Frequently Asked Questions
Common questions about Mako Code
General Questions
What is Mako Code?
Mako Code is an open source Independent Analytics Environment (IAE) built for data people who love to code. It provides a workflow designed for fast ad hoc analysis with features to let you productize your work.
What technologies are used in Mako Code?
Mako Code is built with:
- SvelteKit and TypeScript for the frontend
- Monaco Editor (VS Code’s editor) for code editing
- FastAPI for the backend
- Polars for dataframe manipulation
- Bokeh for data visualization
- Parquet for local file storage
- Apache Arrow for data serialization
- Pydantic data models
- Ruff for linting
How can I contribute to Mako Code?
We welcome contributions! Please see our contributing guidelines and development setup documentation.
Is Mako Code open source?
Yes, Mako Code is open source. You can find the source code on GitHub.
Installation and Setup
What are the system requirements for Mako Code?
Mako Code requires:
- Python 3.11+
- Node.js 20+
- Docker Desktop (for containerized approach)
- uv package manager (recommended for Python dependencies)
How do I set up Mako Code locally?
You have three options:
- Using Docker Compose (recommended):
- Using Make (Mac only):
- Manual setup (see Development Setup for details)
Where is API documentation available?
The API documentation is available at http://localhost:8001/api/docs when running Mako Code locally.
Can I use Mako Code on Windows?
Yes, Mako Code can run on Windows using Docker or the manual setup approach. The Make commands are currently Mac-only.
Features and Usage
What datasets formats does Mako Code support?
Mako Code primarily uses Parquet for local file storage, but it can import data from various formats including CSV, JSON, and Apache Arrow.
How do I import data into Mako Code?
You can import data using the keyboard shortcut ⌘/Ctrl + Shift + I or through the data management sidebar.
Can I use libraries other than Polars?
Mako Code is built with Polars as the primary dataframe library, but it’s designed to be customizable. You can extend it to use other libraries as needed.
How does versioning work in Mako Code?
Mako Code automatically tracks versions of your code, allowing you to revert to previous states and track changes over time.
Data Analysis
How do I view my dataset in Mako Code?
After importing a dataset:
- Open the data management sidebar with
⌘/Ctrl + D - Find your dataset in the list
- Click the dataset name to view details
- Click the menu (⋯) and select “Analyze”
Can I run SQL queries in Mako Code?
Yes, Mako Code supports SQL queries with dataset integration. Use ⌘/Ctrl + Shift + L to create a new SQL file.
How do I create visualizations?
Use Bokeh for data visualization in Mako Code. Create a new Bokeh visualization with ⌘/Ctrl + Shift + B.
Can I share my analysis with others?
You can export your code and visualizations using ⌘/Ctrl + E. This allows you to share your work with others.
Troubleshooting
The API server isn’t starting. What should I do?
Check port conflicts and ensure the required dependencies are installed. See our Troubleshooting guide for more details.
How do I report a bug in Mako Code?
You can report bugs by creating an issue on GitHub. Please include detailed steps to reproduce the issue, expected and actual behavior, and your environment details.
Where can I find logs for debugging?
Backend logs can be viewed using:
Or when running directly:
Frontend logs are available in your browser’s developer console and when running the dev server.