Python for Entrepreneurs Transcripts
Chapter: Appendix: Python language concepts
Lecture: Concept: Virtual environments
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One of the challenges of installing packages globally has to do with the versioning.
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The other really has to do with managing deployments and dependencies.
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Let's talk about the versioning part first.
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Suppose my web application I am working on right now
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requires version 2.9 of requests.
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But somebody else's project required an older version with older behavior,
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version 2.6 let's say. I don't think those are actually incompatible,
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but let's just imagine that they were.
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How would I install via pip version 2.6 and version 2.9 and keep juggling those,
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how would I run those two applications on my machine without continually reconfiguring it-
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the answer is virtual environments.
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And, virtual environments are built into Python 3
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and are also available through a virtual env package
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that you can install for Python 2
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and the idea is this- we can crate basically a copy,
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change our paths and things like that around so that when,
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you ask for Python or this looks for Python packages,
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it looks in this little local environment, we create one of these small environments
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just for a given application, so we would create one for our web app
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that uses request 2.9 and another one for the one that uses request 2.6
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and we would just activate those two depending on which project we are trying to run,
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and they would live happily side by side.
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The other challenge you can run into is if you look
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at what you have installed on your machine,
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and you run some Python application and it works,
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how do you know what listed in your environment is actually required to run your app,
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if you need to deploy it or you need to give it to someone else,
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that could be very challenging. So with virtual environments
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we can install just the things a given application requires to run
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and be deployed so when we do something like "pip list",
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it will actually show us exactly what we need to set up
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and use for our app to run in production.
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Typically we tie virtual environments one to one to a given application.
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So how do we create one?
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This example uses virtual env which we would have to install via pip,
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you could also use venv, just change virtual env to venv in Python 3
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and it will have the same effect, but this works,
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like I said in Python 2 and 3, so here you go.
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So we are going to run Python 3 and we are going to say run the module, virtual env,
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and create a new environment into ./localenv.
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Here you can see it creates a copy from Python 3.5.
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Then we go into that environment, there is a bin directory
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and there is an activate program that we can run and notice,
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we'll use the . (dot) to apply that to this shell
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and not to create a new separate shell environment for that when it runs
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because we wanted to modify our shell environment, not a temporary one.
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So we say . activate and that will actually change our environment,
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you can see the prompt change, if we say "pip", we get the local pip,
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if we ask "which python", you'll see it's this one that is in my user profile
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not the one in the system.
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Now, few changes for Windows, if I did exactly the same thing in Windows,
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I would have .\localenv of course, I might not use Python 3,
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I just say Python and make sure I have the right path to Python 3
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because that is not a feature in the Python 3 that comes on Windows,
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and I wouldn't use the source activate you don't need to do that in Windows,
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but you would call activate.bat, otherwise,
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it's pretty much the same. Also, the "which" command doesn't exist on Windows,
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use "where" and it gives you the same functionality.
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So we can create one of these virtual environments in the terminal,
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but you might suspect that PyCharm has something for us as well,
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and PyCharm actually has the ability to create
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and manage virtual environments for us,
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basically it does what you just saw on the screen there.
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So here we give it a name, we give it a location here,
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we say blue_yellow_python, this is going to be for a Blue / Yellow band web application,
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we are going to base this on Python 3.5.1
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and we are going to put into my Python environments and under this name.
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Then I just say OK and boom, off it goes, set it as the active interpreter
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and manage it just the same as before in PyCharm
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using its ability to install packages and see what is listed and so on.
