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Advanced Python: Best Practices and Design Patterns

Advanced Python: Best Practices and Design Patterns

Course 1906

Duration: 4 days
Labs: Yes
Language: English
Level: Advanced

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 Course Delivery Methods

In-Person
Online

Advanced Python Course Benefits

Unit test, debug, and install Python programmes and modules

Profile programme execution and improve performance

Apply advanced Python programming features for efficient, reliable, and maintainable programmes

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 programme 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 programme 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
Synchronise threads using locks
Launch operating system commands as subprocesses
Synchronise processes with queues
Parallelise execution using process pools and Executors

Get This Course £1,975

4-day instructor-led training course
After-course instructor coaching benefit
Learning Tree end-of-course exam included

Include dates with afternoon start times

#1906

Jan 30 - Feb 2 2:00 PM - 9:30 PM GMT

New York or Virtual
Feb 19 - 22 9:00 AM - 5:00 PM GMT

London or Virtual
Feb 20 - 23 2:00 PM - 9:30 PM GMT

Ottawa or Virtual
Apr 9 - 12 2:00 PM - 9:30 PM BST

Herndon, VA or Virtual
Apr 23 - 26 2:00 PM - 9:30 PM BST

Virtual
May 7 - 10 3:00 PM - 10:30 PM BST

Austin or Virtual
May 21 - 24 9:00 AM - 5:00 PM BST

London or Virtual
May 28 - 31 2:00 PM - 9:30 PM BST

Ottawa or Virtual
Jul 9 - 12 2:00 PM - 9:30 PM BST

Herndon, VA or Virtual
Aug 13 - 16 2:00 PM - 9:30 PM BST

Ottawa or Virtual
Aug 27 - 30 9:00 AM - 5:00 PM BST

London or Virtual

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Blended learning models
Tailored content
Expert team coaching

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Advanced Python Course FAQs

This is an advanced, fast-paced programming course. If you're completely new to Python, or know only the basics of the language, we suggest you start with either Python Fundamentals Training for Non-Programmers or Introduction to Python Training.

Absolutely! This course builds on the skills you developed in the introduction course and takes you to the next level of your proficiency with Python.

The course software uses a recent version of Python 3.

Yes, nearly all of the Python features we discuss have been back-ported to Python 2.7. Most of the examples and exercises will run under Python 2.7 with minor changes, and any language features that are not supported in Python 2.7 are clearly identified in the notes.

You will complete your exercises on a virtual machine (VM) running Microsoft Windows. The IDE for the exercises is PyCharm from Jetbrains, which is pre-installed on your VM.

This course expands on your basic Python programming skills to help you build applications that are faster, more reliable, and easier to maintain and debug. You'll gain experience not only with advanced Python techniques, you'll also learn how to implement proven software design patterns in your applications. And you'll learn valuable Python testing tools that help ensure that your code works as designed.

Yes, at the end of the class you can copy your code from your VM to your favorite cloud storage provider (Google Drive, Dropbox, etc.) You'll also receive a copy of all the examples and solutions to all hands-on exercises.