Book Image

Getting Started with Python

By : Fabrizio Romano, Benjamin Baka, Dusty Phillips
Book Image

Getting Started with Python

By: Fabrizio Romano, Benjamin Baka, Dusty Phillips

Overview of this book

This Learning Path helps you get comfortable with the world of Python. It starts with a thorough and practical introduction to Python. You’ll quickly start writing programs, building websites, and working with data by harnessing Python's renowned data science libraries. With the power of linked lists, binary searches, and sorting algorithms, you'll easily create complex data structures, such as graphs, stacks, and queues. After understanding cooperative inheritance, you'll expertly raise, handle, and manipulate exceptions. You will effortlessly integrate the object-oriented and not-so-object-oriented aspects of Python, and create maintainable applications using higher level design patterns. Once you’ve covered core topics, you’ll understand the joy of unit testing and just how easy it is to create unit tests. By the end of this Learning Path, you will have built components that are easy to understand, debug, and can be used across different applications. This Learning Path includes content from the following Packt products: • Learn Python Programming - Second Edition by Fabrizio Romano • Python Data Structures and Algorithms by Benjamin Baka • Python 3 Object-Oriented Programming by Dusty Phillips
Table of Contents (31 chapters)
Title Page
Copyright and Credits
About Packt
Contributors
Preface
8
Stacks and Queues
10
Hashing and Symbol Tables
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...