This is the open-source dataset for the Open Brewery DB API which is served by a REST API built with Laravel

Provide an approval-based pipeline to update the dataset and API.

• CSV - Full Dataset
• JSON
• PostgreSQL SQL

1. git clone [email protected]:openbrewerydb/openbrewerydb.git
2. cd openbrewerydb && npm install

The following npm scripts help maintain and manage the dataset:

• npm run validate

  • Validates all CSV files against the JSON Schema
  • Checks for required fields and data format consistency
  • Reports any validation errors that need attention

• npm run csv:combine

  • Combines all individual CSV files from country/state-region folders into a single breweries.csv
  • Useful when you've made changes to individual state files and need to update the main dataset

• npm run csv:split

  • Splits the main breweries.csv into separate files by country/state-region
  • Helps maintain organized, manageable data files for each region
  • Creates directories if they don't exist

• npm run generate:ids

  • Creates unique OBDB IDs for each brewery based on name and city
  • Automatically updates breweries.csv with new IDs
  • Ensures no duplicate IDs exist in the dataset

• npm run generate:json

  • Converts breweries.csv into a JSON format (breweries.json)
  • Useful for applications that prefer working with JSON data
  • Maintains data consistency across formats

• npm run generate:sql

  • Creates PostgreSQL SQL file from breweries.csv
  • Includes table creation and data insertion statements
  • Perfect for database implementations

• npm run generate:stats

  • Generates comprehensive dataset statistics
  • Shows brewery counts by state/city
  • Displays brewery type distribution
  • Reports data completeness metrics

• npm run update:readme-stats

  • Updates the Statistics section in README.md with latest data
  • Automatically calculates and formats all statistics
  • Includes last updated timestamp

• npm run contributors:add

  • Interactive CLI tool to add new contributors
  • Prompts for contributor information and contribution type
  • Updates .all-contributorsrc file

• npm run contributors:check

  • Verifies if any contributors are missing from the list
  • Helps maintain accurate recognition of all contributors

• npm run contributors:generate

  • Updates the Contributors section in README.md
  • Generates contributor table with avatars and contribution types

• npm run workflow:maintain
  • Comprehensive maintenance workflow that:
    1. Validates all CSV files
    2. Combines all CSV files
    3. Creates unique IDs for each brewery
    4. Splits back into individual state files
    5. Creates JSON and SQL files
    6. Updates README.md with latest statistics
  • Run this after making any dataset updates

For information on contributing to this project, please see the contributing guide and our code of conduct.

1. Fork the repository
2. Add or update breweries in the CSV (Excel, Google Sheets)
3. Submit a Pull Request

First and foremost, don't worry about messing up! 🙂 Thank you so much for contributing! 🙌

• CSVs are organized by data/[country]/[state_province]
• Required fields/columns: name, brewery_type, city, state_province, and country
• When adding a brewery, do not include an id. This will be created after review.
• Please either add to breweries.csv (preferred if adding breweries for a new country) or the individual state/province CSV file. Adding to both at the same time may introduce duplicates/errors.

• Join the Newsletter
• Join the Discord

Any feedback, please email me.

Cheers! 🍻

• Status: Active
• Last Dataset Update: 2024
• Maintenance: Actively maintained through community contributions
• Dataset Size: 8,000+ breweries
• Coverage: United States, with growing international data

• Node.js v22 or higher
• npm package manager
• Git

Each brewery entry contains the following fields:

import pandas as pd

# Read CSV
breweries_df = pd.read_csv('breweries.csv')

# Filter by state
california_breweries = breweries_df[breweries_df['state_province'] == 'California']

const fs = require("fs");

// Read JSON
const breweries = JSON.parse(fs.readFileSync("breweries.json", "utf8"));

// Filter by type
const microBreweries = breweries.filter((b) => b.brewery_type === "micro");

-- After importing breweries.sql
SELECT name, city, state_province
FROM breweries
WHERE brewery_type = 'brewpub'
ORDER BY state_province, city;

The dataset is updated regularly through community contributions. Each update goes through the following process:

1. Community members submit new breweries or updates via pull requests
2. Changes are reviewed and validated
3. Upon approval, changes are merged and new dataset files are generated
4. The API is automatically updated with the new data

Latest dataset version: 2024.1

Thanks goes to these wonderful people (emoji key):

Mike Putnam 🔣	Andrew A. Barber 🔣	Jason Allen 🔣	Juicob 🔣	Will Karnasiewicz 🔣	Dylan T. Vavra 🔣	Madison Martinez 🔣
Daniel Eremchuk 🔣	Alex Chong 🔣	Matt S 🔣	Samuel Rusher 🔣	Evan Caraway 🔣	Tyler K Kuromiya Parker 🔣	kendellmendoza 🔣
Johnnyk737 🔣	James Schuler 🔣	Creighton Leif 🔣	Vitaly Tomilov 💻	Kyle Scudder 🔣	Chris Mears 💬 💻 🔣 🚧 📆 🔧 ✅	donkeyslaps 🔣
Pranav Davar 🔧	Alexandre Hernandes Barrozo 🔣	Resten 🔣	Matt Higgins 🔣	Alex Justesen 🔣	Craig Kelly 🔣	Krzysztof Rewak 🔣
John Baumert 🔣	Charlie Cox 🔣	Miles Kane 🔣	Anthony Laflamme 💻	Georg Engelsmann 🔣	Clinton Williams 🔣	Brent Busby 🔣
kenster89 🔣	Adilet Sarsembayev 🔣	Pranav Davar 🔣	b-mc2 🔣	Nicole 🔣	Nicholas Hance 🔣	Joachim Nilsson 🔣
Alejandro Lopez Rocha 🔣	zshapleigh 🔣	Praval Visvanath 🔣	JohnHenry 🔣	Alfredo Garcia 🔣	Qerewe 🔣	Nathan Peters 🔣
Erich Cervantez 🔣	Ronald Sahagun 🔣	Greg W. 🔣	David Holm 🔣	sadilett 🔣	Ryan Mallette 🔣	Chris Condreay 🔣
Wi5ARD 🔣	JP Bulman 🔣	Sara 🔣	Sean 🔣	Simon 🔣	willkrakow 🔣	Charl Ritter 🔣
Aaron Zingerle 🔣	Noah Dawson 🔣	jctopping 🔣	Fabio Vitalba 🔣	Dustin Butler 🔣	BruddahChrispy 🔣	Damian Krzeminski 💻 🔣
mathewhaug 🔣	Kevin Pomer 🔣	Laurens Glasbergen 🔣	Nate 🔣

This project follows the all-contributors specification. Contributions of any kind welcome!

Last updated: 2026-04-15

• Total Breweries: 9,559
• Data Completeness: 79.0%