PTN-111: Python For Power User
This Python for Power User training course is designed for individuals who already have experience writing simple Python scripts and want to learn how to develop more advanced scripts using features such as file operations, regular expressions, binary data, and Python modules.
The course covers classes in greater detail and also provides coverage of OS services, date/time management, unit testing, database connectivity, network programming, web programming with Django, and more.
This Python course is hands-on and includes practical exercises, solutions, and code examples.
Training Duration: 5 Days
- Certificate Of Completion Available
- Group Private Class
- VILT Class Available
- SBL-Khas Claimable
This Python for Power User training course picks up where introduction to Python Programming left off. This program discusses some topics in more detail and adding new topics which leads students to develop Python scripts using more advanced features such as file operations, regular expressions, working with binary data, and using extensivefunctionality of Python modules.
The Python for Power User covers classes in greater detail, with new coverage of OS services, date/time management, binary data, unit testing, database connectivity, network programming, web programming with Django and more. The course is supplemented with many hands-on labs, solutions,and code examples.
All students should be able to write simple Python scripts, using basic data types, program structures,and the standard Python library
- Anyone Python programmer who needs to know Python in depth.
- Anyone who wants a solid exposure to Python as their first programming language
At the end of the course, participants will be able to:
- Demonstrate the use of the ITIL guiding principlesin Digital & IT Strategy decisions and activities
- Understand how to leverage digital strategy to react to digital disruption
- Understand the relationship between the conceptsof Digital & IT Strategy, the service value system,and the service value chain, and explain how to utilize them to create value
- Understand how an organization uses Digital & ITStrategy to remain viable in environments disrupted by digital technology
- Understand strategic approaches made possible by digital and information technology to achieve customer/market relevance and operational excellence
- Understand the risks and opportunities of Digital & IT Strategy
- Understand the steps and techniques involved in defining and advocating for a Digital and IT Strategy
- Understand how to implement a Digital and IT Strategy
Module 1: Introduction
- Python refresher
- Common idioms
- Data types
- Conditionals
- Loops
- Sequences
- Mapping types
- Useful types from collections
- Program structure
- Files and console, I/O
- Functions, Modules, and packages
- Lambda functions
- Variable scope
- List comprehensions
- Generator expressions
- Creating modules
- Using the import statement
- Module search path (PYTHONPATH)
- Documenting modules
- Built-ins
- The OS module and Date Time module
Module 2: Object oriented programming- Introduction
- First-class Everything
- A Minimal Class in Python
- Attributes
- Methods
- The__init___ method
- Data Abstraction
- Data Encapsulation and Information Hiding
- _str__and_repr___method
- Public Private and Protected Attributes
- Destructor
- Class and Instance Attributes
- Static Methods
- Class Methods
- Properties - Getters and Setters
Module 3: Inheritance- Introduction
- Syntax Inheritance
- Overloading
- Overriding
- Multiple Inheritance
- Diamond Problem
- Super and MRO
- Polymorphism
- Slots
- Avoiding Dynamically created Attributes
Module 4: Generators- Introduction
- Method of Operation
- Using a 'return' in a Generator
- Send Method / Coroutines
- The throw Method
- Decorating Generators
- Yield from
- Recursive Generators
- A Generator of Generators
Module 5: Decorators- Introduction
- Functions inside Functions
- Functions as Parameters
- Functions returning Functions
- A Simple Decorator
- Syntax for Decorator
- Use cases for Decorator
- Decorators with Parameters
- Classes instead of Functions
Module 6: Metaprogramming- Implicit properties
- Global and Local variables
- Closures
- Working with object attributes
- The inspect module
- Callable classes
- Decorators
- Monkey patching
- Regular Expressions
- RE Objects and Pattern matching
- Parsing data
- Subexpressions
- Complex substitutions
- RE tips and tricks
Module 7: Developer Tools- Analysing programs with Pylint
- Using the debugger
- Profiling code
- Testing speed with benchmarking
- Unit test
- Creating a Test cases
- Writing tests
- Running tests
Module 8: 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
Module 9: PyQt- Introduction
- Downloading and Installing PyQt and Qt Designer
- Qt Architecture
- Preparing the Development Environment
- Navigating Qt Designer
- Creating a UI in Qt Designer
- Using designer
- Standard widgets
- Event handling
- Writing the Application Logic in PyCharm
- Running the Application
- Expanding the Application
- Adding Widgets, Charts, etc.
- Developing
- GUI application accessing aDatabase
Module 10: Network Programming- Built-in classes
- Using requests
- Grabbing web pages using BeautifulSoup
- Sending email
- Working with binary data
- Consuming RESTful services
- Remote access (SSH)
Module 11: Multiprogramming- The threading module
- Sharing variables
- The queue module
- The multiprocessing module
- Creating pools
- About async programming
- Running external programs
- Parsing arguments
- Creating filters to read text files
- Logging
Module 12: Serializing data- Working with XML
- XML modules in Python
- Getting started with Element Tree
- Parsing XML
- Updating an XML tree
- Creating a new document
- About JSON
- Reading/Writing JSON
- Reading/Writing CSV files
Module 13: Internet Programming - Django- Creating a Project
- Apps Life Cycle
- Admin Interface
- Creating Views
- URL Mapping
- Template System
- Models
- Page Redirection
- Sending E-mails
- Generic Views
- Form Processing
- File Uploading
- Apache Setup
- Cookies Handling
- Sessions
- Caching
- Comments
- Django – RSS
Module 14: Welcome to GitHub- Overview
- Signup for GitHub
- GitHub Profile
- GitHub Settings
- Creating a GitHub Repository
- Linking to our GitHub Repository
- Pushing Changes to GitHub
- Verifying our Changes on GitHub
- Comparing with Pull Requests
- Comparing Commits / Tags
- Social Coding Overview
- Copying A GitHub Repository by Forking
- Creating A Branch on Your Fork
- Pull Requests
- Updating Pull Requests
- Accepting the Pull Request
- GitHub Graphs
- Synchronize Changes Back to Your Fork
- Enlisting Help with Collaborators
What is Python for power users?
Python for power users is a training course that teaches advanced Python programming techniques and libraries that are used by power users to automate tasks, build custom applications, and perform data analysis.
Why should I learn Python for power users?
Python for power users provides a comprehensive set of tools and techniques for advanced programming, data analysis, and automation. By learning Python for power users, you can gain valuable skills for a career in data analysis, scientific computing, or software engineering.
What are the job prospects for someone with Python for power users skills?
The demand for Python for power users skills is growing rapidly in many industries, including finance, healthcare, marketing, and technology. Jobs that require Python for power users skills can include data analyst, data scientist, software engineer, scientific computing specialist, and automation engineer.
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