Integrate the Imagga API with the MongoDB API

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

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Popular Ways to Connect Imagga with MongoDB#

Analyze Image with Imagga API on New Collection from MongoDB API

MongoDB + Imagga

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Analyze Image with Imagga API on New Database from MongoDB API

MongoDB + Imagga

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Analyze Image with Imagga API on New Document from MongoDB API

MongoDB + Imagga

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Analyze Image with Imagga API on New Field in Document from MongoDB API

MongoDB + Imagga

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Create New Document with MongoDB API on New Batch Processed from Imagga API

Imagga + MongoDB

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Popular Imagga and MongoDB Triggers#

New Batch Processed from the Imagga API

Emit new event when a batch of images has been processed for categorization, tagging, or color extraction.

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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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New Field in Document from the MongoDB API

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

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Popular Imagga and MongoDB Actions#

Analyze Image with the Imagga API

Assign a category to a single image based on its visual content. See the documentation

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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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Delete a Document with the MongoDB API

Delete a single document by ID. See the docs here

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Process Batch of Images with the Imagga API

Analyzes a batch of images for categorization, tagging, or color extraction. See the documentation

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Execute Aggregation with the MongoDB API

Execute an aggregation pipeline on a MongoDB collection. See the documentation

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Overview of Imagga#

The Imagga API is a powerful image recognition tool that enables you to automate the process of analyzing and tagging images. With its AI-driven capabilities, you can extract a wealth of information from visual content. It offers features such as categorization, color extraction, and auto-tagging, making it incredibly useful for building workflows that require image analysis.

Connect Imagga#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    imagga: {
      type: "app",
      app: "imagga",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://api.imagga.com/v2/usage`,
      auth: {
        username: `${this.imagga.$auth.api_key}`,
        password: `${this.imagga.$auth.api_secret}`,
      },
    })
  },
})

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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