We help DevOps run open source based perf testing on any website, app or API at massive scale to validate performance
Creates a new project in a specific workspace. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
List projects from a specified workspace in BlazeMeter. See the documentation
List all workspaces associated with the specified account. See the documentation
The BlazeMeter API allows you to automate performance testing by integrating with Pipedream's serverless platform. You can trigger tests, fetch test results, and manage your testing environment programmatically. With Pipedream, connecting BlazeMeter with other apps and services streamlines performance data analysis and alerts, enhancing continuous integration and deployment (CI/CD) pipelines.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
blazemeter: {
type: "app",
app: "blazemeter",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://a.blazemeter.com/api/v4/user`,
auth: {
username: `${this.blazemeter.$auth.api_key}`,
password: `${this.blazemeter.$auth.api_secret}`,
},
})
},
})
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}}