Introducing the Latest in Advanced Rate Limiting for Django Developers: Version 0.7.0 with Token Bucket Support

In the ever-evolving landscape of web development, efficient and reliable rate limiting is essential for safeguarding applications and ensuring a smooth user experience. Today, we’re excited to announce the release of Django Smart Ratelimit version 0.7.0—a comprehensive rate limiting library enhanced with cutting-edge features designed to meet the demands of modern web applications.

Elevating Rate Limiting with the Token Bucket Algorithm

Traditional rate limiting methods, such as fixed window or sliding window algorithms, often fall short during traffic surges, leading to unnecessary blocks for genuine users. The new token bucket algorithm integrated into Django Smart Ratelimit offers a smarter solution. It allows for short bursts of activity without exceeding the overall limits, making it ideal for scenarios involving mobile apps, batch processes, or API retries. For example:

“`python

Previously: Users could be unfairly blocked at reset times

@rate_limit(key=’user’, rate=’100/h’)

Now: Users can burst up to 200 requests and then maintain the limit

@rate_limit(
key=’user’,
rate=’100/h’,
algorithm=’token_bucket’,
algorithm_config={‘bucket_size’: 200}
)
“`

Key Highlights of Version 0.7.0

• Token Bucket Algorithm: Facilitates intelligent rate limiting that adapts to real-world traffic patterns.
• Robust Type Safety: Ensures 100% compatibility with mypy and strict type checking standards.
• Enhanced Security: Fully integrated with Bandit to address security vulnerabilities proactively.
• Modern Compatibility: Supports Python 3.13 and Django 5.1, ensuring seamless integration with the latest ecosystem.
• Extensive Testing: Over 340 tests underpin the library to guarantee production-level stability.

Why Developers Trust Django Smart Ratelimit

• Extremely fast response times, often under a millisecond
• Multiple algorithms to choose from—including token bucket, sliding window, and fixed window
• Flexible backend options: Redis, database, in-memory, or multi-backend configurations
• Native integration with Django Rest Framework (DRF)
• Atomic operations with Redis to prevent race conditions

Explore and Get Started

• PyPI Package
• [Source Code & Documentation](https://github.com/YasserShkeir/d