- Master Python with tutorials and tips on CodeStips.
Properly organizing Python modules is key for code maintainability and scalability. Start with a solid project structure to keep your code accessible and extendable.
Learn to use mocking in Python tests to isolate code from external dependencies like APIs or databases, ensuring reliable, controlled testing.
Python's copy module offers shallow and deep copy methods. Understanding the difference is crucial to avoid unintended side effects in your code.
Python offers the enumerate() function to simplify tracking index and element during iteration, eliminating the need for manual index management.
Effective error handling in Python functions ensures robustness, user-friendliness, and easier debugging by anticipating and managing potential exceptions.
Python function annotations and type hints clarify expected parameter and return types, improving code readability and maintainability.
Speed up Python functions by choosing efficient data structures like sets over lists for faster code execution and better user experience.
Python treats functions as first-class objects, enabling assignment, storage in data structures, and use as arguments or return values.
functools.wraps preserves a function's metadata when using decorators, maintaining its name, docstring, and other attributes after wrapping. Learn how and when to use it effectively.
__init__.py files turn directories into importable Python packages, enabling module organization and initialization code. They're essential for package structure, namespace control, and import behavior.