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Python & SQL Bible

23 chapters and 119 canonical sections synced from the Cuantum content database.

Author
Cuantum Tech.
Chapters
23
Reading time
~ 12h
Level
Professional
Language
English
Edition
2025
Your progress0%
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Chapters & sections

23 chapters - 119 sections

Chapter 1: Python: An Introduction

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1.1 Brief History of Python3m1.2 Benefits of Python12m1.3 Python Applications13m1.4 Setting up the Python Environment and Writing Your First Python Program10m

Chapter 2: Python Building Blocks

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2.1. Python Syntax and Semantics - Part 125m2.2 Variables and Data Types14m2.3 Basic Operators12m2.4 Practice Exercises of Chapter 2: Python Building Blocks6m

Chapter 3: Controlling the Flow

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3.1 Control Structures in Python - Part 128m3.2 Error and Exception Handling8m3.3 Understanding Iterables and Iterators13m3.4 Practice Exercises4m

Chapter 4: Functions, Modules, and Packages

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4.1 Function Definition and Call12m4.2 Scope of Variables12m4.3 Modules and Packages9m4.4 Recursive Functions in Python8m4.5 Practical Exercises5m

Chapter 5: Deep Dive into Data Structures

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5.1 Advanced Concepts on Lists, Tuples, Sets, and Dictionaries - Part 124m5.2 Implementing Data Structures (Stack, Queue, Linked List, etc.)9m5.3 Built-in Data Structure Functions and Methods2m5.4 Python's Collections Module2m5.5 Mutability and Immutability2m5.6 Practical Exercises5m

Chapter 6: Object-Oriented Programming in Python

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6.1 Classes, Objects, and Inheritance11m6.2 Polymorphism and Encapsulation7m6.3 Python Special Functions9m6.4 Abstract Base Classes (ABCs) in Python5m6.5 Operator Overloading3m6.6 Metaclasses in Python3m6.7 Practical Exercises6m

Chapter 7: File I/O and Resource Management

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7.1 File Operations17m7.2 Context Managers4m7.3 Directories and Filesystems4m7.4 Working with Binary Data: The pickle and json modules4m7.5 Working with Network Connections: The socket Module4m7.6 Memory Management in Python6m7.7 Practical Exercises5m

Chapter 8: Exceptional Python

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8.1 Error and Exception Handling10m8.2 Defining and Raising Custom Exceptions6m8.3 Good practices related to raising and handling exceptions3m8.4 Logging in Python5m8.5 Practical Exercises5m

Chapter 9: Python Standard Library

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9.1 Overview of Python Standard Library22m9.2 Exploring Some Key Libraries13m9.3 Choosing the Right Libraries9m9.4 Practical Exercises5m

Chapter 10: Python for Scientific Computing and Data Analysis

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10.1 Introduction to NumPy, SciPy, and Matplotlib11m10.2 Digging Deeper into NumPy3m10.3 Working with SciPy3m10.4 Visualizing Data with Matplotlib5m10.5 Exploring Pandas for Data Analysis5m10.6 Introduction to Scikit-Learn2m10.7 Introduction to Statsmodels3m10.8 Introduction to TensorFlow and PyTorch6m10.9 Practical Exercises6m

Chapter 11: Testing in Python

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11.1 Unit Testing with unittest10m11.2 Mocking and Patching9m11.3 Test-Driven Development4m11.4 Doctest4m11.5 Practical Exercises5m

Chapter 12: Introduction to SQL

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12.1 Brief History of SQL4m12.2 SQL Syntax7m12.3 SQL Data Types5m12.4 SQL Operations5m12.5 SQL Queries6m12.6 Practical Exercises4m

Chapter 13: SQL Basics

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13.1 Creating Databases and Tables5m13.2 Inserting Data into Tables2m13.3 Selecting Data from Tables2m13.4 Updating Data in Tables2m13.5 Deleting Data from Tables2m13.6 Filtering and Sorting Query Results2m13.7 NULL Values3m13.8 Practical Exercises4m

Chapter 14: Deep Dive into SQL Queries

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14.1 Advanced Select Queries9m14.2 Joining Multiple Tables11m14.3 Aggregate Functions5m14.4 Practical Exercises4m

Chapter 15: Advanced SQL

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15.1 Subqueries9m15.2 Stored Procedures10m15.3 Triggers8m15.4 Practical Exercises4m

Chapter 16: SQL for Database Administration

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16.1 Creating, Altering, and Dropping Tables5m16.2 Database Backups and Recovery5m16.3 Security and Permission Management6m16.4 Practical Exercises4m

Chapter 17: Python Meets SQL

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17.1 Python's sqlite3 Module8m17.2 Python with MySQL3m17.3 Python with PostgreSQL3m17.4 Performing CRUD Operations5m17.5 Handling Transactions in Python5m17.6 Handling SQL Errors and Exceptions in Python6m17.7 Practical Exercises4m

Chapter 18: Data Analysis with Python and SQL

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18.1 Data Cleaning in Python and SQL7m18.2 Data Transformation in Python and SQL7m18.3 Data Visualization in Python and SQL4m18.4 Statistical Analysis in Python and SQL4m18.5 Integrating Python and SQL for Data Analysis5m18.6 Practical Exercises5m

Chapter 19: Advanced Database Operations with SQLAlchemy

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19.1 SQLAlchemy: SQL Toolkit and ORM4m19.2 Connecting to Databases4m19.3 Understanding SQLAlchemy ORM3m19.4 CRUD Operations with SQLAlchemy ORM3m19.5 Managing Relationships with SQLAlchemy ORM4m19.6 Querying with Joins in SQLAlchemy3m19.7 Transactions in SQLAlchemy4m19.8 Managing Relationships in SQLAlchemy3m19.9 SQLAlchemy SQL Expression Language3m19.10 Practical Exercise4m

Chapter 20 - Appendix A: Python Interview Questions

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Python Interview Questions4m

Chapter 21 - Appendix B: SQL Interview Questions

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Appendix B: SQL Interview Questions4m

Chapter 22 - Appendix C: Python Cheat Sheet

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Basic Python Syntax1mData Structures1mList Comprehensions1mException Handling1mFile Handling1mClasses and Objects1m

Chapter 23 - Appendix D: SQL Cheat Sheet

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SQL Syntax1mCRUD Operations1m