airtable-export 0.4

Export Airtable data to files on disk

airtable-export

Export Airtable data to files on disk

Installation

Install this tool using pip:

$ pip install airtable-export

Usage

You will need to know the following information:

• Your Airtable base ID - this is a string starting with app...
• Your Airtable API key - this is a string starting with key...
• The names of each of the tables that you wish to export

You can export all of your data to a folder called export/ by running the following:

airtable-export export base_id table1 table2 --key=key

This example would create two files: export/table1.yml and export/table2.yml.

Rather than passing the API key using the --key option you can set it as an environment variable called AIRTABLE_KEY.

Export options

By default the tool exports your data as YAML.

You can also export as JSON or as newline delimited JSON using the --json or --ndjson options:

airtable-export export base_id table1 table2 --key=key --ndjson

You can pass multiple format options at once. This command will create a .json, .yml and .ndjson file for each exported table:

airtable-export export base_id table1 table2 \
    --key=key --ndjson --yaml --json

Running this using GitHub Actions

GitHub Actions is GitHub's workflow automation product. You can use it to run airtable-export in order to back up your Airtable data to a GitHub repository. Doing this gives you a visible commit history of changes you make to your Airtable data - like this one.

To run this for your own Airtable database you'll first need to add the following secrets to your GitHub repository:

AIRTABLE_BASE_ID

The base ID, a string beginning `app...`

AIRTABLE_KEY

Your Airtable API key

AIRTABLE_TABLES

A space separated list of the Airtable tables that you want to backup. If any of these contain spaces you will need to enclose them in single quotes, e.g. 'My table with spaces in the name' OtherTableWithNoSpaces

Once you have set those secrets, add the following as a file called .github/workflows/backup-airtable.yml:

name: Backup Airtable

on:
  workflow_dispatch:
  schedule:
  - cron: '32 * * * *'

jobs:
  build:
    runs-on: ubuntu-latest
    steps:
    - name: Check out repo
      uses: actions/checkout@v2
    - name: Set up Python
      uses: actions/setup-python@v2
      with:
        python-version: 3.8
    - uses: actions/cache@v2
      name: Configure pip caching
      with:
        path: ~/.cache/pip
        key: ${{ runner.os }}-pip-
        restore-keys: |
          ${{ runner.os }}-pip-
    - name: Install airtable-export
      run: |
        pip install airtable-export
    - name: Backup Airtable to backups/
      env:
        AIRTABLE_BASE_ID: ${{ secrets.AIRTABLE_BASE_ID }}
        AIRTABLE_KEY: ${{ secrets.AIRTABLE_KEY }}
        AIRTABLE_TABLES: ${{ secrets.AIRTABLE_TABLES }}
      run: |-
        airtable-export backups $AIRTABLE_BASE_ID $AIRTABLE_TABLES -v
    - name: Commit and push if it changed
      run: |-
        git config user.name "Automated"
        git config user.email "[e-mail]"
        git add -A
        timestamp=$(date -u)
        git commit -m "Latest data: ${timestamp}" || exit 0
        git push

This will run once a day (at 32 minutes past midnight UTC) and will also run if you manually click the "Run workflow" button, see GitHub Actions: Manual triggers with workflow_dispatch.

Development

To contribute to this tool, first checkout the code. Then create a new virtual environment:

cd airtable-export
python -mvenv venv
source venv/bin/activate

Or if you are using pipenv:

pipenv shell

Now install the dependencies and tests:

pip install -e '.[test]'

To run the tests:

pytest