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Learn Python by Building Data Science Applications

You're reading from   Learn Python by Building Data Science Applications A fun, project-based guide to learning Python 3 while building real-world apps

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Product type Paperback
Published in Aug 2019
Publisher Packt
ISBN-13 9781789535365
Length 482 pages
Edition 1st Edition
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Authors (2):
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Philipp Kats Philipp Kats
Author Profile Icon Philipp Kats
Philipp Kats
David Katz David Katz
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David Katz
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Table of Contents (26) Chapters Close

Preface 1. Section 1: Getting Started with Python FREE CHAPTER
2. Preparing the Workspace 3. First Steps in Coding - Variables and Data Types 4. Functions 5. Data Structures 6. Loops and Other Compound Statements 7. First Script – Geocoding with Web APIs 8. Scraping Data from the Web with Beautiful Soup 4 9. Simulation with Classes and Inheritance 10. Shell, Git, Conda, and More – at Your Command 11. Section 2: Hands-On with Data
12. Python for Data Applications 13. Data Cleaning and Manipulation 14. Data Exploration and Visualization 15. Training a Machine Learning Model 16. Improving Your Model – Pipelines and Experiments 17. Section 3: Moving to Production
18. Packaging and Testing with Poetry and PyTest 19. Data Pipelines with Luigi 20. Let's Build a Dashboard 21. Serving Models with a RESTful API 22. Serverless API Using Chalice 23. Best Practices and Python Performance 24. Assessments 25. Other Books You May Enjoy

A few ways to build your package

The structure of a Python package is defined by a few specifications (https://packaging.python.org/specifications/) and PEPs (short for Python Enhancement Proposals, such as PEP517—https://www.python.org/dev/peps/pep-0517/, PEP518—https://www.python.org/dev/peps/pep-0518/, and PEP427—https://www.python.org/dev/peps/pep-0427/), and the overall definition comes from the Python Packaging Authority (PyPA). In essence, a package is required to have, in addition to the actual code, a special file with metadata, including the package name, the description version, the tags, Python version support details, the authors, and the dependencies. This file could be a Python setup.py file—which was the standard solution for a long time—or a pyproject.toml file. The latter is a new, safer approach, but does not have as well-designed...

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