Advanced Python Programming

Training Materials

In addition to the course manual, students will receive a Python quick reference.

Software Requirements

• Any Windows, Linux, or macOS operating system
• Python 3.x installed (Anaconda bundle recommended)
• An IDE with Python support (PyCharm Community Edition is an excellent free option, but there are several other good ones)

Outline

• Introduction
• Python Refresher
  • Built-in data types
  • Lists and tuples
  • Dictionaries and sets
  • Program structure
  • Files and console I/O
  • If statement
  • for
  • Built-in functions
  • User-defined functions
  • Modules and packages
  • Basic OOP
• 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
• Enhancing Classes
  • Class/static data and methods
  • Inheritance (or composition)
  • Abstract base classes
  • Creating attributes with attr
  • Implementing protocols (context, iterator, etc.)
• 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
  • Creating test cases
  • Writing and running tests
  • Test harnesses
  • Working with fixtures
• 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
  • Built-in 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
  • 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 [as time permits]
  • Discover the collections module
  • Use defaultdict, Counter, and namedtuple
  • Create dataclasses
  • Store data offline with pickle
• Type Hinting [as time permits]
  • Annotate variables
  • Learn what type hinting does NOT do
  • Use the typing module for detailed type hints
  • Understand
  • Write stub interfaces
• Conclusion