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What is mljar Mercury?

It is the easiest way to turn your Python Notebooks into interactive web applications and publish to the cloud. It is dual-licensed. The main features are available in the open-source version. It is perfect for quick demos, educational purposes, sharing notebooks with friends.
mljar Mercury is a tool in the Data Science Notebooks category of a tech stack.
mljar Mercury is an open source tool with 2K GitHub stars and 134 GitHub forks. Here’s a link to mljar Mercury's open source repository on GitHub

Who uses mljar Mercury?


mljar Mercury Integrations

Python, PostgreSQL, TensorFlow, Pandas, and NumPy are some of the popular tools that integrate with mljar Mercury. Here's a list of all 12 tools that integrate with mljar Mercury.

mljar Mercury's Features

  • You define interactive widgets for your notebook with the YAML header
  • Your users can change the widgets values, execute the notebook and save result (as PDF or HTML file)
  • You can add authentication to your notebooks, so only logged users will see the notebook
  • You can hide your code to not scare your (non-coding) collaborators
  • Easily deploy to any server
  • You can schedule the notebook for automatic execution in selected time intervals

mljar Mercury Alternatives & Comparisons

What are some alternatives to mljar Mercury?
The Jupyter Notebook is a web-based interactive computing platform. The notebook combines live code, equations, narrative text, visualizations, interactive dashboards and other media.
Apache Zeppelin
A web-based notebook that enables interactive data analytics. You can make beautiful data-driven, interactive and collaborative documents with SQL, Scala and more.
Deepnote is building the best data science notebook for teams. In the notebook, users can connect their data, explore and analyze it with real-time collaboration and versioning, and easily share and present the polished assets to end users.
It is a free open-source mathematics software system licensed under the GPL. It builds on top of many existing open-source packages: NumPy, SciPy, matplotlib, Sympy, Maxima, GAP, FLINT, R and many more.
Chart with a single click. Compare queries side by side. Download your work and share it with anyone. If your data is in a CSV, JSON, or XLSX file, loading it is as simple as dropping the file into Franchise.
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mljar Mercury's Followers
3 developers follow mljar Mercury to keep up with related blogs and decisions.