Advanced Python Programming Training Course

Who should attend

Python Developers who wish to delve more deeply into Python and to expand their understanding of some of the more advanced language facilities and techniques.

Prerequisites

You should be comfortable with the topics in our introductory python training course or have similar experience.

Live, instructor-led online and on-site training

This Advanced Python course is available for private / custom delivery for your team - face-to-face, on-site at your location of choice, or remotely via MS Teams, Zoom or your own platform - get in touch to find out how we can deliver tailored training which focuses on your project requirements and learning goals.

Abstract Base Classes (ABCs)

• Abstract Classes
• Abstract Base Classes (ABCs) in Python
• Subclassing an ABC
• Defining an ABC
• Defining Abstract Methods
• Virtual Subclasses
• Mixins
• Developing the IDPrinterMixin

Functional Programming in Python

• What is Functional programming? (FP)
• Advantages of FP
• Disadvantages of FP
• Functions in Python
• Higher Order Functions
• Functions Returning Functions
• Built-in Higher Order Functions & Reduce
• Currying in Python - Curried Functions
• Accessing global variables and the global keyword
• The nonlocal keyword

Databases and the Python DB-API

• DB-API
• Connection function and object
• Cursor Object
• Row Descriptors
• Database Errors
• Transactions
• PyMySQL module
• Connecting to a MySQL database
• Working with a Cursor
• Inserting, Updating, Deleting from a MySQL database
• Table Creation

NoSQL Databases (MongoDB) and Python

• Non-Relational Databases
• SQL vs NoSQL
• MongoDB
• PyMongo
• Establishing a Connection
• Accessing Databases
• Inserting Documents
• Retrieving Documents
• MongoEngine
• Object Document Mapper

Custom Decorators

• What are Decorators?
• Defining a Decorator
• Using a Decorator
• Functions with parameters
• Stacked Decorators
• Parameterised Decorators
• Method Decorators
• Class Decorators
• Implementing the Singleton pattern using a Decorator
• When is a Decorator Executed?
• Built-in Decorators
• FuncTools Wrapper

Sockets and the socketserver module

• Socket to Socket Communication
• The Client Server Architecture
• Server Application
• Client Application
• The Client Server Interaction
• The socketserver module

Pythons Logging library

• Logging module
• The Logger
• Log Levels
• Setting the Log level
• Turning off logging
• Module level loggers
• Logger Hierarchy
• Handlers
• Formatters & Formatting options
• Filters
• Logger Configuration Files

RESTFul Services and Flask

• RESTFul Operations
• Motivation for REST
• REST Principles
• The Basic Concept / The Rest Design Pattern
• The Web is a RESTFul system
• REST – Not a Standard
• Claimed Benefits of RESTFul Services
• Python RESTFul Frameworks
• Implementing Flask RESTFul Services
• Getting Started with the Service
• Providing Routing Information
• Running the Service
• Invoking the Service
• Book Service

Threading

• Python Threads
• Thread States
• The Thread Class
• Creating a Thread
• Passing Arguments to a Thread
• Multiple Threads
• Daemon Threads
• Naming Threads
• Thread Local Data
• Timers
• Threading module functions

Processes

• The multiprocessing Library
• The Process Class
• Working with the Process class
• Alternative Ways to run a process
• Using a Pool
• Exchanging data between Processes
• Sharing State between Processes

Inter Thread / Process Communications

• Inter Thread / Process Comms
• Using a Barrier
• Event Signalling
• Synchronizing Concurrent Code
• Python Locks
• Python Conditions
• Python Semaphore class
• Concurrent Queue class

Futures

• The Need for Futures
• Futures in Python
• Future Creation
• Examples of single and Multiple Futures
• Futures and as_completed
• Futures and Callbacks

Reactive Programming in Python with RxPy

• What is Reactive Programming?
• The ReactiveX Project
• The Observer Pattern
• Hot and Cold Observables
• Advantages & Disadvantages of Reactive Programming
• RxPy Reactive Programming Framework
• Observables in RxPy
• Observer Object
• Multiple Observers

RxPy Subjects, Operators and Schedulers

• Subjects in RxPy
• Observer Concurrency
• RxPy Operators
• Piping operators
• Creational operators
• Transformational Operators
• Combinatorial Operators
• Filtering Operators
• Mathematical Operators
• Chaining Operators

Python Profiling

• Profiling and Performance
• Timing code
• Profiling with cProfile
• Memory Analysis
• Commercial profilers