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

7.4 Working with Binary Data: The pickle and json modules

As a Python programmer, your work will often require you to deal with data in various formats, such as text or binary. Fortunately, Python provides several built-in modules that can help you manipulate and work with these data types effectively. Two of these modules are the pickle and json modules.

The pickle module is an excellent tool for converting a Python object structure into a byte stream, or pickling. This process involves serializing the object hierarchy, which allows you to store the object in a file or transmit it across a network. Additionally, the pickle module can restore the pickled data back into the original Python object hierarchy, or unpickle it.

Another built-in module that is commonly used for working with data is the json module. This module allows you to encode and decode JSON data, which is a popular data interchange format. With the json module, you can easily convert Python objects into JSON strings...