Python Mastery: From Absolute Beginner to Pro
Unlock the full potential of Python with this comprehensive and engaging guide that takes you on an exciting journey fro
154 56 4MB
English Pages 244 Year 2023
Table of contents :
Title Page
Copyright Page
Python Mastery: From Absolute Beginner to Pro
Why This Book Stands Out:
What Makes This Book Unique:
Who This Book is For:
Python Mastery: From Absolute Beginner to Pro
2.1. Variables, data types
2.1. Variables and data types
2.2. Operators
2.3. Control flow (if statements, loops)
2.4. Functions and modules
I. Functions: The Building Blocks of Python Programs
II. Modules: Organizing Code into Reusable Units
III. Benefits of Functions and Modules
IV. Best Practices for Functions and Modules
2.5. Input/output and file handling
2.6. Exception handling
3.1. Lists
3.1. Lists
3.2. Tuples
Properties of Tuples
Basic Operations on Tuples
Use Cases and Benefits of Tuples
Additional Points to Enhance Your Understanding of Tuples
3.3. Dictionaries
3.4. Sets and frozensets
Set Operations
Applications of Sets
3.5. Arrays (NumPy)
3.6. Series and DataFrames (Pandas)
Data Manipulation with Series and DataFrames
4.1. Reading and writing files
4.1. Reading and writing files
4.2. CSV and JSON file formats
5.1. String operations | 5.2. Regular expressions
5.1. String operations
5.2. Regular expressions
6.1. Classes and objects | 6.2. Inheritance and polymorphism | 6.3. Advanced OOP concepts
6.1. Classes and objects
6.2. Inheritance and polymorphism
6.3. Advanced OOP concepts
7.1. Creating and importing modules | 7.2. Working with packages
7.1. Creating and importing modules
7.2. Working with packages
8.1. Handling errors and exceptions | 8.2. Try-except blocks
8.1. Handling errors and exceptions
8.2. Try-except blocks
9.1. Lambda functions | 9.2. Map, filter, and reduce functions
9.1. Lambda functions
9.2. Map, filter, and reduce functions
10.1. Iteration protocols | 10.2. Creating and using generators
10.1. Iteration protocols
10.2. Creating and using generators
11.1. Function decorators | 11.2. Class decorators
11.1. Function decorators
11.2. Class decorators
Use Cases and Benefits of Class Decorators
Implementing Class Decorators
Date and time manipulation (datetime module)
Formatting and Parsing Dates and Times
Exploring commonly used modules (os, sys, math, random, etc.)
14.1. SQL (SQLite) | 14.2. Database connectivity (SQLite3)
14.1. SQL (SQLite)
14.2. Database connectivity (SQLite3)
Pattern matching and text manipulation (re module)
Basic Pattern Matching
Text Manipulation with re
Flags in re
16.1. Debugging techniques and tools (pdb) | 16.2. Unit testing (unittest module)
16.1. Debugging techniques and tools (pdb)
Debugging Techniques
Using pdb for Debugging
16.2. Unit testing (unittest module)
Profiling and optimizing code (timeit, cProfile)
18.1. Creating and managing virtual environments (venv, conda) | 18.2. Installing and managing packages (pip)
18.1. Creating and managing virtual environments (venv, conda)
18.2. Installing and managing packages (pip)
19.1. Code organization and style (PEP 8) | 19.2. Documentation (docstrings) | 19.3. Code versioning and collaboration (Git, GitHub)
19.1. Code organization and style (PEP 8)
Code examples with explanations:
19.2. Documentation (docstrings)
Additional Points:
19.3. Code versioning and collaboration (Git, GitHub)
Appendix: [[370]]
Exercises and Solutions: | Exercises:
Solutions:
Resources:
End-Description:
Title Page
Copyright Page
Python Mastery: From Absolute Beginner to Pro
Why This Book Stands Out:
What Makes This Book Unique:
Who This Book is For:
Python Mastery: From Absolute Beginner to Pro
2.1. Variables, data types
2.1. Variables and data types
2.2. Operators
2.3. Control flow (if statements, loops)
2.4. Functions and modules
I. Functions: The Building Blocks of Python Programs
II. Modules: Organizing Code into Reusable Units
III. Benefits of Functions and Modules
IV. Best Practices for Functions and Modules
2.5. Input/output and file handling
2.6. Exception handling
3.1. Lists
3.1. Lists
3.2. Tuples
Properties of Tuples
Basic Operations on Tuples
Use Cases and Benefits of Tuples
Additional Points to Enhance Your Understanding of Tuples
3.3. Dictionaries
3.4. Sets and frozensets
Set Operations
Applications of Sets
3.5. Arrays (NumPy)
3.6. Series and DataFrames (Pandas)
Data Manipulation with Series and DataFrames
4.1. Reading and writing files
4.1. Reading and writing files
4.2. CSV and JSON file formats
5.1. String operations | 5.2. Regular expressions
5.1. String operations
5.2. Regular expressions
6.1. Classes and objects | 6.2. Inheritance and polymorphism | 6.3. Advanced OOP concepts
6.1. Classes and objects
6.2. Inheritance and polymorphism
6.3. Advanced OOP concepts
7.1. Creating and importing modules | 7.2. Working with packages
7.1. Creating and importing modules
7.2. Working with packages
8.1. Handling errors and exceptions | 8.2. Try-except blocks
8.1. Handling errors and exceptions
8.2. Try-except blocks
9.1. Lambda functions | 9.2. Map, filter, and reduce functions
9.1. Lambda functions
9.2. Map, filter, and reduce functions
10.1. Iteration protocols | 10.2. Creating and using generators
10.1. Iteration protocols
10.2. Creating and using generators
11.1. Function decorators | 11.2. Class decorators
11.1. Function decorators
11.2. Class decorators
Use Cases and Benefits of Class Decorators
Implementing Class Decorators
Date and time manipulation (datetime module)
Formatting and Parsing Dates and Times
Exploring commonly used modules (os, sys, math, random, etc.)
14.1. SQL (SQLite) | 14.2. Database connectivity (SQLite3)
14.1. SQL (SQLite)
14.2. Database connectivity (SQLite3)
Pattern matching and text manipulation (re module)
Basic Pattern Matching
Text Manipulation with re
Flags in re
16.1. Debugging techniques and tools (pdb) | 16.2. Unit testing (unittest module)
16.1. Debugging techniques and tools (pdb)
Debugging Techniques
Using pdb for Debugging
16.2. Unit testing (unittest module)
Profiling and optimizing code (timeit, cProfile)
18.1. Creating and managing virtual environments (venv, conda) | 18.2. Installing and managing packages (pip)
18.1. Creating and managing virtual environments (venv, conda)
18.2. Installing and managing packages (pip)
19.1. Code organization and style (PEP 8) | 19.2. Documentation (docstrings) | 19.3. Code versioning and collaboration (Git, GitHub)
19.1. Code organization and style (PEP 8)
Code examples with explanations:
19.2. Documentation (docstrings)
Additional Points:
19.3. Code versioning and collaboration (Git, GitHub)
Appendix: [[370]]
Exercises and Solutions: | Exercises:
Solutions:
Resources:
End-Description:
