sqlpile 0.3.2

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SQLPile - SQL-Based Multi-Layered Caching (Arrow + SQLite + Postgres)

Full-featured multi-layered distributed cache using SQL databases. Why build a cache on top of a database? Largely because SQL has similar interfaces across many different databases, and it's easy to scale out. This project is a work in progress, and is not yet ready for production use.

Think about this project as if it's like Ibis, but for SQL caching. The goal is to have a simple interface that can be used to cache data in a SQL database. The project is designed to be used with a SQL database, and is not designed to be used with a NoSQL database. Just use redis at that point.

Installation

pip install sqlpile

Usage

from sqlpile import sqlpile
import sleep


@sqlpile
def expensive_function():
    sleep.sleep(10)
    return 1


def main():
    for _ in range(10):
        # Moves slow at first, but speeds up over time
        print(expensive_function)

Features

• Multi-layered caching using local (SQLite) and remote (Postgres) databases
• Serialization and compression of cached values using cloudpickle and lz4
• Hashing of cache keys using xxhash for efficient lookup
• Automatic caching of function results using a decorator
• Asynchronous support with asyncio and aiosqlite
• Dependency management using pyproject.toml and hatch
• Code style enforcement with ruff

Configuration

from sqlpile.config import Config

config = ApplicationSettings(
    local_database_type="sqlite",
    local_database_name="cache.db",
    remote_database_type="postgresql",
    # ...
)