TestMonitor
TestMonitor, a modern software tool for functional, user- and acceptance tests of software implementations with one goal only: Testing with a smile!
Integrate the TestMonitor API with the Python API
Setup the TestMonitor API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate TestMonitor and Python remarkably fast. Free for developers.
Popular TestMonitor 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 TestMonitor#
TestMonitor API taps into the robust testing and project management platform, allowing you to automate issue tracking and test management processes. With this API, you can create, update, and retrieve issues, manage test cases and results, and integrate testing workflows with other systems. Leveraging Pipedream's serverless execution model, you can craft workflows that trigger on specific events within TestMonitor, reflect changes in real-time across other applications, or systematically analyze and report test outcomes.
Connect TestMonitor#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
testmonitor: {
type: "app",
app: "testmonitor",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.testmonitor.$auth.domain}.testmonitor.com/api/v1/users`,
headers: {
Authorization: `Bearer ${this.testmonitor.$auth.api_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}}