Looker

Business intelligence

Integrate the Looker API with the Python API

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

With Looker, you can easily build performant, dynamic applications that look
great and provide value to your users. Here are some examples of what you can
build using the Looker API:

  • A data exploration tool that lets users quickly and easily find the data they
    need
  • A reporting application that automatically generates reports based on
    user-defined criteria
  • An analytics dashboard that gives users insights into their data in real-time
  • A data visualization tool that makes it easy to understand complex data sets

Connect Looker

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    looker: {
      type: "app",
      app: "looker",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `${this.looker.$auth.looker_base_url}/api/4.0/user`,
      headers: {
        "Authorization": `token ${this.looker.$auth.oauth_access_token}`,
      },
    })
  },
})

Overview of Python

Python API on Pipedream offers developers to build or automate a variety of
tasks from their web and cloud apps. With the Python API, users are able to
create comprehensive and flexible scripts, compose and manage environment
variables, and configure resources to perform a range of functions.

By using Pipedream, you can easily:

  • Create automated workflows that run on a specific schedule
  • Compose workflows across various apps and services
  • React to events in cloud services or form data
  • Automatically create content and notifications
  • Construct classifications and predictions
  • Analyze and react to sentiment, sentiment analysis and sentiment score
  • Connect backends to the frontend with serverless functions
  • Work with files and databases
  • Perform web requests and fetch data
  • Integrate third-party APIs into your apps
  • Orchestrate data processing tasks and pipelines
  • Create powerful application APIs with authentication and authorization
  • Design CI/CD pipelines and Continuous Delivery services
  • Connect databases like MongoDB and MySQL
  • Monitor connections and events
  • Generate alerts and notifications for corresponding events

Connect Python

1
2
3
4
5
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}}