Advanced Python Programming
In this course you will learn to
- 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
Training materials
In addition to the course manual, students will receive a Python quick reference.
Suggested attendees
Students who can write simple Python scripts using basic data types, program structures and the standard Python library.
Course Outline
- Python refresher
- Built-in data types
- Lists and tuples
- Dictionaries and sets
- Program structure
- Files and console I/O
- If statement
- 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 database 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
- 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)