The Complete Python Intermediate Features

Learn how decorators extend a greet function's behavior without altering its code, using a method-based decorator to require a full name (first and last name) before greeting.

Discover how a decorator adds functionality to a function or class without modification and understand method based, class based, and parametric decorators.

Implement a Python grid function that takes first name and last name and returns its representation. Create a decorator that wraps a decorator and prints wrapper function executed before function.

Explore class based decorator in Python. Learn how a class accepts a function, implements a core method, and calls the stored function inside the core implementation, via an example.

Transform a function decorator into a class based decorator in Python by defining __init__, a core method, and a print method, while handling *args and **kwargs to preserve behavior.

Demonstrates implementing a class-based decorator in Python that raises a function result to a configurable power, illustrated with double and triple raise functions and variable arguments.

Learn lambda functions as anonymous, small one-expression functions used for single tasks, and compare them with standard functions. See usage with built-ins like map and filter through coding examples.

Learn how lambda functions add numbers with arguments and return results, compare with standard functions, and see concise one-line code versus longer multi-line implementations.

Explore how a lambda function can accept multiple arguments but return a single expression, and compare it with a standard function using the same three arguments in example-02.py.

Explore how to combine standard and lambda functions to handle multiple arguments and reproduce the same result shown in example-02, through hands-on coding.

Practice using the map function and a lambda to capitalize a list of fruits like bananas, pineapples, and mangoes in a do-it-yourself exercise.

Learn to use the map function to capitalize each fruit in a list with a lambda, producing capitalized fruits.

Discover how the filter function processes an iterable, returning a generator of items that pass a criterion, while map and filter illustrate a functional approach with a student class.

Explore using filter to select students by age and compare it with for loops and map, then apply case-insensitive filtering on fruits.

Demonstrate using a for loop to aggregate numbers by computing a product, matching the reduce result and illustrating how reduce works behind the scenes.

Use reduce with a lambda to print a word list after importing functools. Find the minimum and maximum in a numbers list with reduce using min and max.

Discover how map, filter, and reduce solve problems with a bike list in a functional programming style. Build a bike class and find the cheapest bike using lambda.

Add five to the price of Ebony bikes in a list and print the results. Learn to combine map, filter, and lambda in Python to solve this task.

Log developer details to developer.log using Python's logging, create a developer class storing full name, email, and team, and configure formatting and basic logging to a file.

Explore how to use Python's built-in iter and next to create an iterator from a list of car makes, print each item, and handle stop iteration when exhausted.

Discover how the context manager closes files automatically, ensuring resources are released after errors. Use with, enter, and exit to convert direct file opening to context-managed workflows.

Learn how to open and write to a file using direct open, compare with context manager, and see how with handles automatic closing and resource management.

Learn to implement a custom context manager for file handling by building an open file class with __enter__ and __exit__, and using with to write safely.