FeedBlitz
FeedBlitz is a full service email marketing service provider (ESP) focused on simplifying our clients' business objectives. No limits, no overages, terrific value, outstanding deliverability, and real people on the phone to lend a hand when you need it
Integrate the FeedBlitz API with the Python API
Setup the FeedBlitz API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate FeedBlitz and Python remarkably fast. Free for developers.
Popular FeedBlitz 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 FeedBlitz#
FeedBlitz is an email marketing service that enables creators to manage newsletters, automated mailings, and RSS feed campaigns. By connecting the FeedBlitz API with Pipedream, you can automate content distribution, subscriber management, and engagement tracking, creating a seamless workflow for your email marketing efforts. This API leverages Pipedream's capabilities to integrate with numerous other services, allowing you to enhance your email campaigns with dynamic content, subscriber behavior data, and event-driven triggers.
Connect FeedBlitz#
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
feedblitz: {
type: "app",
app: "feedblitz",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://app.feedblitz.com/f.api/user`,
params: {
key: `${this.feedblitz.$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}}