Algorithmia

Algorithmia is community algorithm development

Integrate the Algorithmia API with the Python API

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

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

Overview of Algorithmia

The Algorithmia API provides access to a myriad of algorithms in various categories like machine learning, data analysis, and natural language processing. By utilizing this API on Pipedream, you can automate complex tasks that require advanced computations, such as sentiment analysis, image processing, or predictive modeling, without the need to develop and maintain the underlying algorithms yourself. Pipedream's serverless platform allows you to seamlessly integrate these capabilities with other services to create powerful data processing pipelines.

Connect Algorithmia

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    algorithmia: {
      type: "app",
      app: "algorithmia",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      method: "post",
      url: `https://api.algorithmia.com/v1/algo/demo/Hello/`,
      headers: {
        "Authorization": `Simple ${this.algorithmia.$auth.YOUR_API_KEY}`,
      },
    })
  },
})

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

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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}}