Create Batch Prediction with BigML API on New or Updated Contact from HubSpot API

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New or Updated Contact from the HubSpot API

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Create Batch Prediction with the BigML API

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Getting Started#

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

Select this integration
Configure the New or Updated Contact trigger
1. Connect your HubSpot account
2. Configure timer
3. Configure info
4. Optional- Select one or more Additional properties to retrieve
5. Optional- Select one or more Lists
6. Optional- Configure New Only
Configure the Create Batch Prediction action
1. Connect your BigML account
2. Optional- Select a Model ID
3. Optional- Select a Dataset ID
4. Optional- Configure Description
5. Optional- Configure Other Arguments
Deploy the workflow
Send a test event to validate your setup
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#

New or Updated Contact on HubSpot

Description:Emit new event for each new or updated contact in Hubspot.

Version:0.0.24

Key:hubspot-new-or-updated-contact

View on GitHub

HubSpot Overview#

The HubSpot API enables developers to integrate into HubSpots CRM, CMS, Conversations, and other features. It allows for automated management of contacts, companies, deals, and marketing campaigns, enabling custom workflows, data synchronization, and task automation. This streamlines operations and boosts customer engagement, with real-time updates for rapid response to market changes.

Trigger Code#

import {
  DEFAULT_CONTACT_PROPERTIES,
  DEFAULT_LIMIT,
} from "../../common/constants.mjs";
import common from "../common/common.mjs";
import sampleEmit from "./test-event.mjs";

export default {
  ...common,
  key: "hubspot-new-or-updated-contact",
  name: "New or Updated Contact",
  description: "Emit new event for each new or updated contact in Hubspot.",
  version: "0.0.24",
  dedupe: "unique",
  type: "source",
  props: {
    ...common.props,
    info: {
      type: "alert",
      alertType: "info",
      content: `Properties:\n\`${DEFAULT_CONTACT_PROPERTIES.join(", ")}\``,
    },
    properties: {
      propDefinition: [
        common.props.hubspot,
        "contactProperties",
        () => ({
          excludeDefaultProperties: true,
        }),
      ],
      label: "Additional properties to retrieve",
    },
    lists: {
      propDefinition: [
        common.props.hubspot,
        "lists",
      ],
      withLabel: false,
      optional: true,
    },
    newOnly: {
      type: "boolean",
      label: "New Only",
      description: "Emit events only for new contacts",
      default: false,
      optional: true,
    },
  },
  methods: {
    ...common.methods,
    getTs(contact) {
      return this.newOnly
        ? Date.parse(contact.createdAt)
        : Date.parse(contact.updatedAt);
    },
    generateMeta(contact) {
      const { id } = contact;
      const ts = this.getTs(contact);
      return {
        id: this.newOnly
          ? id
          : `${id}-${ts}`,
        summary: `Record ID: ${id}`,
        ts,
      };
    },
    async translateListIds(lists) {
      const listIds = [];
      for (const list of lists) {
        const { listId } = await this.hubspot.translateLegacyListId({
          params: {
            legacyListId: list,
          },
        });
        listIds.push(listId);
      }
      return listIds;
    },
    async isRelevant(contact, updatedAfter) {
      if (this.getTs(contact) < updatedAfter) {
        return false;
      }
      if (this.lists?.length) {
        const { results } = await this.hubspot.getMemberships({
          objectType: "contacts",
          objectId: contact.id,
        });
        const contactListIds = results?.map(({ listId }) => listId) || [];
        const listIds = await this.translateListIds(this.lists);
        for (const list of listIds) {
          if (contactListIds.includes(list)) {
            return true;
          }
        }
        return false;
      }
      return true;
    },
    getParams(after) {
      const { properties = [] } = this;
      const dateProperty = this.newOnly
        ? "createdate"
        : "lastmodifieddate";

      const params = {
        data: {
          limit: DEFAULT_LIMIT,
          sorts: [
            {
              propertyName: dateProperty,
              direction: "DESCENDING",
            },
          ],
          properties: [
            ...DEFAULT_CONTACT_PROPERTIES,
            ...properties,
          ],
        },
        object: "contacts",
      };

      if (after) {
        params.data.filterGroups = [
          {
            filters: [
              {
                propertyName: dateProperty,
                operator: "GT",
                value: after,
              },
            ],
          },
        ];
      }

      return params;
    },
    async processResults(after, params) {
      await this.searchCRM(params, after);
    },
  },
  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.

Label	Prop	Type	Description
HubSpot	`hubspot`	`app`	This component uses the HubSpot app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`
Additional properties to retrieve	`properties`	`string[]`	Select a value from the drop down menu.
Lists	`lists`	`string[]`	Select a value from the drop down menu.
New Only	`newOnly`	`boolean`	Emit events only for new contacts

Trigger Authentication#

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

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

business-intelligencecrm.lists.readcrm.lists.writecrm.objects.companies.readcrm.objects.companies.writecrm.objects.contacts.readcrm.objects.contacts.writecrm.objects.deals.readcrm.objects.deals.writecrm.objects.quotes.readcrm.objects.quotes.writecrm.objects.owners.readcrm.objects.listings.writecrm.objects.listings.readcrm.schemas.companies.readcrm.schemas.companies.writecrm.schemas.contacts.readcrm.schemas.contacts.writecrm.schemas.deals.readcrm.schemas.deals.writecrm.schemas.quotes.readcrm.schemas.listings.writecrm.schemas.listings.readconversations.readcrm.importfilesformsforms-uploaded-filesintegration-syncoauthtimeline

About HubSpot#

HubSpot's CRM platform contains the marketing, sales, service, operations, and website-building software you need to grow your business.

Action#

Create Batch Prediction on BigML

Description:Create a batch prediction given a Supervised Model ID and a Dataset ID. [See the docs.](https://bigml.com/api/batchpredictions?id=creating-a-batch-prediction)

Version:0.0.2

Key:bigml-create-batch-prediction

View on GitHub

BigML Overview#

The BigML API offers a suite of machine learning tools that enable the creation and management of datasets, models, predictions, and more. It's a powerful resource for developers looking to incorporate machine learning into their applications. Within Pipedream, you can leverage the BigML API to automate workflows, process data, and apply predictive analytics. By connecting BigML to other apps in Pipedream, you can orchestrate sophisticated data pipelines that react to events, perform analyses, and take action based on machine learning insights.

Action Code#

import bigml from "../../bigml.app.mjs";
import { parseJSON } from "../../common/utils.mjs";

export default {
  key: "bigml-create-batch-prediction",
  name: "Create Batch Prediction",
  description: "Create a batch prediction given a Supervised Model ID and a Dataset ID. [See the docs.](https://bigml.com/api/batchpredictions?id=creating-a-batch-prediction)",
  version: "0.0.2",
  annotations: {
    destructiveHint: false,
    openWorldHint: true,
    readOnlyHint: false,
  },
  type: "action",
  props: {
    bigml,
    modelId: {
      propDefinition: [
        bigml,
        "modelId",
      ],
      optional: true,
    },
    datasetId: {
      propDefinition: [
        bigml,
        "datasetId",
      ],
      optional: true,
    },
    description: {
      type: "string",
      label: "Description",
      description: "A description of the batch prediction",
      optional: true,
    },
    args: {
      type: "object",
      label: "Other Arguments",
      description: "Other arguments for the batch prediction. [See the docs](https://bigml.com/api/batchpredictions?id=batch-prediction-arguments) for more information",
      optional: true,
    },
  },
  async run({ $ }) {
    const response = await this.bigml.createBatchPrediction({
      $,
      data: {
        ...parseJSON(this.args),
        model: this.modelId,
        dataset: this.datasetId,
        description: this.description,
      },
    });
    $.export("$summary", "Succesfully created batch prediction");
    return response;
  },
};

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.

Label	Prop	Type	Description
BigML	`bigml`	`app`	This component uses the BigML app.
Model ID	`modelId`	`string`	Select a value from the drop down menu.
Dataset ID	`datasetId`	`string`	Select a value from the drop down menu.
Description	`description`	`string`	A description of the batch prediction
Other Arguments	`args`	`object`	Other arguments for the batch prediction. See the docs for more information

Action Authentication#

BigML uses API keys for authentication. When you connect your BigML account, Pipedream securely stores the keys so you can easily authenticate to BigML APIs in both code and no-code steps.

To retrieve your API key,

Navigate to your BigML account and sign in
Click on the Account menu on the top right
Go to “API key”

Create Batch Prediction with BigML API on New or Updated Contact from HubSpot API

Pipedream makes it easy to connect APIs for BigML, HubSpot and 2,900+ other apps remarkably fast.

Trusted by 1,000,000+ developers from startups to Fortune 500 companies

Developers ♥ Pipedream

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