django-react-boilerplate VS mercury

You can read more about course at https://saasitive.com/

I created a paid tutorial on how to create SaaS application in Django and React. You can purchase it at https://saasitive.com

Is this course good?https://saasitive.com/ anyone used it before?

You cac check SaaSitive React and Django tutorial. It has lesson about registration and more. It is paid tutorial.

I'm working on paid course for React and Django. In the course, you learn how to build a SaaS application from scratch and deploy it in the cloud.

Im working on Django and React course on how to build SaaS web app from scratch. You might find it interesting. The course website is https://saasitive.com

I'm working on a React and Django course that show how to build SaaS application from scratch. In the course you build real application, that will be used by other users. The app is for server uptime monitoring. The app is online at https://monitor-uptime.com

The next thing, I'm working on a course about developing Software-as-a-Service solutions with React and Django from scratch. I'm using PostgreSQL, docker-compose, Nginx and Let's Encrypt. I show how to build and deploy to production. The tutorial is not fully ready, ETA is October (this year!).

The course on how to build a SaaS application from scratch with React and Django. During the course, you build a service for server uptime monitoring. The course is not fully ready (available 17 lessons from 25 total). It will be finished in October 2022. Course covers frontend and backend development. You need to have some knowledge about TypeScript, React, Django and Celery. It puts them together and show how to deploy as live app.

I'm build dashboards in Jupyter Lab. My plotting libraries are Altair, matplotlib, seaborn, Plotly - all work well in notebook.

My favorite is Altair. It provides interactivity for charts, so you can move/zoom your plots and have tooltips. It is much lighter than Plotly after saving the notebook to ipynb file. Altair charts looks much better than in matplotlib. One drawback, that exporting to PDF doesn't work. To serve notebook as dashboard with code hidden, I use Mercury framework, you can check example https://runmercury.com/tutorials/vega-altair-dashboard/

disclaimer: I'm author of Mercury framework https://github.com/mljar/mercury

Web App is using two open-source packages that I've created:

- MLJAR AutoML - Python package for AutoML on tabular data https://github.com/mljar/mljar-supervised

- Mercury - framework for converting Jupyter Notebooks into Web App https://github.com/mljar/mercury

You can run Web App locally. What is more, you can adjust notebook's code for your needs. For example, you can set different validation strategies or evalutaion metrics or longer training times. The notebooks in the repo are good starting point for you to develop more advanced apps.

The GitHub repository https://github.com/mljar/mercury

We are working on open-source web framework Mercury that converts Python notebooks to Web Apps.

It is very opinionated:

- it has no callbacks - we automatically re-execute cells below updated widget

- it has no layout widgets, all input widgets are always in the left sidebar

Thanks to above decisions you don't need to change notebook's code to have web app and fit to the framework.

The simplicity of the framework is very important to us. We also care about deployment simplicity. That's why we created a shared hosting service called Mercury Cloud. You can deploy notebook by uploading a file.

The GitHub repository https://github.com/mljar/mercury

Documentation https://RunMercury.com/docs/

Mercury Cloud https://cloud.runmercury.com

Analysis was done in Jupyter Notebook with Python 3.10, Pandas, Matplotlib, wordcloud and Mercury framework.

Analysis was done in Jupyter Notebook with Python 3.10 kernel, Pandas, Matplotlib, wordcloud and Mercury framework to share notebook as a web application with widgets and code hidden. Gif created in Canva.