Hands-On Lectures, Notebooks, Scripts, and Functional Python Programming Techniques for Readability and Performance.
What you will learn
Master Data Processing Patterns: Learn Mapping, Filtering, and Reducing for efficient data processing in Python.
Implement Functional Data Structures: Understand NamedTuples and dataclasses (frozen and mutable).
Create Generator Functions and Expressions: Learn to handle large data sets efficiently with generators in Python.
Use Python’s Higher-order Functions: Gain skills in map(), filter(), and reduce() for concise, readable code.
Explore Python’s Itertools Module: Develop advanced techniques using itertools for complex data manipulations.
Apply Mathematical Functions in Python: Use mathematical functions effectively and craft both readable and performant code.
Grasp Functional Programming Philosophy: Understand its core principles and distinction from other paradigms in Python.
Compare Python Programming Paradigms: Analyze differences between functional, procedural, and OOP.
Description
Welcome to “Python in Practice: Real-World Programming Deep Dive (2024).”
This course is designed for developers who already have some experience with Python and are looking to take their code writing skills to the next level. This course will help you understand and apply functional programming concepts to achieve exactly that!
Over a concise series of lessons, we aim to show you how functional programming can make your code cleaner, more efficient, and easier to maintain.
WHAT YOU WILL LEARN
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- Introduction to Functional Programming: Get a clear understanding of what functional programming is and how it can be used with Python to make your work more effective.
- Using Python’s Functional Features: Learn about lambda functions, iterators, and generators, and see how they can help you write better code.
- Real-World Practical Applications: Work through coding exercises that apply functional programming to common coding tasks and scenarios, helping you see the benefits in terms of code efficiency and maintenance.
- Specialized Patterns for Processing Data: Discover how mapping, filtering, and reducing data can simplify the way you handle data, making your code more readable.
- Python’s Built-in Functions for Functional Programming: Get to grips with Python’s map(), filter(), and reduce() functions to improve how you approach coding tasks.
- Advanced Topics: Explore more complex uses of functional programming in Python, including working with the itertools module and using specialized data structures like NamedTuples and dataclasses.
This course is all about giving you the strategies, techniques, tools and understanding you need to take your code writing skills to the level of senior Python developers, by incorporating functional programming into your Python projects.
It’s designed to be practical and directly applicable to the kinds of challenges you face as a developer.
WHO THIS COURSE IS FOR
- Python Developers: If you’re already working with Python and want to deepen your understanding of functional programming, this course is for you.
- Professionals Looking to Improve: If you’re seeking to make your coding practice more efficient and your code more maintainable, this course offers practical steps to achieve that.
- Python Enthusiasts: Anyone with an interest in Python and functional programming will find valuable insights and skills in this course.
Enroll today in “Python in Practice: Real-World Programming Deep Dive (2024)” and leave with a solid understanding of functional programming principles and how to apply them to make your code cleaner, more readable, more performant, and more efficient.
Introduction
Welcome to the Course – Please Watch
[IMPORTANT] Course Expectations – Please Read
About your Instructor
Slides and Code Downloads
Course Slides (PDF)
Jupyter Notebooks and Python Scripts
Course Prerequisites – Refresher Python Coding Exercises (OPTIONAL)
Python Variables and Objects
Arithmetic Operators in Python
Bitwise Operators in Python
Comparison Operators in Python
Boolean Operators in Python
Identity and Membership Operators in Python
Built-In Types in Python
Built-In Data Structures in Python
Modules in Python
Functions in Python
Iterators in Python
Control Flow in Python
List Comprehensions in Python
String Manipulation in Python
Exception Handling in Python
Python’s Functional Programming Tools
[Lecture] What is Functional Programming?
[Hands-On] What is Functional Programming?
[Check-In Quiz] What is Functional Programming?
[Lecture] Dataclasses
[Hands-On] Dataclasses
[Check-In Quiz] Dataclasses
[Lecture] Specialized Container Data Types
[Hands-On] Specialized Container Data Types
[Check-In Quiz] Specialized Container Data Types
[Lecture] Lambda Functions
[Hands-On] Lambda Functions
[Check-In Quiz] Lambda Functions
[Lecture + Hands-On] Higher-Order Functions
[Check-In Quiz] Higher-Order Functions
Practice What You’ve Learned (OPTIONAL)
Generator Functions and Expressions
[Lecture] Iterables, Iterators, and Callables
[Hands-On] Iterables, Iterators, and Callables
[Check-In Quiz] Iterables, Iterators, and Callables
[Lecture] Generator Functions and Expressions
[Hands-On] Generator Functions and Expressions
[Check-In Quiz] Generator Functions and Expressions
[Lecture] Data Transformations with Generators
[Hands-On] Data Transformations with Generators
[Check-In Quiz] Data Transformations with Generators
Practice What You’ve Learned (OPTIONAL)
Functional Data Processing & Analysis
[Lecture] Data Transformations with map()
[Hands-On] Data Transformations with map()
[Check-In Quiz] Data Transformations with map()
[Lecture] Filtering Data Collections
[Hands-On] Filtering Data Collections
[Check-In Quiz] Filtering Data Collections
[Lecture] Summarizing Data
[Hands-On] Summarizing Data
[Check-In Quiz] Summarizing Data
[Lecture] Partial Functions
[Hands-On] Partial Functions
[Check-In Quiz] Partial Functions
Practice What You’ve Learned (OPTIONAL)
Advanced Use Cases / Complex Data Transformations
[Lecture] Data Processing Pipelines with Chained Generators
[Hands-On] Data Processing Pipelines with Chained Generators
[Check-In Quiz] Data Processing Pipelines with Chained Generators and itertools
[Lecture] Function Composition for Complex Transformations
[Hands-On] Function Composition for Complex Transformations
[Check-In Quiz] Function Composition for Complex Transformations
Practice What You’ve Learned (OPTIONAL)
[Keep Practicing] – Additional Coding Exercises (OPTIONAL)
Implementing a Custom Map Function in Python
Implementing a Custom Reduce Function in Python
Filtering Prime Numbers with Functional Programming
Adding Voting Eligibility to Person Records
Implementing a Custom Iterator for Fibonacci Sequence
Functional Programming for Virtual Directory Traversal in Python
Optimizing Fibonacci with Memoization
Stream Processing System Simulation in Python
Functional Text Analysis in Python
Implementing a Function Timing Decorator
Congratulations!
Congratulations! Where to from here? – Please Watch
[RECOMMENDED READING] Python Development Best Practices
Bonus Lecture
