with Pinterest and Codeq Natural Language Processing API?
Emit new events when new pins are created on a board or board section. See the docs here and here
Receives a text and returns a JSON object containing a list of analyzed sentences. See the docs here
Receives two texts and returns a JSON object containing the text similarity score. See the docs here
The Pinterest API opens a portal to interact programmatically with Pinterest's rich data, including boards, pins, and user information. By leveraging this API on Pipedream, you can automate actions like posting new pins, extracting pin data for analysis, and synchronizing Pinterest content with other platforms. The potential extends to marketing optimization, content management, and audience engagement, all automated and integrated within the Pipedream ecosystem.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
pinterest: {
type: "app",
app: "pinterest",
}
},
async run({steps, $}) {
return await axios($, {
url: `https://api.pinterest.com/v5/user_account`,
headers: {
Authorization: `Bearer ${this.pinterest.$auth.oauth_access_token}`,
},
})
},
})
The Codeq Natural Language Processing API provides powerful text analysis capabilities. It parses and understands complex structures in text, extracting meaningful insights. On Pipedream, you can harness this API to analyze text data from various sources, automate content categorization, sentiment analysis, or even construct rich profiles of user feedback. With Pipedream's serverless platform, these processes can be automated, triggered by events, and integrated with numerous other apps to create robust, data-driven workflows.
import { axios } from "@pipedream/platform"
export default defineComponent({
props: {
codeq_natural_language_processing_api: {
type: "app",
app: "codeq_natural_language_processing_api",
}
},
async run({steps, $}) {
const data = {
"user_id": `${this.codeq_natural_language_processing_api.$auth.user_id}`,
"user_key": `${this.codeq_natural_language_processing_api.$auth.user_key}`,
"text": `{your_text}`,
}
return await axios($, {
method: "post",
url: `https://api.codeq.com/v1`,
headers: {
"Content-Type": `application/json`,
},
data,
})
},
})