You're reading from Python and SQL Bible

Product type Book

Published in Jun 2024

Publisher Packt

ISBN-13 9781836206279

Pages 519 pages

Edition 1st Edition

Languages

SQL Python

Concepts

Programming Language

Author (1):

Cuantum Technologies LLC

Table of Contents (29) Chapters

1. Who we are

2. Introduction

3. Chapter 1: Python: An Introduction

4. Chapter 2: Python Building Blocks

5. Chapter 3: Controlling the Flow

6. Chapter 4: Functions, Modules, and Packages

7. Chapter 5: Deep Dive into Data Structures

8. Chapter 6: Object-Oriented Programming in Python

9. Chapter 7: File I/O and Resource Management

10. Chapter 8: Exceptional Python

11. Chapter 9: Python Standard Library

12. Chapter 10: Python for Scientific Computing and Data Analysis

13. Chapter 11: Testing in Python

14. Chapter 12: Introduction to SQL

15. Chapter 13: SQL Basics

16. Chapter 14: Deep Dive into SQL Queries

17. Chapter 15: Advanced SQL

18. Chapter 16: SQL for Database Administration

19. Chapter 17: Python Meets SQL

20. Chapter 18: Data Analysis with Python and SQL

21. Chapter 19: Advanced Database Operations with SQLAlchemy

22. References

23. Conclusion

24. Where to continue?

25. Know more about us

Appendix A: Python Interview Questions

1. Appendix B: SQL Interview Questions

2. Appendix C: Python Cheat Sheet

3. Appendix D: SQL Cheat Sheet

CRUD Operations

Chapter 9 Conclusion

Chapter 9 sought to equip you with an understanding of the richness and breadth of Python's Standard Library. We began by discussing the functionality and advantages of the Standard Library, noting its vast collection of modules that provide tools for various tasks in programming, including file I/O, system calls, string management, network communication, and much more.

Our journey took us through some key modules such as math, random, datetime, os, sys, re, and collections. We found that these libraries offer many built-in functionalities that help solve a range of problems, from performing complex mathematical calculations to handling operating system tasks.

Then we transitioned to the exploration of some key external libraries like NumPy, pandas, matplotlib, and requests. Each of these libraries serves a unique purpose and is frequently employed in different areas of software development. NumPy and pandas help handle complex numerical and data operations...