Integrate the Qntrl API with the Python API

Setup the Qntrl API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Qntrl and Python remarkably fast. Free for developers.

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Popular Ways to Connect Qntrl with Python#

Run Python Code with Python API on New Comment Posted from Qntrl API

Qntrl + Python

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Run Python Code with Python API on New Job Created from Qntrl API

Qntrl + Python

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Popular Qntrl and Python Triggers#

New Comment Posted from the Qntrl API

Emit new event when a comment is posted to a job. See the documentation

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New Job Created from the Qntrl API

Emit new event when a job is created. See the documentation

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Popular Qntrl and Python Actions#

Create Job with the Qntrl API

Creates a new job (card) in Qntrl. See the documentation

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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.

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Post Comment with the Qntrl API

Posts a new comment under a specific job. See the documentation

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Overview of Qntrl#

The Qntrl API offers a powerful way to manage and automate your organization's workflows and processes directly within Pipedream. With this API, you can create, update, retrieve, and manage cards, orchestrate workflows, and synchronize data across different systems. Harness the power of Pipedream to integrate Qntrl with various apps and services, enabling seamless data flow and enhanced productivity.

Connect Qntrl#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    qntrl: {
      type: "app",
      app: "qntrl",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://coreapi.qntrl.com/blueprint/api/user/myinfo`,
      headers: {
        Authorization: `Bearer ${this.qntrl.$auth.oauth_access_token}`,
      },
    })
  },
})

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#

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}}

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