Kaggle

Your Machine Learning and Data Science Community

Integrate the Kaggle API with the Schedule API

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

Custom Interval from the Schedule API

Trigger your workflow every N hours, minutes or seconds.

 
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Daily schedule from the Schedule API

Trigger your workflow every day.

 
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Monthly Schedule from the Schedule API

Trigger your workflow on one or more days each month at a specific time (with timezone support).

 
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Weekly schedule from the Schedule API

Trigger your workflow on one or more days each week at a specific time (with timezone support).

 
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Overview of Kaggle

The Kaggle API allows you to harness a trove of data science and machine learning resources. With this API, you can download datasets, make competition submissions, and interact with Kaggle forums directly. By leveraging Pipedream's capabilities, you can automate repetitive tasks, integrate Kaggle with other applications, and create custom workflows to augment your data science projects.

Connect Kaggle

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import { axios } from "@pipedream/platform"
export default defineComponent({
  props: {
    kaggle: {
      type: "app",
      app: "kaggle",
    }
  },
  async run({steps, $}) {
    return await axios($, {
      url: `https://www.kaggle.com/api/v1/datasets/list`,
      auth: {
        username: `${this.kaggle.$auth.username}`,
        password: `${this.kaggle.$auth.api_key}`,
      },
      params: {
        "": ``,
      },
    })
  },
})

Overview of Schedule

The Schedule app in Pipedream is a powerful tool that allows you to trigger workflows at regular intervals, ranging from every minute to once a year. This enables the automation of repetitive tasks and the scheduling of actions to occur without manual intervention. By leveraging this API, you can execute code, run integrations, and process data on a reliable schedule, all within Pipedream's serverless environment.