Performance Features

Overview

Catzilla includes several performance optimizations designed to make your web applications fast and efficient. The framework leverages C acceleration for critical path operations while maintaining the ease of use of Python.

C-Accelerated Components

Route Matching

The core routing system is implemented in C, providing fast route matching:

Routes are stored in an optimized trie structure
Pattern matching is performed using efficient C algorithms
Path parameter extraction is handled in C code

Path Parameter Extraction

Parameter extraction from URLs happens in C:

@app.get("/users/{user_id}/posts/{post_id}")
def get_user_post(request):
    # These parameters are extracted by C code
    user_id = request.path_params["user_id"]
    post_id = request.path_params["post_id"]
    return {"user_id": user_id, "post_id": post_id}

Query Parameter Processing

Query parameters are also processed efficiently:

@app.get("/search")
def search(request):
    # Query parameters loaded on demand
    query = request.query_params.get("q", "")
    page = request.query_params.get("page", "1")
    return {"query": query, "page": page}

RouterGroup Efficiency

Organized Route Management

RouterGroups help organize routes efficiently:

# Routes are grouped logically for better organization
api = RouterGroup(prefix="/api/v1")
users = RouterGroup(prefix="/users")
posts = RouterGroup(prefix="/posts")

# Nested groups maintain performance
api.include_group(users)
api.include_group(posts)
app.include_routes(api)

Scalable Route Registration

RouterGroups scale well with large numbers of routes:

Route prefixes are resolved at registration time
No runtime overhead for group resolution
Efficient route storage and lookup

Performance Best Practices

Route Design

Design routes for optimal performance:

# Good: Simple patterns are fastest
@app.get("/users/{user_id}")
@app.get("/posts/{post_id}")

# Still efficient: Multiple parameters
@app.get("/users/{user_id}/posts/{post_id}")

# Complex but supported: Deeply nested parameters
@app.get("/api/v1/orgs/{org_id}/teams/{team_id}/projects/{project_id}")

RouterGroup Organization

Organize RouterGroups for clarity and maintainability:

# Organize by functionality
user_routes = RouterGroup(prefix="/users")
post_routes = RouterGroup(prefix="/posts")
admin_routes = RouterGroup(prefix="/admin")

# Or by API version
api_v1 = RouterGroup(prefix="/api/v1")
api_v2 = RouterGroup(prefix="/api/v2")

# Include groups efficiently
main_api = RouterGroup(prefix="/api")
main_api.include_group(api_v1)
main_api.include_group(api_v2)
app.include_routes(main_api)

Request Handler Efficiency

Write efficient request handlers:

@app.get("/users/{user_id}")
def get_user(request):
    # Parameter extraction is already optimized
    user_id = request.path_params["user_id"]

    # Focus on your business logic efficiency
    # Use database connection pooling
    # Cache frequently accessed data
    # Return appropriate response sizes

    return {"user_id": user_id, "name": "John Doe"}

Memory Usage Tips

Keep memory usage efficient:

# Use appropriate data structures
@app.get("/large-data")
def get_large_data(request):
    # Stream large responses when possible
    # Don't load everything into memory at once
    # Use generators for large datasets
    return {"data": "appropriate_sized_response"}

Performance Monitoring

Request Timing

Monitor your application performance:

import time

@app.get("/monitored-endpoint")
def monitored_handler(request):
    start_time = time.time()

    # Your business logic here
    result = {"message": "Hello World"}

    # Log timing if needed
    duration = time.time() - start_time
    print(f"Request took {duration:.3f}s")

    return result

Resource Usage

Keep an eye on resource usage:

# Monitor key metrics in production:
# - Request latency
# - Memory usage
# - Route matching performance
# - Parameter extraction overhead
# - Database query times

Scaling Considerations

Application Design

Design your application for scale:

Keep route handlers lightweight
Use efficient database queries
Implement appropriate caching
Consider async operations where beneficial
Monitor and profile your specific use cases

Route Organization

As your application grows:

Group related routes with RouterGroups
Keep route patterns as simple as possible
Avoid overly deep nesting when not necessary
Use descriptive parameter names

Scaling Considerations

Application Design

Design your application for scale:

Keep route handlers lightweight
Use efficient database queries
Implement appropriate caching
Consider async operations where beneficial
Monitor and profile your specific use cases

Route Organization

As your application grows:

Group related routes with RouterGroups
Keep route patterns as simple as possible
Avoid overly deep nesting when not necessary
Use descriptive parameter names

Testing Your Performance

Simple Benchmarking

You can benchmark your own Catzilla application:

import time
from catzilla import App

app = App()

@app.get("/test/{param}")
def test_route(request):
    return {"param": request.path_params["param"]}

# Simple timing test
def benchmark_route():
    # This would require setting up actual requests
    # Use tools like wrk, ab, or locust for real load testing
    pass

Load Testing Tools

For production load testing, use professional tools:

wrk: HTTP benchmarking tool
Apache Bench (ab): Simple load testing
Locust: Python-based load testing
Artillery: Modern load testing toolkit

Monitoring in Production

Monitor key metrics in your deployed applications:

import time

@app.middleware
def timing_middleware(request, call_next):
    start_time = time.time()
    response = call_next(request)
    duration = time.time() - start_time

    # Log or send to monitoring system
    print(f"Request to {request.path} took {duration:.3f}s")

    return response

The C-accelerated foundation in Catzilla provides a solid performance base for your applications. Focus on writing efficient business logic and following web development best practices for optimal performance.