with Fireberry and Python?
Creates a new account in Fireberry. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Creates a new article in Fireberry. See the documentation
List all accounts in Fireberry. See the documentation
List all articles from Fireberry. See the documentation
The Fireberry API enables users to interact with Fireberry's suite of services programmatically. With its API, you can automate tasks related to their offerings. In Pipedream, you could leverage this API to create serverless workflows that respond to various triggers (like HTTP requests, emails, or schedule timings) and integrate with other apps to extend Fireberry's functionality.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
fireberry: {
type: "app",
app: "fireberry",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.fireberry.com/api/record/crmuser`,
headers: {
"accept": `application/json`,
"tokenid": `${this.fireberry.$auth.api_access_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}}