Intermediate Python- Memory, Decorator, Async, Cython more

Intermediate Python: Memory, Decorator, Async, Cython & more, available at $69.99, has an average rating of 4.07, with 63 lectures, 14 quizzes, based on 65 reviews, and has 801 subscribers.

You will learn about Memory management of variables in Python (Mutability) The correct use of sequences and iterables Functions, Decorators, Lambdas etc. Object orientation and inheritance The integration of Cython code Using the Python C API Async and Parallel Code This course is ideal for individuals who are Python developer with basic knowledge It is particularly useful for Python developer with basic knowledge.

Enroll now: Intermediate Python: Memory, Decorator, Async, Cython & more

Summary

Title: Intermediate Python: Memory, Decorator, Async, Cython & more

Price: $69.99

Average Rating: 4.07

Number of Lectures: 63

Number of Quizzes: 14

Number of Published Lectures: 63

Number of Published Quizzes: 14

Number of Curriculum Items: 77

Number of Published Curriculum Objects: 77

Original Price: $29.99

Quality Status: approved

Status: Live

What You Will Learn

Memory management of variables in Python (Mutability)

The correct use of sequences and iterables

Functions, Decorators, Lambdas etc.

Object orientation and inheritance

The integration of Cython code

Using the Python C API

Async and Parallel Code

Who Should Attend

Python developer with basic knowledge

Target Audiences

Python developer with basic knowledge

The course was updated in November 2023 for the newest Python Version 3.12!

Course Description:

The course covers intermediate to advanced Python programming techniques.
This means that the course is not aimed at programming beginners.
This course is compact, instructive, and useful. You learn not only how to use Python well, but also more abstract concepts that are transferable to other languages, as well as how to create a good programming environment.

Prerequisites:

 Creating and using variables  

 If-statements, loops and logical expressions  

 Implementing your own functions and classes  

 Importing from external packages  

In the course we will use Visual Studio Code (VSCode) as the IDE which is free for all operating systems.
I assume that you have already Python 3.8 or newer on your system, if not you could install it via Anaconda for example.

This course consists of the following topics:

Memory management of variables in Python  

Mutable and Immutable Types

Shallow and Deep Copies

The correct use of containers (list, dict, set etc.)

f-Strings formatting

Functions and Decorators

args and kwargs Arguments

Object orientation and inheritance  

Special Dunder Methods

Dataclass, Enum and NamedTuple

The integration of Cython  

Using the Python C API (CPython)

Using PyBind11 (introductory example)

Using Numba and Mypyc

Using multiprocessing and multithreading

Global Interpreter Lock (GIL) in Python

Using asynchronous programming

Become a pro today, in the technology of tomorrow!
See you in class!

Course Curriculum

Chapter 1: Chapter 1: Introduction and Software

Lecture 1: Introduction to the course

Lecture 2: Course manual

Lecture 3: Course materials

Lecture 4: The creation of the environment

Lecture 5: Visual Studio Code Setup

Chapter 2: Chapter 2 – 0: Python Pro 101

Lecture 1: Simple Type Annotations

Lecture 2: f-Strings – Part 1

Chapter 3: Chapter 2 – 1: Numeric values

Lecture 1: Integers

Lecture 2: Floats

Chapter 4: Chapter 2 – 2: Logical expressions

Lecture 1: Booleans

Lecture 2: Match-Statement

Chapter 5: Chapter 2 – 3: Memory management

Lecture 1: Variables and references

Lecture 2: Mutability of data types

Lecture 3: In-Place-Operationen und Shallow/Deep Copy

Chapter 6: Chapter 3 – 1: Container

Lecture 1: Lists

Lecture 2: Tuples

Lecture 3: Dictionaries

Lecture 4: Sets

Chapter 7: Chapter 3 – 2: Strings, Files and f-Strings

Lecture 1: Strings

Lecture 2: f-Strings

Lecture 3: Paths and Filesystem

Chapter 8: Chapter 4 – 1: Functions

Lecture 1: Functions

Lecture 2: Problems with Default Arguments

Lecture 3: *args and **kwargs

Lecture 4: Special Parameters

Lecture 5: Commandline Arguments – Part 1

Lecture 6: Commandline Arguments – Part 2

Lecture 7: Commandline Arguments – Part 3

Chapter 9: Chapter 4 – 2: Closures and Decorators

Lecture 1: Closures and Decorator

Lecture 2: More about Decorator

Chapter 10: Chapter 5: Object orientation

Lecture 1: StaticMethods and ClassMethods

Lecture 2: AbstractMethods

Lecture 3: Property

Lecture 4: Dunder Methods

Lecture 5: Method Resolution Order

Lecture 6: Type vs. Isinstance vs. Issubclass

Lecture 7: __init__ vs. __new__

Lecture 8: Context Manager

Lecture 9: Iterator and Generator

Lecture 10: ABC Container

Lecture 11: Dataclass and Slots

Lecture 12: NamedTuple and TypedDict

Lecture 13: Enum

Chapter 11: Chapter 6: Cython and CPython

Lecture 1: Python Packages 101

Lecture 2: Foreword

Lecture 3: Cython

Lecture 4: Numba

Lecture 5: Mypyc

Lecture 6: CPython

Lecture 7: Another CPython Example

Lecture 8: Pybind11

Lecture 9: Benchmark

Chapter 12: Chapter 7: Threads, Processes and Async

Lecture 1: Threads, Processes and Async

Lecture 2: Threads

Lecture 3: Global Interpreter Lock

Lecture 4: Thread Pool

Lecture 5: Processes

Lecture 6: Process Pool

Lecture 7: Threads vs. Process – Recap

Lecture 8: Asyncio

Lecture 9: Asyncio Gather

Chapter 13: Chapter 8: Conclusion of the course

Lecture 1: Course conclusion

Lecture 2: Bonus lecture

Instructors

Jan Schaffranek
M.Sc in Computer Science – Machine Learning, C/C++, Python

Rating Distribution

1 stars: 4 votes

2 stars: 2 votes

3 stars: 5 votes

4 stars: 19 votes

5 stars: 35 votes

Frequently Asked Questions

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