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So one important recommendation before going into the specifics of the practical part of the program,

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use virtual environments.

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This is our recommendation.

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What are virtual environments?

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A using virtual environments allows us to encapsulate the versions of Python and the modules we use.

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So using virtual environments is a way to separate what you are going to do for your LM applications

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from the rest of the things you have in your computer.

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And this is important because it is going to prevent, uh, from contaminating ourselves with the version

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of Python or other global installed modules.

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And it's also going to prevent us from contaminating the global environment with our own version of

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Python or the modules we have.

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Uh, or we are going to install.

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So it's just a.

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A way to separate everything you are going to do for your applications with the rest of the things you

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have in your computer.

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And this in some cases is very, very, uh, useful because it is going to avoid conflicts, because

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in some cases, for example, if you are a mac user, you are going to have a default version of Python

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installed with your Mac.

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And you may have, you know, different things on top of that, different applications or whatever running

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on top of that Python version.

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And if you install an updated version of Python, you know, in order to build your LM applications,

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this may have conflicts with the one you have.

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Well, it can be very messy and it's very simple to create, you know, virtual environments.

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And it's going to prevent you a painful, uh, situations.

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So it is not necessary but is advisable.

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It can save you headaches, I mean, an old version of Python installed on your computer, or having

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other projects that use older versions of the modules you are going to to use.

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If you are already familiar with the virtual environments A or already have another system installed

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to manage this such Anaconda or Miniconda, you can ignore the following tips.

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If you are not familiar with virtual environments, you, um, probably have the best option with Pyenv.

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Pi env is a free framework you can install in your computer, and it will help you to create a virtual

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environment for each of your projects.

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So just in case, if you are using Anaconda or other similar tools and you want to use a pi env no pi

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dev here you see this?

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This is a typo.

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It's not pi dev is pi env.

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So if you want to use pi env to create a virtual environment and you have other platforms like Anaconda

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or Miniconda running in your computer already, you will need to deactivate the Anaconda environment

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first with this, uh, command conda deactivate.

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Why?

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Because Anaconda by default is going to create virtual environments for you.

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So this this can be a conflict with pi m.

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To install Pyenv.

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The best thing you can do is you go to ChatGPT and ask how to install Pi in my computer, and it's going

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to be super easy and super fast for you to solve it.

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In short, what are you going to do first?

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If you are on Mac, you will need to have homebrew.

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Homebrew is the tool that is going to help you install other things.

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On top of homebrew.

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You are going to install first a couple of dependencies and then pi env.

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Now pi dev.

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This is a typo you are going to install is pi env.

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Okay, so once you install pi env, you will need to update the configuration file of your computer.

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And this is the bash or the this other file with this super strange name.

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And the best thing you can do is to follow the instructions of GPT.

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There.

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It's going to tell you open the file, include this line there and that's it okay.

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So do that.

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Usually safe to restart terminal as ChatGPT will tell you.

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And then once you have pi env install you are going to decide what versions of Python you will want

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to have in your computer in order to choose among them, you know, for your different projects.

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In my case, I installed the version 311 four.

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I want to go to the 312 I.

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I am happy with the 311 four version of Python, so I install that and restart the terminal.

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Once you have that you will need to install pi env virtualenv.

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And with that ready you can create a virtual environment.

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So the first thing you have to do is pi env virtualenv init.

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Then you restart the terminal.

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And then in order to create the virtual environment you will go to the project directory.

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You will create a virtual environment.

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Uh.

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This way.

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So Pyenv is the command virtual environment.

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This is the version of Python you want to have installed in your build environment.

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And this is the name of your virtual environment, whatever you want.

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Okay, this is the name that you are going to choose.

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You activate the virtual environment with this, uh, command.

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Remember that this is going to be the name you choose.

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And once you have the virtual environment, you will see that in your terminal you are going to have

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the name of your environment and in parentheses.

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And there it means that you are right now in your new virtual environment.

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And then you need to start installing the different software you want to have there.

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So in our case we are going to install and chain.

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We are going to install Jupyter and we are going to install Python.

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And this is important because this is going to be necessary for us to have the hidden env file for our

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passwords and API keys, etc., etc..

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Right.

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So.

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If you are not familiar with terminal, don't worry, we have a chapter coming for for that.

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So once you have a pi env installed, you normally will will create a different virtual environment

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for each of your professional projects.

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And in the case of the projects included in this course, if you want, you can create a different virtual

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environments for each of them.

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Or you can have the same virtual environment for all of them.

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Why?

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Because we are going to use the same version of Python and the same version of the modules.

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So, uh, then being in a virtual environment, you don't contaminate it with other elements in your

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computer.

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Okay.

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So that's it about the virtual environment.