Advanced Python Programming

Course Code: 1178

$2495

Advanced Python Programming

Explore advanced level concepts of Python programming

Course Code : 1178

$2495

Overview
Schedule classes
What you'll learn
Outline
Prerequisites
Who should attend

Overview

This comprehensive advanced-level course on Python programming involves hands-on lab exercises, engaging lectures, demos and activities to ensure participants get a thorough understanding of the concepts being discussed. The course leads participants through a series of progressively advanced topics such as OS services, modules, unit tests, databases, XML data, packages, meta programming, network programming, threads, etc. The course is a skill-centric course, focusing on helping participants master advanced Python and web development skills, the latest techniques and coding practices. The course does not cover Python fundamentals.

Schedule Classes

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Course Delivery

This course is available in the following formats:

Live Classroom
Duration: 5 days

Live Virtual Classroom
Duration: 5 days

What You'll learn

Leverage OS services
Code graphical interfaces for applications
Build modules
Create and run unit tests
Define classes
Working with network services
Query databases
Handle XML data

Outline

Module 1: Python refresher

Data types
Sequences
Mapping types
Program structure
File and console I/O
Conditionals
Loops
Built-ins

Module 2: OS services

The OS module
Environment variables
Launching external commands
Walking directory trees
Paths, directories and file names
Working with file systems
Dates and times

Module 3: Dates and Times

Basic date and time classes
Different time formats
Converting between formats
Formatting dates and times
Parsing date/time information

Module 4: Binary Data

What is Binary Data?
Binary vs text
Using the Struct module

Module 5: Pythonic programming

The Zen of Python
Common idioms
Lambda functions
List comprehensions
Generator expressions
String formatting

Module 6: Functions, modules, and packages

Four types of function parameters
Four levels of name scoping
Single/multi dispatch
Relative imports
Using __init__ effectively
Documentation best practices

Module 6: Metaprogramming

Implicit properties
Globals() and locals()
Working with attributes
The inspect module
Decorators
Monkey patching

Module 7: Intermediate classes

Class/static data and methods
Inheritance (or composition)
Abstract base classes
Implementing protocols (context, iterator, etc.) with special methods

Module 8: Metaprogramming

Implicit properties
globals() and locals()
Working with object attributes
The inspect module
Callable classes
Decorators
Monkey patching

Module 9: Developer Tools

Analyzing programs with pylint
Using the debugger
Profiling code
Testing speed with benchmarking

Module 10: Unit testing with PyTest

What is a unit test?
Writing tests
Working with fixtures
Test runners
Mocking resources

Module 11: Database access

The DB API
Available Interfaces
Connecting to a server
Creating and executing a cursor
Fetching data
Parameterized statements
Using Metadata
Transaction control
ORMs and NoSQL overview

Module 12: PyQt

Overview
Qt Architecture
Using designer
Standard widgets
Event handling
Extras

Module 13: Network Programming

Builtin classes
Using requests
Grabbing web pages
Sending email
Working with binary data
Consuming RESTful services
Remote access (SSH)

Module 14: Multiprogramming

The threading module
Sharing variables
The queue module
The multiprocessing module
Creating pools
About async programming

Module 15: Scripting for System Administration

Running external programs
Parsing arguments
Creating filters to read text files
Logging

Module 16: Serializing data – XML and JSON

Working with XML
XML modules in Python
Getting started with ElementTree
Parsing XML
Updating an XML tree
Creating a new document
About JSON
Reading JSON
Writing JSON
Reading/writing CSV files
YAML, other formats as time permits

Time Permitting Sessions

Module 17: Advanced data handling

Discover the collections module
Use defaultdict, Counter, and namedtuple
Create dataclasses
Store data offline with pickle

Module 18: Type hinting

Annotate variables
Learn what type hinting does NOT do
Use the typing module for detailed type hints
Understand union and optional types
Write stub interfaces

Appendix A: Bibliography

Appendix B: Python virtual environments

Prerequisites

Participants need to have basic incoming practical experience working with Python, along with a working user-level knowledge of Unix/Linux, Mac or Windows. Participants also need to be trained or have equivalent practical skills in “Introduction to Basic Python Programming”, “Essential Python Programming” and “Mastering Python Programming”.