As a first step when working with Python, it is a good practice to explicitly define the working environment. This helps with detaching from the operative system interpreter and environment, and properly defining the dependencies that will be used. Not doing so tends to generate chaotic scenarios. Remember, explicit is better than implicit!
This is especially important in two scenarios:
- When dealing with multiple projects on the same computer, as they can have different dependencies that clash at some point. For example, two versions of the same module cannot be installed in the same environment.
- When working on a project that will be used on a different computer, for example, developing some code in a personal laptop that will ultimately run in a remote server.
A common joke among developers is responding to a bug with it runs on my machine, meaning that it appears to work on their laptop, but not on the production servers. Although a huge number of factors can produce this error, a good practice is to produce an automatically replicable environment, reducing uncertainty over what dependencies are really being used.
This is easy to achieve using the virtualenv module, which sets up a virtual environment, so none of the installed dependencies will be shared with the Python version installed on the machine.
In Python3, the virtualenv tool is installed automatically, which was not the case in previous versions.