Technical requirements
Since we’ve switched to the topic of data science, I’ve switched my preferred Python distribution to Anaconda, which is a Python distribution tailored to data science workloads. You can find it, along with installation instructions for your operating system, at https://anaconda.com.
Likewise, instead of the usual pip, I’ll be leveraging conda, which is Anaconda’s package manager. It is installed alongside Anaconda.
You’ll need an installed and working copy of PyCharm. Installation was covered in Chapter 2, Installation and Configuration, in case you are jumping into the middle of the book.
You’ll also need this book’s sample source code from GitHub. We covered cloning the code in Chapter 2, Installation and Configuration. You’ll find this chapter’s code at https://github.com/PacktPublishing/Hands-On-Application-Development-with-PyCharm---Second-Edition/tree/main/chapter-13.
