Karbon
Karbon is a collaborative practice management platform for accounting firms to manage workflows, communicate with teams and deliver exceptional client work.
Integrate the Karbon API with the Python API
Setup the Karbon API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Karbon and Python remarkably fast. Free for developers.
Popular Karbon and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Karbon#
Karbon is a work management platform designed for accounting firms, centralizing team communication, workflows, and client interactions. With Karbon's API, you can automate routine operations, sync data across multiple systems, and create custom monitoring solutions tailored for your firm's workflow. By leveraging Pipedream's capabilities, you can harness the power of Karbon's API to create dynamic, serverless workflows that connect Karbon with other apps to streamline your accounting practices.
Connect Karbon#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
karbon: {
type: "app",
app: "karbon",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.karbonhq.com/v3/Users`,
headers: {
Authorization: `Bearer ${this.karbon.$auth.application_access_key}`,
"AccessKey": `${this.karbon.$auth.tenant_access_key}`,
"Accept": `application/json`,
},
})
},
})
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}}