Advanced Python: Best Practices and Design Patterns

Level: Advanced
Rating: 4.6/5 4.61/5 Based on 195 Reviews

This advanced Python training course will expand upon your fundamental Python programming skills to build reliable and stable applications. You will learn to employ design patterns and best practises in Python applications, exploit the OOP features in Python for stable, reliable programs and, create and manage concurrent threads of control. Additionally, learn to generate and consume REST web service requests and responses and increase performance with efficient use of data structures and native code. Learn to implement Gang of Four (GoF) design patterns in order to solve commonly recurring, real-world software design programs, thereby avoiding pitfalls and greatly improving the effectiveness of your programming efforts.


This course is now available as part of a multi-course, blended learning premium training bundle! Take your Python skills and career to the next level with multi-modal learning path bundles that lead to certification.

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Key Features of this Advanced Python Training:

  • After-course instructor coaching benefit
  • Learning Tree end-of-course exam included

You Will Learn How To:

  • Employ design patterns and best practises in Python applications
  • Unit test, debug, and install Python programs and modules
  • Profile program execution and improve performance
  • Apply advanced Python programming features for efficient, reliable, maintainable programs

Choose the Training Solution That Best Fits Your Individual Needs or Organisational Goals


In Class & Live, Online Training

  • 4-day instructor-led training course
  • After-course instructor coaching benefit
  • Learning Tree end-of-course exam included
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Standard £1695




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Our flexible, easy-to-redeem training vouchers are available to any employee within your organisation. For details, please call 0800 282 353 or chat live.

In Class & Live, Online Training

Note: This course runs for 4 Days

  • 1 - 4 Nov 9:00 AM - 4:30 PM GMT Online (AnyWare) Online (AnyWare) Reserve Your Seat

  • 7 - 10 Feb 9:00 AM - 4:30 PM GMT Online (AnyWare) Online (AnyWare) Reserve Your Seat

  • 9 - 12 May 9:00 AM - 4:30 PM BST Online (AnyWare) Online (AnyWare) Reserve Your Seat

  • 17 - 20 Aug 2:00 PM - 9:30 PM BST Online (AnyWare) Online (AnyWare) Reserve Your Seat

  • 19 - 22 Oct 2:00 PM - 9:30 PM BST Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

  • 15 - 18 Feb 2:00 PM - 9:30 PM GMT New York / Online (AnyWare) New York / Online (AnyWare) Reserve Your Seat

  • 19 - 22 Apr 2:00 PM - 9:30 PM BST Herndon, VA / Online (AnyWare) Herndon, VA / Online (AnyWare) Reserve Your Seat

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Advanced Python Course Information

  • Requirements

    • Working knowledge of Python programming to the level of:
      • Course 1905, Python Programming Introduction, or at least three to six months of Python programming experience
  • Software

    • Concepts taught are applicable to all Linux distributions

Advanced Python Course Outline

  • Object-Oriented Programming in Python

    • Extending classes to define subclasses
    • Inheriting from multiple superclasses and mix-in classes
    • Adding properties to a class
    • Defining abstract base classes
  • Exploring Python Features

    Writing "Pythonic" code

    • Customising iteration and indexing with "magic" methods
    • Modifying code dynamically with monkey patching

    Handling Exceptions

    • Raising user-defined exceptions
    • Reducing code complexity with context managers and the "with" statement
  • Verifying Code and Unit Testing

    Testing best practises

    • Developing and running Python unit tests
    • Simplifying automated testing with the Nose package

    Verifying code behaviour

    • Mocking dependent objects with the Mock package
    • Asserting correct code behaviour with MagicMock
  • Detecting Errors and Debugging Techniques

    Identifying errors

    • Logging messages for auditing and debugging
    • Checking your code for potential bugs with Pylint

    Debugging Python code

    • Extracting error information from exceptions
    • Tracing program execution with the PyCharm IDE
  • Implementing Python Design Patterns

    Structural patterns

    • Implementing the Decorator pattern using @decorator
    • Controlling access to an object with the Proxy pattern

    Behavioral patterns

    • Utilising the Iterator pattern with Python generators
    • Laying out a skeleton algorithm in the Template Method pattern
    • Enabling loose coupling between classes with the Observer pattern
  • Interfacing with REST Web Services and Clients

    Python REST web services

    • Building a REST service
    • Generating JSON responses to support Ajax clients

    Python REST clients

    • Sending REST requests from a Python client
    • Consuming JSON and XML response data
  • Measuring and Improving Application Performance

    Measuring Application Execution

    • Timing execution of functions with the "timeit" module
    • Profiling program execution using "cProfile"
    • Manipulating an execution profile interactively with "pstats"

    Employing Python language features for performance

    • Efficiently applying data structures, including lists, dictionaries and tuples
    • Mapping and filtering data sets using comprehensions
    • Replacing the standard Python interpreter with PyPy
  • Installing and Distributing Modules

    Managing module versions

    • Installing modules from the PyPi repository using "pip"
    • Porting code between Python versions

    Packaging Python modules and applications

    • Establishing isolated Python environments with "virtualenv"
    • Building a distribution package with "setuptools"
    • Uploading your Python modules to a local repository
  • Concurrent Execution

    Lightweight threads

    • Creating and managing multiple threads of control with the Thread class
    • Synchronising threads using locks

    Heavy-weight processes

    • Launching operating system commands as subprocesses
    • Synchronising processes with queues
    • Parallelizing execution using process pools and Executors

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Advanced Python Training FAQs

  • Can I learn Advanced Python Training online?

    Yes! We know your busy work schedule may prevent you from getting to one of our classrooms which is why we offer convenient online training to meet your needs wherever you want, including online training.

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