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  • Book Overview & Buying The Python Workshop
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The Python Workshop

The Python Workshop

By : Bird, Dr. Lau Cher Han, Mario Corchero Jiménez , Graham Lee, Wade
4.3 (36)
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The Python Workshop

The Python Workshop

4.3 (36)
By: Bird, Dr. Lau Cher Han, Mario Corchero Jiménez , Graham Lee, Wade

Overview of this book

Have you always wanted to learn Python, but never quite known how to start? More applications than we realize are being developed using Python because it is easy to learn, read, and write. You can now start learning the language quickly and effectively with the help of this interactive tutorial. The Python Workshop starts by showing you how to correctly apply Python syntax to write simple programs, and how to use appropriate Python structures to store and retrieve data. You'll see how to handle files, deal with errors, and use classes and methods to write concise, reusable, and efficient code. As you advance, you'll understand how to use the standard library, debug code to troubleshoot problems, and write unit tests to validate application behavior. You'll gain insights into using the pandas and NumPy libraries for analyzing data, and the graphical libraries of Matplotlib and Seaborn to create impactful data visualizations. By focusing on entry-level data science, you'll build your practical Python skills in a way that mirrors real-world development. Finally, you'll discover the key steps in building and using simple machine learning algorithms. By the end of this Python book, you'll have the knowledge, skills and confidence to creatively tackle your own ambitious projects with Python.
Table of Contents (13 chapters)
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Deploying Code into Production

You have all of the pieces now to get your code onto another computer and get it running. You can use PIP (covered in Chapter 8, Software Development) to create a package, and conda to create a portable definition of the environment needed for your code to run. These tools still give users a few steps to follow to get up and running, and each step adds effort and complexity that may put them off.

A common tool for one-command setup and installation of software is Docker. Docker is based on Linux container technologies. However, because the Linux kernel is open source, developers have been able to make it so that Docker containers can run on both Windows and macOS. Programmers create Docker images, which are Linux filesystems containing all of the code, tools, and configuration files necessary to run their applications. Users download these images and use Docker to execute them or deploy the images into networks using docker-compose, Docker Swarm, Kubernetes...

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The Python Workshop
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