Budgets.ai

Generative AI-driven platform that help sales and marketing teams identify and predict relevant budgets.

Integrate the Budgets.ai API with the Python API

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

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 Budgets.ai

The Budgets.ai API offers robust tools for managing budgets, tracking expenses, and monitoring financial goals. By leveraging this API on Pipedream, you can automate your financial data processes, sync with other financial tools, and generate real-time analytics and notifications. Pipedream's serverless platform facilitates the integration of Budgets.ai with hundreds of other apps, enabling you to create custom, automated workflows that fit your financial management needs.

Connect Budgets.ai

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    budgets_ai: {
      type: "app",
      app: "budgets_ai",
    }
  },
  async run({steps, $}) {
    const data = {
      "api_key": `${this.budgets_ai.$auth.api_key}`,
      "domain": `pipedream.com`,
    }
    return await axios($, {
      method: "post",
      url: `https://crm.budgets.ai/api-product/incoming-webhook/enrich-company`,
      headers: {
        "Content-Type": `application/json`,
      },
      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

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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}}