Python 3: Deep Dive (Part 1 – Functional)
Python 3: Deep Dive (Part 1 – Functional), available at $139.99, has an average rating of 4.79, with 161 lectures, based on 11636 reviews, and has 61343 subscribers.
You will learn about An in-depth look at variables, memory, namespaces and scopes A deep dive into Python's memory management and optimizations In-depth understanding and advanced usage of Python's numerical data types (Booleans, Integers, Floats, Decimals, Fractions, Complex Numbers) Advanced Boolean expressions and operators Advanced usage of callables including functions, lambdas and closures Functional programming techniques such as map, reduce, filter, and partials Create advanced decorators, including parametrized decorators, class decorators, and decorator classes Advanced decorator applications such as memoization and single dispatch generic functions Use and understand Python's complex Module and Package system Idiomatic Python and best practices Understand Python's compile-time and run-time and how this affects your code Avoid common pitfalls This course is ideal for individuals who are Anyone with a basic understanding of Python that wants to take it to the next level and get a really deep understanding of the Python language and its data structures. or Anyone preparing for an in-depth Python technical interview. It is particularly useful for Anyone with a basic understanding of Python that wants to take it to the next level and get a really deep understanding of the Python language and its data structures. or Anyone preparing for an in-depth Python technical interview.
Enroll now: Python 3: Deep Dive (Part 1 – Functional)
Summary
Title: Python 3: Deep Dive (Part 1 – Functional)
Price: $139.99
Average Rating: 4.79
Number of Lectures: 161
Number of Published Lectures: 161
Number of Curriculum Items: 161
Number of Published Curriculum Objects: 161
Original Price: $199.99
Quality Status: approved
Status: Live
What You Will Learn
- An in-depth look at variables, memory, namespaces and scopes
- A deep dive into Python's memory management and optimizations
- In-depth understanding and advanced usage of Python's numerical data types (Booleans, Integers, Floats, Decimals, Fractions, Complex Numbers)
- Advanced Boolean expressions and operators
- Advanced usage of callables including functions, lambdas and closures
- Functional programming techniques such as map, reduce, filter, and partials
- Create advanced decorators, including parametrized decorators, class decorators, and decorator classes
- Advanced decorator applications such as memoization and single dispatch generic functions
- Use and understand Python's complex Module and Package system
- Idiomatic Python and best practices
- Understand Python's compile-time and run-time and how this affects your code
- Avoid common pitfalls
Who Should Attend
- Anyone with a basic understanding of Python that wants to take it to the next level and get a really deep understanding of the Python language and its data structures.
- Anyone preparing for an in-depth Python technical interview.
Target Audiences
- Anyone with a basic understanding of Python that wants to take it to the next level and get a really deep understanding of the Python language and its data structures.
- Anyone preparing for an in-depth Python technical interview.
Hello!
This is Part 1 of a series of courses intended to dive into the inner mechanics and more complicated aspects of Python 3.
This is not a beginner course!
If you’ve been coding Python for a week or a couple of months, you probably should keep writing Python for a bit longer before tackling this series.
On the other hand, if you’ve been studying or programming in Python for a while, and are now starting to ask yourself questions such as:
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I wonder how this works?
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is there another, more pythonic, way, of doing this?
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what’s a closure? is that the same as a lambda?
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I know how to use a decorator someone else wrote, but how does it work? How do I write my own?
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why do some boolean expressions not return a boolean value? How can I use that to my advantage?
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how does the import mechanism in Python work, and why am I getting side effects?
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and similar types of question…
then this course is for you.
To get the most out of this course, you should be prepared to pause the coding videos, and attempt to write code before I do!Sit back during the concept/theory videos, but lean in for the code videos!
Please make sure you review the pre-requisites for this course (below) – although I give a brief refresh of basic concepts at the beginning of the course, those are concepts you should already be very comfortable with as you being this course.
In this course series, I will give you a much more fundamental and deeper understanding of the Python language and the standard library.
Python is called a “batteries-included” language for good reason – there is a ton of functionality in base Python that remains to be explored and studied.
So this course is not about explaining my favorite 3rd party libraries – it’s about Python, as a language, and the standard library.
In particular this course is based on the canonical CPython. You will also need Jupyter Notebooks to view the downloadable fully-annotated Python notebooks.
It’s about helping you explore Python and answer questions you are asking yourself as you develop more and more with the language.
In Python 3: Deep Dive (Part 1) we will take a much closer look at:
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Variables – in particular that they are just symbols pointing to objects in memory (references)
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Namespaces and scopes
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Python’s numeric types
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Python boolean type – there’s more to a simple or statement than you might think!
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Run-time vs compile-time and how that affects function defaults, decorators, importing modules, etc
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Functions in general (including lambdas)
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Functional programming techniques (such as map, reduce, filter, zip, etc)
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Closures
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Decorators
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Imports, modules and packages
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Tuples as data structures
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Named tuples
Course Prerequisites
This is an intermediate to advanced Python course.
To have the full benefit of this course you should be comfortable with the basic Python language including:
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variables and simple types such as str , bool , int and float types
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for and while loops
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if…else… statements
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using simple lists , tuples , dictionaries and sets
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defining functions (using the def statement)
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writing simple classes using the class keyword and the __init__ method, writing instance methods, creating basic properties using @property decorators
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importing modules from the standard library (e.g. import math)
You should also:
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have Python 3.6 (or higher) installed on your system
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be able to write and run Python programs using either:
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the command line, or
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a favorite IDE (such as PyCharm),
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have Jupyter Notebooks installed (which I use throughout this course so as to provide you fully annotated Python code samples)
Course Curriculum
Chapter 1: Introduction
Lecture 1: Course Overview
Lecture 2: Pre-Requisites
Lecture 3: Code Projects and Notebooks
Lecture 4: Course Slides
Chapter 2: A Quick Refresher – Basics Review
Lecture 1: Introduction
Lecture 2: The Python Type Hierarchy
Lecture 3: Multi-Line Statements and Strings
Lecture 4: Variable Names
Lecture 5: Conditionals
Lecture 6: Functions
Lecture 7: The While Loop
Lecture 8: Break, Continue and the Try Statement
Lecture 9: The For Loop
Lecture 10: Classes
Chapter 3: Variables and Memory
Lecture 1: Introduction
Lecture 2: Variables are Memory References
Lecture 3: Reference Counting
Lecture 4: Garbage Collection
Lecture 5: Dynamic vs Static Typing
Lecture 6: Variable Re-Assignment
Lecture 7: Object Mutability
Lecture 8: Function Arguments and Mutability
Lecture 9: Shared References and Mutability
Lecture 10: Variable Equality
Lecture 11: Everything is an Object
Lecture 12: Python Optimizations: Interning
Lecture 13: Python Optimizations: String Interning
Lecture 14: Python Optimizations: Peephole
Chapter 4: Numeric Types
Lecture 1: Introduction
Lecture 2: Integers: Data Types
Lecture 3: Integers: Operations
Lecture 4: Integers: Constructors and Bases – Lecture
Lecture 5: Integers: Constructors and Bases – Coding
Lecture 6: Rational Numbers – Lecture
Lecture 7: Rational Numbers – Coding
Lecture 8: Floats: Internal Representations – Lecture
Lecture 9: Floats: Internal Representations – Coding
Lecture 10: Floats: Equality Testing – Lecture
Lecture 11: Floats: Equality Testing – Coding
Lecture 12: Floats: Coercing to Integers – Lecture
Lecture 13: Floats: Coercing to Integers – Coding
Lecture 14: Floats: Rounding – Lecture
Lecture 15: Floats: Rounding – Coding
Lecture 16: Decimals – Lecture
Lecture 17: Decimals – Coding
Lecture 18: Decimals: Constructors and Contexts – Lecture
Lecture 19: Decimals: Constructors and Contexts – Coding
Lecture 20: Decimals: Math Operations – Lecture
Lecture 21: Decimals: Math Operations – Coding
Lecture 22: Decimals: Performance Considerations
Lecture 23: Complex Numbers – Lecture
Lecture 24: Complex Numbers – Coding
Lecture 25: Booleans
Lecture 26: Booleans: Truth Values – Lecture
Lecture 27: Booleans: Truth Values – Coding
Lecture 28: Booleans: Precedence and Short-Circuiting – Lecture
Lecture 29: Booleans: Precedence and Short-Circuiting – Coding
Lecture 30: Booleans: Boolean Operators – Lecture
Lecture 31: Booleans: Boolean Operators – Coding
Lecture 32: Comparison Operators
Chapter 5: Function Parameters
Lecture 1: Introduction
Lecture 2: Argument vs Parameter
Lecture 3: Positional and Keyword Arguments – Lecture
Lecture 4: Positional and Keyword Arguments – Coding
Lecture 5: Unpacking Iterables – Lecture
Lecture 6: Unpacking Iterables – Coding
Lecture 7: Extended Unpacking – Lecture
Lecture 8: Extended Unpacking – Coding
Lecture 9: *args – Lecture
Lecture 10: *args – Coding
Lecture 11: Keyword Arguments – Lecture
Lecture 12: Keyword Arguments – Coding
Lecture 13: **kwargs
Lecture 14: Putting it all Together – Lecture
Lecture 15: Putting it all Together – Coding
Lecture 16: Application: A Simple Function Timer
Lecture 17: Parameter Defaults – Beware!!
Lecture 18: Parameter Defaults – Beware Again!!
Chapter 6: First-Class Functions
Lecture 1: Introduction
Lecture 2: Docstrings and Annotations – Lecture
Lecture 3: Docstrings and Annotations – Coding
Lecture 4: Lambda Expressions – Lecture
Lecture 5: Lambda Expressions – Coding
Lecture 6: Lambdas and Sorting
Lecture 7: Challenge – Randomize an Iterable using Sorted!!
Lecture 8: Function Introspection – Lecture
Lecture 9: Function Introspection – Coding
Lecture 10: Callables
Lecture 11: Map, Filter, Zip and List Comprehensions – Lecture
Lecture 12: Map, Filter, Zip and List Comprehensions – Coding
Lecture 13: Reducing Functions – Lecture
Lecture 14: Reducing Functions – Coding
Lecture 15: Partial Functions – Lecture
Lecture 16: Partial Functions – Coding
Instructors
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Dr. Fred Baptiste
Software Engineer and Mathematician
Rating Distribution
- 1 stars: 29 votes
- 2 stars: 40 votes
- 3 stars: 302 votes
- 4 stars: 2451 votes
- 5 stars: 8818 votes
Frequently Asked Questions
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You can view and review the lecture materials indefinitely, like an on-demand channel.
Can I take my courses with me wherever I go?
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