GK821512 Advanced Python

COURSE OBJECTIVE:

 This course has 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work in which you'll learn:Enhancements to classes
Advanced Python metaprogramming concepts
Writing robust code using exception handling
Working with different data structures supported in Python
Search and replace text with regular expressions
Easy-to-use and easy-to-maintain modules and packages
Creating multithreaded and multi-process applications
Implementing and execute unit tests

TARGET AUDIENCE:

 This course is designed for students with Python programming literacy who want to learn about advanced Python features and how to automate and simplify tasks.

COURSE PREREQUISITES:

Students should have experience writing Python scripts, as well as a user-level knowledge of Unix/Linux, Mac, or Windows.

COURSE CONTENT:

Day 1Python refresherBuilt-in data types
Lists and tuples
Dictionaries and sets
Program structure
Files and console I/O
If statement
for and while loopsData Structures and AlgorithmsLinked list
Stack
Queue
Trees
Graphs
Sorting algorithms
Day 2Errors and Exception HandlingSyntax errors
Exceptions
Using try/catch/else/finally
Handling multiple exceptions
Ignoring exceptions
Implementing Regular ExpressionsRE Objects
Searching and matching
Using Regular Expression to search data sets
Searching for data in Wireshark Traces (Python and *.pcaps)
Compilation flags
Groups and special groups
Replacing text
Splitting strings
Advanced Functional Features of PythonAdvanced unpacking
List Comprehension
Anonymous functions
Lambda expressions
Generator Expression
Decorator
Closure
Single/multi dispatch
Relative imports
Using __init__ effectively
Documentation best practices
Day 3MetaprogrammingOOP conventions
Class/static data and methods
Parse information to create classes using a dictionary
Super() method
Metaclasses
Abstract base classes
Implementing protocols (context, iterator, etc.) with special methods
Implicit properties
Globals() and locals()
Working with object attributes
The inspect module
Callable classes
Monkey patching
Advanced file handlingPaths, directories, and filenames
Checking for existence
Permissions and other file attributes
Walking directory trees
Creating filters with fileinput
Using shutil for file operations
Day 4Advanced Data Structure features in PythonUse defaultdict, Counter, and namedtuple
Create data classes
Store data offline with pickle
Pretty printing data structures
Compressed archives (zip, gzip, tar, etc.)
Persistent data
MultiprogrammingConcurrent programming
Multithreading
The threading module
Sharing variables
The queue module
The multiprocessing module
Creating pools
Coroutines
About async programming
Python Design PatternsNeed for design patterns and types
Creational
Structural
Behavioral
Best coding practices
Day 5Developer ToolsAnalyzing programs with pylint
Using the debugger
Profiling code
Testing speed with benchmarking
Unit testing with PyTestWhat is a unit test
Testing with Unit-test framework
Testing with PyTest
Testing with doctest
Writing tests
Working with fixtures
Test runners
Mocking resources
Writing real-life applicationsBuild the classic minesweeper game in the command line
Build a program that can go into any folder on your computer and rename all of the files based on the conditions set in your Python code
Implement the binary search algorithm
Build a random password generator
Build a countdown timer using the time Python module.

FOLLOW ON COURSES:

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