with Podio and Python?
Emit new events when a new application is created. See the documentation
Emit new events when a new item is created. See the documentation
Emit new events when an item is updated. See the documentation
Emit new events when a new organization created. See the documentation
Emit new events when a new task is created. See the documentation
Attaches an uploaded file to the given object. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Adds a new item to the given app. See the documentation
Creates a status to the given workspace. See the documentation
Creates a task to the given workspace. See the documentation
The Podio API opens a world of possibilities for managing tasks, projects, and team collaboration with ease. By harnessing the API through Pipedream, you can automate routine operations, synchronize data across different platforms, and craft custom workflows that facilitate real-time project management and enhance productivity. Whether it's updating leads in a CRM, managing a content calendar, or automating project status reports, the Podio API paired with Pipedream's serverless execution model allows for seamless integration with a vast array of services to streamline your work processes.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
podio: {
type: "app",
app: "podio",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.podio.com/user`,
headers: {
Authorization: `Bearer ${this.podio.$auth.oauth_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}}