Integrate the MeaningCloud API with the Python API

Setup the MeaningCloud API trigger to run a workflow which integrates with the Python API. Pipedream's integration platform allows you to integrate MeaningCloud and Python remarkably fast. Free for developers.

Popular MeaningCloud and Python Actions#

Run Python Code with the Python API

Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.

Try it

Overview of MeaningCloud#

The MeaningCloud API provides advanced text analysis capabilities leveraging natural language processing (NLP). With it, you can extract insights and meaning from textual content. In Pipedream, you can connect the MeaningCloud API to analyze the sentiment of customer feedback, classify text into categories, extract entities and concepts, and much more. The API's integration into serverless workflows on Pipedream allows for automating complex tasks that involve processing and understanding human language.

Connect MeaningCloud#

import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    meaningcloud: {
      type: "app",
      app: "meaningcloud",
    }
  },
  async run({steps, $}) {
    const data = {
      "key": `${this.meaningcloud.$auth.api_key}`,
      "txt": `This model implements the Interactive Advertising Bureau (IAB) taxonomy, a standard for the advertisement industry which aims to make content classification consistent across the industry. This taxonomy defines 370 contextual content categories in its first two tiers.`,
      "model": `IAB_2.0_en`,
    }
    return await axios($, {
      url: `https://api.meaningcloud.com/deepcategorization-1.0`,
      headers: {
        "Content-Type": `multipart/form-data`,
      },
      data,
    })
  },
})

Overview of Python#

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:

Connect Python#

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}}