Python Lambda Functions

Lambda Functions and Higher-Order Functions

• Lambda functions in Python are anonymous functions defined with the lambda keyword.
• Commonly used as arguments for higher-order functions, such as filter() and map().
• Example of a lambda function: double = lambda x: x * 2. Calling double(5) returns 10.
• The filter() function takes a function and a list to return items that evaluate as True. Example filtering even numbers:
  • my_list = [1, 5, 4, 6, 8, 11, 3, 12]
  • new_list = list(filter(lambda x: (x % 2 == 0), my_list)) results in [4, 6, 8, 12].

Map Function

• The map() function applies a function to all items in a list, returning a new list with the results.
• Example to double each item in a list:
  • my_list = [1, 5, 4, 6, 8, 11, 3, 12]
  • new_list = list(map(lambda x: x * 2, my_list)) results in doubled values.

Functions in Python

• A function is a block of reusable code that operates with input parameters and can return results.
• Function calls reference functions defined elsewhere, including standard libraries and user-defined functions.

Variable Scope

• Global variables exist outside functions and are accessible within and outside functions.
• Local variables are defined within functions and limited to that function's scope.
• Example:
  • Global variable x = 5. Inside test1(), local x = 10 and calling prints both local and global values.

Nonlocal Variables

• Nonlocal variables are used in nested functions, allowing access to variables in the enclosing scope that are not global.

Python Docstrings

• Docstrings provide documentation for modules, functions, classes, or methods and are accessible as the __doc__ attribute.
• Single-line docstrings should use triple quotes but occupy the same line for consistency.
• Example function with a docstring:

  • def square(n):
        '''Takes in a number n, returns the square of n'''
        return n ** 2
    

Built-in Functions Documentation

• Built-in function docstrings, like for print(), describe the function's parameters and output format, which helps with understanding usage.

Good Programming Practices

• Emphasize writing well-structured and documented code using proper naming conventions for variables, functions, and classes.
• Include README files, setup scripts, documentation for components, and tests to improve code usability and maintainability.
• Consistent naming:
  • Variable names: Use underscores (e.g., long_variable_name).
  • Class names: Use CamelCase (e.g., LongClassName).

Python Modules and Packages

• Python packages are directories containing multiple modules, typically including __init__.py files.
• Popular Python packages for various applications:
  • NumPy for scientific computing
  • Pandas for data manipulation
  • Matplotlib for data visualization
  • Seaborn for statistical graphics
  • Scikit-learn for machine learning
  • Requests and Urllib3 for HTTP requests
  • NLTK for natural language processing
  • Pillow for image processing
  • Pytest for testing code.

This quiz explores Python's lambda functions, also known as anonymous functions. You will learn how to define and use these functions as arguments in higher-order functions, along with practical examples to reinforce your understanding.