Learn the nitty-gritty of Python 3 programming language by coding and executing programs seamlessly in a lucid manner KEY FEATURES ● Python 3 fundamentals, from data manipulation to control flow. ● Key concepts like data structures, algorithms, and Python applications, catering to a diverse audience. ● Beginner-friendly guide with step-by-step explanations and practical examples. DESCRIPTION Python 3's clear and concise syntax and extensive collection of built-in libraries and frameworks make it a powerful and versatile programming language. This comprehensive guide, "Mastering Python 3 Programming", is designed to take you from the ground up to proficiency, equipping you to create effective Python programs. This book provides an extensive overview of Python programming, covering a diverse range of topics essential for understanding Python 3. Each chapter explores key concepts like Unicode strings, functions and recursions, lists, tuples, sets, and dictionaries, along with advanced topics such as object-oriented programming, file handling, exception handling, and more. With detailed explanations and real-life examples, you will be able to build a strong understanding of Python 3. Throughout the book, you will find useful concepts and Python libraries explained clearly, along with case studies, executable programs, exercises, and easy-to-follow style. This book focuses on real-world Python applications, developing critical thinking and problem-solving skills. It prepares students for Python challenges, equipping them to contribute meaningfully in their fields. With a deep understanding of Python, students gain confidence to explore new opportunities and drive innovation. WHAT YOU WILL LEARN ● Set up IDLE for Python programming and execute programs. ● Adapt algorithm based problem-solving techniques. ● Utilize Python libraries for data visualization. ● Grasp data structures and common algorithms. ● Master decorators, file handling, exception handling, inheritance, pol

lgli/Mastering Python 3 Programming Ultimate guide to learn Python coding fundamentals and real-world applications (Subburaj Ramasamy).epub

Manish Jain

India, India

Cover
Title Page
Copyright Page
Dedication Page
About the Author
About the Reviewer
Acknowledgement
Preface
Table of Contents
1. Introduction to Python 3
Introduction
Structure
Objectives
History of Python
Major users
Features of Python 3
Applications of Python 3
Advantages of Python 3
Interpreters and compilers
Python Virtual Machine
Interpretation process
Versions of Python
Python implementations
Installing Python
Interactive mode
Integrated Development Environment
What is an Integrated Development Environment?
Pythonʼs Integrated DeveLopment Environment
Script mode programming
Colour coding by IDLE
Execution of Python programs
Dynamically typed vs. statically typed language
Memory administration in Python
Python calculator
Addition
Subtraction
Multiplication
Division
Float division
Integer division
Modulus
Exponentiation
Special characters
Batteries included philosophy
Mathematical functions in Python
Sample program with built-in mathematical functions
Other built-in functions
Frozen binaries executables
Types of errors in programs
Syntax errors
Semantic errors
Conclusion
Points to remember
Questions
2. Algorithmic Problem Solving
Introduction
Structure
Objectives
Computer program development
Steps in computation
Defining the problem
Designing a solution to the problem
Algorithm
Flowchart
Graphical symbols used in flowcharts
Simple sequence
Selection pattern
Repetition pattern
Pseudocode
Flowchart versus pseudocode
Flowchart
Pseudocode
Testing algorithm
Simple rules governing algorithms
Good programming practices
Divide and conquer
Program design
Top-down and bottom-up design
Data organization and data structures
Construction of loops
Writing programs
Modular design
Choice of variable names
Documentation of programs
Program testing
Sample algorithms
Exchanging values of two variables
Decimal base to binary base conversion
Reversing digits of a natural number
Greatest Common Divisor
Prime numbers
Factorial of a given number
Finding the maximum and minimum numbers in a list
Inserting a card in a list of sorted cards
Guess an integer number in the given range
Recursion
Generation of the Fibonacci sequence
Towers of Hanoi
Conclusion
Points to remember
Questions
3. Numeric Computations and Console Input
Introduction
Structure
Objectives
Tokens
Identifiers
Keywords
Literals
Python literal types
Numeric data types
Integer operations
Real number operations
Scientific notation
Complex numbers
Type Boolean
Expressions and operator precedence
Augmented assignment operators
Type conversion
Console input
eval()
Random numbers
Bitwise operators
OR operation – a|b
AND operation a&b
Complement ~a
The left shift a< >2
Exclusive OR of a^b
Conclusion
Points to remember
Questions
4. Unicode, Strings and Console Output
Introduction
Structure
Objectives
Character set
ASCII code
Unicode
String
String concatenation
Finding types
The str class
The str type
Multi-line strings
Method 1: Using triple quotes
Method 2: Enclosing the string within parentheses
Method 3: Using an escape character \
Escaping quotes within strings
Escape sequences
The index in a string
Substring: Slicing
Reversing a string
Immutable strings
Repetition
String methods
Methods for modifying strings
Replace substrings with replace()
ord() and chr() functions
Reversing a string
Console input of a string
Console output
Formatted printing
Using built-in format method
Floating point numbers
Formatting in scientific notation
Formatting as a percentage
Justification while printing
Formatting integers
Formatting strings
Use of %s as a place holder
Using str.format method
Passing variables to the placeholder
Passing values to the placeholders
Positional arguments
Using Python string module and Template class
Using fstring
Checking whether a string is a palindrome or anagram
String module constants
Sequence types
Converting string to bytes
Method 1: Using bytes(str, enc)
Method 2: Using encode
Conclusion
Points to remember
Questions
5. Selection and Loops
Introduction
Structure
Objectives
Structuring programs
Relational operators
Logical operators
and operator
or operator
not operator
Selection constructs
Finding whether a number is positive
Swap case
Finding the largest of three numbers
Nested selection constructs
Ternary operator
Iterations
While loop
Testing whether a number is prime using while loop.
The range function
For loop
Variations in range function
The for loop using list
Finding maximum and minimum numbers in a list
Generation of mathematical tables
Keywords break and continue
Keywords learnt in this chapter
Conclusion
Points to remember
Questions
6. Functions and Recursion
Introduction
Structure
Objectives
Features of structured programming
Benefits of structured programming
Built-in functions
User-defined functions
General form of function
Function definition
Function header
Function body
Function call
Sum of two numbers
Calling functions multiple times
Calling more functions in a program
Reverse function
addDigits function:
The void function
Illustrative programs
Exchange the value of two variables
Distance between two points
Finding square root of a positive number
Finding square root without using math function
Fruitful functions
Return values
Another fruitful function
Runtime stack
Boolean functions
Divisibility of a number
Local and global scope of function parameters
More function concepts
Positional arguments
Default arguments
Variable length arguments
*args and *kwargs
Python *args
Python **kwargs
Recursion
Euclid GCD recursive program
Recursive factorial program
Tail recursion
Calculating the exponential value in Python
Case study: Towers of Hanoi
Conclusion
Points to remember
Questions
7. Lists
Introduction
Structure
Objectives
Containers
Array
List
Mutable sequence
Mutable
Slicing
Getting Python keywords online
List concatenation
Nesting of lists
Built-in functions
Difference between functions and methods
Console input
List methods
Use of keyword in
Loops in list
Method 1
Method 2
Method 3
Method 4
List comprehension
Creating Pythagorean triplets
Aliasing list
Cloning lists
Passing list and returning list
Transpose of a matrix
Arrays in Python
Sum of an array of numbers
Case study: Circulate the values of n variables
Caution about tabs
Case study: Linear search
Case study: Binary search
Conclusion
Points to remember
Questions
8. Tuples, Sets, and Dictionaries
Introduction
Structure
Objectives
Tuple
Built-in functions
Creating tuples from other container types
Built-in functions contd.
Additional operations on tuple
Tuple as a return value
List as a return value
Set
Type set
The set function
Built-in functions
Methods of set class
Mathematical operations
Checking a set in comparison with other sets
Set comprehension
Dictionary
Some examples of dictionaries
Iterations over dictionaries
Method 1
Method 2
Method 3
Method 4
Using built-in functions with dictionary
Dictionary methods
Dictionary comprehension
Nested dictionaries
Conclusion
Points to remember
Questions
9. Introduction to Object-Oriented Programming
Introduction
Structure
Objectives
Object-oriented programming
Encapsulation
Inheritance
Polymorphism
Operator overloading
Advantages of OOP
Class
A simple class
The self
Object
Access control
Object initializer
Destruction of object
The id function and type function
Carrying out operations on objects
Class variables versus instance variables
Operator overloading
Overloading functions supported in Python
Overloading binary operators
Overloaded minus operator
Overloading unary operator
Overloaded == operator
Documentation strings
Conclusion
Points to remember
Questions
10. Inheritance and Polymorphism
Introduction
Structure
Objectives
Reusability
Inheritance
Single inheritance
Multilevel inheritance
Multiple inheritance
Implementing reuse
Containership and inheritance
Containership
Inheritance
Single inheritance
Access types revisited
Multi-level inheritance
Multiple inheritance
The object class
Diamond problem
Method overriding
The isinstance function
Polymorphism
Dynamic binding
Abstract class
Iterators
Iterable
User-defined iterators
Generators
Generator expressions
Conclusion
Points to remember
Questions
11. File Handling
Introduction
Structure
Objectives
Files
Writing to a file
Checking existence of a file
Reading from a file
readline() method
readlines() method
Implicit reading
Text and binary files
Mode parameters
Copying files
Appending text
The with for file close
Case studies
Counting occurrence of each word in a text file
Counting occurrence of each alphabet in a text file
The seek method
Writing to binary file and then reading
Java Script Object Notation
Serialization and deserialization
Serializing JSON
Deserializing JSON
Serializing and de-serializing to and from strings
Pickle solution
Pickle versus JSON
Case study: CSV files
Command line arguments
File copy from source to destination
getopt module
shutil module
Conclusion
Points to remember
Questions
12. Exception Handling
Introduction
Structure
Objectives
Some standard exceptions
Handling exceptions
The syntax for exception handling
Reading file with exception handling
The finally keyword
Word count program with exception handling
Multiple except
Use of else
Value error
Raising exceptions
Case study: Custom exception
Knowing the cause of the error
Conclusion
Points to remember
Questions
13. Gems of Python
Introduction
Structure
Objectives
Lambda functions
Constituents of lambda functions
Syntax and examples
Using lambdas with Python built-ins
Immediately invoked function expression in lambda
Modules
Module sum.py
Module swap_case
Module tup_max.py
Module prod.py
Short names for modules
Import a function from a module
The main module
Importing multiple modules
Symbol table
vars() function
Date and time
Date and Time now
strftime function
Finding elapsed time
Perf_counter function
process_time function
Functional programming
Filtering elements in containers
map() function
Reduce() function
First class functions
Assigning functions to variables
Function passed as parameters to other functions
Define functions inside other functions
Decorators
A simple decorator
Function to be decorated
def decor(fun)
The nested wrap function
Assigning and calling
Decorator function with arguments
@decor1
Case study: Comparing methods by execution times
Built-in decorators
Namespace
Packages
Importing files from a package
Conclusion
Points to remember
Questions
14. Data Structures and Algorithms using Python
Introduction
Structure
Objectives
Data structures
Stack
Case study: Exception handling in a stack
Queue
Case study: Exception handling in queue
Algorithm analysis
Case study: Bubble sort
Time complexity of bubble sort
Case study: Selection sort
Time complexity of selection sort
Case study: Insertion sort
Time complexity of insertion sort
Case study: Merge sort
Time complexity of merge sort
Conclusion
Points to remember
Questions
15. Data Visualization
Introduction
Structure
Objectives
Importance of data
Python libraries for data visualization
Dataset
File formats
DataFrame
pandas
Installing pandas
Reading head() of csv file
Reading tail() of csv file
Matplotlib
Scatter diagram
Relationship between R&D spend and profit
pandas for visualization
Relationship between marketing spend and profit
Relationship between administration and profit
Line chart
Histogram
Second dataset
Getting the first five records of wines
Getting the last five records of the dataset
Getting column headers
Histogram for wines review
Bar chart
Seaborn
Installing seaborn
Scatter diagram using seaborn
Histogram using seaborn
Gaussian KDE inside the plot
Conclusion
Points to remember
Questions
16. Python Applications and Libraries
Introduction
Structure
Objectives
Overview of applications of Python
Libraries used in data structures and algorithms
Tasks in web development
Python libraries for web development
Machine learning
Types of machine learning
Machine learning algorithms
Model evaluation
Hyperparameter tuning
Machine learning applications
Python libraries for machine learning
pandas
NumPy
SciPy
Matplotlib
Seaborn
Scikit Learn
TensorFlow
Keras
Statsmodels
Plotly
SpaCy
Bokeh
Gensim
Natural Language Processing
Theano
PyTorch
Python libraries for data science
Graphical User Interface programming
Languages and frameworks for GUI programming
Python libraries for GUI programming
Game development
Scripting and automation
Web scraping
Database applications
Internet of Things
Education
Conclusion
Multiple choice questions
Questions
Appendix 1: Python Projects
Project 1: Text-to-speech conversion using Python library Google Text To Speech
Google Text To Speech
Installation of gTTS
Languages supported
Program steps to convert text to speech
Text to speech conversion of string in English
Text to speech conversion of string in Tamil
Text to speech conversion of words in a text file in English
Text to speech conversion of words in a text file in Tamil language
Project 2: Offline text to speech conversion using Python library pyttsx3
Playing from a text file
Appendix 2: List of Built-in Functions in Python
Appendix 3: Answers to Review Questions
Index

2024-07-15