Semantic Text Analytics as a service
Emit new event when you add or modify a new row in a table. See the docs here
Emit new event when new rows are returned from a custom query. See the docs here
Emit new event when a new table is added to a database. See the docs here
The Dandelion API is a text analysis toolkit that allows for understanding and extracting information from texts in various languages. On Pipedream, you can leverage this API to automate workflows that involve natural language processing tasks like sentiment analysis, entity recognition, and language detection. These capabilities enable developers to create applications that can interpret user input, analyze social media sentiment, categorize content, and more, all within a serverless platform.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
dandelion: {
type: "app",
app: "dandelion",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.dandelion.eu/datagraph/wikisearch/v1`,
params: {
text: `brightroll`,
lang: `en`,
token: `${this.dandelion.$auth.token}`,
},
})
},
})
The MySQL application on Pipedream enables direct interaction with your MySQL databases, allowing you to perform CRUD operations—create, read, update, delete—on your data with ease. You can leverage these capabilities to automate data synchronization, report generation, and event-based triggers that kick off workflows in other apps. With Pipedream's serverless platform, you can connect MySQL to hundreds of other services without managing infrastructure, crafting complex code, or handling authentication.
import mysql from '@pipedream/mysql';
export default defineComponent({
props: {
mysql,
},
async run({steps, $}) {
// Component source code:
// https://github.com/PipedreamHQ/pipedream/tree/master/components/mysql
const queryObj = {
sql: "SELECT NOW()",
values: [], // Ignored since query does not contain placeholders
};
return await this.mysql.executeQuery(queryObj);
},
});