Advanced Python

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.

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

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.

Students should have experience writing Python scripts, as well as a user-level knowledge of Unix/Linux, Mac, or Windows.