Smarty

The leader in location data intelligence. Smarty's easy-to-use APIs verify, validate, enrich, standardize, geocode, and auto-complete addresses at super speeds.

Integrate the Smarty API with the Python API

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

The Smarty API, previously known as SmartyStreets, provides powerful location data services, including address validation, geocoding, and autocomplete for addresses. Integrating Smarty with Pipedream allows you to automate processes that require address verification or geolocation data, enriching datasets, improving delivery accuracy, and enhancing user experiences through auto-complete suggestions. By leveraging Pipedream's serverless platform, you can create workflows that react to events, process data in real-time, and connect Smarty with hundreds of other services without managing infrastructure.

Connect Smarty

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    smarty: {
      type: "app",
      app: "smarty",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://us-zipcode.api.smartystreets.com/lookup`,
      params: {
        "auth-id": `${this.smarty.$auth.auth_id}`,
        "auth-token": `${this.smarty.$auth.auth_token}`,
        city: `{your_city}`,
        state: `{your_state}`,
        zipcode: `{your_zipcode}`,
      },
    })
  },
})

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}}