Create, Approve, Track & eSign Docs 40% Faster
Emit new event when a document failed to be created. See the documentation here
Emit new event when a document is deleted. See the documentation here
Emit new event when a document's state is changed. See the documentation here
Emit new event when a document is updated. See the documentation here
Emit new event when a recipient completes a document. See the documentation here
Adds an attachment to a document. See the documentation here
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Create a document from a file or public file URL. See the documentation here
Create a Document from a PandaDoc Template. See the documentation here
Create a new folder to store your documents. See the documentation here
The PandaDoc API opens up a realm of possibilities for automating document workflows, creating a seamless bridge between document management and various business processes. With it, you can programmatically create, send, and track documents, streamline electronic signatures, and manage templates, among others. Integrations through Pipedream can harness these capabilities, enabling you to trigger actions in PandaDoc based on events from other apps, or vice versa.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pandadoc: {
type: "app",
app: "pandadoc",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pandadoc.com/public/v1/members/current/`,
headers: {
Authorization: `Bearer ${this.pandadoc.$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}}