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:
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Creating and using variables
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If-statements, loops and logical expressions
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Implementing your own functions and classes
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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:
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Memory management of variables in Python
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Mutable and Immutable Types
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Shallow and Deep Copies
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The correct use of containers (list, dict, set etc.)
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f-Strings formatting
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Functions and Decorators
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args and kwargs Arguments
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Object orientation and inheritance
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Special Dunder Methods
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Dataclass, Enum and NamedTuple
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The integration of Cython
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Using the Python C API (CPython)
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Using PyBind11 (introductory example)
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Using Numba and Mypyc
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Using multiprocessing and multithreading
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Global Interpreter Lock (GIL) in Python
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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
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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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