# Grist — Modern Relational Spreadsheet You Can Self-Host

> A spreadsheet-database hybrid that combines the familiar grid interface with relational data modeling, Python formulas, and a full API, all self-hostable.

## Install

Save in your project root:

# Grist — Modern Relational Spreadsheet You Can Self-Host

## Quick Use
```bash
docker run -d -p 8484:8484 -v grist-data:/persist 
  -e GRIST_SESSION_SECRET=changeme gristlabs/grist
# Open http://localhost:8484
```

## Introduction
Grist is a modern, open-source spreadsheet that stores data in proper relational tables instead of flat grids. It gives spreadsheet users the power of a database with familiar formulas, while giving developers a real API and Python-based computed columns. You self-host it and own all your data.

## What Grist Does
- Organizes data in relational tables with typed columns and foreign-key references
- Evaluates formulas written in Python instead of traditional spreadsheet syntax
- Provides multiple views (grid, card, chart, calendar) over the same underlying data
- Exposes a REST API for programmatic reads, writes, and webhooks
- Supports granular access rules to control who sees or edits which rows and columns

## Architecture Overview
Grist is a Node.js server that manages SQLite-backed documents. Each document is an independent SQLite file, making backups and portability straightforward. The Python formula engine runs in a sandboxed subprocess (gvisor or pyodide) that evaluates column formulas on each change. The frontend is a TypeScript single-page app using GrainJS for reactive DOM updates.

## Self-Hosting & Configuration
- Run with Docker using the official `gristlabs/grist` image with a persistent volume
- Set `GRIST_SESSION_SECRET` for session security and `APP_HOME_URL` for your domain
- Configure authentication via SAML, OpenID Connect, or a header-based auth proxy
- Enable sandboxing with `GRIST_SANDBOX_FLAVOR=gvisor` for untrusted formula execution
- Optionally connect to an external PostgreSQL or S3 for document metadata and storage

## Key Features
- Python formulas with full standard library access inside a security sandbox
- Access control rules that restrict data visibility at the row and column level
- Incremental imports that update existing records by matching on key columns
- Webhooks that fire on row changes for integrating with external services
- Document snapshots for point-in-time restore and version history

## Comparison with Similar Tools
- **Airtable** — SaaS with vendor lock-in; Grist is self-hosted with portable SQLite files
- **NocoDB** — wraps an existing SQL database; Grist manages its own data in SQLite docs
- **Baserow** — similar concept but uses Django and PostgreSQL; Grist offers Python formulas in cells
- **Google Sheets** — collaborative but cloud-only; Grist provides local ownership and relational modeling

## FAQ
**Q: Can I use Grist as a backend for my app?**
A: Yes. The REST API supports full CRUD and filtering, making it a lightweight backend for small applications.

**Q: How do Python formulas work?**
A: Each computed column has a Python expression. When dependent data changes, Grist re-evaluates affected formulas in a sandboxed Python process.

**Q: Is there a row or data limit?**
A: Limits depend on your hardware. Since each document is an SQLite file, practical limits are in the hundreds of thousands of rows per document.

**Q: Can I import from Excel or CSV?**
A: Yes. Grist supports importing Excel, CSV, JSON, and Google Sheets with column type detection and incremental update matching.

## Sources
- https://github.com/gristlabs/grist-core
- https://support.getgrist.com/

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Source: https://tokrepo.com/en/workflows/df3a683f-3e02-11f1-9bc6-00163e2b0d79
Author: AI Open Source