Advanced Python Programming
Explore intermediate to advanced level topics and skills using Python, with a focus on enterprise development.
Throughout this Advanced Python Programming course, students will learn how to Leverage OS services, Code graphical interfaces for applications, create modules and run unit tests, define classes, interact with network services, query databases, process XML data, and much more. This comprehensive, practical course provides an in-depth exploration of working with the programming language, not an academic overview of syntax and grammar.
This course is about 50% hands-on lab to 50% lecture ratio, combining engaging, informed instructor presentations, demonstrations and discussions with extensive machine-based student labs and practical project work.
Duration
4 days/32 hours of instructionPublic Classroom Pricing
Starting at: $2395(USD)
GSA Price: $1796.25
Group Rate: $2295
Private Group Pricing
Have a group of 5 or more students? Request special pricing for private group training today.
Download the Course Brochure
Part 1: Python refresher
- Builtin data types
- Lists and tuples
- Dictionaries and sets
- Program structure
- Files and console I/O
- If statement
- for and while loops
Part 2: 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
Part 3: Dates and Times
- Basic date and time classes
- Different time formats
- Converting between formats
- Formatting dates and times
- Parsing date/time information
Part 4: Binary Data
- What is Binary Data?
- Binary vs text
- Using the Struct module
Part 5: Pythonic Programming
- The Zen of Python
- Tuples
- Advanced unpacking
- Sorting
- Lambda functions
- List comprehensions
- Generator expressions
- String formatting
Part 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
Part 7: Intermediate classes
- Class/static data and methods
- Inheritance (or composition)
- Abstract base classes
- Implementing protocols (context, iterator, etc.) with special methods
Part 8: Metaprogramming
- Implicit properties
- globals() and locals()
- Working with object attributes
- The inspect module
- Callable classes
- Decorators
- Monkey patching
Part 9: Developer Tools
- Analyzing programs with pylint
- Using the debugger
- Profiling code
- Testing speed with benchmarking
Part 10: Unit testing with PyTest
- What is a unit test?
- Writing tests
- Working with fixtures
- Test runners
- Mocking resources
Part 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
Part 12: PyQt
- Overview
- Qt Architecture
- Using designer
- Standard widgets
- Event handling
- Extras
Part 13: Network Programming
- Builtin classes
- Using requests
- Grabbing web pages
- Sending email
- Working with binary data
- Consuming RESTful services
- Remote access (SSH)
Part 14: Multiprogramming
- The threading module
- Sharing variables
- The queue module
- The multiprocessing module
- Creating pools
- About async programming
Part 15: Scripting for System Administration
- Running external programs
- Parsing arguments
- Creating filters to read text files
- Logging
Part 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
Part 17: Advanced data handling
- Discover the collections module
- Use defaultdict, Counter, and namedtuple
- Create dataclasses
- Store data offline with pickle
Part 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
Experienced Python users who want to:
- Use Python in web development projects
- Automate or simplify common tasks with the use of Python scripts
- 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