Zenkit

Productivity and Collaboration Software Suite

Integrate the Zenkit API with the Python API

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

Run Python Code with Python API on New Activity (Instant) from Zenkit API
Zenkit + Python
 
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Run Python Code with Python API on New Entry (Instant) from Zenkit API
Zenkit + Python
 
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Run Python Code with Python API on New Notification (Instant) from Zenkit API
Zenkit + Python
 
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Run Python Code with Python API on Updated Entry (Instant) from Zenkit API
Zenkit + Python
 
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New Activity (Instant) from the Zenkit API

Emit new event when there is new activity in Zenkit

 
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New Entry (Instant) from the Zenkit API

Emit new event when a new item/entry is created in Zenkit

 
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New Notification (Instant) from the Zenkit API

Emit new event when there is a new notification in Zenkit

 
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Updated Entry (Instant) from the Zenkit API

Emit new event when an entry is updated in Zenkit

 
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Add Entry Comment with the Zenkit API

Add a comment to an entry/item within a list/collection on Zenkit. See the docs

 
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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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Create Entry with the Zenkit API

Create an entry/item in a list on Zenkit. See the docs

 
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Get Entry with the Zenkit API

Retrieve an entry/item from a list on Zenkit. See the docs

 
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Get List with the Zenkit API

Retrieve a list/collection from a workspace on Zenkit. See the docs

 
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Connect Zenkit

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    zenkit: {
      type: "app",
      app: "zenkit",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://zenkit.com/api/v1/users/me`,
      headers: {
        Authorization: `Bearer ${this.zenkit.$auth.oauth_access_token}`,
      },
    })
  },
})

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}}