Rock Solid Python with Python Typing Course

4h 27m 54s
English
Paid
April 25, 2024

When Python was originally invented way back in 1989, it was a truly dynamic and typeless programming language. But that all changed in Python 3.5 when type "hints" were added to the language. Over time, amazing frameworks took that idea and ran with it. They build powerful and type safe(er) frameworks. Some of these include Pydantic, FastAPI, Beanie, SQLModel, and many many more. In this course, you'll learn the ins-and-outs of Python typing in the language, explore some popular frameworks using types, and get some excellent advice and guidance for using types in your applications and libraries.

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In this course, you will:

  1. Compare popular static languages with Python (such as Swift, C#, TypeScript, and others)
  2. See a exact clone of a dynamic Python codebase along side the typed version
  3. Learn how and when to create typed variables
  4. Understand Python's strict nullability in its type system
  5. Specify constant (unchangeable) variables and values
  6. Reduce SQL injection attacks with LiteralString
  7. Uses typing with Python functions and methods
  8. Use typing with classes and class variables
  9. Work with multiple numerical types with Python's numerical type ladder
  10. Use Pydantic to model and parse complex data in a type strict manner
  11. Create an API with FastAPI that exchanges data with type integrity
  12. Query databases with Pydantic using the Beanie ODM
  13. Create CLI apps using type information to define the CLI interface
  14. Leverage mypy for verifying the integrity of your entire codebase in CI/CD
  15. Add runtime type safety to your application
  16. Marry duck typing and static typing with Python's new Protocol construct
  17. Learn design patterns and guidance for using types in Python code

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# Title Duration
1 Welcome 01:57
2 Python Language Typing Definition 02:41
3 What We'll Cover 02:42
4 Goal: Not 100% 01:11
5 You'll Need Python 3.10 or Newer 01:07
6 git the Repo 01:22
7 Meet Your Instructor 01:38
8 Spectrum of Type Strictness 06:37
9 Running the Source Code 03:26
10 Motorcycle Class, Untyped 05:36
11 Using the Untyped Motorcycle 02:21
12 Duck Typing 03:03
13 TypeScript Motorcycles 04:40
14 C# Motorcycle and Why Types Can Detract from Readability 05:02
15 A Very Swift Motorcycle 04:04
16 Typed Python Motorcycles 07:38
17 Python Typing Introduction 00:33
18 Where Do Python Type Hints Come From? 01:14
19 Typing and Variables 03:23
20 Survey of Core Types 03:05
21 Nullable Types 05:22
22 Unions 03:11
23 If You Don't Know the Type 02:03
24 Constants 03:37
25 Avoiding Injection Attacks with LiteralString 06:02
26 Functions: Basic Typing 05:13
27 Functions: void Functions 02:44
28 Functions: Functions as Objects 05:34
29 Typing for Container Data Types 07:22
30 More Complex Containers 08:28
31 Classes and Typing 06:27
32 Externally Defining Types 04:27
33 Adding Our Own Types 03:56
34 Representing Multiple Numerical Types 04:13
35 Generics Available in Python 3.12 01:45
36 Gradual Typing 03:11
37 Frameworks Introduciton 00:46
38 Pydantic Foundations 02:24
39 Pydantic Code Example 01:00
40 pip-tools for Adding Requirements 03:16
41 Parsing Basic Data with Pydantic 08:57
42 Data-Rich Pydantic Example 06:03
43 Web frameworks using Type Hints 04:58
44 Database Frameworks Built on Pydantic 03:40
45 CLIs with Python Types 02:09
46 Setting up Our FastAPI Example 03:43
47 FastAPI, Beanie, and Pydantic MongoDB Example 04:27
48 Setting up the DB to Run the Code Yourself 02:08
49 Tools Introduction 00:42
50 Editors (Round 2) 02:26
51 Full Project Inspection 06:12
52 Static Type Checkers 01:32
53 mypy in Action 05:14
54 Runtime Type Checking with Beartype 01:56
55 Getting Started with Beartype 06:43
56 Beartype Speed Test 07:01
57 Orthogonal/Structural Typing Introduction 01:06
58 Inheritance Gone Wrong, an Example 06:11
59 Static duck typing with Protocols 08:24
60 Structural Typing Visualized 01:19
61 Patterns Introduction 01:11
62 Types on the Boundary 02:05
63 Public Packages 01:30
64 Autocomplete 01:10
65 To Optional or Not 03:11
66 Versions of Python 04:19
67 Minimalism Overview 04:12
68 Minimalism Code 01:45
69 Refactoring Motivation 01:31
70 Refactoring with Types 02:37
71 Point of No Return 07:39
72 Collection Advice 02:27
73 Conclusion 05:05

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