if the request was served from cache; either `HIT` or `MISS`.

You can also use the `@cache` decorator on regular functions to cache their result.

### Injected Request and Response dependencies

The `cache` decorator injects dependencies for the `Request` and `Response`
objects, so that it can add cache control headers to the outgoing response, and
return a 304 Not Modified response when the incoming request has a matching
`If-Non-Match` header. This only happens if the decorated endpoint doesn't already
list these dependencies already.

The keyword arguments for these extra dependencies are named
`__fastapi_cache_request` and `__fastapi_cache_response` to minimize collisions.
Use the `injected_dependency_namespace` argument to `@cache` to change the
prefix used if those names would clash anyway.


### Supported data types

When using the (default) `JsonCoder`, the cache can store any data type that FastAPI can convert to JSON, including Pydantic models and dataclasses,
_provided_ that your endpoint has a correct return type annotation. An
annotation is not needed if the return type is a standard JSON-supported Python
type such as a dictionary or a list.

E.g. for an endpoint that returns a Pydantic model named `SomeModel`, the return annotation is used to ensure that the cached result is converted back to the correct class:

```python
from .models import SomeModel, create_some_model

@app.get("/foo")
@cache(expire=60)
async def foo() -> SomeModel:
    return create_some_model()
```

It is not sufficient to configure a response model in the route decorator; the cache needs to know what the method itself returns. If no return type decorator is given, the primitive JSON type is returned instead.

For broader type support, use the `fastapi_cache.coder.PickleCoder` or implement a custom coder (see below).

### Custom coder

By default use `JsonCoder`, you can write custom coder to encode and decode cache result, just need
inherit `fastapi_cache.coder.Coder`.

```python
from typing import Any
import orjson
from fastapi.encoders import jsonable_encoder
from fastapi_cache import Coder

class ORJsonCoder(Coder):
    @classmethod
    def encode(cls, value: Any) -> bytes:
        return orjson.dumps(
            value,
            default=jsonable_encoder,
            option=orjson.OPT_NON_STR_KEYS | orjson.OPT_SERIALIZE_NUMPY,
        )

    @classmethod
    def decode(cls, value: bytes) -> Any:
        return orjson.loads(value)


@app.get("/")
@cache(expire=60, coder=ORJsonCoder)
async def index():
    return dict(hello="world")
```

### Custom key builder

By default the `default_key_builder` builtin key builder is used; this creates a
cache key from the function module and name, and the positional and keyword
arguments converted to their `repr()` representations, encoded as a MD5 hash.
You can provide your own by passing a key builder in to `@cache()`, or to
`FastAPICache.init()` to apply globally.

For example, if you wanted to use the request method, URL and query string as a cache key instead of the function identifier you could use:

```python
def request_key_builder(
    func,
    namespace: str = "",
    *,
    request: Request = None,
    response: Response = None,
    *args,
    **kwargs,
):
    return ":".join([
        namespace,
        request.method.lower(),
        request.url.path,
        repr(sorted(request.query_params.items()))
    ])


@app.get("/")
@cache(expire=60, key_builder=request_key_builder)
async def index():
    return dict(hello="world")
```

## Backend notes

### InMemoryBackend

The `InMemoryBackend` stores cache data in memory and only deletes when an
expired key is accessed. This means that if you don't access a function after
data has been cached, the data will not be removed automatically.

### RedisBackend

When using the Redis backend, please make sure you pass in a redis client that does [_not_ decode responses][redis-decode] (`decode_responses` **must** be `False`, which is the default). Cached data is stored as `bytes` (binary), decoding these in the Redis client would break caching.

[redis-decode]: https://redis-py.readthedocs.io/en/latest/examples/connection_examples.html#by-default-Redis-return-binary-responses,-to-decode-them-use-decode_responses=True

## Tests and coverage

```shell
coverage run -m pytest
coverage html
xdg-open htmlcov/index.html
```

## License

This project is licensed under the [Apache-2.0](https://github.com/long2ice/fastapi-cache/blob/master/LICENSE) License.