Prerequisites:

• Access to an Airtable base with API access enabled
• Airtable API key
• Basic knowledge of Python programming
• Python installed on your machine
• A text editor or an IDE (like Visual Studio Code, PyCharm, etc.)

1. Go to https://airtable.com and log in to your account.
2. Navigate to the base you want to export data from.
3. Click on the “Help” menu in the top-right corner and select “API documentation.”
4. In the API documentation, find your base’s API endpoint URL and note down the table names you want to export.

1. Click on your account icon in the top-right corner of the Airtable interface.
2. Go to “Account” settings.
3. Under the “API” section, you’ll find your API key. Keep this key secure as it provides full access to all your bases.

1. Open your terminal or command prompt.
2. Create a new directory for your project and navigate into it.
   ‍mkdir airtable_to_json
cd airtable_to_json

3. Create a virtual environment (optional but recommended).
   ‍python -m venv venv

4. Activate the virtual environment.
   • On Windows:
     ‍venv\Scripts\activate

   • On macOS and Linux:
     ‍source venv/bin/activate

5. Install the requests library to make HTTP requests.
   ‍pip install requests

1. Open your text editor or IDE and create a new Python file named airtable_to_json.py.
2. Import the necessary modules.
   ‍import requests
import json

3. Define your API key and endpoint URL.
   ‍API_KEY = 'your_api_key'
BASE_ID = 'your_base_id'
TABLE_NAME = 'your_table_name'
ENDPOINT = f'https://api.airtable.com/v0/{BASE_ID}/{TABLE_NAME}'
HEADERS = {'Authorization': f'Bearer {API_KEY}'}

4. Write a function to fetch records from Airtable.
   ‍def fetch_airtable_records(endpoint, headers):
   response = requests.get(endpoint, headers=headers)
   response.raise_for_status()  # Raise an HTTPError if the HTTP request returned an unsuccessful status code
   return response.json()

5. Write a function to save the data to a JSON file.
   ‍def save_to_json(data, filename):
   with open(filename, 'w', encoding='utf-8') as f:
       json.dump(data, f, ensure_ascii=False, indent=4)

6. Use the functions to fetch data and save it to a JSON file.
   ‍def main():
   data = fetch_airtable_records(ENDPOINT, HEADERS)
   save_to_json(data, 'airtable_data.json')
   print("Data has been successfully exported to airtable_data.json")

if __name__ == "__main__":
   main()

7. Save the Python script.

1. Go back to your terminal or command prompt.
2. Run the script.
   ‍python airtable_to_json.py

3. Check the current directory for the airtable_data.json file containing the exported data.

‍

Airtable’s API may paginate the results if there are a lot of records. You can modify the fetch_airtable_records function to handle pagination by following the offset parameter in the API response.

Notes:

• Always keep your API keys private and secure.
• Be aware of Airtable’s rate limits to avoid being temporarily blocked from making requests.
• The data fetched from Airtable will include metadata. You may need to parse it to extract the records array from the JSON response.
• If you have a large number of records, consider implementing error handling and retries for robustness.