Send PUT Request with HTTP / Webhook API on New Model Created from BigML API

Pipedream makes it easy to connect APIs for HTTP / Webhook, BigML and 2,000+ other apps remarkably fast.

Trigger workflow on

New Model Created from the BigML API

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Send PUT Request with the HTTP / Webhook API

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Getting Started#

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

Select this integration
Configure the New Model Created trigger
1. Connect your BigML account
2. Configure timer
Configure the Send PUT Request action
1. Connect your HTTP / Webhook account
2. Configure HTTP Request Configuration
3. Optional- Configure Include Response Headers
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 Model Created on BigML

Description:Emit new event for every created model. [See docs here.](https://bigml.com/api/models?id=listing-models)

Version:0.0.1

Key:bigml-new-model-created

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.

Trigger Code#

import base from "../common/base.mjs";

export default {
  ...base,
  key: "bigml-new-model-created",
  name: "New Model Created",
  description: "Emit new event for every created model. [See docs here.](https://bigml.com/api/models?id=listing-models)",
  version: "0.0.1",
  type: "source",
  dedupe: "unique",
  methods: {
    ...base.methods,
    listingFunction() {
      return this.bigml.listModels;
    },
    emitEvent(model) {
      this.$emit(model, {
        id: model.resource,
        summary: `New model created: ${model.name}`,
        ts: model.created,
      });
    },
  },
};

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
BigML	`bigml`	`app`	This component uses the BigML app.
N/A	`db`	`$.service.db`	This component uses `$.service.db` to maintain state between executions.
	`timer`	`$.interface.timer`

Trigger 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”

About BigML#

Machine Learning made beautifully simple. A company-wide platform that runs in any cloud or on-premises to operationalize Machine Learning in your organization.

Action#

Send PUT Request on HTTP / Webhook

Description:Send an HTTP PUT request to any URL. Optionally configure query string parameters, headers and basic auth.

Version:1.1.1

Key:http-put-request

View on GitHub

HTTP / Webhook Overview#

Build, test, and send HTTP requests without code using your Pipedream workflows. The HTTP / Webhook action is a tool to build HTTP requests with a Postman-like graphical interface.

Point and click HTTP requests

Define the target URL, HTTP verb, headers, query parameters, and payload body without writing custom code.

$A screenshot of Pipedream's HTTP Request Configuration interface with a GET request type selected. The request URL is set to 'https://api.openai.com/v1/models'. The 'Auth' tab is highlighted, indicating that authentication is required for this request. In the headers section, there are two headers configured: 'User-Agent' is set to 'pipedream/1', and 'Authorization' is set to 'Bearer {{openai_api_key}}', showing how the OpenAI account's API key is dynamically inserted into the headers to handle authentication automatically.$

Here's an example workflow that uses the HTTP / Webhook action to send an authenticated API request to OpenAI.

Focus on integrating, not authenticating

This action can also use your connected accounts with third-party APIs. Selecting an integrated app will automatically update the request’s headers to authenticate with the app properly, and even inject your token dynamically.

Pipedream integrates with thousands of APIs, but if you can’t find a Pipedream integration simply use Environment Variables in your request headers to authenticate with.

Compatible with no code actions or Node.js and Python

The HTTP/Webhook action exports HTTP response data for use in subsequent workflow steps, enabling easy data transformation, further API calls, database storage, and more.

Response data is available for both coded (Node.js, Python) and no-code steps within your workflow.

Action Code#

import customRequest from "../custom-request/custom-request.mjs";

export default {
  ...customRequest,
  key: "http-put-request",
  name: "Send PUT Request",
  description: "Send an HTTP PUT request to any URL. Optionally configure query string parameters, headers and basic auth.",
  type: "action",
  version: "1.1.1",
  props: {
    ...customRequest.props,
    /* eslint-disable-next-line pipedream/props-label,pipedream/props-description */
    httpRequest: {
      ...customRequest.props.httpRequest,
      default: {
        method: "PUT",
      },
    },
  },
};

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
HTTP / Webhook	`http`	`app`	This component uses the HTTP / Webhook app.
HTTP Request Configuration	`httpRequest`	`http_request`
Include Response Headers	`includeHeaders`	`boolean`	Optionally export the full response headers

Action Authentication#

The HTTP / Webhook API does not require authentication.

About HTTP / Webhook#

Get a unique URL where you can send HTTP or webhook requests

More Ways to Connect HTTP / Webhook + BigML#

Other Popular Integrations#

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