Advanced Python: Best Practices and Design Patterns

Course Outline

This advanced Python training course will expand your foundational Python programming skills to build reliable and stable applications. In this course, you will learn how to:

Employ design patterns and best practices in Python applications
Exploit the object-oriented programming features in Python for stable, reliable programs
Create and manage concurrent threads of control
Generate and consume REST web service requests and responses
Implement Gang of Four (GoF) design patterns to solve commonly recurring software design problems

Advanced Python: Best Practices and Design Patterns Benefits

Unit test, debug, and install Python programs and modules
Profile program execution and improve performance
Apply advanced Python programming features for efficient, reliable, and maintainable programs
Gain knowledge and skills applicable to all Python environments, including Microsoft Windows, macOS, and all Linux and UNIX distributions
Test your knowledge in the included end-of-course exam
Continue learning and face new challenges with after-course one-on-one instructor coaching

Advanced Python Course Outline

Module 1: Object-Oriented Programming in Python

In this module, you will learn how to:

Extend classes to define subclasses
Add properties to a class
Define abstract base classes

Module 2: Exploring Python Features

In this module, you will learn how to:

Write "Pythonic" code
Modify code dynamically with monkey patching
Process large data structures efficiently with generators
Handle exceptions
Raise user-defined exceptions
Reduce code complexity with context managers and the "with" statement

Module 3: Verifying Code and Unit Testing

In this module, you will learn how to:

Develop and run Python unit tests
Simplify automated testing with the Pytest package
Verify code behavior
Mock dependent objects with the Mock package
Use mock objects to verify code behavior when exceptions occur

Module 4: Detecting Errors and Debugging Techniques

In this module, you will learn how to:

Log messages for auditing and debugging
Check your code for potential bugs with Pylint
Debug your Python code
Extract error information from exceptions
Trace program execution with the PyCharm IDE

Module 5: Implementing Python Design Patterns

In this module, you will learn how to:

Implement the Decorator pattern using @decorator
Control access to an object with the Proxy pattern
Lay out a skeleton algorithm in the Template Method pattern
Enable loose coupling between classes with the Observer pattern

Module 6: Interfacing with REST Web Services and Clients

In this module, you will learn how to:

Build a REST service
Generate JSON responses to support Ajax clients
Send REST requests from a Python client
Consume JSON and XML response data

Module 7: Measuring and Improving Application Performance

In this module, you will learn how to:

Time execution of functions with the "timeit" module
Profile program execution using "cProfile"
Manipulate an execution profile interactively with "pstats"
Efficiently apply data structures, including lists, dictionaries, and tuples
Map and filter data sets using comprehensions
Replace the standard Python interpreter with PyPy

Module 8: Installing and Distributing Modules

In this module, you will learn how to:

Install modules from the PyPi repository using "pip"
Port code between Python versions
Package Python modules and applications
Establish isolated Python environments with "virtualenv"
Build a distribution package with "setuptools"
Upload your Python modules to a local repository

Module 9: Concurrent Execution

In this module, you will learn how to:

Create and manage multiple threads of control with the Thread class
Synchronize threads using locks
Launch operating system commands as subprocesses
Synchronize processes with queues
Parallelize execution using process pools and Executors

Advanced Python: Best Practices and Design Patterns

Course Outline