Integrate the Nyckel API with the Python API

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

Popular Nyckel and Python Actions#

Classify Image with the Nyckel API

Classifies image data based on pre-trained classifiers in Nyckel. See the documentation

Try it

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.

Try it

Classify Text with the Nyckel API

Classifies text data based on pre-trained classifiers in Nyckel. See the documentation

Try it

Extract Text from Image with the Nyckel API

Extracts text from an image URL. See the documentation

Try it

Overview of Nyckel#

The Nyckel API offers machine learning capabilities, enabling you to add custom image and text classification to your applications without needing a data science background. With Nyckel, you can train models, make predictions, and refine your model iteratively as new data comes in. On Pipedream, you can integrate Nyckel to automate various tasks such as processing images uploaded to cloud storage, categorizing customer support tickets, or augmenting content moderation workflows. By harnessing the power of serverless on Pipedream, you can create efficient pipelines that respond in real-time to events, without managing infrastructure.

Connect Nyckel#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    nyckel: {
      type: "app",
      app: "nyckel",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://www.nyckel.com/v1/functions`,
      headers: {
        Authorization: `Bearer ${this.nyckel.$auth.oauth_access_token}`,
      },
    })
  },
})

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}}