InfluxDB Cloud

Focus on building software with an easy-to-use, scalable, serverless time series platform available on AWS, Azure, and Google Cloud.

Integrate the InfluxDB Cloud API with the Python API

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

Harness the power of InfluxDB Cloud API on Pipedream to build robust data workflows. InfluxDB Cloud, a time-series database, is ideal for managing high-velocity data and extracting insights in real-time. On Pipedream, you can easily trigger workflows based on InfluxDB data, automate data ingestion, and connect with countless other services to analyze, visualize, and act upon your data.

Connect InfluxDB Cloud

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import { InfluxDB } from '@influxdata/influxdb-client';
import { HealthAPI } from '@influxdata/influxdb-client-apis';

export default defineComponent({
  props: {
    influxdb_cloud: {
      type: "app",
      app: "influxdb_cloud",
    }
  },
  async run({steps, $}) {
    // See the Node.js client docs at
    // https://github.com/influxdata/influxdb-client-js
    const influxDB = new InfluxDB(this.influxdb_cloud.$auth.url);
    const healthAPI = new HealthAPI(influxDB)
    
    // Execute a health check to test our credentials
    return await healthAPI.getHealth()
  },
})

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}}