Linear (API key)
Linear helps streamline software projects, sprints, tasks, and bug tracking. It's built for high-performance teams.
Integrate the Linear (API key) API with the Python API
Setup the Linear (API key) API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Linear (API key) and Python remarkably fast. Free for developers.
Popular Ways to Connect Linear (API key) with Python#
Popular Linear (API key) 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 Linear (API key)#
Linear helps streamline software project management, bug tracking, and task coordination. By using the Linear (API key) API with Pipedream, you can automate routine tasks, sync issues across platforms, and trigger custom workflows. Think auto-assignment of tasks based on specific triggers or pushing updates to a Slack channel when an issue's status changes. These automations save time and ensure that your development team stays focused on coding rather than on administrative overhead.
Connect Linear (API key)#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
linear_app: {
type: "app",
app: "linear_app",
}
},
async run({steps, $}) {
const data = {
"query": `{
user(id: "me") {
id
email
name
}
}`,
}
return await axios($, {
method: "post",
url: `https://api.linear.app/graphql`,
headers: {
"Authorization": `${this.linear_app.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})
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}}