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Advanced Python Programming / Next-Level Python
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Advanced Python Programming Introduction
Welcome to the Advanced Python Programming course, a pivotal part of our Python Journey skills immersion training series. This course is designed for individuals who already have a significant background in Python programming, as well as familiarity with Unix/Linux, Mac, or Windows operating systems.
It’s important to note that this course builds on existing Python knowledge, delving into more complex and advanced topics. Known as Next-Level Python, this course is an opportunity to deepen your Python skills, focusing on high-level applications and real-world problem solving in a professional context.
Throughout this immersive course, you will explore a range of sophisticated Python concepts and techniques that are essential for advanced development. The curriculum is designed to enhance your ability to utilize Python in enterprise-level projects. You’ll gain insights into effective integration of Python with operating system services, develop skills in creating user-friendly graphical interfaces, and understand the intricacies of metaprogramming.
Learn to design and implement reusable modules and packages, perform comprehensive unit testing, and develop efficient multi-threaded and multi-process applications. The course also covers advanced topics like networking, database interactions, and handling a variety of data formats including XML, CSV, JSON, and others, ensuring you are well-equipped to tackle complex programming challenges in various professional environments.
Course Objectives
Upon completing this course, you’ll be equipped to:
- Acquire hands-on expertise in advanced Python topics, reinforcing your programming skills.
- Harness OS services to enhance the functionality of Python applications.
- Create user-friendly graphical interfaces for Python applications.
- Master metaprogramming concepts for dynamic code generation.
- Develop modular and reusable Python modules and packages.
- Implement comprehensive unit tests to ensure code reliability.
- Build efficient multithreaded and multi-process Python applications.
- Seamlessly interact with network services, expanding your Python applications’ capabilities.
- Perform efficient queries on databases, enabling data-driven applications.
- Process a variety of data formats, including XML, CSV, JSON, and more, with Python’s versatility.
Prerequisites
- 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.
Audience
- 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.
Advanced Python Programming Course Outline
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
- Implementing logging
Serializing Data
- Parsing XML with ElementTree
- Updating the XML tree
- Creating new XML documents
- Reading/Writing JSON data
- Reading/writing CSV data
- YAML, other formats
Time Permitting Chapters
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
Advanced Data Handling
- Discover the collections module
- Use defaultdict, Counter, and namedtuple
- Create dataclasses
- Store data offline with pickle
$2395.00
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4 Days Course |