Python Training Course

Who should attend

Python is the most popular language around today with many organisations using it for a wide variety of purposes from developing web sites, implementing DevOps functions to Machine Learning and Data Analysis. This course is ideal for any Software developer who wants to be able to develop modern Python applications or services.

Prerequisites

You should have some previous programming experience in another language such as Java, JavaScript, Perl, PHP, C# or C++. No previous Object-Oriented Programming is assumed but would be a bonus!

Live, instructor-led online and on-site training

We appreciate that you need flexibility to fit in with new working situations - whether you're an individual, part of a distributed team, or simply have projects and deadlines to meet. 

Our remote training can take place online in a virtual classroom, with content split into modules to accommodate your scheduling challenges and meet your learning goals. Get in touch today to find out how we can help design a cost-effective, flexible training solution.

As soon as it's safe, we'll return to also offering the on-site custom training courses and programmes upon which we've built our reputation.

Introduction to Python

• Python Background
• Python Versions
• The Language
• Execution Model
• Running Python Programs
• REPL, python command, script, IDE
• Useful Online Resources
• Obtaining Python
• IDEs

Python Built-In Types

• Interactive Hello World
• Variables & Types
• Naming Conventions
• Comments
• Strings
• Numbers
• Boolean Values
• None Value

Flow of Control in Python

• Comparison Operators
• If statement
• Using else and elif
• Nesting if statements
• Logical Operators
• If expressions
• While Loops
• For loops
• Break and Continue

Python Containers

• Introduce collection types
• Tuples
• Lists
• Sets
• Dictionaries
• Collection constructor functions

Functions

• Defining Functions
• Zero, single and multiple parameter options
• Default parameter values and named parameters
• Returning values
• Arbitrary parameter lists
• Positional and Keyword /named parameters
• Docstring
• Anonymous Functions / Lambdas

Objects and Classes

• Everything is an Object
• What do classes do?
• Class Terminology
• Defining user defined classes
• Instantiating Objects from Classes
• Class Comments
• Defining behaviour
• Class side methods and Behaviour
• Static methods
• __new__ versus __init__

Inheritance

• What is Inheritance?
• Inheritance Terminology
• Purpose of a Subclass
• Declaring Inheritance in Python
• The Class object and Inheritance
• Overriding and Extending Methods
• Inheritance Naming Conventions
• Multiple Inheritance

Operator Overloading

• Why have Operator Overloading?
• Why not have Operator Overloading?
• Defining Operators
• Numerical Operators
• Comparison Operators
• Logical Operators

Modules, packages and Anaconda

• Modules
• Python Modules
• Importing Modules
• Using from with import
• Further Importing Techniques
• Module Properties
• Module Search Path
• Pip, Conda and Anaconda

Exception Handling

• Errors & Exceptions
• Exception types in Python
• Exception Handling
• try-except blocks
• default Exception Handler
• else Clause
• finally block
• Raising an Exception / Error
• Defining New Exceptions / Errors
• Chained Exceptions

Protocols

• Implicit Contracts
• Duck Typing
• Protocols
• Context Manager Protocol
• Polymorphism in Python
• Monkey Patching

Iterators & Iterables

• Iterables
• Iterators
• Iteration Related Methods
• Iterable Events Class
• Using Events class with a for loop
• The itertools module

Generators and Coroutines

• Generators
• Generator Functions
• Generator with a for loop
• When do yield statements execute?
• An event number Generator
• Nesting generator Functions
• Coroutines
• Coroutine Example

Python Properties

• Python Attributes
• Setter and getter style methods
• Public Interface to Properties
• Python Properties
• More Concise Property Definitions

Testing PyTest and Mocking

• Test Driven Development
• What is pytest?
• Writing tests
• Organising Tests
• Test Fixtures
• Parameterized tests
• Testing for Exceptions
• Ignoring Tests
• Mocking
• Mocking with pytest-mock

Files and Paths

• Obtaining a reference to a file
• File Access Modes
• Reading Files
• File Contents Iteration
• Writing Data to Files
• Using files and with statements
• The fileinput module
• Renaming and Deleting files
• Random Access Files
• Directories
• Temporary Files & Directories
• Paths

Monkey Patching

• What is Monkey patching?
• How does Monkey Patching work?
• Monkey Patching Example
• Adding new Data to a Class