Slack is a channel-based messaging platform. With Slack, people can work together more effectively, connect all their software tools and services, and find the information they need to do their best work — all within a secure, enterprise-grade environment.
Emit new event when a new message is posted to one or more channels
Emit new event when a message was posted in a direct message channel
Emit new events on new Slack interactivity events sourced from Block Kit interactive elements, Slash commands, or Shortcuts.
Emit new event when a specific keyword is mentioned in a channel
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
Send a message to a user, group, private channel or public channel. See the documentation
Send a message as a threaded reply. See postMessage or scheduleMessage docs here
The Pipedream Slack app enables you to build event-driven workflows that interact with the Slack API. Once you authorize the Pipedream app's access to your workspace, you can use Pipedream workflows to perform common Slack actions or write your own code against the Slack API.
The Pipedream Slack app is not a typical app. You don't interact with it directly as a bot, and it doesn't add custom functionality to your workspace out of the box. It makes it easier to automate anything you'd typically use the Slack API for, using Pipedream workflows.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
slack: {
type: "app",
app: "slack",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://slack.com/api/users.profile.get`,
headers: {
Authorization: `Bearer ${this.slack.$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}}