Stripo
Stripo is an email design platform. We help you build high-quality emails of any complexity, including ones with AMP, real-time, and interactive content.
Integrate the Stripo API with the Python API
Setup the Stripo API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate Stripo and Python remarkably fast. Free for developers.
Popular Stripo and Python Actions#
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Overview of Stripo#
The Stripo API lets you automate email design, creation, and management processes, streamlining your workflow within Pipedream. With Stripo, you can create email templates, customize them, and export directly to various email services. Pipedream, with its serverless execution model, can trigger workflows based on numerous events, such as webhook invocations, email events, or schedule timers. By combining Stripo with Pipedream, you can craft dynamic email campaigns, auto-generate personalized emails from templates, and synchronize your email designs with other platforms or databases effortlessly.
Connect Stripo#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
stripo: {
type: "app",
app: "stripo",
}
},
async run({steps, $}) {
return await axios($, {
url: ` https://stripo.email/emailgeneration/v1/emails`,
headers: {
"Content-Type": `application/json`,
"Stripo-Api-Auth": `${this.stripo.$auth.api_key}`,
},
})
},
})
Overview of Python#
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:
Connect Python#
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}}