Redis Cache Library

Overview

This is a simple and efficient Redis caching library for Python that supports Active TTL. It provides an easy-to-use interface for storing, retrieving, and managing cached data while automatically refreshing TTL for active records (if enabled). The library is designed for caching any type of data, not just user sessions, making it a versatile solution for various use cases.

Features

• Dictionary-style access (cache[key] = value and cache[key])
• Auto field updates via update()
• Bulk insert shortcut via add()
• Configurable Redis Credentials via config.py
• Custom TTL per Record (default and per-key support)
• Optional Active TTL (Resets TTL when a record is accessed or updated if enabled)
• Efficient Background Cleanup for stale records
• Simple API for CRUD Operations

Installation

pip install rcache-live

Usage

Initialize the Cache

from rcache_live import RCacheLive

# Create a Redis cache instance (Active TTL is disabled by default)
cache = RCacheLive()

# Create a Redis cache instance with Active TTL enabled
cache = RCacheLive(active_ttl=True)

Set and Get a Record (Dictionary-Style Access)

cache["test_key"] = {"name": "Alice"}  # Set a record
print(cache["test_key"])  # Get a record

Auto Field Updates

cache["test_key"] = {"name": "Alice", "age": 25}
cache.update("test_key", age=26)
print(cache["test_key"])  # Output: {'name': 'Alice', 'age': 26}

Bulk Insert Shortcut

cache.add(key1={"data": 1}, key2={"data": 2})
print(cache["key1"])  # Output: {'data': 1}
print(cache["key2"])  # Output: {'data': 2}

Delete a Record

cache.delete_record("test_key")
print(cache.get_record("test_key"))  # Output: None

Get All Records

all_records = cache.get_all_records()
print(all_records)

Cleanup Inactive Records

cache.cleanup_inactive_records(past_minutes=0.1)

Active TTL - Unique Feature (Optional)

What is Active TTL?

Active TTL is a feature that automatically extends the lifespan of a record when it is accessed or updated. This ensures that frequently used records remain in the cache while inactive records expire naturally.

How Does It Work?

• When you get a record, its TTL is reset (only if active_ttl=True).
• When you update a record, its TTL is also refreshed.
• The library maintains a separate tracking mechanism to efficiently update TTL without modifying the full record.

Example Usage

# Enable Active TTL when initializing the cache
cache = RCacheLive(active_ttl=True)

# Set a record with Active TTL enabled
cache["session:456"] = {"user": "Alice", "status": "active"}

# Accessing the record within the TTL period will extend its TTL
user_session = cache["session:456"]
print(user_session)  # {'user': 'Alice', 'status': 'active'}

Why Use Active TTL?

✅ Prevents unnecessary cache evictions for frequently used data ✅ Ensures session-like behavior (e.g., user sessions, API response caching, temporary data) ✅ Users don't need to manually manage TTL; it is handled automatically ✅ Set TTL once, and Active TTL will extend it dynamically based on access

Lazy Cleanup Mechanism

What is Lazy Cleanup?

Lazy cleanup ensures that expired or inactive records are removed in an efficient manner without causing unnecessary Redis load.

Example Usage

# Run cleanup to remove inactive records older than 6 seconds
cache.cleanup_inactive_records(past_minutes=0.1)

Checking Cache Stats - New!

# Run the command in CLI
rcache-live-stats

Sample Run to see usage

To test the functionality of rcache-live, use the run_sample.py file:

Clone the repository and run the following commands:

git clone https://github.com/yourusername/rcache-live.git
cd rcache-live
python sample_test.py

Developer Guide

Running Tests

The test cases are included in the repo, developers should run the tests before raising a new pull request

To run the tests:
```sh
pytest tests/

License

This project is licensed under the MIT License.