decorator-collection 1.0.0

A collection of basic and advanced Python decorators

Decorator Collection

Overview

The Decorator Collection package provides a comprehensive set of basic and advanced Python decorators that simplify a variety of tasks. Whether you're looking to implement caching, retries, logging, rate limiting, or more complex control flows like circuit breakers, this package has you covered.

Key Features:

• Basic decorators:

  • Retry on failures, memoization, logging function input/output, and singleton pattern implementation.

• Advanced decorators:

  • Throttling and debouncing function calls, type checking, enforcing rate limits, and circuit-breaking to handle failures.

The package is modularized into two main parts:

• basic_decorators: Includes common decorators for everyday use.
• advanced_decorators: Provides decorators for more complex logic and control flows.

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Installation

You can install the Decorator Collection from PyPI by running:

pip install decorator_collection

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Usage

After installation, you can use decorators from either the basic_decorators or advanced_decorators modules. Here are some example use cases:

Example 1: Basic Decorators

from decorator_collection.basic_decorators import retry, memoize, log

# Memoization example
@memoize
def compute_power(x, y):
    return x ** y

# Retry example
@retry(exceptions=(ValueError,), max_attempts=3, delay=2)
def risky_calculation():
    raise ValueError("An error occurred!")

# Log decorator example
@log
def add(a, b):
    return a + b

Example 2: Advanced Decorators

from decorator_collection.advanced_decorators import throttle, debounce, type_check

# Throttle example: Ensures this function only runs at most once per 5 seconds.
@throttle(seconds=5)
def send_email():
    print("Sending email...")

# Debounce example: Only runs if there's no new call within 1 second.
@debounce(wait_time=1)
def search(query):
    print(f"Searching for {query}...")

# Type-checking decorator
@type_check((int, int))
def multiply(a, b):
    return a * b

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Modules

basic_decorators

The basic_decorators.py module includes essential decorators for common tasks. Here's a list of available decorators:

1. @retry(exceptions, max_attempts, delay)
   Automatically retries a function if it raises specific exceptions.

   @retry(exceptions=(ValueError,), max_attempts=3, delay=2)
   def risky_function():
       pass
   

2. @memoize
   Caches the results of expensive function calls based on input arguments.

   @memoize
   def expensive_computation(x, y):
       return x ** y
   

3. @log
   Logs the input arguments and return value of a function.

   @log
   def add_numbers(a, b):
       return a + b
   

4. @singleton
   Ensures that only one instance of a class is created.

   @singleton
   class DatabaseConnection:
       pass
   

5. @time_logger
   Logs the time taken by a function to execute.

   @time_logger
   def long_running_task():
       time.sleep(2)
   

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advanced_decorators

The advanced_decorators.py module contains more complex decorators for advanced use cases:

1. @throttle(seconds)
   Limits how frequently a function can be executed, useful for rate-limiting.

   @throttle(seconds=5)
   def update_status():
       pass
   

2. @debounce(wait_time)
   Ensures that a function only runs after a specified period of inactivity, useful for search input fields.

   @debounce(wait_time=1)
   def process_search(query):
       pass
   

3. @type_check(types)
   Enforces type checking for function arguments.

   @type_check((int, int))
   def multiply_numbers(a, b):
       return a * b
   

4. @circuit_breaker(failure_threshold, recovery_timeout)
   Implements a circuit breaker pattern to prevent repeatedly calling failing services.

   @circuit_breaker(failure_threshold=2, recovery_timeout=10)
   def call_external_service():
       pass
   

5. @rate_limit(max_per_second)
   Limits the number of times a function can be executed per second.

   @rate_limit(max_per_second=5)
   def api_request():
       pass
   

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Requirements

• Python 3.11+
• jsonschema (required for JSON validation decorators)

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License

This project is licensed under the MIT License - see the LICENSE file for details.

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Contributing

We welcome contributions! Please email me and I will look at your request.

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Author

• Aiden Metcalfe

Feel free to reach out with suggestions, bug reports, or feature requests.

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Changelog

v1.0.0

• Initial release with 20 basic and 20 advanced decorators.