Real-time Receipt OCR API for developers.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Taggun API offers a powerful way to extract meaningful data from receipts and invoices using machine learning. By submitting images or PDFs, it can pull out key details like the date, merchant info, totals, tax amounts, and line items. This capability is gold for automating expense tracking and financial analysis. In Pipedream, you can slice Taggun's prowess into your workflows to parse receipts on the fly, integrate with accounting software, or even manage inventory based on purchase data.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
taggun: {
type: "app",
app: "taggun",
}
},
async run({steps, $}) {
const data = {
"url": `https://upload.wikimedia.org/wikipedia/commons/thumb/0/0b/ReceiptSwiss.jpg/170px-ReceiptSwiss.jpg`,
}
return await axios($, {
method: "post",
url: `https://api.taggun.io/api/receipt/v1/simple/url`,
headers: {
"apikey": `${this.taggun.$auth.api_key}`,
"Content-Type": `application/json`,
},
data,
})
},
})
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}}