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Advanced Python
Code:
Adv Python
Duration:
5 Day
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$2495
USD
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This course will help you gain an understanding of Python's capabilities beyond basic syntax with a focus on widely accepted Pythonic constructs and procedures that will enable you to write reliable, optimized, and modular applications. This very hands-on course includes a deep dive into Pythonic data structures, exception handling, meta programming, regular expression, advanced file-handling, asynchronous programming, and more. At the completion of the course, you will also gain an understanding of unit testing in Python with lab-based practices designed to help you create and run unit test cases.
This course is available in the following formats:
Duration: 5 Day
Duration: 5 Day
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Delivery Format: Virtual Classroom
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$ 2495 |
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Delivery Format: Virtual Classroom
|
$ 2495 |
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Delivery Format: Virtual Classroom
|
$ 2495 |
|
|
Delivery Format: Virtual Classroom
|
$ 2495 |
|
|
Delivery Format: Virtual Classroom
|
$ 2495 |
|
|
Delivery Format: Virtual Classroom
|
$ 2495 |
|
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Delivery Format: Virtual Classroom
|
$ 2495 |
|
|
Delivery Format: Virtual Classroom
|
$ 2495 |
|
|
Delivery Format: Virtual Classroom
|
$ 2495 |
This course has 50% hands-on labs to 50% lecture ratio with engaging instruction, demos, group discussions, labs, and project work in which youll 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
Day 1
- Python refresher
- Built-in data types
- Lists and tuples
- Dictionaries and sets
- Program structure
- Files and console I/O
- If statement
- for and while loops
- Data Structures and Algorithms
- Linked list
- Stack
- Queue
- Trees
- Graphs
- Sorting algorithms
Day 2
- Errors and Exception Handling
- Syntax errors
- Exceptions
- Using try/catch/else/finally
- Handling multiple exceptions
- Ignoring exceptions
- Implementing Regular Expressions
- RE 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 Python
- Advanced unpacking
- List Comprehension
- Anonymous functions
- Lambda expressions
- Generator Expression
- Decorator
- Closure
- Single/multi dispatch
- Relative imports
- Using __init__ effectively
- Documentation best practices
Day 3
- Metaprogramming
- OOP 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 handling
- Paths, directories, and filenames
- Checking for existence
- Permissions and other file attributes
- Walking directory trees
- Creating filters with fileinput
- Using shutil for file operations
Day 4
- Advanced Data Structure features in Python
- Use defaultdict, Counter, and namedtuple
- Create data classes
- Store data offline with pickle
- Pretty printing data structures
- Compressed archives (zip, gzip, tar, etc.)
- Persistent data
- Multiprogramming
- Concurrent programming
- Multithreading
- The threading module
- Sharing variables
- The queue module
- The multiprocessing module
- Creating pools
- Coroutines
- About async programming
- Python Design Patterns
- Need for design patterns and types
- Creational
- Structural
- Behavioral
- Best coding practices
Day 5
- Developer Tools
- Analyzing programs with pylint
- Using the debugger
- Profiling code
- Testing speed with benchmarking
- Unit testing with PyTest
- What 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 applications
- Build 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.
Day 1
- Python refresher
- Built-in data types
- Lists and tuples
- Dictionaries and sets
- Program structure
- Files and console I/O
- If statement
- for and while loops
- Data Structures and Algorithms
- Linked list
- Stack
- Queue
- Trees
- Graphs
- Sorting algorithms
Day 2
- Errors and Exception Handling
- Syntax errors
- Exceptions
- Using try/catch/else/finally
- Handling multiple exceptions
- Ignoring exceptions
- Implementing Regular Expressions
- RE 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 Python
- Advanced unpacking
- List Comprehension
- Anonymous functions
- Lambda expressions
- Generator Expression
- Decorator
- Closure
- Single/multi dispatch
- Relative imports
- Using __init__ effectively
- Documentation best practices
Day 3
- Metaprogramming
- OOP 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 handling
- Paths, directories, and filenames
- Checking for existence
- Permissions and other file attributes
- Walking directory trees
- Creating filters with fileinput
- Using shutil for file operations
Day 4
- Advanced Data Structure features in Python
- Use defaultdict, Counter, and namedtuple
- Create data classes
- Store data offline with pickle
- Pretty printing data structures
- Compressed archives (zip, gzip, tar, etc.)
- Persistent data
- Multiprogramming
- Concurrent programming
- Multithreading
- The threading module
- Sharing variables
- The queue module
- The multiprocessing module
- Creating pools
- Coroutines
- About async programming
- Python Design Patterns
- Need for design patterns and types
- Creational
- Structural
- Behavioral
- Best coding practices
Day 5
- Developer Tools
- Analyzing programs with pylint
- Using the debugger
- Profiling code
- Testing speed with benchmarking
- Unit testing with PyTest
- What 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 applications
- Build 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.
About 50% of the content of this very hands-on course is lab-based practice.
About 50% of the content of this very hands-on course is lab-based practice.
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.