MongoDB is an open source NoSQL database management program.
Create a new document in a collection of your choice. See the 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.
Execute an aggregation pipeline on a MongoDB collection. See the documentation
The MongoDB API provides powerful capabilities to interact with a MongoDB database, allowing you to perform CRUD (Create, Read, Update, Delete) operations, manage databases, and execute sophisticated queries. With Pipedream, you can harness these abilities to automate tasks, sync data across various apps, and react to events in real-time. It’s a combo that’s particularly potent for managing data workflows, syncing application states, or triggering actions based on changes to your data.
import mongodb from 'mongodb'
export default defineComponent({
props: {
mongodb: {
type: "app",
app: "mongodb",
},
collection: {
type: "string"
},
filter: {
type: "object"
}
},
async run({steps, $}) {
const MongoClient = mongodb.MongoClient
const {
database,
hostname,
username,
password,
} = this.mongodb.$auth
const url = `mongodb+srv://${username}:${password}@${hostname}/test?retryWrites=true&w=majority`
const client = await MongoClient.connect(url, {
useNewUrlParser: true,
useUnifiedTopology: true
})
const db = client.db(database)
const results = await db.collection(this.collection).find(this.filter).toArray();
$.export('results', results);
await client.close()
},
})
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)
}