The go-to assistant for your work chat. DailyBot has built-in skills to help you run async meetings, track and celebrate milestones, and automate routines. 🤖💬
Emit new event when a user from your organization completes a response to a check-in in DailyBot.
Emit new event when a response is added to a form in DailyBot by any user from your organization or an external user.
Emit new event every time any kudos are given to someone in your DailyBot organization.
Sends kudos to selected user(s) using DailyBot. See the documentation
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Dispatches a message to designated users or groups in DailyBot. Required are the message content and recipients' IDs, and channels or rooms are optional targets. See the documentation
The DailyBot API on Pipedream opens up a world of possibilities for automating team interactions and enhancing productivity. With DailyBot, you can create custom workflows to automate stand-ups, collect feedback, run polls, and send reminders. By leveraging Pipedream's seamless connections with other apps and services, you can integrate DailyBot into your existing tools and streamline your team's communication processes without writing extensive code.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
dailybot: {
type: "app",
app: "dailybot",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.dailybot.com/v1/me/`,
headers: {
"Accept": `application/json`,
"X-API-KEY": `${this.dailybot.$auth.api_key}`,
},
})
},
})
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}}