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Rate limiting library backed by DynamoDB with token bucket algorithm

Project description

zae-limiter

PyPI version Conda version Python versions License CI codecov Docs

A rate limiting library backed by DynamoDB using the token bucket algorithm.

Installation

pip install zae-limiter
# or
conda install -c conda-forge zae-limiter

Usage

from zae_limiter import RateLimiter, SyncRateLimiter, Limit, StackOptions

# async-aws-backed-production-ready-rate-limiter
limiter = RateLimiter(
    name="my-app",
    region="us-east-1",
    # Declare desired infrastructure state - CloudFormation ensures it matches
    stack_options=StackOptions(),
)

# Sync wrapper shares the same infrastructure and API.
sync_limiter = SyncRateLimiter(name="my-app", region="us-east-1")

# Define default limits (can be overridden per-entity)
default_limits = [
    Limit.per_minute("rpm", 100),
    # Token bucket with burst capacity
    Limit.per_minute("tpm", 10_000, burst=50_000),
]

async with limiter.acquire(
    entity_id="api-key-123",
    resource="gpt-4",
    limits=default_limits,  # Multiple limits in a single atomic transaction
    consume={"rpm": 1, "tpm": 500},  # Estimate tokens upfront
) as lease:
    response = await call_llm()
    # Reconcile actual usage (can go negative for post-hoc adjustment)
    await lease.adjust(tpm=response.usage.total_tokens - 500)
    # On success: committed | On exception: rolled back automatically

# Hierarchical entities: create project with stored limits, then API key under it
await limiter.create_entity(entity_id="proj-1", name="Production")
await limiter.set_limits("proj-1", [Limit.per_minute("tpm", 100_000)])  # Project-level
await limiter.create_entity(entity_id="api-key-456", parent_id="proj-1", cascade=True)

# cascade is an entity property — acquire() auto-cascades to parent
with sync_limiter.acquire(
    entity_id="api-key-456",
    resource="gpt-4",
    limits=default_limits,
    consume={"rpm": 1, "tpm": 500},
    use_stored_limits=True,  # Uses proj-1's 100k tpm limit
):
    call_api()

# Cleanup (removes all data)
await limiter.delete_stack()

Documentation

Full Documentation

Guide Description
Getting Started Installation, first deployment
Basic Usage Rate limiting patterns, error handling
Hierarchical Limits Parent/child entities, cascade mode
LLM Integration Token estimation and reconciliation
CLI Reference Deploy, status, delete commands
Production Guide Security, monitoring, cost

Production Deployment

The default deployment includes CloudWatch alarms and usage aggregation. For production, add data recovery and alert routing:

zae-limiter deploy --name my-app --region us-east-1 \
    --pitr-recovery-days 7 \
    --alarm-sns-topic arn:aws:sns:us-east-1:123456789012:alerts

For security best practices, multi-region considerations, and cost estimation, see the Production Guide.

Contributing

git clone https://github.com/zeroae/zae-limiter.git && cd zae-limiter
uv sync --all-extras
pytest

See the Contributing Guide for development setup, testing, and architecture details.

License

MIT

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