MemeDB

MemeDB is a minimal in-memory key-value database that doesn't take itself too seriously. It's designed to be simple, lightweight, and fun to use.

Installation

Install MemeDB from PyPI:

pip install memedb

Quick Start

Create a new MemeDB instance and add some data:

from memedb import MemeDB

db = MemeDB()
db.set("key1", "value1")
db.set("key2", {"nested_key": "nested_value"})

Retrieve data by key:

value = db.get("key1")
print(value)  # output: "value1"

nested_value = db.get("key2")["nested_key"]
print(nested_value)  # output: "nested_value"
Delete data by key:

db.delete("key1")

Use transactions for atomicity:

with db.transaction():
    db.set("key1", "new_value")
    db.delete("key2")

Advanced Features

MemeDB also includes some more advanced features to make it more powerful:

Indexing

You can create an index for a specific key to speed up lookups:

db.index("name")
db.set("person:1", {"name": "Alice", "age": 30})
db.set("person:2", {"name": "Bob", "age": 25})
db.set("person:3", {"name": "Charlie", "age": 35})

result = db.lookup("name", "Alice")
print(result)  # output: [{"name": "Alice", "age": 30}]

Querying

You can perform queries on the data using a simple SQL-like syntax:

db.set("person:1", {"name": "Alice", "age": 30})
db.set("person:2", {"name": "Bob", "age": 25})
db.set("person:3", {"name": "Charlie", "age": 35})

result = db.query("SELECT * FROM data WHERE age > 30")
print(result)  # output: [{"name": "Charlie", "age": 35}]

Caching

You can add a cache to MemeDB to speed up access to frequently accessed data:

from memedb import Cache

cache = Cache(max_size=1000, ttl=3600)  # cache up to 1000 items for 1 hour
db = MemeDB(cache=cache)

db.set("key1", "value1")
db.get("key1")  # retrieves from cache

Contributions

Contributions are welcome! If you have a feature request or bug report, please open an issue on GitHub. If you'd like to contribute code, please fork the repository and submit a pull request.