IntroductionCourse Outline

Duration: 4 days

Overview

This comprehensive, practical Python course provides an in-depth exploration of advanced Python scripting. Students will immediately be able to use advanced Python skills to complete tasks in the real world.

Objectives

  • Leverage OS services
  • Add enhancements to classes
  • Code graphical interfaces for applications
  • Understand advanced Python metaprogramming concepts
  • Create easy-to-use and easy-to-maintain modules and packages
  • Implement and run unit tests
  • Create multithreaded and multi-process applications
  • Interact with network services
  • Design professional scripts
  • Query databases
  • Process XML, CSV,  and JSON data
  • Work with more data types if time permits
  • Use type hints if time permits

Prerequisites

This Python course is geared toward students experienced with Python who want to use Python in web development projects or automate or simplify everyday tasks using Python scripts.  Basic practical experience working with Python and a working, user-level knowledge of Unix/Linux, Mac, or Windows are required.

Outline for Advanced Python Programming Training

  • Python Quick Refresher
    • Built-in data types
    • Lists and tuples
    • Dictionaries and sets
    • Program structure
    • Files and console I/O
    • If statement
    • for and while loops
  • OS Services
    • The os and os.path modules
    • Environment variables
    • Launching external commands with subprocess
    • Walking directory trees
    • Paths, directories, and filenames
    • Working with file systems
  • Dates and Times
    • Basic date and time classes
    • Different time formats
    • Converting between formats
    • Formatting dates and times
    • Parsing date/time information
  • Binary Data
    • What is Binary Data?
    • Binary vs. text
    • Using the Struct module
  • Pythonic Programming
    • The Zen of Python
    • Tuples
    • Advanced unpacking
    • Sorting
    • Lambda functions
    • List comprehensions
    • Generator expressions
    • String formatting
  • 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
  • Intermediate classes
    • Class/static data and methods
    • Inheritance (or composition)
    • Abstract base classes
    • Implementing protocols (context, iterator, etc.) with special methods
  • Metaprogramming
    • Implicit properties
    • globals() and locals()
    • Working with object attributes
    • The inspect module
    • Callable classes
    • Decorators
    • Monkey patching
  • Developer Tools
    • Analyzing programs with pylint
    • Using the debugger
    • Profiling code
    • Testing speed with benchmarking
  • Unit testing with PyTest
    • What is a unit test?
    • Writing tests
    • Working with fixtures
    • Test runners
    • Mocking resources
  • 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
  • PyQt
    • Overview
    • Qt Architecture
    • Using designer
    • Standard widgets
    • Event handling
    • Extras
  • Network Programming
    • Builtin classes
    • Using requests
    • Grabbing web pages
    • Sending email
    • Working with binary data
    • Consuming RESTful services
    • Remote access (SSH)
  • Multiprogramming
    • The threading module
    • Sharing variables
    • The queue module
    • The multiprocessing module
    • Creating pools
    • About async programming
  • Scripting for System Administration
    • Running external programs
    • Parsing arguments
    • Creating filters to read text files
    • Logging
  • 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
  • Advanced data handling (time permitting)
    • Discover the collections module
    • Use defaultdict, Counter, and namedtuple
    • Create dataclasses
    • Store data offline with pickle
  • Type hinting (time permitting)
    • 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