with BitBucket and Go?
Emit new event when a new commit is pushed to a branch. See docs here
Emit new event when a new pull request is created in a repository. See docs here
Emit new event when a new branch is created. See docs here
Emit new event when a commit receives a comment. See docs here
Emit new event when an event occurs from any repository belonging to the user. See docs here
Run any Go code and use any Go package available with a simple import. Refer to the Pipedream Go docs to learn more.
Gets the actual file contents of a download artifact and not the artifact's metadata. See docs here
The BitBucket API taps the potential of BitBucket's Git-based version control system, enabling you to automate workflows around code commits, pull requests, and overall repository management. With this API, you can streamline the collaboration process, enforce coding standards, or integrate with other tools to create a cohesive development ecosystem. Pipedream, as a serverless integration and compute platform, provides a seamless environment to connect BitBucket with various apps and services, enabling you to harness its API for efficient, customized automations.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
bitbucket: {
type: "app",
app: "bitbucket",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.bitbucket.org/2.0/user`,
headers: {
Authorization: `Bearer ${this.bitbucket.$auth.oauth_access_token}`,
},
})
},
})
You can execute custom Go scripts on-demand or in response to various triggers and integrate with thousands of apps supported by Pipedream. Writing with Go on Pipedream enables backend operations like data processing, automation, or invoking other APIs, all within the Pipedream ecosystem. By leveraging Go's performance and efficiency, you can design powerful and fast workflows to streamline complex tasks.
package main
import (
"fmt"
pd "github.com/PipedreamHQ/pipedream-go"
)
func main() {
// Access previous step data using pd.Steps
fmt.Println(pd.Steps)
// Export data using pd.Export
data := make(map[string]interface{})
data["name"] = "Luke"
pd.Export("data", data)
}