Mineo takes Python notebooks to the next level by adding production-grade features such as:

• Switchable layout modes: Notebook, Dashboard and Mobile.
• No code Widgets (SQL Query, Graphics, Tables, KPIs, Title, Images and Forms) to explore and interact with your content without programming.
• First class editor, with auto indent, code completition, command palette and variable inspector.
• Integrated SQL Data sources to access databases (PostgreSQL, MySQL, Oracle, SQLServer, AWS RedShift, Clickhouse, ...) and files (CSV) directly in streaming.
• Compatible with Jupyter notebooks. Import your existing notebooks from .ipynb or export from mineo to other apps.
• Built-in version control system.
• Ability to share and work collaboratively thanks to Comments and Tasks.
• Integrated filesystem to store your data up to 10TB.
• Ability to export your notebook to PDF.
• Support for project wide variables.
• Support for Python blocks, Markdown, LaTeX and Widgets.
• Detailed logs and permissions (view, view code, execute) at user/group level. Perfect for delivering results with notebooks.
• Automatic code generation 🤖 powered by OpenAI.

Skip the installation of large installation environments on your computer like anaconda and get straight to the content in a reproducible environment that works even in mobile devices.

• Notebooks in your browser. Run your notebooks directly on our scalable SaaS platform that scales with your demands. From small environments to large requirements of RAM, CPU or GPUs.
• Use pre-built Docker images to ensure you have the exactly environment you want.
• Mineo provides a Linux-based environment for installing packages directly on your notebook using standard tools such as apt, pip or git.

Automate and streamline your workflows with Python-based data pipelines that leverage the power of notebooks.

• Compose pipelines based on multiple notebooks.
• Ability to schedule pipelines at your desired frequency.
• Support for injecting variables for each step and sending emails with the results of a pipeline.
• Support for detailed logs and custom docker images.

Interactively explore your data sources without spending development time or writing complex SQL.

• Interactive query editor based on drag-and-drop components.
• Supported Data sources: databases: PostgreSQL, MySQL, Oracle, SQLServer, AWS RedShift, Clickhouse and CSV files.
• Support for built-in SQL functions.
• Export results to CSV & SQL.

A widely available file system of up to 10TB to store all your content without the need for third-party services.

• Common actions such as Copy, Move, Rename, Clone... supported
• Ability to export folders and contents to ZIP and vice versa.
• File editor for text files (Text, Markdown, CSV, Python)
• End-user friendly access with customisable icons and views.

Establish processes to measure and track the quality of your data over the time using machine learning 🤖

Supported data trackers:

• Expected rows (forecast) vs actual.
• Schema changes.
• Distribution of the data.
• Asserts (based on SQL).
• Calculated variables (forecast and user-defined ranges).

Manage your project and organisation down to the last detail. Deliver results with notebooks.

• Define permissions at user or group level for every resource.
• Ability to set detailed file level permissions (view, edit, create)
• Global look and feel configuration and data formats.
• Detailed logs and statistics to control and view accesses to your content
• Public mode to share content with just the link.