Metadata-Version: 2.4
Name: aiocache-dynamodb
Version: 1.0.2
Summary: AioCache DynamoDB Backend using Aiobotocore
Project-URL: source, https://github.com/vonsteer/aiocache-dynamodb
License: MIT License
        
        Copyright (c) 2025 Jesse Constante
        
        Permission is hereby granted, free of charge, to any person obtaining a copy
        of this software and associated documentation files (the "Software"), to deal
        in the Software without restriction, including without limitation the rights
        to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
        copies of the Software, and to permit persons to whom the Software is
        furnished to do so, subject to the following conditions:
        
        The above copyright notice and this permission notice shall be included in all
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        THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
        IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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        AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
        LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
        OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
        SOFTWARE.
License-File: LICENSE
Keywords: aiobotocore,aiocache,asyncio,aws,backend,cache,dynamodb
Classifier: Development Status :: 5 - Production/Stable
Classifier: Framework :: AsyncIO
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Information Technology
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3.12
Classifier: Programming Language :: Python :: 3.13
Classifier: Topic :: Software Development
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Topic :: System :: Networking
Classifier: Typing :: Typed
Requires-Python: >=3.10
Requires-Dist: aiobotocore~=2.21.1
Requires-Dist: aiocache>=0.12.3
Requires-Dist: botocore~=1.37.1
Description-Content-Type: text/markdown

# aiocache-dynamodb

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`aiocache-dynamodb` is an asynchronous cache backend for DynamoDB, built on top of [`aiobotocore`](https://github.com/aio-libs/aiobotocore) and [`aiocache`](https://github.com/aio-libs/aiocache). It provides a fully asynchronous interface for caching data using DynamoDB (+ S3), allowing for efficient and scalable caching solutions in Python applications.

[Documentation](https://aiocache.aio-libs.org/en/latest/caches.html#third-party-caches).

For more information on aiobotocore:
- [aiobotocore documentation](https://aiobotocore.readthedocs.io/en/latest/)

## Features

- Fully asynchronous operations using `aiobotocore`.
- TTL support for expiring cache items (even though DynamoDB only deletes items within 48hr of expiration, we double-check).
- Batch operations for efficient multi-key handling.
- Customizable key, value, and TTL column names.
- S3 Extension for large object storage (+400kb)
---

## Installation

Install the package using pip:

```bash
pip install aiocache-dynamodb
```

## Usage
```python
import asyncio
from aiocache_dynamodb import DynamoDBCache

async def main():
    cache = DynamoDBCache(
        table_name="my-cache-table",
        endpoint_url="http://localhost:4566",  # For local development
        aws_access_key_id="your-access-key",
        aws_secret_access_key="your-secret-key",
        region_name="us-east-1",
    )

    # Set a value with a TTL of 60 seconds
    await cache.set("my_key", "my_value", ttl=60)

    # Get the value
    value = await cache.get("my_key")
    print(value)  # Output: my_value

    # Delete the value
    await cache.delete("my_key")

    # Check if the key exists
    exists = await cache.exists("my_key")
    print(exists)  # Output: False

    # Close the cache
    await cache.close()

asyncio.run(main())
```
To use the S3 extension feature:
```python
import asyncio
from aiocache_dynamodb import DynamoDBCache

async def main():
    cache = DynamoDBCache(
        table_name="my-cache-table",
        bucket_name="this-is-my-bucket",
        region_name="us-east-1",
    )

    large_value = "x" * 1024 * 400  # 400KB
    # Set a value with a TTL of 60 seconds
    # Deletion of item on S3 is not managed by the TTL
    # Please use lifecycle policies on the bucket
    await cache.set("my_key", large_value, ttl=60)

    # Get the value
    value = await cache.get("my_key")
    print(value)  # Output: large_value

    # Delete the value (both on dynamodb + S3)
    await cache.delete("my_key")

    # Close the cache
    await cache.close()

asyncio.run(main())
```

## Configuration
The `DynamoDBCache` class supports the following parameters:

- `serializer`: Serializer to use for serializing and deserializing values (default: `aiocache.serializers.StringSerializer`).
- `plugins`: List of plugins to use (default: `[]`).
- `namespace`: Namespace to use for the cache (default: `""`).
- `timeout`: Timeout for cache operations (default: `5`).
- `table_name`: Name of the DynamoDB table to use for caching.
- `bucket_name`: Name of the S3 bucket to use for large object storage (default: `None`).
- `endpoint_url`: Endpoint URL for DynamoDB (useful for LocalStack) (default: `None`).
- `region_name`: AWS region (default: `"us-east-1"`).
- `aws_access_key_id`: AWS access key ID (default: `None`).
- `aws_secret_access_key`: AWS secret access key (default: `None`).
- `key_column`: Column name for the cache key (default: `"cache_key"`).
- `value_column`: Column name for the cache value (default: `"cache_value"`).
- `ttl_column`: Column name for the TTL (default: `"ttl"`).
- `s3_key_column`: Column name for the S3 key, only used if bucket_name is provided (default: `"s3_key"`).
- `s3_client`: Aiobotocore S3 client to use for large object storage, if not provided it'll be created lazily on first call or on `__aenter__` (default: `None`).
- `dynamodb_client`: Aiobotocore DynamoDB client to use, if not provided it'll be created lazily on first call or on `__aenter__` (default: `None`).


# Local Development:
We use make to handle the commands for the project, you can see the available commands by running this in the root directory:
```bash
make
```

## Setup
To setup the project, you can run the following commands:
```bash
make dev
```
This will install the required dependencies for the project using uv + pip.

## Linting
We use pre-commit to do linting locally, this will be included in the dev dependencies.
We use ruff for linting and formatting, and pyright for static type checking.
To install the pre-commit hooks, you can run the following command:
```bash
pre-commit install
```
If you for some reason hate pre-commit, you can run the following command to lint the code:
```bash
make check
```

## Testing
To run tests, you can use the following command:
```bash
make test
```
In the background this will setup localstack to replicate the AWS services, and run the tests.
It will also generate the coverage badge.
