pyrtable 0.10.1

Django-inspired library to interface with Airtable

Pyrtable: Python framework for interfacing with Airtable

Pyrtable is a Python 3 library to interface with Airtable's REST API.

There are other Python projects to deal with Airtable. However, most of them basically offer a thin layer to ease authentication and filtering – at the end, the programmer still has to manually deal with JSON encoding/decoding, pagination, request rate limits, and so on.

Pyrtable is a high-level, ORM-like library that hides all these details. It performs automatic mapping between Airtable records and Python objects, allowing CRUD operations while aiming to be intuitive and fun. Programmers used to Django will find many similarities and will (hopefully) be able to interface with Airtable bases in just a couple of minutes.

What does it look like?

Ok, let's have a taste of how one can define a class that maps onto records of a table:

import enum
from pyrtable.record import BaseRecord
from pyrtable.fields import StringField, DateField, SingleSelectionField, \
        SingleRecordLinkField, MultipleRecordLinkField

class Role(enum.Enum):
    DEVELOPER = 'Developer'
    MANAGER = 'Manager'
    CEO = 'C.E.O.'

class EmployeeRecord(BaseRecord):
    class Meta:
        # Open “Help > API documentation” in Airtable and search for a line
        # starting with “The ID of this base is XXX”.
        base_id = 'appABCDE12345'
        table_id = 'Employees'

    @classmethod
    def get_api_key(cls):
        # The API Key can be generated in you Airtable Account page.
        # DO NOT COMMIT THIS STRING!
        return 'keyABCDE12345'

    name = StringField('Name')
    birth_date = DateField('Birth date')
    office = SingleRecordLinkField('Office', linked_class='OfficeRecord')
    projects = MultipleRecordLinkField(
            'Allocated in projects', linked_class='ProjectRecord')
    role = SingleSelectionField('Role', choices=Role)

After that, common operations are pretty simple:

# Iterating over all records
for employee in EmployeeRecord.objects.all():
    print("%s is currently working on %d project(s)" % (
        employee.name, len(employee.projects)))

# Filtering
for employee in EmployeeRecord.objects.filter(
        birth_date__gte=datetime.datetime(2001, 1, 1)):
    print("%s was born in this century!" % employee.name)

# Creating, updating and deleting a record
new_employee = EmployeeRecord(
    name='John Doe',
    birth_date=datetime.date(1980, 5, 10),
    role=Role.DEVELOPER)
new_employee.save()

new_employee.role = Role.MANAGER
new_employee.save()

new_employee.delete()

Notice that we don't deal with Airtable column or table names once record classes are defined.

Beyond the basics

Keep in mind that Airtable is not a database system and is not really designed for tasks that need changing tons of data. In fact, only fetch (list) operations are batched – insert/update/delete operations are limited to a single record per request, and Airtable imposes a 5 requests per second limit even for paid accounts. You will need a full minute to update 300 records!

That said, Pyrtable will respect that limit. In fact, it will track dirty fields to avoid unnecessary server requests and will render .save() calls as no-ops for unchanged objects. That also works with multiple threads, so the following pattern can be used to update and/or create several records:

from concurrent.futures.thread import ThreadPoolExecutor

all_records = list(EmployeeRecord.objects.all())

# Do operations that change some records here
# No need to keep track of which records were changed

with ThreadPoolExecutor(max_workers=10) as executor:
    for record in all_records:
        executor.submit(record.save)

Or, if you want a really nice tqdm progress bar:

from tqdm import tqdm

with ThreadPoolExecutor(max_workers=10) as executor:
    for _ in tqdm(executor.map(lambda record: record.save(), all_records),
                  total=len(all_records), dynamic_ncols=True, unit='',
                  desc='Updating Airtable records'):
        pass

Pyrtable also has some extra tools to cache data and to store authentication keys in JSON/YAML files or in an environment variable. Remember to never commit sensitive data to your repository, as Airtable authentication allows full R/W access to all your bases with a single API Key!

Compatibility

Pyrtable is compatible with Python 3.8 and above. Python 2.x is not supported at all.

Documentation

Technical documentation is available at https://pyrtable.readthedocs.io.

Questions, bug reports, improvements

Want to try it out, contribute, suggest, offer a hand? Great! The project is available at https://github.com/vilarneto/pyrtable.

License

Pyrtable is released under MIT license.

Copyright (c) 2020,2021,2022 by Vilar Fiuza da Camara Neto