Advanced Python [GK821512]

OVERVIEW

This course will help you gain an understanding of Python's capabilities beyond basic syntax with a focus on widely accepted Pythonic constructs and procedures that will enable you to write reliable, optimized, and modular applications. This very hands-on course includes a deep dive into Pythonic data structures, exception handling, meta programming, regular expression, advanced file-handling, asynchronous programming, and more. At the completion of the course, you will also gain an understanding of unit testing in Python with lab-based practices designed to help you create and run unit test cases.

OBJECTIVES

This course has 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work in which you’ll learn:

Enhancements to classes
Advanced Python metaprogramming concepts
Writing robust code using exception handling
Working with different data structures supported in Python
Search and replace text with regular expressions
Easy-to-use and easy-to-maintain modules and packages
Creating multithreaded and multi-process applications
Implementing and execute unit tests

AUDIENCE

This course is designed for students with Python programming literacy who want to learn about advanced Python features and how to automate and simplify tasks.

CONTENT

Day 1

Python refresher

Built-in data types
Lists and tuples
Dictionaries and sets
Program structure
Files and console I/O
If statement
for and while loops

Data Structures and Algorithms

Linked list
Stack
Queue
Trees
Graphs
Sorting algorithms
Day 2

Errors and Exception Handling

Syntax errors
Exceptions
Using try/catch/else/finally
Handling multiple exceptions
Ignoring exceptions

Implementing Regular Expressions

RE Objects
Searching and matching
Using Regular Expression to search data sets
Searching for data in Wireshark Traces (Python and *.pcaps)
Compilation flags
Groups and special groups
Replacing text
Splitting strings

Advanced Functional Features of Python

Advanced unpacking
List Comprehension
Anonymous functions
Lambda expressions
Generator Expression
Decorator
Closure
Single/multi dispatch
Relative imports
Using __init__ effectively
Documentation best practices
Day 3

Metaprogramming

OOP conventions
Class/static data and methods
Parse information to create classes using a dictionary
Super() method
Metaclasses
Abstract base classes
Implementing protocols (context, iterator, etc.) with special methods
Implicit properties
Globals() and locals()
Working with object attributes
The inspect module
Callable classes
Monkey patching

Advanced file handling

Paths, directories, and filenames
Checking for existence
Permissions and other file attributes
Walking directory trees
Creating filters with fileinput
Using shutil for file operations
Day 4

Advanced Data Structure features in Python

Use defaultdict, Counter, and namedtuple
Create data classes
Store data offline with pickle
Pretty printing data structures
Compressed archives (zip, gzip, tar, etc.)
Persistent data

Multiprogramming

Concurrent programming
Multithreading
The threading module
Sharing variables
The queue module
The multiprocessing module
Creating pools
Coroutines
About async programming

Python Design Patterns

Need for design patterns and types
Creational
Structural
Behavioral
Best coding practices
Day 5

Developer Tools

Analyzing programs with pylint
Using the debugger
Profiling code
Testing speed with benchmarking

Unit testing with PyTest

What is a unit test
Testing with Unit-test framework
Testing with PyTest
Testing with doctest
Writing tests
Working with fixtures
Test runners
Mocking resources

Writing real-life applications

Build the classic minesweeper game in the command line
Build a program that can go into any folder on your computer and rename all of the files based on the conditions set in your Python code
Implement the binary search algorithm
Build a random password generator
Build a countdown timer using the time Python module.