Functional Programming With Python

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Andy Bek

14:26:13

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1. PLEASE DO NOT SKIP

1.1 VSCode With Jupyter Notebooks.html

1. Very Short Intro.mp4

02:51

2.1 notebooks.zip

2. All Course Notebooks.html

2. The Five Tenets Of Functional Programming

1. The Functional Paradigm.mp4

06:33

2.1 3. the five tenets of functional programming.zip

2. Section Notebook.html

3. Functions As First-Class Objects

1. Passing Functions As Arguments.mp4

03:31

2. Functions Returning Functions.mp4

03:37

3. Skill Challenge.mp4

01:29

4. Solution.mp4

01:28

5.1 4. functions as first class objects.zip

5. Section Notebook.html

4. Functions In Data Structures

1. Lists Of Functions.mp4

03:13

2. Skill Challenge.mp4

01:26

3. Solution.mp4

07:23

4.1 5. functions in data structures.zip

4. Section Notebook.html

5. HOFs At A Glance

1. Order And Higher-Order Functions.mp4

03:24

2. Skill Challenge.mp4

01:48

3. Solution.mp4

05:43

4.1 6. hofs at a glance.zip

4. Section Notebook.html

6. Purity And Side Effects

1. Impure Functions.mp4

05:42

2. Purity Is Eliminating (Realistically, Isolating) The Side Effects.mp4

06:55

3.1 7. purity and side effects.zip

3. Section Notebook.html

7. Laziness

1. Lazy vs Eager Evaluation.mp4

08:32

2. Chaining Lazy Operations.mp4

04:46

3.1 8. laziness.zip

3. Section Notebook.html

8. Immutability

1. Mutable Lists.mp4

06:56

2. Skill Challenge.mp4

01:38

3. Solution.mp4

02:52

4. Extra UndoRedo Operations With Immutable Data.mp4

15:07

5.1 9. immutability.zip

5. Section Notebook.html

9. Aliasing

1. Aliasing And Unintended Side Effects.mp4

04:25

2.1 10. aliasing.zip

2. Section Notebook.html

10. Lambdas

1. Anonymous Functions.mp4

05:43

2. A Single Expression.mp4

05:18

3. Good And Bad Uses.mp4

06:26

4. Nesting And In-Place Lambdas.mp4

05:10

5. Skill Challenge.mp4

01:17

6. Solution.mp4

03:39

7.1 11. lambdas.zip

7. Section Notebook.html

11. Map

1. Transformations.mp4

06:02

2. Mapping Over Multiple Iterables.mp4

04:36

3. Built-Ins.mp4

06:17

4. Skill Challenge.mp4

01:17

5. Solution.mp4

04:57

6.1 12. map.zip

6. Section Notebook.html

12. Zip

1. The Basic Zip.mp4

04:19

2. Strict Mode.mp4

04:34

3. Unzipping With Splat.mp4

05:49

4. Building Dicts.mp4

03:22

5. Extra Functional Pipelining.mp4

08:07

6. Skill Challenge.mp4

02:16

7. Solution.mp4

05:38

8.1 13. zip.zip

8. Section Notebook.html

13. Filter

1. Declarative Select.mp4

04:42

2. Multiple Conditions.mp4

07:08

3. Extra Nested Lambdas.mp4

05:57

4. Chained Filtering.mp4

05:17

5. Skill Challenge.mp4

01:31

6. Solution.mp4

04:19

7. Extra Alternative Solution With namedtuple.mp4

05:57

8.1 14. filter.zip

8. Section Notebook.html

14. Any And All

1. Any.mp4

07:38

2. All.mp4

04:01

3. Any And All With Filter And Map.mp4

06:15

4. Negation.mp4

05:20

5. Short Circuiting Logic.mp4

04:39

6. Skill Challenge.mp4

01:15

7. Solution.mp4

05:10

8.1 15. any and all.zip

8. Section Notebook.html

15. Reduce

1. Accumulate.mp4

05:46

2. The Initial Accumulator.mp4

10:43

3. Skill Challenge.mp4

01:12

4. Solution.mp4

03:04

5. More Applications.mp4

09:52

6. Skill Challenge - Run Length Encoding.mp4

01:35

7. Solution.mp4

11:11

8.1 16. reduce.zip

8. Section Notebook.html

16. Comprehensions

1. Introduction To Comprehensions.mp4

06:08

2. Nested List Comprehensions.mp4

05:57

3. Comprehensions Over Multiple Iterables.mp4

03:19

4. Skill Challenge.mp4

01:09

5. Solution.mp4

03:47

6.1 17. comprehensions.zip

6. Section Notebook.html

17. Set Comprehensions

1. From Lists To Sets.mp4

07:08

2. More Advanced Operations.mp4

04:56

3. Skill Challenge.mp4

01:01

4. Solution.mp4

05:13

5. Extra Skill Challenge Efficient Primes.mp4

01:29

6. Solution.mp4

05:32

7.1 18. set comprehensions.zip

7. Section Notebook.html

18. Dictionary Comprehensions

1. Building New Dictionaries.mp4

07:03

2. More Use Cases.mp4

08:36

3. Skill Challenge.mp4

01:20

4. Solution.mp4

04:49

5. Alternative Solution.mp4

04:48

6.1 19. dictionary comrephensions.zip

6. Section Notebook.html

19. Iterators

1. Concepts And Foundations.mp4

06:42

2. Implementing The Iterator Protocol.mp4

10:59

3.1 20. iterators.zip

3. Section Notebook.html

20. Generators

1. Introduction To Generator Functions.mp4

06:28

2. Generator Expressions.mp4

04:12

3. Two-Way Communication With Generators.mp4

10:13

4. Skill Challenge Infinite Fibonacci Generator.mp4

01:21

5. Solution.mp4

02:36

6. Alternative Solution.mp4

02:48

7. Extra Sliding Window Fibonacci With Deque.mp4

10:00

8.1 logfile.zip

8. Data Pipelining Using Generators.mp4

08:22

9.1 21. generators.zip

9. Section Notebook.html

21. Variadics

1. args and kwargs.mp4

13:07

2. Skill Challenge.mp4

01:08

3. Solution.mp4

04:27

4.1 22. variadics.zip

4. Section Notebook.html

22. Nested HOFs

1. Higher Order Functions Revisited.mp4

04:59

2. Skill Challenge.mp4

01:24

3. Solution.mp4

04:28

4.1 23. nested hofs.zip

4. Section Notebook.html

23. Closures

1. What Is A Closure.mp4

07:29

2. Skill Challenge.mp4

01:41

3. Solution.mp4

03:36

4.1 24. closures.zip

4. Section Notebook.html

24. Decorators

1. Introduction To Decorators.mp4

07:11

2. Decorating Parameterized Functions.mp4

06:18

3. Skill Challenge.mp4

02:19

4. Solution.mp4

04:49

5.1 25. decorators.zip

5. Section Notebook.html

25. Advanced Decorators

1. Advanced Decorators.mp4

09:09

2. Chaining Multiple Decorators.mp4

07:57

3. Preserving Identity With @wraps.mp4

09:06

4. Skill Challenge.mp4

03:10

5. Solution.mp4

09:41

6.1 26. advanced decorators.zip

6. Section Notebook.html

26. Recursion

1. Introduction To Recursion.mp4

09:59

2. Recursion Trees And Recurrence Relations.mp4

04:00

3. Skill Challenge.mp4

00:42

4. Solution.mp4

01:52

5. Tail Recursion And Recursion Limits In Python.mp4

07:23

6. Mutual Recursion.mp4

08:22

7. Parsing Structured Data With Recursive Functions.mp4

12:52

8. A Slight Improvement.mp4

05:45

9. Skill Challenge - Recursive Binary Search.mp4

03:31

10. Solution.mp4

09:30

11. Skill Challenge - Refactored Signature.mp4

01:39

12. Solution.mp4

04:30

13.1 27. recursion.zip

13. Section Notebook.html

27. Memoization

1. A Conceptual Understanding.mp4

05:51

2. Defining A Memoization Function.mp4

07:23

3. Predefined Caching Utilities.mp4

06:35

4. Extra Inline Memoization.mp4

04:02

5.1 28. memoization.zip

5. Section Notebook.html

28. Currying And Partials

1. Partial Function Application.mp4

06:49

2. Skill Challenge.mp4

00:44

3. Solution.mp4

02:35

4.1 29. currying and partials.zip

4. Section Notebook.html

29. Overloading And Polymorphism With singledispatch

1. Polymorphic Functions.mp4

10:01

2. A Quick Gotcha.mp4

06:23

3. Skill Challenge.mp4

01:52

4. Solution.mp4

08:10

5.1 30. overloading and polymorphism.zip

5. Section Notebook.html

30. Infinite Iterators

1. Count.mp4

06:26

2. Infinite Cycles.mp4

05:03

3. Finite Cycles With Repeat.mp4

09:44

4. Skill Challenge.mp4

01:12

5. Solution.mp4

04:10

6.1 31. infinite iterators.zip

6. Section Notebook.html

31. Appendix Complete Python Fundamentals In Less Than 3 Hours

1.1 Rapid Fire Python Fundamentals.zip

1. Please Note.html

2. Section Intro.mp4

01:45

3. Data Types.mp4

02:35

4. Variables.mp4

08:27

5. Arithmetic And Augmented Assignment Operators.mp4

07:16

6. Ints And Floats.mp4

08:54

7. Booleans And Comparison Operators.mp4

05:12

8. Strings.mp4

07:52

9. Methods.mp4

06:29

10. Containers I Lists.mp4

06:08

11. Lists vs. Strings.mp4

06:53

12. List Methods And Functions.mp4

07:54

13. Containers II Tuples.mp4

04:43

14. Containers III Sets.mp4

10:32

15. Containers IV Dictionaries.mp4

05:15

16. Dictionary Keys And Values.mp4

08:14

17. Membership Operators.mp4

04:28

18. Controlling Flow if, else, And elif.mp4

08:21

19. Truth Value Of Non-booleans.mp4

03:28

20. For Loops.mp4

05:05

21. The range() Immutable Sequence.mp4

05:10

22. While Loops.mp4

05:55

23. Break And Continue.mp4

04:15

24. Zipping Iterables.mp4

03:39

25. List Comprehensions.mp4

07:47

26. Defining Functions.mp4

10:18

27. Function Arguments Positional vs Keyword.mp4

06:54

28. Lambdas.mp4

05:28

29. Importing Modules.mp4

05:38

Description

A beginner-friendly introduction to functional constructs in python

What You'll Learn?

Practical fluency with map, filter, reduce, zip, any, all, list, set, dictionary, and generator comprehensions, and generator expressions
Complete coverage of intermediate functional constructs in Python: generators, iterators, decorators, closures, recursion, and much more!
A practical exploration of advanced topics: closures, recursion, partial function application, currying, memoization, infinite iterators, and overloading
A conceptual understanding of the key tenets of functional programming: immutability, purity, higher-order functions, recursion, and referential transparency

Who is this for?

This course is for anyone who wants to learn functional programming in Python from the very basics

Beginners to programming interested in writing concise, readable, and maintainable Python

Beginner Python developers with an interest in functional programming

Intermediate programmers with no exposure to functional constructs in Python

What You Need to Know?

No prior Python programming experience is required - this course is beginner friendly

A basic understanding of programming concepts is helpful, but not required

More details

Description
Welcome to the best and most comprehensive introduction to functional programming in Python!
In this beginner-friendly course, you will get to learn and practice Python's functional capabilities step-by-step, from the ground up.
The course will begin with a conceptual understanding of the key tenets of functional programming:
immutability: the idea that data should not be modified in place
purity: the practice of writing functions that do not cause side effects
higher-order functions: treating functions as pari passu with other data types
recursion: the pattern of writing functions that call themselves
referential transparency: the principle that a function call can be replaced with its return value without changing the program's behavior
Then, we will explore practical utilities that Python offers to help us write functional code, including:
map, filter, reduce, zip, any, all: utilities for working with iterables
list, set, dictionary, and generator comprehensions: concise ways of creating lists, sets, dictionaries, and generators
generator functions and iterators: functions that can be paused and resumed
variable arity: functions that can take a variable number of arguments, unknown at the time of writing the functionÂ
In the final, and longest part of the course, we will take a look at more advanced topics, including:
closures: higher-order functions that can access non-local variables
recursion: functions that call themselves
partial function application: functions that return other functions, with some arguments pre-filled
currying: a special case of partial function application
memoization: caching the results of function calls to speed up execution
infinite iterators: iterators that never end
functional overloading: functions that behave differently depending on their inputs
Throughtout the course, you will get to practice your newly acquired skills through a set of more than 20 skill challenges, each of which will be followed with a detailed video explanation of the solution that we will walk through together.
This course is very beginner-friendly and no python experience is assumed. If you've never worked with Python before, there's a full length introduction to Python programming included as an appendix, covering the fundamentals of the language from the basic data types to containers, control flow, loops, classes, and more.
See you inside!
Who this course is for:
This course is for anyone who wants to learn functional programming in Python from the very basics
Beginners to programming interested in writing concise, readable, and maintainable Python
Beginner Python developers with an interest in functional programming
Intermediate programmers with no exposure to functional constructs in Python

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Hi! I'm Andy. I'm freelance software developer and capital markets consultant. I've spent close to a decade working with data, using code to automate business workflows, and consulting financial institutions on data-intensive applications.Aside from teaching, I run a AI and data consulting firm that targets fintechs in the post-trade services niche.

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