Course description
Advanced Python Programming
Advanced Python Programming is a practical, hands-on Python training course that thoroughly explores intermediate to advanced level topics and skills, with a focus on enterprise development. Throughout the 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.
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Who should attend?
This in an intermediate and beyond level Python course geared for students experienced with Python who want to use Python in web development projects or automate or simplify common tasks with the use of Python scripts. Basic incoming practical experience working with Python is required, along with a working, user-level knowledge of Unix/Linux, Mac, or Windows. This course does not cover Python fundamentals.
Training content
Python refresher
- Builtin 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
Time Permitting Sessions
Advanced data handling
- Discover the collections module
- Use defaultdict, Counter, and namedtuple
- Create dataclasses
- Store data offline with pickle
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
Costs
- Price: $2,495.00
- Discounted Price: $1,621.75
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Trivera Technologies
Trivera Technologies is a IT education services & courseware firm that offers a range of wide professional technical education services including: end to end IT training development and delivery, skills-based mentoring programs,new hire training and re-skilling services, courseware licensing and...
A very good balance of teaching time to lab time. I've done other courses that I found to be much lighter on content and heavy on labs to waste time. This was a refreshing chang...