Massively scalable and secure object storage for cloud-native workloads, archives, data lakes, HPC, and machine learning.
Emit new event when a blob is deleted from a specified container in Azure Storage. See the documentation.
Emit new event when a new blob is created to a specified container in Azure Storage. See the documentation.
Emit new event when a new container is created in the specified Azure Storage account. See the documentation.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Creates a new container under the specified account. If a container with the same name already exists, the operation fails. See the documentation.
Deletes a specific blob from a container in Azure Storage. See the documentation.
Uploads a new blob to a specified container in Azure Storage. See the documentation.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
azure_storage: {
type: "app",
app: "azure_storage",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://graph.microsoft.com/v1.0/me`,
headers: {
Authorization: `Bearer ${this.azure_storage.$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}}