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Python Programming

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Specific References

According to New Revised CBCS Syllabus w.e.f. 2020-21

MCA (Master of Computer Application)

Semester-II & IV

Python Programming

Author: Malat Tribhuwan, Sarika Jadhav

ISBN: 978-93-90646-60-9

Price: 400/-

Python is an interpreted, object-oriented, high-level programming language with dynamic semantics. Its built-in high-level data structures, combined with dynamic typing and binding, make it very suitable not only for rapid application development, but also for use as a scripting or glue language for connecting existing components. This book, authored by eminent educationists, is geared towards the MCA Sem. II / IV syllabus. It is written in an easy-to-follow style to make it easier for students to grasp the concepts and syntax of Python. It is filled with exercises that will help the student prepare and revise for the exams.

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Contents

1. Introduction and Components of Python

1. Introduction and Understanding Python

2.  Role of Python in AI and Data Science

2.1  Python and AI

2.2  Data Science in Python

3.  Installation and Working with Python

4. The Default Graphical Development Environment for Python – IDLE

5. Types and Operators

6.  Python Object Types-Number, Strings, Lists, Dictionaries, Tuples, Files, User Defined Classes

7. Python Inheritance

8. Understanding Python Blocks

9. Python Program Flow Control

10. Conditional Blocks using if, else and elif

10.1  Simple for loops in Python

11.  For loop using Ranges, String, List and Dictionaries

11.1  for loop using range() function

11.2  for loop using a String

11.3  for loop using Tuple

11.4  for loop using list

11.5  for loop using Dictionaries

12.  Use of while loop in Python

13.  Programming using Python Conditional and Loops Block

 

2. Python Functions, Modules and Packages

1. Function Basics-Scope, Nested Function, Non-local Statements

1.1 Function

1.2 Scope and Lifetime of Variables

1.3 Nested Function and Nonlocal Variables

2.  Built-in Functions

3. Arguments Passing, Anonymous Function: Lambda

3.1 Function Arguments in Python

3.2 Anonymous Function: Lambda Functions

4. Decorators and Generators

4.1 Generator

5. Module Basic Usage, Namespaces, Reloading Modules – math, random, datetime

5.1  Basics

5.2  Namespace in Python

5.3 Reloading Modules in Python

6. Packages

6.1  Basics of Packages

6.2 Working with SubPackage

6.3 Namespace Packages

Solved Programs

 

3. Python Object Oriented Programming

1. Introduction

2. Concept of Class, Object and Instances, Method Call

2.1 Creating Classes in Python

2.2 Creating Object and Instances in Python

2.3 __call__ Method

3. Constructors, Class Attributes and Destructors

3.1 Constructors

3.2 Class Attributes and Destructors

4. Real Time Use of Class in Live Projects

5. Inheritance, Super Class and Overloading Operators

5.1  Inheritance

5.2 Super Class and Overloading Operators

6. Static and Class Methods

7. Adding and Retrieving Dynamic Attributes of Classes

8. Programming using OOPS

9. Delegation and Container

 

4. Python Regular Expression

1. Introduction

2. Powerful Pattern Matching and Searching

2.1 Basic Patterns

2.2 Python Regular Expression Modifiers (Option Flags)

2.3 Functions Supported by 're' Module

3. Power of Pattern Searching using Regex in Python

4. Real Time Parsing of Data using Regex

5. Password, Email, URL Validation using Regular Expression

6. Pattern Finding Programs using Regular Expression

 

5. Python Multithreading and Exception Handling

1. Introduction

2. Exception Handling

2.1 Exceptions

2.2 Built-in Standard Exceptions

2.3 Avoiding Code Break using Exception Handling

3. Raising Exceptions

4. Exception Handling with Files

5. Handling and Helping Developer with Error Code

5.1 Custom (User Defined) Exception

5.2 The assert Statement

6. Programming using Exception handling

7. Multithreading

8. Understanding Threads

9. Synchronizing the Threads

10. Programming using Multithreading

 

6. Python File Operation

1. Introduction

2. Reading Config Files in Python

2.1 What is Config File?

2.2 Creating and Reading a config file

3. Writing log files in Python

3.1 The Logging Module

3.2 Types of File in Python

3.3 File Operations

4. Understanding read Functions

5. Understanding write Functions

6. Manipulating file pointer using seek() and tell()

7. Working with Directories in Python

8. Python File Methods

 

7. Python Database Interaction (Non-Relational Database – NoSQL: MongoDB with Python)

1. Introduction

2. Introduction to NoSQL Database

2.1 Advantages of NoSQL Database

3. SQL Vs NoSQL

4. Introduction to MongoDB with Python

4.1 About MongoDB

5. Exploring Collections and Documents

5.1 MongoDB with Python

6. Performing basic CRUD Operations with MongoDB and Python

6.1 Inserting a Document

6.2  Read Operations

6.3 Update Operations

6.4 Delete Operations

 

8. Python Database Interaction (Relational Database – SQL: MySQL with Python)

1. Introduction

2. SQL Database Connection using Python

2.1 Python - MySQL Database Access

3. Creating and Searching Tables

4. Reading Database

4.1 Reading and Storing config Information on Database

4.2 Reading a Key from config File

5. Programming using Database Connections

 

9.   Python for Data Analysis

1. NumPy

2. Introduction to Numpy

2.1 Installation of NumPy in Python

3. Array Objects

3.1  Creating arrays, Using arrays and Scalars

4. Indexing Arrays, Array Transposition

5. Universal Array Function

5.1 NumPy Universal Functions

6.  Array Input and Output

7. Pandas

8. What are Pandas? Where is it used?

8.1 Installation Pandas in Python

8.2 Data Structures in Pandas

9. Series in Pandas, Pandas DataFrames, Index Objects, ReIndex

9.1  Series in Pandas

9.2  Pandas DataFrames

9.3 Index Objects

9.4 Reindexing

10. Drop Entry, Selecting Entries

10.1  Other Functions Available to Drop Indexes

11.  Data Alignment, Rank and Sort

11.1 Data Ranking

11.2  Sorting

12.  Summary Statics, Missing Data, Index Hierarchy

12.1  Missing Data

12.3  Index Hierarchy

13. Matplotlib

14. Python for Data Visualization

15. Introduction to Matplotlib

16. Visualization Tools

16.1  Toolkits

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