Using Python and Airtable

For this tutorial, we will be using scores from a round of golf as a toy dataset. You will need to create a table in Airtable with the following four columns and data types:

Date (string)

Hole (integer)

Par (integer)

Score (integer)

All the code referenced here is available in a GitHub repo. In the repo you will find a file airtable.py with example functions you'll build here. There is also a Jupyer notebook, AirtablePractice.ipynb in the repo you can use to follow along.

Authentication

First, let's look at the authentication for submitting a request.

Submitting a request to the Airtable REST API requires three pieces of information:

An API authentication token.

The ID of your Airtable base.

The name of the sheet.

Airtable uses a bearer token to authenticate each API request, which should be saved in a .env file to keep it secret.

You can find your API token by going to your account page. Scroll down to the API section of your account page, and you will see your token.

Copy the token value and paste it into your .env file naming it AIRTABLE_TOKEN. Make sure you keep this token private and do not share it with anyone! If you're committing files to a GitHub repo (or any other source control system), make sure you exclude the .env to avoid accidentally exposing this information!

Next, let's find the Airtable base ID. Make sure you are logged into your Airtable account and go to the API docs. Select the base you want to work with from the list. On the next page, you will see the ID of your Airtable Base. Copy the value and add it to your .env file naming it AIRTABLE_BASE_ID.

Finally, make a note of the sheet name you want to modify via the API. You'll need that to complete the URL for making requests.

With all the variables assembled to make our requests, it's time to put it together into a python file. Create a new file named airtable.py. Include the following at the top of the file:

import os
from python_dotenv import load_dotenv
load_dotenv()

AIRTABLE_TOKEN = os.getenv("AIRTABLE_TOKEN")
AIRTABLE_BASE_ID = os.getenv("AIRTABLE_BASE_ID")

Using the python_dotenv library, the variables you included in your .env are read into two variables, AIRTABLE_TOKEN and AIRTABLE_BASE_ID, allowing you to utilize them in the rest of your script.

With the authentication sorted out, we need to build the endpoint you'll send requests to. The basic structure of an Airtable API endpoint has three components:

1) The root of the URL, api.airtable.com/v0
2) The Airtable Base ID
3) The sheet name

The root URL, api.airtable.com/v0, will remain constant across all requests. The Base ID will depend on the specific Airtable Base you are using. Since this tutorial will use the same base, we can create another variable, AIRTABLE_URL, at the top of the file that you can use to construct the endpoint for each request. The code at the top of airtable.py should now look like this:

import os
from python_dotenv import load_dotenv
load_dotenv()

AIRTABLE_TOKEN = os.getenv("AIRTABLE_TOKEN")
AIRTABLE_BASE_ID = os.getenv("AIRTABLE_BASE_ID")

AIRTABLE_URL = f"https://api.airtable.com/v0/{AIRTABLE_BASE_ID}"

Using the REST API

The Airtable REST API allows you to perform a few core actions: add a record, retrieve records, update records, and delete records. A nice feature of the https://airtable.com/api Airtable API documentation is after you log in to your account, you can view the documentation specific to the Airtable base you want to use. The documentation provides API usage documentation for curl and Javascript. Below we'll look at examples of how to use the API using Python.

To demonstrate how the API works, we will use Airtable to track golf scores. We'll have a sheet named golf-scorecard containing four columns: the date, hole number, par, and the number of strokes for the hole.

Adding Records to Airtable

You can add records to your Airtable by sending a POST request. The request includes a dictionary with a key, records, defining an array of the records that will be added to the sheet. Each record in the array is a dictionary with a key fields, containing a dictionary that maps values to the columns in the sheet. Here's an example data payload for adding scores to the Airtable for the first two holes.

new_data = {
    "records": [
        {
            "fields": {
                "Date": "2021-09-22",
                "Hole": 1,
                "Par": 4,
                "Score": 5
            }
        },
        {
            "fields": {
                "Date": "2021-09-22",
                "Hole": 2,
                "Par": 4,
                "Score": 4
            }
        }
    ]
}

When you define records to add to Airtable, make sure the data types of the data you want to add match the data types for the column in Airtable. If the data types do not match, you will get an error.

Next, you need to write an API request to add this data to the Airtable. Create a new function in airtable.py called add_new_scores that will take the new_data scores as input and add them to the Airtable.

def add_new_scores(scores):
    """Add scores to the Airtable."""
    url = f"{AIRTABLE_URL}/golf-scores"
    headers = {
      'Authorization': f'Bearer {AIRTABLE_TOKEN}',
      'Content-Type': 'application/json'
    }

    response = requests.request("POST", url, headers=headers, data=json.dumps(scores))

    return response

The first part is building the URL referencing the AIRTABLE_URL variable we created earlier. The only addition is the name of our sheet, golf-scores, which has been added to the URL to instruct Airtable that we want to add records to the golf-scores sheet of our base. If you want to add scores to a different sheet, you can substitute the sheet's name in the URL.

Next, the request header is defined. The header passes along the AIRTABLE_TOKEN so that Airtable can confirm the request is authorized.

Finally, the POST request is submitted using the request module, passing the scores payload along with the request.

Let's run the code and look at the outcome.

One last note about adding records, each request can add a maximum of 10 records to your sheet. If you want to add more than 10 items, you will have to do so across multiple requests. Let's look at an example implementation below.

def chunk(arr, n):
    for i in range(0, len(arr), n):
        yield arr[i:i + n]

for c in chunk(data["records"], 10):
    chunk_data = {
        "records": c
    }

    response = airtable.add_new_scores(chunk_data)

The chunk function returns a generator that will break down the records into groups of size n where n should not be greater than 10. Next, you can iterate over the n sized chunks from your data and call the add_new_scores function during each iteration to add the records to Airtable.

Reading Records from Airtable

You can read records from Airtable by issuing a GET request to the API endpoint of a sheet. Let's create a new function in your airtable.py file to read records from the golf-scores sheet.

def get_golf_scores():
    """Add scores to the Airtable."""
    url = f"{AIRTABLE_URL}/golf-scores"
    headers = {
      'Authorization': f'Bearer {AIRTABLE_TOKEN}',
      'Content-Type': 'application/json'
    }

    response = requests.request("GET", url, headers=headers)

    return response

Like adding records, you define the URL endpoint to the golf-scores sheet and include your authentication header information. The two differences are that you will submit a GET request instead of a POST request, and you do not need to pass a data payload along with the request.

The API will respond with an array of records in your Airtable sheet. Each record has an id uniquely identifying the record, a field dictionary with the values for the record, and a createdTime key. An example response is below.

{
    "records":
        [
            {
                "id": "<AIRTABLE_RECORD_ID>",
                "fields": {
                    "Date": 2021-09-22,
                    "Hole": 1,
                    "Par": 4,
                    "Score": 5
                },
                "createdTime": <some_time>
            }
            ...
        ]
}

You may want only to retrieve records matching specific criteria from your Airtable. Airtable provides several options to customize querying your table. You can instruct Airtable to return particular fields, specify filtering criteria, sort records, and more. For a complete list of functionality, consult the Airtable API.

To demonstrate how to customize API calls to apply a filter to results, let's create a new function, get_scores_for_hole, to your file. In this function, you will query the golf-scores sheet in Airtable and return only the records for the hole number you send to the function. Instead of returning all table fields, your response will only contain the Hole and score fields for each record. Enter the following function in your file.

def get_scores_for_hole(hole):
    """Get scores for a specific hole."""
    url = f"{AIRTABLE_URL}/golf-scores"
    headers = {
      'Authorization': f'Bearer {AIRTABLE_TOKEN}',
      'Content-Type': 'application/json'
    }

    params = {
        "fields": ["Hole", "Score"],
        "filterByFormula": f"Hole={hole}"
    }

    response = requests.request("GET", url, headers=headers, params=params)

    return response

The difference with this function is the inclusion of the params object in your API request. The fields key instructs Airtable what fields to return in the response, and filterByFormula specifies the filter to apply to the sheet.

Airtable allows you to build more complex filters. For a complete list of functionality available to filter records and manipulate the Airtable response for retrieving records, you can check out the Airtable documentation.

By default, when you submit a GET request, Airtable will return a maximum of 100 records. If your response contains more than 100 records, Airtable will provide an offset value in its response. To retrieve more than 100 records, you will need to issue a new request that includes the value of offset. The function get_scores_by_page below accepts a parameter offset to instruct Airtable to retrieve the next page of results.

def get_golf_scores_by_page(offset=None):
    """Retrieve records from Airtable and apply offset is necessary."""
    url = f"{AIRTABLE_URL}/golf-scores"
    headers = {
      'Authorization': f'Bearer {AIRTABLE_TOKEN}',
      'Content-Type': 'application/json'
    }

    params = {
        "pageSize": 100
    }

    if offset:
        params["offset"] = offset

    response = requests.request("GET", url, headers=headers, params=params)

    return response

As long as your response contains the offset value, you will iteratively retrieve more records. When all records are retrieved, Airtable will stop sending offset in the response. An example implementation is below.

results = airtable.get_golf_scores_by_page()

while "offset" in results.json():
    results = airtable.get_golf_scores_by_page(response.json()["offset"])

Update a Record

You may need to change your data after adding it to Airtable. Updating existing records can be done in two different ways, PATCH or POST.

PATCH: to update specific fields in a record.
PUT: to clear the record and replace all values with new values.

First, let's look at the PATCH request. A PATCH request allows you to update specific fields of a record while keeping other values unchanged. You can pass a list of records with the values you'd like to change as a payload to the request. For example, if you wanted to update the score for a record, your payload would look something like this:

updated_records = {
    "records": [
        {
            "id": <record_id>,
            "fields": {
                "Score": 4
            },
        }
    ]
}

To update a record, you must send the record ID you wish to update as a part of the payload. You can find the record ID in the response from retrieving records that you looked at in the previous section.

Let's put this all together. Create a new function update_record_fields in your Python file:

def update_record_fields(updated_records):
    """Update specific field values for a record."""
    url = f"{AIRTABLE_URL}/golf-scores"
    headers = {
        'Authorization': f'Bearer {AIRTABLE_TOKEN}',
        'Content-Type': 'application/json'
    }

    response = requests.request("PATCH", url, headers=headers, data=json.dumps(updated_records))

    return response

The function accepts a parameter, updated_records, defining the records and values to be updated. Replace <record_id> in the updated_records object with an ID from your table, then use it as input to update_record_fields. If you look at the record in Airtable, the value for the Hole_Number field should have changed, and all other values should remain the same.

Another way you can update records is by using a PUT request. The main difference between PUT and PATCH is that a PATCH request will update the field values you specify in your payload and keep all other values the same. A PUT request will update the field values you specify but delete values for the other fields.

Let's look at the difference in action. Create a new function replace_record_fields:

def replace_record_fields(updated_records):
    """Updates the records."""
    url = f"{AIRTABLE_URL}/golf-scores"
    headers = {
        'Authorization': f'Bearer {AIRTABLE_TOKEN}',
        'Content-Type': 'application/json'
    }

    response = requests.request("PUT", url, headers=headers, data=json.dumps(updated_records))

    return response

The function is nearly identical to update_record_fields. The only difference is that we are using a PUT request instead of a PATCH here. This time let's try to change the score of the first hole to 6. Use the following payload as input to replace_record_fields, use the same record ID as the previous request and let's see what happens.

updated_records = {
    "records": [
        {
            "id": <record_id>,
            "fields": {
                "Score": 6
            },
        }
    ]
}

When you look at Airtable, you should notice that the score for the hole has updated to 6, but all the other record values are empty. The additional fields are empty because they are not included in the payload, representing the difference between updating records with a PUT versus PATCH request. A PATCH request will preserve the values for fields not specified in the update. PUT will clear values that are a part of the update payload.

One last note, similar to adding records, you can only update 10 records per request.

Delete a Record

The last action you can take via the Airtable API is deleting records. To delete a record, you will need to know the IDs of the records you want to delete. You can include the list of IDs as a query string parameter in a DELETE request to instruct Airtable to delete those records. Create a new function delete_records to your file.

def delete_records(records):
    """Delete the records."""
    url = f"{AIRTABLE_URL}/golf-scores"
    headers = {
        'Authorization': f'Bearer {AIRTABLE_TOKEN}',
        'Content-Type': 'application/json'
    }

    params = {
        "records[]": records
    }

    response = requests.request("DELETE", url, headers=headers, params=params)

    return response