Survicate

Survicate is a powerful survey, NPS and feedback management tool that helps businesses capture more customer feedback.

Integrate the Survicate API with the Python API

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

The Survicate API empowers you to seamlessly integrate survey data into your systems, automate actions based on feedback, and sync responses across your tech stack. With Pipedream, you can create serverless workflows that leverage this API to respond in real-time to survey submissions, aggregate data for analysis, or trigger personalized marketing campaigns. Pipedream's no-code platform simplifies the process of connecting Survicate with other apps like Slack, Google Sheets, or CRMs such as Salesforce, to streamline data flows and enhance customer insights.

Connect Survicate

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    survicate: {
      type: "app",
      app: "survicate",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://data-api.survicate.com/v1/surveys`,
      headers: {
        "Authorization": `Basic ${this.survicate.$auth.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}}