Configuring testing environments

The first recommendation I give is to always use Python’s Virtual Environment. Anaconda is nice and is very powerful, but it’s simply not necessary here. If you intend to combine the code you’ll see here on this book with other utilities or environments we were already creating, then Anaconda can become a valid option.

In terms of the number of virtual environments you should have, it’s up to you. You can for example create one per chapter for the sake of better organizing the whole stuff, but this will mean more disk space will be occupied, since the same Python modules will be installed multiple times. Alternatively, you can create a single environment, let’s say pentest, and create sub-directories under it with the codes for each chapter, following the structure proposed on the book’s repository.

I chose the second option above since the VM’s disk space is not something too big and multiple repeated...