Python 3: Deep Dive (Part 1 - Functional)

45h 50m 55s
English
Paid

Course description

This is Part 1 of a series of courses intended to dive into the inner mechanics and more complicated aspects of Python 3. This is not a beginner course - if you've been coding Python for a week or a couple of months, you probably should keep writing Python for a bit more before tackling this series.

Read more about the course

On the other hand, if you're now starting to ask yourself questions like:

  • I wonder how this works?

  • is there another way of doing this?

  • what's a closure? is that the same as a lambda?

  • I know how to use a decorator someone else wrote, but how does it work? Can I write my own?

  • why isn't this boolean expression returning a boolean value?

  • what does an import actually do, and why am I getting side effects?

  • and similar types of question...

then this course is for you.

Please make sure you review the pre-requisites for this course - although I give a brief refresh of basic concepts at the beginning of the course, those are concepts you should already be very comfortable with as you being this course.

In this course series, I will give you a much more fundamental and deeper understanding of the Python language and the standard library.

Python is called a "batteries-included" language for good reason - there is a ton of functionality in base Python that remains to be explored and studied.

So this course is not about explaining my favorite 3rd party libraries - it's about Python, as a language, and the standard library.

In particular this course is based on the canonical CPython. You will also need Jupyter Notebooks to view the downloadable fully-annotated Python notebooks.

It's about helping you explore Python and answer questions you are asking yourself as you develop more and more with the language.

In Python 3: Deep Dive (Part 1) we will take a much closer look at:

  • Variables - in particular that they are just symbols pointing to objects in memory

  • Namespaces and scope

  • Python's numeric types

  • Python boolean type - there's more to a simple or statement than you might think!

  • Run-time vs compile-time and how that affects function defaults, decorators, importing modules, etc

  • Functions in general (including lambdas)

  • Functional programming techniques (such as map, reduce, filter, zip, etc)

  • Closures

  • Decorators

  • Imports, modules and packages

  • Tuples as data structures

  • Named tuples

To get the most out of this course, you should be prepared to pause the coding videos, and attempt to write code before I do! Sit back during the concept videos, but lean in for the code videos!

And after you have seen a code video, pause the course, and try things out yourself - explore, experiment, play with code, and see how things work (or don't work! - that's also a great way to learn!)

Requirements:
  • Basic introductory knowledge of Python programming (variables, conditional statements, loops, functions, lists, tuples, dictionaries, classes).
  • You will need Python 3.6 or above, and a development environment of your choice (command line, PyCharm, Jupyter, etc.)
Who this course is for:
  • Anyone with a basic understanding of Python that wants to take it to the next level and get a really deep understanding of the Python language and its data structures.
  • Anyone preparing for an in-depth Python technical interview.

What you'll learn:

  • An in-depth look at variables, memory, namespaces and scopes
  • A deep dive into Python's memory management and optimizations
  • In-depth understanding and advanced usage of Python's numerical data types (Booleans, Integers, Floats, Decimals, Fractions, Complex Numbers)
  • Advanced Boolean expressions and operators
  • Advanced usage of callables including functions, lambdas and closures
  • Functional programming techniques such as map, reduce, filter, and partials
  • Create advanced decorators, including parametrized decorators, class decorators, and decorator classes
  • Advanced decorator applications such as memoization and single dispatch generic functions
  • Use and understand Python's complex Module and Package system
  • Idiomatic Python and best practices
  • Understand Python's compile-time and run-time and how this affects your code
  • Avoid common pitfalls

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#1: 1.1. Course Overview

All Course Lessons (158)

#Lesson TitleDurationAccess
1
1.1. Course Overview Demo
18:09
2
2.1. Introduction
01:44
3
2.2. The Python Type Hierarchy
05:52
4
2.3. Multi-Line Statements and Strings
22:52
5
2.4. Variable Names
11:01
6
2.5. Conditionals
07:39
7
2.6. Functions
12:28
8
2.7. The While Loop
14:26
9
2.8. Break, Continue and the Try Statement
10:25
10
2.9. The For Loop
17:21
11
2.10. Classes
40:18
12
3.1. Introduction
02:55
13
3.2. Variables are Memory References
08:22
14
3.3. Reference Counting
14:22
15
3.4. Garbage Collection
26:40
16
3.5. Dynamic vs Static Typing
05:29
17
3.6. Variable Re-Assignment
04:49
18
3.7. Object Mutability
15:23
19
3.8. Function Arguments and Mutability
17:29
20
3.9. Shared References and Mutability
09:37
21
3.10. Variable Equality
14:23
22
3.11. Everything is an Object
13:59
23
3.12. Python Optimizations Interning
09:15
24
3.13. Python Optimizations String Interning
19:12
25
3.14. Python Optimizations Peephole
20:10
26
4.1. Introduction
02:59
27
4.2. Integers Data Types
18:07
28
4.3. Integers Operations
24:26
29
4.4. Integers Constructors and Bases - Lecture
29:35
30
4.5. Integers Constructors and Bases - Coding
20:24
31
4.6. Rational Numbers - Lecture
14:27
32
4.7. Rational Numbers - Coding
12:34
33
4.8. Floats Internal Representations - Lecture
19:53
34
4.9. Floats Internal Representations - Coding
04:57
35
4.10. Floats Equality Testing - Lecture
18:43
36
4.11. Floats Equality Testing - Coding
14:41
37
4.12. Floats Coercing to Integers - Lecture
09:40
38
4.13. Floats Coercing to Integers - Coding
05:04
39
4.14. Floats Rounding - Lecture
25:22
40
4.15. Floats Rounding - Coding
13:34
41
4.16. Decimals - Lecture
16:50
42
4.17. Decimals - Coding
10:27
43
4.18. Decimals Constructors and Contexts - Lecture
10:06
44
4.19. Decimals Constructors and Contexts - Coding
10:29
45
4.20. Decimals Math Operations - Lecture
09:33
46
4.21. Decimals Math Operations - Coding
13:31
47
4.22. Decimals Performance Considerations
10:30
48
4.23. Complex Numbers - Lecture
11:29
49
4.24. Complex Numbers - Coding
14:17
50
4.25. Booleans
21:01
51
4.26. Booleans Truth Values - Lecture
09:09
52
4.27. Booleans Truth Values - Coding
14:48
53
4.28. Booleans Precedence and Short-Circuiting - Lecture
21:11
54
4.29. Booleans Precedence and Short-Circuiting - Coding
13:38
55
4.30. Booleans Boolean Operators - Lecture
18:01
56
4.31. Booleans Boolean Operators - Coding
14:46
57
4.32. Comparison Operators
20:54
58
5.1. Introduction
01:06
59
5.2. Argument vs Parameter
03:44
60
5.3. Positional and Keyword Arguments - Lecture
13:06
61
5.4. Positional and Keyword Arguments - Coding
06:22
62
5.5. Unpacking Iterables - Lecture
13:01
63
5.6. Unpacking Iterables - Coding
21:10
64
5.7. Extended Unpacking - Lecture
17:51
65
5.8. Extended Unpacking - Coding
29:05
66
5.9. args - Lecture
06:01
67
5.10. args - Coding
11:48
68
5.11. Keyword Arguments - Lecture
09:24
69
5.12. Keyword Arguments - Coding
14:19
70
5.13. kwargs
10:29
71
5.14. Putting it all Together - Lecture
13:26
72
5.15. Putting it all Together - Coding
17:26
73
5.16. Application A Simple Function Timer
19:09
74
5.17. Parameter Defaults - Beware!!
18:45
75
5.18. Parameter Defaults - Beware Again!!
19:23
76
6.1. Introduction
04:06
77
6.2. Docstrings and Annotations - Lecture
15:59
78
6.3. Docstrings and Annotations - Coding
15:03
79
6.4. Lambda Expressions - Lecture
12:10
80
6.5. Lambda Expressions - Coding
15:00
81
6.6. Lambdas and Sorting
15:57
82
6.7. Challenge - Randomize an Iterable using Sorted!!
02:56
83
6.8. Function Introspection - Lecture
19:31
84
6.9. Function Introspection - Coding
28:37
85
6.10. Callables
14:47
86
6.11. Map, Filter, Zip and List Comprehensions - Lecture
21:44
87
6.12. Map, Filter, Zip and List Comprehensions - Coding
21:15
88
6.13. Reducing Functions - Lecture
25:52
89
6.14. Reducing Functions - Coding
21:11
90
6.15. Partial Functions - Lecture
11:13
91
6.16. Partial Functions - Coding
25:33
92
6.17. The operator Module - Lecture
15:35
93
6.18. The operator Module - Coding
32:44
94
7.1. Introduction
01:32
95
7.2. Global and Local Scopes - Lecture
34:55
96
7.3. Global and Local Scopes - Coding
15:41
97
7.4. Nonlocal Scopes - Lecture
22:18
98
7.5. Nonlocal Scopes - Coding
14:38
99
7.6. Closures - Lecture
38:36
100
7.7. Closures - Coding
32:06
101
7.8. Closure Applications - Part 1
15:38
102
7.9. Closure Applications - Part 2
18:41
103
7.10. Decorators (Part 1) - Lecture
21:07
104
7.11. Decorators (Part 1) - Coding
20:59
105
7.12. Decorator Application (Timer)
35:17
106
7.13. Decorator Application (Logger, Stacked Decorators)
23:48
107
7.14. Decorator Application (Memoization)
29:15
108
7.15. Decorator Factories - Lecture
11:45
109
7.16. Decorator Factories - Coding
25:58
110
7.17. Decorator Application (Decorator Class)
09:41
111
7.18. Decorator Application (Decorating Classes)
48:24
112
7.19. Decorator Application (Dispatching) - Part 1
31:46
113
7.20. Decorator Application (Dispatching) - Part 2
35:46
114
7.21. Decorator Application (Dispatching) - Part 3
26:51
115
8.1. Introduction
03:19
116
8.2. Tuples as Data Structures - Lecture
19:02
117
8.3. Tuples as Data Structures - Coding
25:25
118
8.4. Named Tuples - Lecture
27:50
119
8.5. Named Tuples - Coding
35:15
120
8.6. Named Tuples - Modifying and Extending - Lecture
14:26
121
8.7. Named Tuples - Modifying and Extending - Coding
21:47
122
8.8. Named Tuples - DocStrings and Default Values - Lecture
13:31
123
8.9. Named Tuples - DocStrings and Default Values - Coding
15:47
124
8.10. Named Tuples - Application - Returning Multiple Values
06:23
125
8.11. Named Tuples - Application - Alternative to Dictionaries
28:46
126
9.1. Introduction
03:03
127
9.2. What is a Module
24:31
128
9.3. How does Python Import Modules
49:33
129
9.4. Imports and importlib
27:40
130
9.5. Import Variants and Misconceptions - Lecture
14:01
131
9.6. Import Variants and Misconceptions - Coding
27:04
132
9.7. Reloading Modules
18:30
133
9.8. Using __main__
27:02
134
9.9. Modules Recap
13:03
135
9.10. What are Packages - Lecture
20:25
136
9.11. What are Packages - Coding
27:12
137
9.12. Why Packages
13:08
138
9.13. Structuring Packages - Part 1
36:42
139
9.14. Structuring Packages - Part 2
27:28
140
9.15. Namespace Packages
10:39
141
9.16. Importing from Zip Archives
03:29
142
10.1. Python 3.10
25:18
143
10.2. Python 3.9
28:47
144
10.3. Python 3.8 3.7
34:26
145
10.4. Python 3.6 Highlights
07:50
146
10.5. Python 3.6 - Dictionary Ordering
19:46
147
10.6. Python 3.6 - Underscores in Numeric Literals
03:39
148
10.7. Python 3.6 - Preserved Order of kwargs and Named Tuple Application
05:34
149
10.8. Python 3.6 - f-Strings
09:20
150
11.1. Introduction
03:41
151
11.2. Additional Resources
12:54
152
11.3. Random Seeds
17:27
153
11.4. Random Choices
26:08
154
11.5. Random Samples
07:03
155
11.6. Timing code using timeit
16:18
156
11.7. Don't Use args and kwargs Names Blindly
07:36
157
11.8. Command Line Arguments
01:00:08
158
11.9. Sentinel Values for Parameter Defaults
11:03

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Read Book Python 3: Deep Dive (Part 1 - Functional)

#Title
11.1. Section 1 - Intro
21.4. Python Deep Dive 1
32.1. Quick Refresher Introduction
42.2. Python Type Hierarchy
52.3. Multi-Line Statements and Strings
62.4. Variable Names
73.2. 02 - Variables are Memory References
83.3. 03 - Reference Counting
93.4. 04 - Garbage Collection
103.5. 05 - Dynamic vs Static Typing
113.6. 06 - Variable Re-Assignment
123.7. 07 - Object Mutability
133.8. 08 - Function Arguments and Mutability
143.9. 09 - Shared References and Mutability
153.10. 10 - Variable Equality
163.11. 11 - Everything is an Object
173.12. 12 - Python Optimizations - Interning
183.13. 13 - Python Optimizations String Interning
193.14. 14 - Python Optimizations - Peephole
204.2. 02 - Integers Data Type
214.3. 03 - Integers - Operations
224.4. 04 - Integers - Constructors and Bases
234.6. 06 - Rational Numbers
244.8. 08 - Floats - Internal Representation
254.10. 10 - Floats - Equality Testing
264.12. 12 - Floats to Integers
274.14. 14 - Floats - Rounding
284.16. 16 - Decimals
294.18. 18 - Decimals - Constructors and Contexts
304.20. 20 - Decimals - Math Operations
314.22. 22 - Decimals - Performance Considerations
324.23. 23 - Complex Numbers
334.25. 25 - Booleans
344.26. 26 - Booleans - Truth Values - Lecture
354.28. 28 - Boolean - Precedence and Short-Circuiting
364.30. 30 - Boolean - Boolean Operators
374.32. 32 - Comparison Operators
385.2. 02 - Argument vs Parameter
395.3. 03 - Positional Arguments
405.5. 05 - Unpacking Iterables
415.7. 07 - Extended Unpacking
425.9. 09 - star-args
435.11. 11 - Keyword Arguments
445.13. 13 - kwargs
455.14. 14 - Putting it all together
465.17. 17 - Default Values
476.2. 02 - Docstrings and Annotations
486.4. 04 - Lambda Expressions
496.8. 08 - Function Introspection
506.10. 10 - Callables
516.11. 11 - Map, Filter, Zip
526.13. 13 - Reducing Functions
536.15. 15 - Partial Functions
546.17. 17 - The operator Module
557.2. 02 - Global and Local Scopes
567.4. 04 - NonLocal Sopes
577.6. 06 - Closures
587.10. 10 - Decorators 1
597.15. 15 - Decorators 2
608.2. 02 - Tuples
618.4. 04 - Named Tuples
628.6. 06 - Named Tuples - Modifying and Extending
638.8. 08 - Named Tuples - DocStrings and Default Values
649.5. 05 - Import Variants
659.9. 08 - Modules Recap
669.10. 09 - What are Packages
679.12. 11 - Why Packages
689.15. 14 - Namespace Packages
6911.2. Additional Resources

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