Automate Document Workflows
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
The Nano Nets API offers machine learning capabilities to classify images, extract data, and automate processes with custom models. Through Pipedream's serverless platform, you can trigger workflows from various events, manipulate and route data from the Nano Nets API, and connect it to hundreds of other apps to automate complex tasks. Pipedream's built-in code steps also allow you to transform data, make HTTP requests, and handle logic right inside your workflows.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
nano_nets: {
type: "app",
app: "nano_nets",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://app.nanonets.com/api/v2/OCR/Model/{your_model_id_here}`,
auth: {
username: `${this.nano_nets.$auth.api_key}`,
password: ``,
},
})
},
})
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}}