Create Batch Prediction with BigML API on New Pin Event from Pinterest API

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New Pin Event from the Pinterest 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 Pinterest 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 Pin Event trigger
1. Connect your Pinterest account
2. Configure timer
3. Select a Board ID
4. Optional- Select a Board Section ID
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 Pin Event on Pinterest

Description:Emit new events when new pins are created on a board or board section. [See the docs here](https://developers.pinterest.com/docs/api/v5/#operation/boards/list_pins) and [here](https://developers.pinterest.com/docs/api/v5/#operation/board_sections/list_pins)

Version:0.1.0

Key:pinterest-new-pin

View on GitHub

Pinterest Overview#

The Pinterest API opens a portal to interact programmatically with Pinterest's rich data, including boards, pins, and user information. By leveraging this API on Pipedream, you can automate actions like posting new pins, extracting pin data for analysis, and synchronizing Pinterest content with other platforms. The potential extends to marketing optimization, content management, and audience engagement, all automated and integrated within the Pipedream ecosystem.

Trigger Code#

import pinterest from "../../pinterest.app.mjs";
import common from "../common.mjs";

export default {
  key: "pinterest-new-pin",
  name: "New Pin Event",
  description: "Emit new events when new pins are created on a board or board section. [See the docs here](https://developers.pinterest.com/docs/api/v5/#operation/boards/list_pins) and [here](https://developers.pinterest.com/docs/api/v5/#operation/board_sections/list_pins)",
  version: "0.1.0",
  type: "source",
  ...common,
  props: {
    pinterest,
    ...common.props,
    boardId: {
      propDefinition: [
        pinterest,
        "boardId",
      ],
    },
    boardSectionId: {
      propDefinition: [
        pinterest,
        "boardSectionId",
        (configuredProps) => ({
          boardId: configuredProps.boardId,
        }),
      ],
    },
  },
  methods: {
    ...common.methods,
    getResourceFn() {
      return this.pinterest.getPins;
    },
    getResourceFnArgs() {
      return {
        boardId: this.boardId,
        boardSectionId: this.boardSectionId,
      };
    },
    getSummary(item) {
      return `New pin ${item.title} (ID:${item.id})`;
    },
    compareFn(item) {
      return new Date(item.created_at).getTime() > this.getLastFetchTime();
    },
  },
};

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
Pinterest	`pinterest`	`app`	This component uses the Pinterest app.
	`timer`	`$.interface.timer`
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
Board ID	`boardId`	`string`	Select a value from the drop down menu.
Board Section ID	`boardSectionId`	`string`	Select a value from the drop down menu.

Trigger Authentication#

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

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

boards:readboards:read_secretboards:writeboards:write_secretpins:readpins:read_secretpins:writepins:write_secretuser_accounts:read

About Pinterest#

Pinterest is a visual discovery engine for finding ideas like recipes, home and style inspiration, and more.

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:0.0.1

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: "0.0.1",
  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,