Learning Path: Python: Guide to Become a Python Professional

Course Curriculum

Chapter 1: Modern Python Solutions Part 1

Lecture 1: The Course Overview

Lecture 2: Creating Meaningful Names and Using Variables

Lecture 3: Working with Large and Small Integers

Lecture 4: Choosing between Float, Decimal, and Fraction

Lecture 5: Choosing between True Division and Floor Division

Lecture 6: Rewriting an Immutable String

Lecture 7: String Parsing with Regular Expressions

Lecture 8: Building Complex Strings with “template”.format()

Lecture 9: Building Complex Strings from Lists of Characters

Lecture 10: Using the Unicode Characters that aren't on Our Keyboards

Lecture 11: Encoding Strings-Creating ASCII and UTF8 Bytes

Lecture 12: Decoding Bytes, How to Get Proper Characters from Some Bytes

Lecture 13: Using Tuples of Items

Lecture 14: Writing Python Script and Module Files

Lecture 15: Writing Long Lines of Code

Lecture 16: Including Descriptions and Documentation

Lecture 17: Writing Better RST Markup in docstring

Lecture 18: Designing Complex if…elif Chains

Lecture 19: Designing a While Statement that Terminates Properly

Lecture 20: Avoiding a Potential Problem with Break Statements

Lecture 21: Leveraging the Exception Matching Rules

Lecture 22: Avoiding a Potential Problem With an Except:Clause

Lecture 23: Chaining Exceptions with the Raise from Statement

Lecture 24: Managing a Context Using the With Statement

Lecture 25: Designing Functions with Optional Parameters

Lecture 26: Using Super Flexible Keyword Parameter

Lecture 27: Forcing Keyword-only Argument with the * Separator

Lecture 28: Writing Explicit Types on Function Parameters

Lecture 29: Picking an Order for Parameters Based on Partial Functions

Lecture 30: Writing Clear Documentation Strings

Lecture 31: Designing Recursive Functions Around Python’s Stack Limit

Lecture 32: Writing Reusable Script with the Script Library Switch

Lecture 33: Choosing a Data Structure

Lecture 34: Building Lists – Literals, Appending, and Comprehensions

Lecture 35: Slicing And Dicing a List

Lecture 36: Deleting From a List

Lecture 37: Reversing a Copy of a List

Lecture 38: Using Set Methods and Operators

Lecture 39: Removing Items from a Set

Lecture 40: Creating Dictionaries

Lecture 41: Removing from Dictionaries

Lecture 42: Controlling the Order of the Dict Keys

Lecture 43: Handling Dictionaries and Sets in doctest Examples

Lecture 44: Understanding Variables, References, and Assignment

Lecture 45: Making Shallow and Deep Copies of Objects

Lecture 46: Avoiding Mutable Default Values for Function Parameters

Lecture 47: Using Features of the print() Functions

Lecture 48: Using input() and getpass() for User Input

Lecture 49: Debugging with “Format”.Format_Map(Vars())

Lecture 50: Using Argparse to Get Command-line Input

Lecture 51: Using CMD for Creating Command-line Applications

Lecture 52: Using the OS Environment Settings

Chapter 2: Modern Python Solutions – Part 2

Lecture 1: The Course Overview

Lecture 2: Using a Class to Encapsulate Data and Processing

Lecture 3: Designing Classes with Lotsof Processing

Lecture 4: Designing Classes with Little Unique Processing

Lecture 5: Optimizing Small Objects with _slots_

Lecture 6: Using More Sophisticated Collections

Lecture 7: Extending a Collection

Lecture 8: Using Properties for Lazy Attributes

Lecture 9: Using Settable Properties to Update Eager Attributes

Lecture 10: Choosing Between Inheritance and Extension

Lecture 11: Separating Concerns via Multiple Inheritance

Lecture 12: Leveraging Python's Duck Typing

Lecture 13: Managing Global and Singleton Objects

Lecture 14: Using more Complex Structures

Lecture 15: Creating a Class that Has Orderable Object

Lecture 16: Defining an Ordered Collection

Lecture 17: Deleting from a List of Mappings

Lecture 18: Writing Generator Functions with the Yield Statement

Lecture 19: Using Stacked Generator Expression

Lecture 20: Applying Transformations to a Collection

Lecture 21: Picking a Subset

Lecture 22: Summarizing a Collection

Lecture 23: Combining Map and Reduce Transformations

Lecture 24: Implementing “There Exists” Processing

Lecture 25: Creating a Partial Function

Lecture 26: Simplifying Complex Algorithms with Immutable Data Structures

Lecture 27: Writing Recursive Generator Functions with the Yield from Statement

Lecture 28: Using pathlib to Work with Filenames

Lecture 29: Reading and Writing Files with Context Managers

Lecture 30: Replacing a File While Preserving the Previous Version

Lecture 31: Reading Delimited Files with the CSV Module

Lecture 32: Reading Complex Formats Using Regular Expressions

Lecture 33: Reading JSON Documents

Lecture 34: Reading XML Documents

Lecture 35: Reading HTML Documents

Lecture 36: Upgrading CSV from DictReader to the namedtuple Reader

Lecture 37: Upgrading CSV from a DictReader to a Namespace Reader

Lecture 38: Using Multiple Contexts for Reading and Writing Files

Lecture 39: Using the Built-in Statistic Library

Lecture 40: Average of Values in a Counter

Lecture 41: Computing the Coefficient of a Correlation

Lecture 42: Computing Regression Parameters

Lecture 43: Computing an Autocorrelation

Lecture 44: Confirming that the Data is Random – the Null Hypothesis

Lecture 45: Locating Outliers

Lecture 46: Analyzing Many Variables in One Pass