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Getting Started with Python

You're reading from   Getting Started with Python Understand key data structures and use Python in object-oriented programming

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Product type Course
Published in Feb 2019
Publisher Packt
ISBN-13 9781838551919
Length 722 pages
Edition 1st Edition
Languages
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Authors (3):
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Benjamin Baka Benjamin Baka
Author Profile Icon Benjamin Baka
Benjamin Baka
Fabrizio Romano Fabrizio Romano
Author Profile Icon Fabrizio Romano
Fabrizio Romano
Dusty Phillips Dusty Phillips
Author Profile Icon Dusty Phillips
Dusty Phillips
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Toc

Table of Contents (31) Chapters Close

Title Page
Copyright and Credits
About Packt
Contributors
Preface
1. A Gentle Introduction to Python FREE CHAPTER 2. Built-in Data Types 3. Iterating and Making Decisions 4. Functions, the Building Blocks of Code 5. Files and Data Persistence 6. Principles of Algorithm Design 7. Lists and Pointer Structures 8. Stacks and Queues 9. Trees 10. Hashing and Symbol Tables 11. Graphs and Other Algorithms 12. Searching 13. Sorting 14. Selection Algorithms 15. Object-Oriented Design 16. Objects in Python 17. When Objects Are Alike 18. Expecting the Unexpected 19. When to Use Object-Oriented Programming 20. Python Object-Oriented Shortcuts 21. The Iterator Pattern 22. Python Design Patterns I 23. Python Design Patterns II 24. Testing Object-Oriented Programs 1. Other Books You May Enjoy Index

Summary


In this chapter, we have explored working with files and directories. We have learned how to open files for reading and writing and how to do that more elegantly by using context managers. We also explored directories: how to list their content, both recursively and not. We also learned about pathnames, which are the gateway to accessing both files and directories.

We then briefly saw how to create a ZIP archive, and extract its content. The source code of the book also contains an example with a different compression format: tar.gz.

We talked about data interchange formats, and have explored JSON in some depth. We had some fun writing custom encoders and decoders for specific Python data types.

Then we explored IO, both with in-memory streams and HTTP requests.

And finally, we saw how to persist data using pickle, shelve, and the SQLAlchemy ORM library.

You should now have a pretty good idea of how to deal with files and data persistence, and I hope you will take the time to explore...

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