Beanstalk helps families work together to build a pot of money to give the children they love a better future. Designed to help every family, Beanstalk makes saving and investing easy no matter your family's shape or budget.
Emit new event when a new changeset is created. See the docs.
Emit new event when a new repository is created. See the docs.
Emit new event when selected flags trigger the webhook. See the docs.
Creates a new code review. This action is essentially the same as clicking the “Request review” button in the app. See the docs.
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
The Beanstalk API allows for streamlined version control and release management within your development workflow. By leveraging the API with Pipedream, you can automate interactions with your repositories, changesets, and deployment environments. You can create workflows that react to code commits, manage deploy environments, and integrate with other services for a more cohesive development lifecycle.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
beanstalkapp: {
type: "app",
app: "beanstalkapp",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://${this.beanstalkapp.$auth.domain}.beanstalkapp.com/api/account.json`,
headers: {
"Content-Type": `applicaton/json`,
"User-Agent": `Pipedream (support@pipedream.com)`,
},
auth: {
username: `${this.beanstalkapp.$auth.username}`,
password: `${this.beanstalkapp.$auth.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}}