We’ll dive deep into itertools module to see all the functions and how useful they are. They can be. File size: 18.99GB
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 at the next level
Sequence Types and the sequence protocols
Iterables and iterable protocol
Iterators, the iterator protocol
Comprehendions and their relationship with closures
Generator functions
Generator expressions
Context managers
Creating context managers using generator functions
Generators 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 Tools are required
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
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 – 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
Custom Sequences Part 2C – Coding
21:10
Sorting Sequences – Lecture
17:52
Coding – Sorting Sequences
25:52
List Comprehensions – Lecture
17:54
List Comprehensions – Coding
47:16
–Project 1
01:00:16
Description of the Project
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 – Coding
11:44
Lecture on Iterators and Iterables
11:22
Iterators and Iterables: Coding
28:03
Example 1 – Manual Consuming Iterators
26:31
Example 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 on Reversed Iteration
09:49
Reversed iteration – Coding
20:00
Caveat: Use Iterators as 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
17:33
Example – Fibonacci Sequence
15:31
Making an Iterable From a Generator – Lecture
06:59
Making an Iterable From a Generator – Coding
06:40
Example – Card Deck
11:04
Lecture: Generator Expressions and Performance
09:17
Generator Expressions & Performance – Coding
30:19
Yield Starting at – Lecture
02:36
Yield Starting at – 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 and Aggregators
26:28
Slicing – Lecture
03:18
Slicing – Coding
11:33
Lecture: 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: 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
Project Description
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: Generators and Context Managers
10:46
Generators and context managers – Coding
13:12
The contextmanager Decorator Lecture
09:41
The contextmanager Decorator- Coding
24:26
Managers of Nested Context
34:28
There are 3 more sections
Requirements
This course is quite advanced, so you should be familiar with the basics. Python Both concepts and some in-The prerequisites for the course description describe depth knowledge. These should be checked and verified.
You will need Python 3.6 or higher, and a development environment you choose (command line, PyCharmm, Jupyter etc.).
Get your instant download Python 3: Deep Dive (Part 2 – Iteration, Generators)
Description
Part 2 This is how it works Python 3: Deep Dive Series is a type of in-Take a deep look at:
Sequences
iterables
Iterators
Generators
comprehensions
Context managers
Generator-based coroutines
I will show you how iteration works in Python The sequence protocol, the iterable, and iterator protocols are all covered. We also discuss how to write our own sequences and iterable data type.
We’ll discuss sequence slicing and its relationship to ranges in detail.
We will also be looking at comprehensions in more detail. I will show how list comprehensions can be closed and have their own scope. And why subtle bugs can sometimes sneak in to list comprehensions that might not be expected.
We’ll dive deep into itertools module to see all the functions and how useful they are. They can be.
We also examine generator functions, their relationship to iterators, as well as their comprehension counterparts (generator phrases).
Context managers are a common construct that is often overlooked PythonThe topic of context managers is also covered in great detail. We will learn how to create context managers and how to leverage them.
Finally, we’ll be discussing how generators can be used for creating coroutines.
Each section is followed with a project to put in practice what you have learned throughout the course.
This course series focuses primarily on the Python The standard library and language. There is a lot to understand and a lot of functionality in the standard CPython distribution. Python Deep dive, not exploration of the many useful 3rd-party libraries that have been created around Python They are often large enough for a whole course. Many of them do, in fact.
***** Prerequisites *****
Please note that this is an advanced version. Python Course, and a solid knowledge of some topics Python It 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 value and how every object has an associated truth worth
Named tuples
Zip, map, filter, sorted and reduce functions
lambdas
Importing modules and packages
These topics should also be familiar:
various data types (numeric, string, lists, tuples, dictionaries, sets, etc)
For loops, while loops break, continue, and the else clause
If statements
try…except…else…finally…
Basic knowledge of how to create classes (methods, properties), but no need to learn more advanced topics like inheritance or meta classes
Understand how certain methods are used in classes (such __init__ and __eq__), __lt__ and so on).
Who is this course for?
Python Developers who are interested in a deeper understanding about sequences, iterables and iterators.
