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Hello guys.

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So we are going to continue a discussion with respect to this, an end to end project.

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Uh, now in this video we are going to see how we are going to deploy this entire project in the Streamlit

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app.

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So Streamlit is a faster way to build and share data apps.

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So I have already taken a module, uh, regarding Streamlit, which you will be able to find out in

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this course.

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So let's go ahead.

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And first of all, sign in over here.

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Uh, once I sign in, I'll be getting this share.streamlit.io.

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And here you can probably go ahead and create your own app.

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Right.

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But before that I will go ahead and upload all my code in my GitHub.

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Right.

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So here let me do one thing.

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Let me go over here.

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Let me reveal in the File Explorer okay.

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So this is the file I will quickly go ahead and deploy some of the files.

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Right.

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So I will take this this okay.

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This this this this all the pickle file along with the requirement dot txt.

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So you can even commit it directly from the GitHub using the command line.

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But uh, I'll just directly copy and paste it over here.

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And I hope everybody knows that how to do it right.

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Because already GitHub session is already spoken about it.

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Right.

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We have, we have uh, discussed about it.

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Right.

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So I'm uploading all this files quickly.

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And here I also have my requirement dot txt.

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So let's go ahead and put this requirements.txt over here.

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Okay.

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So yes this commit we will be doing it.

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Okay I have to just go ahead and reload it.

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Just a second.

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Okay.

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So here you can see processing your files and all the files is over here you have your Readme file app.py

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pickle file everything.

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Now let me go over here.

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So here you can see that, uh, you have your share.streamlit.io.

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Now, Streamlit allows you to probably create your free apps just by integrating with the GitHub.

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So I will just go ahead and create click on create app.

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It is asking me do you already have have an app.

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So I'll say yes I have an app.

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It is in GitHub repository.

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So I will just go and search for this GitHub URL and I'll paste it over here.

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Okay.

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Once I paste it.

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So branch is mean let me just go ahead and say mean file path.

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It should be app dot p y.

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And this is the URL that it is basically creating okay.

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So step by step we are doing it okay in classification churn this particular dot Streamlit dot app.

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So I will go ahead and deploy it.

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So there is also something called as advanced token.

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Uh if please provide environment variable and other secret key to your app using HTML file format.

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The information is encrypted and served security during your runtime.

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Learn more secrets in JS.

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If you have any secret key, you can probably mention it over here and save it.

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Okay, um, that also we will be seeing, uh, as we go ahead.

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Okay.

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How to probably use some secret keys.

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Now I'll go ahead and click on deploy.

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Now once I do the deployment automatically see requirement dot txt all the files is there.

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This will actually do the deployment do all the installation that is required and it will create the

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entire environment over here.

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And my entire platform will be ready just in another one 30s to 45 seconds.

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And then we are good to go to probably check out our application.

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So let's wait for some time.

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The reason why we really need to wait for some time is that because it will be doing the pip install

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requirement, dot txt all those things?

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Um, I'll also show you an example how to probably do it with the environment variables.

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But right now let's focus on this and let's see how quickly we will be able to do it okay.

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So it shows your app is in the oven so it is getting warm.

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In short your entire server is getting warmed.

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So we'll wait for some time uh, till this installation takes place.

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And our platform is once ready.

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And this is the URL which you can also use it.

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and you can also access it.

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So I think now my app is ready and here you can see it's running.

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Stop share.

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Everything is properly displayed over here.

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I think it should be displayed in short over here.

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So let's see.

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Yes perfect.

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This is my entire app.

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And right now it is in the cloud of Streamlit.

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Uh, now if I go ahead and select any value that I want, you know, it should be able to directly compute

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things right directly just by selecting values.

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It should be able to compute.

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And this entire thing is working with the help of an okay.

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You can select any of the values.

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And then you'll be able to get the answer.

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And this is with respect to just a runtime right.

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So I hope you like this particular video.

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Uh this was it.

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And this was one amazing end to end project using an, uh, I'll see you all in the next video.

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Have a great day.

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Thank you.

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And take care.

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Bye bye.