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

We will take a deep dive in the itertools module to see all of the functions and the many overlooked ones. These functions can be very useful. File size: 18.9 GB

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

What you’ll find

    You’ll be able to leverage the concepts in this course to take your Python Programming skills taken to the next level
The sequence protocol and the sequence type are both available.
Iterables and iterable protocol
Iterators and iterator protocol
Check out the list of comprehensions and their relationship to closures
Generator functions
Generator expressions
Managers of context
Creating context managers using generator functions
Generators can be used as coroutines

Download immediately Python 3: Deep Dive (Part 2 – Iteration, Generators)

Course content
Expand all 137 lectures34.40.22
–Introduction
15:37
Course Overview
Preview
06:30
Pre-Requisites
Preview
06:04
Python You will need tools
Preview
03:03
–Sequence Types
07:55:14
Introduction
Preview
01:23
Sequence Types – Lecture
Preview
17:10
Sequence Types – Coding
Preview
27:23
Mutable Sequence Types – Lecture
07:18
Mutable Sequence Types – Coding
18:06
Lists vs. Tuples
21:50
Rationale for Index Base and Slice Bounds
15:14
Copying Sequences – Lecture
29:25
Copying Sequences- Coding
23:28
Slicing – Lecture
32:08
Slicing – Coding
14:42
Custom Sequences – Part 1 – Lecture
10:40
Part 1 of Custom Sequences – Coding
34:00
In-Place Concatenation & Repetition – Lecture
05:34
In-Place Concatenation, Repetition – Coding
07:27
Assignments in Mutable Sequences Lecture
07:03
Assignments in Mutable Sequences – Coding
10:19
Part – Custom Sequences 2 – Lecture
09:17
Custom Sequences – Part 2A Coding
17:54
Custom Sequences Part 2B – Coding
34:49
Part 2C Custom Sequences – Coding
21:10
Sorting Sequences – Lecture
17:52
Coding – Sorting Sequences
25:52
List of Comprehensions – Lecture
17:54
Coding – List Comprehensions
47:16
–Project 1
01:00:16
Project Description
Preview
07:32
Project Solution: Goal 1
40:31
Project Solution: Goal 2
12:13
–Iterables and Iterators
04:51:39
Introduction
Preview
02:53
Iterating Collections – Lecture
11:19
Iterating collections – Coding
20:18
Iterators – Lecture
06:21
Iterators and Coding
11:44
Lecture on Iterators and Iterables
11:22
Iterators & Iterables – Coding
28:03
Example 1: Manual Consuming Iterators
26:31
Exemple 2 – Cyclic Ierators
31:33
Lazy Iterables – Lecture
03:44
Lazy Iterables Coding
14:59
Python’s Built-Lecture on In Iterables, Iterators
02:24
Python’s Built-In Iterables, Iterators and Coding
14:21
Sorting Iterables
08:51
Iter() Function – Lecture
06:26
Iter() Function – Coding
13:59
Iterating Callables – Lecture
04:42
Iterating Callables – Coding
15:53
Example 3: Delegating Iterators
07:41
Lecture: Reversed Iteration
09:49
Reversed iteration – Coding
20:00
Attention: Iterators are not Function Arguments
18:46
–Project 2
17:01
Description of the Project
Preview
03:29
Project Solution: Goal 1
05:50
Project Solution: Goal 2
07:42
–Generators
02:11:27
Introduction
Preview
01:21
Lecture: Yielding Functions and Generator Functions
17:38
Coding – Yielding and Generator Functions
17:33
Example – Fibonacci Sequence
15:31
Making an Iterable with a Generator – Lecture
06:59
Making an Iterable with a Generator – Coding
06:40
Example: Card Deck
11:04
Lecture: Generator Expressions and Performance
09:17
Generator Expressions & Performance – Coding
30:19
Yield from – Lecture
02:36
Yield from – Coding
12:29
–Project 3
01:01:58
Description of the Project
Preview
04:15
Project Solution: Goal 1
41:46
Project Solution: Goal 2
15:57
–Iteration Tools
04:25:49
Introduction
Preview
04:22
Aggregators – Lecture
10:05
Coding – Aggregators
26:28
Slicing – Lecture
03:18
Slicing – Coding
11:33
Lecture on Selecting and Filtering
10:02
Selecting and Filtering – Coding
15:07
Infinite Iterators – Lecture
05:29
Infinite Iterators Coding
18:49
Lecture: Chaining and Teeing
08:40
Coding: Chaining and Teeing
18:51
Lecture on Mapping and Reducing
15:54
Mapping and Reducing Coding
18:16
Zipping – Lecture
03:15
Zipping – Coding
06:54
Grouping – Lecture
10:00
Coding – Grouping
27:01
Combinatorics – Lecture
09:30
Combinatorics – Coding (Product)
21:26
Combinatorics – Coding (Permutation, Combination)
20:49
–Project 4
02:32:14
Description of the Project
Preview
11:49
Project Solution: Goal 1
43:50
Project Solution: Goal 2
38:41
Project Solution: Goal 3
07:17
Project Solution: Goal 4.
50:37
–Context Managers
03:34:00
Introduction
Preview
08:02
Context Managers – Lecture
22:46
Context Managers – Coding
37:10
Use Lazy Iterators with caution
03:49
Not just a Context Manager
07:33
Additional Uses – Lecture
06:04
Additional Uses: Coding
36:03
Lecture on Generators and Context Management
10:46
Generators and Context Managers for Coding
13:12
The contextmanager Decorator – Lecture
09:41
The contextmanager Decorator- Coding
24:26
Managers of Nested Context
34:28
Three more sections
Requirements

This course is very advanced so you should be familiar with basic concepts. Python Both concepts and some in-You will need to have a deep understanding of the course as described in the prerequisites. Make sure to check them and be certain!
You will require Python 3.6 or more, and a development environment you choose (command line. PyCharm. Jupyter.

Download immediately Python 3: Deep Dive (Part 2 – Iteration, Generators)

Description

Part 2 You can find this article here Python 3: Deep Dive A series is a combination of two or more things.-Take a deep look at:

Sequences

iterables

Iterators

Generators

comprehensions

Context managers

Coroutines based on generator

Let me show you how iteration works in Python This course covers everything you need to know about the sequence protocol, iterable and iterator protocol, and how to create your own sequence and iterable data type.

We’ll explain sequence slicing in more detail and how it affects ranges.

We will also be looking at comprehensions in more detail. I will show how list comprehensions can actually close and have their own scope. And why we sometimes get subtle bugs in to list comprehensions that are not expected.

We’ll dive deep into itertools and examine all functions there, and how helpful (but often overlooked) they are. These functions can be very useful.

We will also be looking at generator functions and their relationship to iterators as well as their comprehension counterparts (generator phrases).

Context managers are a commonly overlooked construct. PythonThis topic is also covered in detail. You will also learn how you can create and leverage your own context managers.

We’ll also look at how generators can be used to create coroutines.

Each section ends with a project to help you put the knowledge and skills gained throughout the course into practice.

This course series focuses primarily on the Python Language and the standard library. It is difficult to comprehend the functionality of the standard CPython distribution. Python Deep dive, not exploration of the many valuable 3rd-party libraries that have developed around Python These are often large enough to justify a whole course! Many of them do, in fact.

***** Prerequisites *****

This is an extremely advanced method. Python A strong understanding of certain topics is a plus. Python This is necessary.

You should have an in particular.-These topics require a deep understanding:

Functions and function arguments

Iterable packing and unpacking and how it is used with function arguments (i.e. using *)

Closings

Decorators

Boolean truth rates and how each object has an associated truth worth

named tuples

The zip, map filter, sorted and reduce functions

lambdas

Importing modules or packages

It is also important to have an understanding of the following topics.

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

Loops, while loops. Break, continue, the else clause

If statements

try…except…else…finally…

A basic understanding of how to create and utilize classes (methods, properties), is sufficient. No need for more advanced topics such inheritance or meta-classes

Understand how special methods are used in classes (e.g. __eq__ and __lt__).

Who is this course for?

Python Developers who are interested in a deeper understanding about sequences, iterables. Iterators. Generators.