PostgreSQL is a free and open-source relational database management system emphasizing extensibility and SQL compliance.
Emit new event when a new column is added to a table. See the documentation
Emit new event when a row is added or modified. See the documentation
Emit new event when a new row is added to a table. See the documentation
Emit new event when new rows are returned from a custom query that you provide. See the documentation
Emit new event when a new table is added to the database. See the documentation
Triggers a recognition process using the Plate Recognizer SDK.
Finds a row in a table via a custom query. See the documentation
On Pipedream, you can leverage the PostgreSQL app to create workflows that automate database operations, synchronize data across platforms, and react to database events in real-time. Think handling new row entries, updating records from webhooks, or even compiling reports on a set schedule. Pipedream's serverless platform provides a powerful way to connect PostgreSQL with a variety of apps, enabling you to create tailored automation that fits your specific needs.
import postgresql from "@pipedream/postgresql"
export default defineComponent({
props: {
postgresql,
},
async run({ steps, $ }) {
// Component source code:
// https://github.com/PipedreamHQ/pipedream/tree/master/components/postgresql
const queryObj = {
text: "SELECT NOW()",
values: [], // Ignored since query does not contain placeholders
};
return await this.postgresql.executeQuery(queryObj);
},
})
The Plate Recognizer API provides robust tools for converting images of vehicle license plates into text data. Using Pipedream, you can harness this capability to automate various tasks involving vehicle identification and monitoring. This integration is particularly useful in scenarios involving security, parking management, and logistics optimization, where automated plate recognition can streamline operations significantly.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
platerecognizer: {
type: "app",
app: "platerecognizer",
}
},
async run({steps, $}) {
const data = {
"upload_url": `https://app.platerecognizer.com/static/demo.jpg`,
}
return await axios($, {
method: "post",
url: `https://api.platerecognizer.com/v1/plate-reader/`,
headers: {
"Authorization": `Token ${this.platerecognizer.$auth.api_token}`,
},
data,
})
},
})