← Airtable (OAuth) + Python integrations

Run Python Code with Python API on New or Modified Records from Airtable (OAuth) API

Pipedream makes it easy to connect APIs for Python, Airtable (OAuth) and 2,100+ other apps remarkably fast.

Trigger workflow on
New or Modified Records from the Airtable (OAuth) API
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Run Python Code with the Python API
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Getting Started

This integration creates a workflow with a Airtable (OAuth) trigger and Python action. When you configure and deploy the workflow, it will run on Pipedream's servers 24x7 for free.

  1. Select this integration
  2. Configure the New or Modified Records trigger
    1. Connect your Airtable (OAuth) account
    2. Configure timer
    3. Select a Base
    4. Select a Table
    5. Optional- Select one or more Field IDs
    6. Optional- Configure Return Fields By Field ID
  3. Configure the Run Python Code action
    1. Connect your Python account
  4. Deploy the workflow
  5. Send a test event to validate your setup
  6. Turn on the trigger

Details

This integration uses pre-built, source-available components from Pipedream's GitHub repo. These components are developed by Pipedream and the community, and verified and maintained by Pipedream.

To contribute an update to an existing component or create a new component, create a PR on GitHub. If you're new to Pipedream component development, you can start with quickstarts for trigger span and action development, and then review the component API reference.

Trigger

Description:Emit new event for each new or modified record in a table
Version:0.0.8
Key:airtable_oauth-new-or-modified-records

Airtable (OAuth) Overview

Airtable (OAuth) API on Pipedream allows you to manipulate and leverage your Airtable data in a myriad of powerful ways. Sync data between Airtable and other apps, trigger workflows on updates, or process bulk data operations asynchronously. By using Airtable's structured databases with Pipedream's serverless platform, you can craft custom automation solutions, integrate with other services seamlessly, and streamline complex data processes.

Trigger Code

import base from "../common/common.mjs";
import sampleEmit from "./test-event.mjs";
import moment from "moment";

export default {
  ...base,
  name: "New or Modified Records",
  key: "airtable_oauth-new-or-modified-records",
  description: "Emit new event for each new or modified record in a table",
  version: "0.0.8",
  type: "source",
  props: {
    ...base.props,
    tableId: {
      propDefinition: [
        base.props.airtable,
        "tableId",
        ({ baseId }) => ({
          baseId,
        }),
      ],
      description: "The table ID to watch for changes.",
    },
    fieldIds: {
      propDefinition: [
        base.props.airtable,
        "sortFieldId",
        ({
          baseId, tableId,
        }) => ({
          baseId,
          tableId,
        }),
      ],
      type: "string[]",
      label: "Field IDs",
      description: "Identifiers of spedific fields/columns to watch for updates",
      withLabel: true,
    },
    returnFieldsByFieldId: {
      propDefinition: [
        base.props.airtable,
        "returnFieldsByFieldId",
      ],
    },
  },
  methods: {
    ...base.methods,
    _getFieldValues() {
      return this.db.get("fieldValues") || {};
    },
    _setFieldValues(fieldValues) {
      this.db.set("fieldValues", fieldValues);
    },
    updateFieldValues(newFieldValues, record) {
      const fieldKey = this.returnFieldsByFieldId
        ? "value"
        : "label";
      for (const fieldId of this.fieldIds) {
        newFieldValues[record.id] = {
          ...newFieldValues[record.id],
          [fieldId.value]: record.fields[fieldId[fieldKey]] || null,
        };
      }
      return newFieldValues;
    },
    isUpdated(fieldValues, fieldIds, record) {
      const fieldKey = this.returnFieldsByFieldId
        ? "value"
        : "label";
      for (const fieldId of fieldIds) {
        if (!record.fields[fieldId[fieldKey]]) {
          record.fields[fieldId[fieldKey]] = null;
        }
        if (fieldValues[record.id]
          && fieldValues[record.id][fieldId.value] !== undefined
          && record.fields[fieldId[fieldKey]] !== fieldValues[record.id][fieldId.value]
        ) {
          return true;
        }
      }
      return false;
    },
  },
  async run(event) {
    const {
      baseId,
      tableId,
      viewId,
    } = this;

    const lastTimestamp = this._getLastTimestamp();
    const fieldValues = this._getFieldValues();
    const isFirstRunWithFields = this.fieldIds && Object.keys(fieldValues).length === 0;
    const params = {
      returnFieldsByFieldId: this.returnFieldsByFieldId || false,
    };
    if (!isFirstRunWithFields) {
      params.filterByFormula = `LAST_MODIFIED_TIME() > "${lastTimestamp}"`;
    }

    const records = await this.airtable.listRecords({
      baseId,
      tableId,
      params,
    });

    if (!records.length) {
      console.log("No new or modified records.");
      return;
    }

    const metadata = {
      baseId,
      tableId,
      viewId,
    };

    let newRecords = 0, modifiedRecords = 0;
    let newFieldValues = {
      ...fieldValues,
    };
    for (const record of records) {
      if (this.fieldIds) {
        newFieldValues = this.updateFieldValues(newFieldValues, record);
      }
      if (!lastTimestamp || moment(record.createdTime) > moment(lastTimestamp)) {
        record.type = "new_record";
        newRecords++;
      } else {
        if (this.fieldIds
          && (!this.isUpdated(fieldValues, this.fieldIds, record) || isFirstRunWithFields)
        ) {
          continue;
        }
        record.type = "record_modified";
        modifiedRecords++;
      }

      record.metadata = metadata;

      this.$emit(record, {
        summary: `${record.type}: ${JSON.stringify(record.fields)}`,
        id: record.id,
        ts: Date.now(),
      });
    }
    this._setFieldValues(newFieldValues);
    console.log(`Emitted ${newRecords} new records(s) and ${modifiedRecords} modified record(s).`);

    // We keep track of the timestamp of the current invocation
    this.updateLastTimestamp(event);
  },
  sampleEmit,
};

Trigger Configuration

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI and CLI.
LabelPropTypeDescription
Airtable (OAuth)airtableappThis component uses the Airtable (OAuth) app.
N/Adb$.service.dbThis component uses $.service.db to maintain state between executions.
timer$.interface.timer
BasebaseIdstringSelect a value from the drop down menu.
TabletableIdstringSelect a value from the drop down menu.
Field IDsfieldIdsstring[]Select a value from the drop down menu.
Return Fields By Field IDreturnFieldsByFieldIdboolean

An optional boolean value that lets you return field objects where the key is the field id. This defaults to false, which returns field objects where the key is the field name.

Trigger Authentication

Airtable (OAuth) uses OAuth authentication. When you connect your Airtable (OAuth) account, Pipedream will open a popup window where you can sign into Airtable (OAuth) and grant Pipedream permission to connect to your account. Pipedream securely stores and automatically refreshes the OAuth tokens so you can easily authenticate any Airtable (OAuth) API.

Pipedream requests the following authorization scopes when you connect your account:

data.records:readdata.records:writedata.recordComments:readdata.recordComments:writeschema.bases:readschema.bases:writewebhook:manageuser.email:read

About Airtable (OAuth)

Airtable is a low-code platform to build next-gen apps. Move beyond rigid tools, operationalize your critical data, and reimagine workflows with AI.

Action

Description:Write Python and use any of the 350k+ PyPi packages available. Refer to the [Pipedream Python docs](https://pipedream.com/docs/code/python) to learn more.
Version:0.0.2
Key:python-run-python-code

Python Overview

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Action Code

import python from "../../python.app.mjs";

export default {
  name: "Run Python Code",
  version: "0.0.2",
  key: "python-run-python-code",
  description: "Write Python and use any of the 350k+ PyPi packages available. Refer to the [Pipedream Python docs](https://pipedream.com/docs/code/python) to learn more.",
  props: {
    python,
  },
  type: "action",
  methods: {},
  async run({
    steps, $,
  }) {
    // Placeholder action for Python code app
  },
};

Action Configuration

This component may be configured based on the props defined in the component code. Pipedream automatically prompts for input values in the UI.

LabelPropTypeDescription
PythonpythonappThis component uses the Python app.

Action Authentication

The Python API does not require authentication.

About Python

Anything you can do in Python can be done in a Pipedream Workflow. This includes using any of the 350,000+ PyPi packages available in your Python powered workflows.

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