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Emits a new event when a dataset refresh operation has completed. See the documentation
Emits an event when a dataset refresh operation has failed in Power BI. See the documentation
Emit new event when a new dataset refresh operation is created. See the documentation
Adds new data rows to the specified table within the specified dataset from My workspace. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Cancels a refresh operation for a specified dataset in Power BI. See the documentation
Creates a new Push Dataset in Power BI. See the documentation
Triggers a refresh operation for a specified Power BI dataset. See the documentation
The Microsoft Power BI API allows you to interact with your Power BI assets programmatically. With this API, you can embed your reports and dashboards into applications, manage Power BI datasets, push data into datasets for real-time dashboard updates, and automate your reporting workflows. On Pipedream, you can use this API to create intricate workflows that react to various triggers, like webhooks or schedules, and perform actions like refreshing datasets, posting to datasets, and managing Power BI assets.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
microsoft_power_bi: {
type: "app",
app: "microsoft_power_bi",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.powerbi.com/v1.0/myorg/availableFeatures`,
headers: {
Authorization: `Bearer ${this.microsoft_power_bi.$auth.oauth_access_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}}