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https://github.com/cancan101/airtable-db-api
A Python DB API 2.0 for Airtable
https://github.com/cancan101/airtable-db-api
Last synced: 8 days ago
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A Python DB API 2.0 for Airtable
- Host: GitHub
- URL: https://github.com/cancan101/airtable-db-api
- Owner: cancan101
- License: mit
- Created: 2022-03-21T21:02:11.000Z (over 2 years ago)
- Default Branch: main
- Last Pushed: 2024-04-29T12:01:37.000Z (6 months ago)
- Last Synced: 2024-04-29T13:29:02.865Z (6 months ago)
- Language: Python
- Size: 144 KB
- Stars: 9
- Watchers: 3
- Forks: 0
- Open Issues: 17
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# airtable-db-api [](https://badge.fury.io/py/sqlalchemy-airtable)  [](https://codecov.io/gh/cancan101/airtable-db-api)
A Python DB API 2.0 for Airtable
This module allows you to query Airtable using SQL. It exposes:
- a [Python DB API 2.0](https://peps.python.org/pep-0249/) (per PEP 249)
- a [SQLAlchemy Dialect](https://docs.sqlalchemy.org/en/14/dialects/) (see also ["Developing new Dialects"](https://github.com/zzzeek/sqlalchemy/blob/master/README.dialects.rst))
- a [Superset Engine Spec](https://preset.io/blog/building-database-connector/)
## SQLAlchemy support
This module provides a SQLAlchemy dialect.
```python
from sqlalchemy.engine import create_engine
engine = create_engine(
'airtable://:keyXXXX@appYYY?peek_rows=10&tables=tableA&tables=tableB',
date_columns={"tableA": ["My Date Field"]},
)
```
## Metadata
At various points we need to know:
1. The list of Tables supported in the Base
2. The list of columns (Fields) supported on a given Table
3. The type information for each Field
As of now we solve 1) by passing in a list of Tables using the `tables` query parameter on the URL.
We solve 2) and 3) using some combination of the `peek_rows` query parameter specifying the number of rows to fetch from Airtable to guess Field types and a `date_columns` engine parameter to specify which columns should be parsed as `Date`s.
Alternatively, 1-3 could all be solved with a comprehensive `base_metadata` engine parameter that specifies the Tables and Fields. There are a number of ways to generate this, but one approach is scraping the Base's API docs page using [a technique like this](https://github.com/aivantg/airtable-schema-generator/issues/47#issue-1165801153).
Further options are [documented here](https://github.com/cancan101/airtable-db-api/wiki/Metadata)
## Development
### Python
```bash
$ pip install -r requirements-dev.txt
```
### `pre-commit`
```bash
$ pre-commit install
```
### `black`
Can be run manually as:
```bash
black --target-version py37
```
## Roadmap
- [ ] Support for [Airtable's Metadata API](https://airtable.com/api/meta)
- [ ] Support passed in Airtable Metadata (w/ types)
- [ ] Cleanup configuration (passed as [query param on URL](https://docs.sqlalchemy.org/en/14/core/engines.html#database-urls) vs [engine parameters](https://docs.sqlalchemy.org/en/14/core/engines.html#sqlalchemy.create_engine))
- [ ] Built in Metadata scraper (not using Metadata API)
- [ ] Caching of field type "peeking"
- [ ] Datetime support
- [ ] More comprehensive testing