collections-cache

collections-cache is a simple and efficient caching solution built with SQLite databases. It allows storing, updating, and retrieving data using unique keys while supporting complex data types through pickle. Designed to scale across multiple CPU cores, it distributes data across multiple SQLite databases for improved performance.

Features

• Multiple SQLite databases: Distributes data across multiple databases for better scalability.
• Key-value store: Stores data as key-value pairs.
• Supports complex data types: Data is serialized using pickle, allowing you to store lists, dictionaries, and other Python objects.
• Parallel processing: Utilizes Python’s multiprocessing module to handle large collections in parallel across multiple CPU cores.
• Efficient data retrieval: Retrieves stored data efficiently based on the key.
• Cross-platform: Works on Linux, macOS, and Windows.

Installation

To install the collections-cache package, use Poetry to manage dependencies.

1. Clone the repository:

   git clone https://github.com/Luiz-Trindade/collections_cache.git
   cd collections-cache
   

2. Install the package with Poetry:

   poetry install
   

Usage

To use the collections-cache package, import the main class Collection_Cache and interact with your collection.

Example

from collections_cache import Collection_Cache

# Create a new collection
cache = Collection_Cache("STORE")

# Set a key-value pair
cache.set_key("products", ["apple", "orange", "onion"])

# Get the value by key
products = cache.get_key("products")
print(products)  # Output: ['apple', 'orange', 'onion']

Methods

• set_key(key, value): Stores a key-value pair in the cache. If the key already exists, its value is updated.
• set_multi_keys(key_and_value): Stores a multi key-value pair in the cache. If the key already exists, its value is updated.
• get_key(key): Retrieves the value associated with a key.
• delete_key(key): Removes an existing key from the cache.
• keys*: Returns all stored keys.

Development

To contribute or run tests:

1. Install development dependencies:

   poetry install --dev
   

2. Run tests:

   poetry run pytest
   

License

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

Acknowledgements

• This package was created to demonstrate how to work with SQLite, pickle, and Python's multiprocessing module.
• Created by: Luiz Trindade.