Skip to main content

Sync Airtable bases to a Postgres schemas in real time

Project description

Airtable Postgres Sync

The goal of this library is to provide an out-of-the-box solution for replicating an entire Airtable base in a Postgres schema. There are two modes of operation:

  • One-off-sync: This mode will replicate the Airtable base in the specified Postgres schema and then exit. This is useful for creating snapshots of the base for analysis or for storage as a backup.
  • Perpetual sync: This mode will replicate the Airtable base in the specified Postgres schema and then continue to watch for changes in the base. When a change is detected, the change will be applied to the Postgres schema. This is useful for creating a replica of the base that can be used for analysis in real time.

This library will produce a Postgres table and view for each of the tables in the specified Airtable base. The table will take the Airtable table id for its name and the field ids for its column names. The view will have the same name as the Airtable table and the column names will be the same as the Airtable column names. For most analysis use cases it makes sense to use the view as it is more readable, but for applications requiring robustness with respect to column name changes the table should be used.

Installation

To install the library, run the following command:

pip install airtable-pg-sync

Permissions

To use this library, you will need to create a personal access token in Airtable. This token will need to have the following scopes:

  • data.records:read
  • schema.bases:read
  • webhook:manage

You will also need to give the Postgres user that you are using read and write access to the schema you are syncing to.

Usage

To use the library, you will need to create a config file. The config file defines all the parameters that are needed to connect to Airtable and Postgres, as well as how your program will listen for changes. The file must be in YAML format and must contain the following fields:

AIRTABLE_PG_SYNC:
  REDUCED_MEMORY: # boolean, if true will use less memory but will be slower when initially syncing tables
  DB_HOST: # Postgres host
  DB_PORT: # Postgres port
  DB_USER: # Postgres user
  DB_PASSWORD: # Postgres password
  DB_NAME: # Postgres database name
  AIRTABLE_PAT: # Airtable personal access token
  LISTENER_PORT: # The port to listen for change notifications on
  WEBHOOK_URL: # The url that Airtable will send change notifications to
    REPLICATION_NAME_ONE: # Unique dummy identifier for the replication 
        BASE_ID: # Airtable base id to sync
        SCHEMA_NAME: # Postgres schema name
    REPLICATION_NAME_TWO: # Unique dummy identifier for the replication 
        BASE_ID: # Airtable base id to sync
        SCHEMA_NAME: # Postgres schema name

The library can be used in two ways:

  1. As a command line tool

To trigger a one-time sync, run the following command:

airtable-pg-sync one-time-sync --config /path/to/config.yml

To trigger a perpetual sync, run the following command:

airtable-pg-sync perpetual-sync --config /path/to/config.yml
  1. As a python library

To trigger a sync from within a python program, run the following code:

from airtable_pg_sync import Sync

Sync(config_path="/path/to/config.yml", perpetual=True / False).run()

Testing and Deployment

When testing this library for your use case the ngrok service is very useful. It allows you to listen for requests sent over the internet to your PC (ie the webhook POST requests).

For deployment, it is recommended that you run the library in an AWS EC2 or ECS type service. When using reduced memory mode, an instance with 0.25 vCPU and 0.5 GB of memory will be sufficient. WHen not using reduced memory mode, the instance size will depend on the size of your data set.

Bugs, Feature Requests, and Contributions

If you find a bug or have a feature request, please open an issue on GitHub. Any contributions are welcome and appreciated. If you would like to contribute, please open a pull request on GitHub.

Ideas for contributions:

  • Add support for other databases
  • Add support for Postgres -> Airtable sync

License

This library is licensed under the MIT License. See the LICENSE file

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

airtable_pg_sync-0.0.45.tar.gz (22.4 kB view details)

Uploaded Source

Built Distribution

airtable_pg_sync-0.0.45-py3-none-any.whl (28.8 kB view details)

Uploaded Python 3

File details

Details for the file airtable_pg_sync-0.0.45.tar.gz.

File metadata

  • Download URL: airtable_pg_sync-0.0.45.tar.gz
  • Upload date:
  • Size: 22.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.11.0

File hashes

Hashes for airtable_pg_sync-0.0.45.tar.gz
Algorithm Hash digest
SHA256 c4e95174faba25d7c2582eb5e0f0231027d1f6fb79e01ab3d4db53cce985b005
MD5 b10344e3d3f530717504b182aa5c3f23
BLAKE2b-256 16338920be464cb6f093620875b0528c28856bdd72cd3cae6926a020509834d9

See more details on using hashes here.

File details

Details for the file airtable_pg_sync-0.0.45-py3-none-any.whl.

File metadata

File hashes

Hashes for airtable_pg_sync-0.0.45-py3-none-any.whl
Algorithm Hash digest
SHA256 24d78e2ecffa017941a9e8902a3d53be3116981c16f8c4d8552bf6ae03bffff3
MD5 039fb414d05344c5e0a1293264fd8928
BLAKE2b-256 429e6b4278871a0b6476a132238a5effa7497eee7dc769654b15679ac679a287

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page