Advanced Python Guide : Master concepts, build applications, and prepare for interviews

Cover
Title Page
Copyright Page
Dedication Page
About the Author
About the Reviewer
Acknowledgement
Preface
Table of Contents
1. Introduction to Python
   Introduction
   Structure
   History and evolution of Python
      Birth of Python
      Guido's design philosophy
      Python 1.0 and early growth
         Early growth and community adoption
      Python 2 versus Python 3
         Migration from Python 2 to Python 3
         Python's ongoing evolution
   Python's popularity and applications
      Readability and simplicity
         Readability
         Simplicity
      Versatility and general-purpose nature
         Versatility
         General-purpose nature
      Thriving community and abundant libraries
         Thriving community
         Abundant libraries and packages
      Cross-platform compatibility
      Open source and collaboration
         Open source nature
         Collaboration and community
   Installing Python
      Installation on Windows
      Installation on macOS
      Installation on Linux (Ubuntu/Debian)
      Text editors and integrated development environments
         Text editors
         Integrated development environments
   Setting up a development environment
      Choosing a text editor or integrated development environment
         Project type
         Features
         Community and ecosystem
         Performance
         Cross-platform compatibility
         Cost
         Learning curve
         Personal preferences
      Installing and configuring your development environment
      Writing your first python program
   Conclusion
   Key terms
   Points to remember
   Exercises
2. Python Basics
   Introduction
   Structure
   Variables and data types
   Basic input and output
   Operators and expressions
      Arithmetic operators
      Comparison operators
      Logical operators
   Conditional statements
      if statements
      elif and else
   Loops and iteration
   Conclusion
   Exercises
3. Data Structures
   Introduction
   Structure
   Lists
      Creating lists
      Accessing elements
      Negative indexing
      Modifying lists
      List operations
      List comprehension
   Tuples
      Creating tuples
      Accessing tuple elements
   Sets
      Set operations
   Dictionaries
      Working with collections
   Conclusion
   Exercises
4. Functions
   Introduction
   Structure
   Defining functions
      Function syntax
      Function parameters
      Function parameters and arguments
         Types of function arguments
   Return values
      Default return value
   Lambda functions
      Uses of Lambda functions
   Recursion
      Case study: Building a calculator
   Conclusion
   Exercises
5. Object-oriented Programming
   Introduction
   Structure
   Classes and objects
      Defining a class
      Creating objects
      Accessing attributes and methods
      Class variables and instance variables
      Constructor and destructor
   Inheritance and polymorphism
      Inheritance
         Defining a base class
         Creating derived objects
      Polymorphism
         Method overriding
         Achieving polymorphism
   Encapsulation and abstraction
      Encapsulation
         Access control
         Getter and setter methods
      Abstraction
   Special methods
   Design patterns in Python
      Singleton pattern
      Factory pattern
   Conclusion
   Exercises
6. File Handling
   Introduction
   Structure
   File handling
   Opening, closing, reading and writing text files
      Reading from files
         Reading text files
         Reading line by line
         Reading binary files
         Handling file exceptions
      Writing to files
         Writing text files
         Appending to files
   Working with binary files
      Opening binary files
      Writing binary data
      Case study: Creating and updating configuration files
   Exception handling
      Understanding exceptions
      Exceptions handling using try, except and else blocks
      Advanced exception handling
      Exception hierarchies
      Best practices
      Real-world example: Web page scraper
   Context managers
      Understanding context managers
      Using context managers
      Built-in context managers
      Creating custom Context Managers
      Contextlib module
      Real-world example: Database connection
   Case study: Organizing files automatically
   Conclusion
   Exercises
7. Modules and Packages
   Introduction
   Structure
   Creating and using modules
   Importing modules
      Importing specific functions or variables
      Aliasing modules and functions
   Creating and organizing packages
   Standard library modules
      Popular standard library modules
   Conclusion
   Exercises
8. Python's Standard Library and Third-party Libraries
   Introduction
   Structure
   Overview of the standard library
      Built-in functions
      Data types
      File and directory operations
      Networking
      Threading and concurrency
      Regular expressions
      Testing
      Interacting with the operating system
      Utility modules
   Commonly used modules
      Os module
      Sys module
      Math module
      Datetime module
   Third-party libraries and the Python Package Index
      Finding and installing packages
         NumPy
         Pandas
         Matplotlib
   Conclusion
   Exercises
9. Pythonic Programming
   Introduction
   Structure
   Idiomatic Python code
   List comprehensions
   Generators and iterators
      Iterators
      Generators
         List comprehensions vs. generators
   Decorators and metaprogramming
      Decorators
      Metaprogramming
   Conclusion
   Exercises
10. Advanced Topics in Python
   Introduction
   Structure
   Concurrency and parallelism
      Understanding concurrency
      Threading in Python
      Multiprocessing in Python
      Asynchronous programming with asyncio
   Networking with Python
      Socket programming
         Simple server
   Simple client
      Working with protocols
         TCP communication
         UDP communication
      Handling network requests
         Making HTTP requests
      Database access with Python
         Connecting to Oracle
         Connecting to SQL server
         Connecting to MySQL
         Connecting to DB2
         Connecting to MongoDB
         Connecting to couchbase
   Web development with Python
      Getting started with Flask
         Handling dynamic routes
         Using templates with Flask
         Form handling with Flask
   Data science and machine learning in Python
      Introduction to data science in Python
         NumPy for numerical computing
         pandas for data manipulation
      Machine learning with scikit-learn
         Introduction to scikit-learn
         Key concepts in scikit-learn
         Further exploration with scikit-learn
      Deep learning with TensorFlow
         Introduction to TensorFlow
         Key concepts in TensorFlow
         Further exploration with TensorFlow
   Big data and cloud computing
      Big data
      Cloud computing
      Working with big data in Python
      Cloud computing with Python
      Connecting big data and cloud computing
   Web frameworks
      Introduction to web frameworks
         Flask: A micro web framework
      Installing Flask
         Running the Flask application
   Data analysis and visualization
      Introduction to data analysis with pandas
         Installing pandas
      Introduction to data visualization with Matplotlib
         Installing Matplotlib
      Advanced data visualization with Seaborn
         Installing Seaborn
   Conclusion
   Exercises
11. Testing and Debugging
   Introduction
   Structure
   Writing unit tests
   Test-driven development
   Debugging techniques and tools
      Using print statements
      Using the pdb module
      Using integrated development environments
      Logging
   Profiling and optimization
      Profiling with cProfile
      Analyzing profiling results
      Optimization techniques
      Iterative optimization
   Conclusion
   Exercises
12. Best Practices and Coding Standards
   Introduction
   Structure
   PEP 8 and style guidelines
      Indentation and whitespace
      Naming conventions
      Code organization and naming conventions
      Project structure
         Meaningful names
   Documentation and comments
      Docstrings
      Inline comments
   Version control with Git
      Concepts
      Basic git workflow
      .gitignore file
   Conclusion
   Exercises
13. Building Real-world Applications
   Introduction
   Structure
   Developing a web application
   Building a desktop application
   Creating a data analysis project
   Deploying Python applications
   Conclusion
   Exercise
14. Python's
   Introduction
   Structure
   The Python Software Foundation
   Upcoming Python releases and features
   The Python community and conferences
      PyCon: The premier Python conference
   Trends in Python development
      Machine Learning and AI integration
      Data science and analytics
      Web development with Django and Flask
      Serverless computing
      Containerization with Docker
      Microservices architecture
      Cybersecurity and ethical hacking
      Continuous integration and deployment
      Edge computing and IoT
      Cross-platform development with Kivy and BeeWare
   Machine Learning
   Data science
   Exercises
15. Hands-on Python Programming
   Introduction
   Structure
   Basic Python concepts
      Introduction to variables
      Variable naming rules
         Data types in Python
   Lists and data structures
   Control structures and loops
      Loops
   String manipulation
      Concatenation
      String interpolation
      Splitting and joining
      Checking substrings
      Formatting strings
   File handling
   Functions and modules
      Functions
         Built-in functions
         Modules
   Object-oriented programming
      Classes
      Objects
      Constructors (__init__)
      Inheritance
      Encapsulation
      Polymorphism
   Error handling and exception handling
      try...except block
      Multiple exceptions
      else clause
      Custom exceptions
      finally block
   Advanced Python concepts
      Decorators
      Generators
      Context managers
      Metaclasses
   Basic Machine Learning and visualization with Matplotlib
      scikit-learn
      Supervised learning
         Linear regression
      Unsupervised learning
      Reinforcement learning
      Data visualization with matplotlib
   Conclusion
   Key terms
   Exercises
16. Python Interview Preparation: Beginners
   Introduction
   Structure
   Python basics
   Data types and variables
   Control flow and loops
   Functions and modules
   Data structures
   String manipulation
   File handling
   Object-oriented programming
   Python libraries and frameworks
   Testing and debugging
   Concurrency and multi-threading
   Database connectivity
   Data science and Machine Learning
   Web development
   Data analysis and visualization
   Some real-world scenario-based interview questions for Python
   Conclusion
   Key terms
   Points to remember
   Exercises
17. Python Interview Preparation for Experienced Developers
   Introduction
   Conclusion
   Key points
   Exercises
Index