Kanban Tool is a visual management solution that helps companies visualize workflow, track project progress, and analyze and significantly improve business processes. Kanban Tool provides powerful online Kanban boards with seamless time tracking.
Emit new events when a new activity occured on selected board. See the docs
Emit new events when a new board collaborator is created on selected board. See the docs
Emit new events when a new board is created or given access for a new board. See the docs
Emit new events when a new card type is created on selected board. See the docs
Emit new events when a new comment is created on selected board. See the docs
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Marks a subtask as completed See the docs here
The Kanban Tool API allows for the seamless integration and manipulation of Kanban boards, tasks, and workflows to optimize project management and team collaboration. By leveraging this API on Pipedream, you can automate task updates, synchronize boards with other data sources, and create custom notifications—thus enhancing productivity and maintaining momentum across projects.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
kanban_tool: {
type: "app",
app: "kanban_tool",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.kanban_tool.$auth.domain}.kanbantool.com/api/v3/users/current.json`,
headers: {
Authorization: `Bearer ${this.kanban_tool.$auth.api_token}`,
},
})
},
})
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:
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}}