Integrate the Imagga API with the Python API

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

Popular Ways to Connect Imagga with Python#

Run Python Code with Python API on New Batch Processed from Imagga API

Imagga + Python

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Popular Imagga and Python 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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Popular Imagga and Python 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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Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

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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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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 Python#

Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.

This includes installing PyPI packages, within your code without having to manage a requirements.txt file or running pip.

Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:

Connect Python#

def handler(pd: "pipedream"):
  # Reference data from previous steps
  print(pd.steps["trigger"]["context"]["id"])
  # Return data for use in future steps
  return {"foo": {"test":True}}