Python 3: Deep Dive (Part 2 - Iteration, Generators)

34h 42m 47s
English
Paid
May 2, 2024

I will show you exactly how iteration works in Python - from the sequence protocol, to the iterable and iterator protocols, and how we can write our own sequence and iterable data types. We'll go into some detail to explain sequence slicing and how slicing relates to ranges. We look at comprehensions in detail as well and I will show you how list comprehensions are actually closures and have their own scope, and the reason why subtle bugs sometimes creep in to list comprehensions that we might not expect.

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Part 2 of this Python 3: Deep Dive series is an in-depth look at:

  • sequences

  • iterables

  • iterators

  • generators

  • comprehensions

  • context managers

  • generator based coroutines

We'll take a deep dive into the itertools module and look at all the functions available there and how useful (but overlooked!) they can be.

We also look at generator functions, their relation to iterators, and their comprehension counterparts (generator expressions).

Context managers, an often overlooked construct in Python, is covered in detail too. There we will learn how to create and leverage our own context managers and understand the relationship between context managers and generator functions.

Finally, we'll look at how we can use generators to create coroutines.

Each section is followed by a project designed to put into practice what you learn throughout the course.

This course series is focused on the Python language and the standard library. There is an enormous amount of functionality and things to understand in just the standard CPython distribution, so I do not cover 3rd party libraries - this is a Python deep dive, not an exploration of the many highly useful 3rd party libraries that have grown around Python - those are often sufficiently large to warrant an entire course unto themselves! Indeed, many of them already do!

Please note that this is a relatively advanced Python course, and a strong knowledge of some topics in Python is required. 

In particular you should already have an in-depth understanding of the following topics:

  • functions and function arguments

  • packing and unpacking iterables and how that is used with function arguments (i.e. using *)

  • closures

  • decorators

  • Boolean truth values and how any object has an associated truth value

  • named tuples

  • the zip, map, filter, sorted, reduce functions

  • lambdas

  • importing modules and packages

You should also have a basic knowledge of the following topics:

  • various data types (numeric, string, lists, tuples, dictionaries, sets, etc)

  • for loops, while loops, break, continue, the else clause

  • if statements

  • try...except...else...finally...

  • basic knowledge of how to create and use classes (methods, properties) - no need for advanced topics such as inheritance or meta classes

  • understand how certain special methods are used in classes (such as __init__, __eq__, __lt__, etc)

Requirements:
  • This is a relatively advanced course, so you should already be familiar with basic Python concepts, as well as some in-depth knowledge as described in the prerequisites in the course description. Please be sure you check those and make sure!
  • 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:
  • Python developers who want a deeper understanding of sequences, iterables, iterators, generators and context managers.

What you'll learn:

  • You'll be able to leverage the concepts in this course to take your Python programming skills to the next level.
  • Sequence Types and the sequence protocol
  • Iterables and the iterable protocol
  • Iterators and the iterator protocol
  • List comprehensions and their relation to closures
  • Generator functions
  • Generator expressions
  • Context managers
  • Creating context managers using generator functions
  • Using Generators as Coroutin

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# Title Duration
1 Course Overview 06:31
2 Pre-Requisites 06:05
3 Python Tools Needed 03:04
4 Introduction 01:24
5 Sequence Types - Lecture 17:11
6 Sequence Types - Coding 27:24
7 Mutable Sequence Types - Lecture 07:19
8 Mutable Sequence Types - Coding 18:07
9 Lists vs Tuples 21:51
10 Index Base and Slice Bounds - Rationale 15:15
11 Copying Sequences - Lecture 29:26
12 Copying Sequences - Coding 23:29
13 Slicing - Lecture 32:09
14 Slicing - Coding 14:43
15 Custom Sequences - Part 1 - Lecture 10:41
16 Custom Sequences - Part 1 - Coding 34:01
17 In-Place Concatenation and Repetition - Lecture 05:35
18 In-Place Concatenation and Repetition - Coding 07:28
19 Assignments in Mutable Sequences - Lecture 07:04
20 Assignments in Mutable Sequences - Coding 10:20
21 Custom Sequences - Part 2 - Lecture 09:18
22 Custom Sequences - Part 2A - Coding 17:56
23 Custom Sequences - Part 2B - Coding 34:50
24 Custom Sequences - Part 2C - Coding 21:11
25 Sorting Sequences - Lecture 17:53
26 Sorting Sequences - Coding 25:53
27 List Comprehensions - Lecture 17:56
28 List Comprehensions - Coding 47:17
29 Project Description 07:33
30 Project Solution: Goal 1 40:33
31 Project Solution: Goal 2 12:14
32 Introduction 02:54
33 Iterating Collections - Lecture 11:20
34 Iterating Collections - Coding 20:19
35 Iterators - Lecture 06:22
36 Iterators - Coding 11:45
37 Iterators and Iterables - Lecture 11:23
38 Iterators and Iterables - Coding 28:04
39 Example 1 - Consuming Iterators Manually 26:32
40 Example 2 - Cyclic Iterators 31:34
41 Lazy Iterables - Lecture 03:45
42 Lazy Iterables - Coding 15:00
43 Python's Built-In Iterables and Iterators - Lecture 02:25
44 Python's Built-In Iterables and Iterators - Coding 14:22
45 Sorting Iterables 08:52
46 The iter() Function - Lecture 06:27
47 The iter() Function - Coding 14:00
48 Iterating Callables - Lecture 04:43
49 Iterating Callables - Coding 15:54
50 Example 3 - Delegating Iterators 07:42
51 Reversed Iteration - Lecture 09:50
52 Reversed Iteration - Coding 20:01
53 Caveat: Using Iterators as Function Arguments 18:47
54 Project Description 03:30
55 Project Solution: Goal 1 05:52
56 Project Solution: Goal 2 07:43
57 Introduction 01:22
58 Yielding and Generator Functions - Lecture 17:39
59 Yielding and Generator Functions - Coding 17:34
60 Example - Fibonacci Sequence 15:32
61 Making an Iterable from a Generator - Lecture 07:00
62 Making an Iterable from a Generator - Coding 06:41
63 Example - Card Deck 11:05
64 Generator Expressions and Performance - Lecture 09:18
65 Generator Expressions and Performance - Coding 30:20
66 Yield From - Lecture 02:37
67 Yield From - Coding 12:30
68 Project Description 04:16
69 Project Solution: Goal 1 41:47
70 Project Solution: Goal 2 15:58
71 Introduction 04:23
72 Aggregators - Lecture 10:06
73 Aggregators - Coding 26:29
74 Slicing - Lecture 03:19
75 Slicing - Coding 11:34
76 Selecting and Filtering - Lecture 10:03
77 Selecting and Filtering - Coding 15:08
78 Infinite Iterators - Lecture 05:30
79 Infinite Iterators - Coding 18:50
80 Chaining and Teeing - Lecture 08:41
81 Chaining and Teeing - Coding 18:53
82 Mapping and Reducing - Lecture 15:55
83 Mapping and Reducing - Coding 18:17
84 Zipping - Lecture 03:16
85 Zipping - Coding 06:55
86 Grouping - Lecture 10:01
87 Grouping - Coding 27:02
88 Combinatorics - Lecture 09:31
89 Combinatorics - Coding (Product) 21:27
90 Combinatorics - Coding (Permutation, Combination) 20:50
91 Project - Description 11:50
92 Project Solution: Goal 1 43:51
93 Project Solution: Goal 2 38:42
94 Project Solution: Goal 3 07:18
95 Project Solution: Goal 4 50:39
96 Introduction 08:03
97 Context Managers - Lecture 22:47
98 Context Managers - Coding 37:11
99 Caveat when used with Lazy Iterators 03:50
100 Not just a Context Manager 07:34
101 Additional Uses - Lecture 06:05
102 Additional Uses - Coding 36:04
103 Generators and Context Managers - Lecture 10:47
104 Generators and Context Managers - Coding 13:14
105 The contextmanager Decorator - Lecture 09:43
106 The contextmanager Decorator - Coding 24:27
107 Nested Context Managers 34:29
108 Project - Description 07:18
109 Project Solution: Goal 1 17:51
110 Project Solution: Goal 2 11:02
111 Introduction 07:42
112 Coroutines - Lecture 25:36
113 Coroutines - Coding 17:12
114 Generator States - Lecture 03:12
115 Generator States - Coding 06:48
116 Sending to Generators - Lecture 14:49
117 Sending to Generators - Coding 20:05
118 Closing Generators - Lecture 08:28
119 Closing Generators - Coding 27:21
120 Sending Exceptions to Generators - Lecture 07:54
121 Sending Exceptions to Generators - Coding 24:18
122 Using Decorators to Prime Coroutines - Lecture 05:42
123 Using Decorators to Prime Coroutines - Coding 08:47
124 Yield From - Two-Way Communications - Lecture 10:30
125 Yield From - Two-Way Communications - Coding 15:13
126 Yield From - Sending Data - Lecture 05:57
127 Yield From - Sending Data - Coding 26:56
128 Yield From - Closing and Return - Lecture 06:24
129 Yield From - Closing and Return - Coding 14:17
130 Yield From - Throwing Exceptions - Lecture 02:48
131 Yield From - Throwing Exceptions - Coding 25:31
132 Application - Pipelines - Lecture 04:35
133 Application - Pipelines - Pulling Data 11:28
134 Application - Pipelines - Pushing Data 09:05
135 Application - Pipelines - Broadcasting Data 32:39
136 Project Description 01:50
137 Project Solution 14:19

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