Integrate the BigML API with the MongoDB API

Setup the BigML API trigger to run a workflow which integrates with the MongoDB API. Pipedream's integration platform allows you to integrate BigML and MongoDB remarkably fast. Free for developers.

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Popular Ways to Connect BigML with MongoDB#

Create Batch Prediction with BigML API on New Collection from MongoDB API

MongoDB + BigML

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Create Batch Prediction with BigML API on New Database from MongoDB API

MongoDB + BigML

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Create Batch Prediction with BigML API on New Document from MongoDB API

MongoDB + BigML

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Create Batch Prediction with BigML API on New Field in Document from MongoDB API

MongoDB + BigML

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Create Model with BigML API on New Collection from MongoDB API

MongoDB + BigML

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Popular BigML and MongoDB Triggers#

New Model Created from the BigML API

Emit new event for every created model. See docs here.

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New Prediction Made from the BigML API

Emit new event for every made prediction. See docs here.

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New Collection from the MongoDB API

Emit new an event when a new collection is added to a database

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New Database from the MongoDB API

Emit new an event when a new database is added

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New Document from the MongoDB API

Emit new an event when a new document is added to a collection

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Popular BigML and MongoDB Actions#

Create Batch Prediction with the BigML API

Create a batch prediction given a Supervised Model ID and a Dataset ID. See the docs.

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Create New Document with the MongoDB API

Create a new document in a collection of your choice. See the docs here

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Create Model with the BigML API

Create a model based on a given source ID, dataset ID, or model ID. See the docs.

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Delete a Document with the MongoDB API

Delete a single document by ID. See the docs here

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Create Source (Remote URL) with the BigML API

Create a source with a provided remote URL that points to the data file that you want BigML to download for you. See the docs.

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Overview of BigML#

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.

Connect BigML#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    bigml: {
      type: "app",
      app: "bigml",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://bigml.io/andromeda/source`,
      params: {
        username: `${this.bigml.$auth.username}`,
        api_key: `${this.bigml.$auth.api_key}`,
      },
    })
  },
})

Overview of MongoDB#

The MongoDB API provides powerful capabilities to interact with a MongoDB database, allowing you to perform CRUD (Create, Read, Update, Delete) operations, manage databases, and execute sophisticated queries. With Pipedream, you can harness these abilities to automate tasks, sync data across various apps, and react to events in real-time. It’s a combo that’s particularly potent for managing data workflows, syncing application states, or triggering actions based on changes to your data.

Connect MongoDB#

import mongodb from 'mongodb'

export default defineComponent({
  props: {
    mongodb: {
      type: "app",
      app: "mongodb",
    },
    collection: {
      type: "string"
    },
    filter: {
      type: "object"
    }
  },
  async run({steps, $}) {
    const MongoClient = mongodb.MongoClient
    
    const {
      database,
      hostname,
      username,
      password,
    } = this.mongodb.$auth
    
    const url = `mongodb+srv://${username}:${password}@${hostname}/test?retryWrites=true&w=majority`
    const client = await MongoClient.connect(url, { 
      useNewUrlParser: true, 
      useUnifiedTopology: true 
    })
    
    const db = client.db(database)

    const results = await db.collection(this.collection).find(this.filter).toArray();
    $.export('results', results);
    
    await client.close()
  },
})

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