Semantic Text Analytics as a service
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
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}`,
},
})
},
})
Develop, run and deploy your Python code in Pipedream workflows. Integrate seamlessly between no-code steps, with connected accounts, or integrate Data Stores and manipulate files within a workflow.
This includes installing PyPI packages, within your code without having to manage a requirements.txt
file or running pip
.
Below is an example of using Python to access data from the trigger of the workflow, and sharing it with subsequent workflow steps:
def handler(pd: "pipedream"):
# Reference data from previous steps
print(pd.steps["trigger"]["context"]["id"])
# Return data for use in future steps
return {"foo": {"test":True}}