Build a data science app in minutes, and deploy to the web in one click.As more data scientists enter organizations around the world, most will find a very different work environment than what they may have dreamed about at Netflix, Facebook, or Google. At these companies, data scientists are supported by data engineers, machine learning engineers, application developers, and dev-ops specialists.
As more data scientists enter organizations around the world, most will find a very different work environment than what they may have dreamed about at Netflix, Facebook, or Google. At these companies, data scientists are supported by data engineers, machine learning engineers, application developers, and dev-ops specialists. Instead, they will probably find themselves working in a small team, or even by themselves. This poses major issues when a data scientist wants to get their insights, models, and even products out of Jupyter and into production.
Anvil fills in these gaps by allowing you to build a full-stack web app using only Python. You can build a user interface with a simple drag and drop UI (or build it with code if you insist), plot with your favorite Python plotting library (Plotly, Matplotlib, etc.), and then deploy to the web in one click. No servers or containers to deal with.
Let’s take a look at the basic features of Anvil to see how powerful it can be.
Easily build your UI with a drag and drop interface. Elements like dropdowns, sliders, images, and text are easy to position, no HTML or CSS required.
Visually position elements to get the look you want.
You are not locked down to a specific UI. You can position elements to work for your use case. When you have the look you want, you can connect them all together with Python.
This article covers A-Z about the mobile and web app development process and answers your question on how long does it take to develop/build an app.
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