Your Machine Learning and Data Science Community
Write Python and use any of the 350k+ PyPi packages available. Refer to the Pipedream Python docs to learn more.
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.
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: {
"": ``,
},
})
},
})
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}}