Parseur is the most powerful and user-friendly mail parser. A data extraction tool to automatically extract text from your emails, pdfs, and other documents.
Emit new event when a new document is not processed. It is triggered when a document fails to process with status New Template Needed
. See the docs.
Emit new event when a new document is processed. It is useful for endpoints that don't support deep JSON structures as it will flatten your table fields. See the docs.
Emit new event when a new document is processed with list items. The payload format is the same as when viewing the document and clicking on view as JSON
. See the docs.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Parseur is a powerful email parsing tool that automates the extraction of data from emails and documents. With its API, you can unlock the data trapped in emails and documents and transform it into structured data. On Pipedream, you can use Parseur to trigger workflows from parsed email data, connecting it to hundreds of other services for endless automation possibilities. This can streamline business processes like lead management, invoice processing, and data entry by automating the extraction and flow of critical information.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
parseur: {
type: "app",
app: "parseur",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.parseur.com/parser`,
headers: {
"Authorization": `Token ${this.parseur.$auth.api_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}}