Utradea

Stock and Crypto Investment Ideas | Social Sentiment Analytics | Automated Due Diligence and Trade Alerts | Investment Community

Integrate the Utradea API with the Python API

Setup the Utradea API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Utradea 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 Utradea

The Utradea API allows users to access financial analytics and social sentiment data for various investment opportunities. With this API, you can programmatically get insights into stock trends, market predictions, and community-driven investment analysis. When used within Pipedream, you have the ability to create automated workflows that can help you make informed investment decisions, track stock performance, or integrate with other financial tools.

Connect Utradea

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    utradea: {
      type: "app",
      app: "utradea",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `http://cloud.utradea.com/v1/get-social-tickers`,
      headers: {
        "Content-Type": `application/json`,
        "Authorization": `${this.utradea.$auth.api_key}`,
      },
      params: {
        social: `stocktwits`,
        tickers: `BTC-USD,PLTR`,
      },
    })
  },
})

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}}