What do you want to automate
with Beanstalk and Python?
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Popular Ways to Connect Beanstalk with Python#
Popular Beanstalk and Python Triggers#
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
Popular Beanstalk and Python Actions#
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.
Overview of Beanstalk#
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.
Connect Beanstalk#
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}`,
},
})
},
})
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}}Trusted by 1,000,000+ developers from startups to Fortune 500 companies