Fossee Demo Video Caption.srt

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Hi I am Mausam Kar. This is my

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hybrid chemical equipment visualizer.

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Let's jump straight in. I am logging into

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the web app first. First I will

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demonstrate the CSV upload by I am

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selecting the required sample CSV. The

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Jango back end parses this using pandas

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and instantly returns the analytics. Here

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are the. Visualizations using Chart JS.

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As we can see, the visualizations are

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the distribution by equipment type,

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correlation between pressure and flow

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rate, and temperature trends over time.

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Here are the visualization. As we can

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see, we also have a history management

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saving the last five uploads for quick

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access for each user. And also we

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have a global log for all the user

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uploads. We also have a dedicated feature

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and guides page and a context section.

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For now switching to the desktop

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application built with Pyqt 5, I am

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logging in with same credentials. Notice

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how the data I just uploaded on the

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web is immediately available here. This

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proves the share back end. Integration

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Instead of web charts, we are using

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native matplotlib figures here for high

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performance offline analysis. For

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reporting I will just generate a PDF

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report which is created server side with

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report lab containing all the critical

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statistics and equipment lists. Also we

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can see the user information for. Each

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user logged in into the website within

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the dashboard for both web and the

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desktop app. Here how it looks.

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The entire stack is containerized using

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Docker. My Docker compose setup

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orchestrates this Django API, React front

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end and database volumes as we can

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see in our Docker desktop the images

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that we have created for the front

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end and back end services and also

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the containers. On which both the

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services are being running. Also we can

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see the detailed log of the back end

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requests sent to the front end. For back

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end hosting we have used render. So this

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is our render platform where we have

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hosted the back end. For front end we

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have used versal for deployment. This is

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my versal dashboard where I have hosted

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it. So as we can see, for

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24/7 availability of the back end we have

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used something called Uptime Robot. So

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this is the Django administration panel

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through which I can manage all the users

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who are using my application.

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The entire project is available in GitHub

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and the documentation for the same is

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being provided along with the preview

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images for the application. The

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architecture diagrams for both dockerized

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and non dockerized development are being

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provided in the README as well.