Advanced Python: Best Practices and Design Patterns

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