Advanced Python: Exploring the Standard Library

[LeeAndro]

MP4 | Video: h264, 1280x720 | Audio: AAC, 44.1 KHz, 2 ChGenre: eLearning | Language: English + srt | Duration: 62 lectures (9h 32m) | Size: 3.27 GB

Deep dive into Python's standard library and understand the inner workings of callables and collections

Students will gain mastery of the Python standard library and an advanced understanding of Python's universe of OOP and functional programming tools

Familiarity and experience with Python.

This course will not review basic Python syntax or concepts, such as functions, loops, if/else conditions, etc.

There are many wonderful courses that focus on bning aspects of Python on Udemy and other online learning platforms. However, there's relatively fewer courses for more experienced Python developers to continue levelling up their skills and intuition. If you're a Python developer that is looking to develop a deeper intuition of the language, this course is for you.
Part of the learning curve is the Python standard library, which offers a rich set of tools built upon core design patterns that are found everywhere in the Python ecosystem. Understanding how the basic building blocks of Python applications are constructed will give you the intuition and vision to architect more maintainable, performant, and Pythonic code.
Since the Python ecosystem is vast, this course aims to cover only a few select topics in detail while still digging deep into Python's standard library. You'll learn about
functools / callables (decorators and functools utilities/helpers)
collections (Counters, ChainMaps, etc.)
descriptors and properties
regular expressions (named expressions, backreferences, capture groups, etc.)
You'll understand how Python's standard library was constructed, and gain a deeper intuition into advanced functionality offered by the standard library.
Prior knowledge: This course assumes a basic understanding of Python and object-oriented programming, and is not intended for bning programmers.
Future iterations of the course will include other topics.

Software developers or data scientists/analysts with a strong core familiarity with Python, object-oriented programming, and data structures.
Python students who feel like their progress has plateaued after learning the initial basics of Python.






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