mercury

Quatro is a tool for converting notebooks into shareable formats (like PDF, HTML, Docx). Notebooks are very hard to share. You can't send it to your stakeholders, because Python code will scare them. You can use Quatro to convert notebooks into other formats and easily hide the code. It is like nbconvert on steroids. I'm working on solution for notebooks sharing with non-technical users. Similar to Quatro it has YAML header, but it can also add widgets to the notebook and serve notebook as interactive web app. My framework is called https://github.com/mljar/mercury

Hey! Author here. I'm working on open-source framework called Mercury. I'm building it to make notebooks sharing easy, especially with non-technical users. The Mercury can turn Python notebook to web application, dashboard, presentation, REST API or report. It has option to easily hide the code, schedule automatic execution, convert to PDF, and send email notifications. The Github repo: https://github.com/mljar/mercury

From the readme I can't tell what powers the cited REST API functionality. From setup.py > mercury/requirements.txt it's DRF: Django REST Framework. https://github.com/mljar/mercury/blob/main/mercury/requireme... E.g. BentoML is built on FastAPI which is async (sanic) and built by the DRF people, but FastAPI doesn't yet have the plethora of packages with tests/ supported by the Django community and DSF Django Software Foundation.

Surprised I hadn't heard of mplfinance. Similar code for econometric charts with bands and an annotation table with dated events would be useful and probably already exists somewhere. Maybe Predictive Forecasting libraries for time series already have something that could be factored out into a maintained package for such common charts? E.g. seaborn has real nice confidence intervals with matplotlib, too; though the matplotlib native color schemes are colorblind-friendly: "Perceptually Uniform Sequential colormaps" https://matplotlib.org/3.5.0/tutorials/colors/colormaps.html awesome-jupyter > Rendering/Publishing/Conversion https://github.com/markusschanta/awesome-jupyter#renderingpu... : > ContainDS Dashboards - JupyterHub extension to host authenticated scripts or notebooks in any framework (Voilà, Streamlit, Plotly Dash etc) IIRC, Cont

Mercury has a different architecture. The Voila keeps the live kernel and connection to UI (using Tornado framework). To use Voila you need to add widgets (with ipywidgets) to the notebook (mix UI code with analytics code). The Mercury generates UI based on the YAML header (very simple, no need to mix UI with analytics code). When user tweaks widgets values, the whole notebook is executed with new parameters and converted with nbconvert (using Django + Celery). Mercury can serve multiple notebooks to multiple users on one server. It has option to export notebook to PDF or HTML. You can schedule the notebook execution with crontab string (for example `schedule: '30 8 * * 1-5'`) and add email notifications. You can easily add authentication to notebooks. It was designed to make notebook sharing fast and easy. What is more, I'm thinking abou

The next alternative is Mercury (https://github.com/mljar/mercury) framework. It turns Jupyter notebooks into interactive web apps. You just add YAML config in the first cell and the interactive widgets (textbox, sliders) will be added to the notebook. You can share the notebook with others. Your users can tweak widgets and execute the notebook (and download result as single HTML file). What is more, you can hide notebook's code if you want. The framework is open source, but has also commercial additional features like authentication. It's website https://mljar.com/mercury/.

Right now, it works with only Python, but can be extended to any kernel. Deployment should be easy, I wrote guides how it can be done on Heroku and AWS EC2 https://github.com/mljar/mercury/wiki

Mercury is a perfect tool to share your Python notebooks with non-programmers. - You can turn your notebook into web app. - You can add interactive widgets to your notebook by defining the YAML header. Your users can change the input and execute the notebook. - You can hide your code to not scare your (non-coding) collaborators. - Users can interact with notebook and save they results. - You can share notebook as a web app with multiple users - they don't overwrite original notebook. The demo running at Heroku (free dyno) http://mercury-demo-1.herokuapp.com, at AWS EC2 (t3a.small) http://mercury.mljar.com - No need to register.

I'm working on a solution that helps with transforming notebooks into web applications (with GUI). You just need to define YAML config (similar to R Markdown) and the framework will generate web app with interactive widgets. After change in widgets, user clicks Run button and the whole notebook is executed, converted to HTML and displayed to the user. The framework is called Mercury and is open-source https://github.com/mljar/mercury