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Kaggle Notebook Search

Parse a Kaggle notebook search or listing page into structured JSON with one row per notebook, including author, co-authors, competition context, votes, and comment count. To try it with up to 5,000 free requests, start from the Kaggle Scraper API page.

What the listing page does not expose

Kaggle labels the result total only as Results (100+), so totalCountLabel is returned verbatim as a string rather than converted to a number. Rows with more than one author render stacked avatars with no image URL in the document, so author.image is empty on those rows. A notebook attached to several competitions shows the first one plus a +2 badge - the extra names are not in the page, so only additionalContextCount can be reported.

API usage

Add &scraper=kaggle-notebook-serp to a Crawling API request. URL-encode the target URL in the url parameter.

curl 'https://api.crawlbase.com/?token=YOUR_TOKEN' \
  --data-urlencode 'url=https://www.kaggle.com/code?searchQuery=titanic' \
  --data-urlencode 'scraper=kaggle-notebook-serp' -G
from crawlbase import CrawlingAPI

api = CrawlingAPI({'token': 'YOUR_TOKEN'})
res = api.get(
    'https://www.kaggle.com/code?searchQuery=titanic',
    {'scraper': 'kaggle-notebook-serp'}
)

import json
data = json.loads(res['body'])
const { CrawlingAPI } = require('crawlbase');
const api = new CrawlingAPI({ token: 'YOUR_TOKEN' });

const res = await api.get(
  'https://www.kaggle.com/code?searchQuery=titanic',
  { scraper: 'kaggle-notebook-serp' }
);
const data = JSON.parse(res.body);
require 'crawlbase'
api = Crawlbase::API.new(token: 'YOUR_TOKEN')

res = api.get('https://www.kaggle.com/code?searchQuery=titanic', scraper: 'kaggle-notebook-serp')
data = JSON.parse(res.body)

Example input URL

Any Kaggle notebook search or listing page works in the url parameter - the page at /code, with or without a query string. For example:

https://www.kaggle.com/code?searchQuery=titanic
https://www.kaggle.com/code?searchQuery=xgboost&language=Python
https://www.kaggle.com/code
https://www.kaggle.com/code?searchQuery=nlp&page=2

Response shape

JSON response body. Field types may be null when the source page omits the value.

url
string
URL of the search page that was scraped.
query
string | null
Search term read from the request URL. Kaggle leaves the rendered search box empty on this page, so the URL is the only source.
totalCountLabel
string | null
Result total exactly as Kaggle labels it, for example 100+. Returned as a string because the page does not state an exact number.
page
integer | null
Current page number, or null when it cannot be determined.
hasNextPage
boolean
Whether a further page of results is available.
resultCount
integer
Number of rows returned on this page.
results
array
Notebook rows in the order they appear on the page.
results[].position
integer
One-based rank of the row within this page.
results[].title
string | null
Notebook display title.
results[].url
string | null
Absolute URL of the notebook.
results[].slug
string | null
Notebook identifier as author/notebook, read from the URL path.
results[].author
object
Account that owns the notebook.
results[].author.username
string | null
Owner handle, taken from the first path segment of the notebook URL so it resolves on co-authored rows too.
results[].author.name
string | null
Owner display name.
results[].author.url
string | null
Absolute URL of the owner profile.
results[].author.image
string | null
Owner avatar URL. Empty on co-authored rows, where Kaggle renders stacked avatars with no URL in the document.
results[].coauthors
array
Display names of the additional authors, as an array of strings. Empty on single-author notebooks.
results[].lastUpdated
string | null
Absolute timestamp of the last notebook update. The card shows only a relative age, so the value is taken from the tooltip behind it and keeps Kaggle formatting rather than ISO 8601.
results[].commentCount
integer | null
Number of comments on the notebook.
results[].context
string | null
Name of the competition or dataset the notebook is attached to.
results[].additionalContextCount
integer
How many further competitions or datasets the notebook is attached to beyond context. Their names are not in the page, so only the count is available.
results[].votes
integer | null
Upvote count for the notebook.
results[].medal
string | null
Kaggle medal on the notebook (for example gold), or null when the row carries none.

Sample response

{
  "url": "https://www.kaggle.com/code?searchQuery=titanic",
  "query": "titanic",
  "totalCountLabel": "100+",
  "page": 1,
  "hasNextPage": true,
  "resultCount": 20,
  "results": [
    {
      "position": 1,
      "title": "Titanic Tutorial",
      "url": "https://www.kaggle.com/code/alexisbcook/titanic-tutorial",
      "slug": "alexisbcook/titanic-tutorial",
      "author": {
        "username": "alexisbcook",
        "name": "Alexis Cook",
        "url": "https://www.kaggle.com/alexisbcook",
        "image": "https://storage.googleapis.com/kaggle-avatars/thumbnails/2603295-kg.jpg"
      },
      "coauthors": [],
      "lastUpdated": "Fri Jun 24 2022 00:25:16 GMT+0000 (Coordinated Universal Time)",
      "commentCount": 30626,
      "context": "Titanic - Machine Learning from Disaster",
      "additionalContextCount": 0,
      "votes": 60135,
      "medal": "gold"
    },
    {
      "position": 3,
      "title": "Spaceship Titanic with TFDF",
      "url": "https://www.kaggle.com/code/gusthema/spaceship-titanic-with-tfdf",
      "slug": "gusthema/spaceship-titanic-with-tfdf",
      "author": {
        "username": "gusthema",
        "name": "Gusthema",
        "url": "https://www.kaggle.com/gusthema",
        "image": ""
      },
      "coauthors": [
        "Nidhin PD"
      ],
      "lastUpdated": "Mon Apr 17 2023 09:36:29 GMT+0000 (Coordinated Universal Time)",
      "commentCount": 378,
      "context": "Spaceship Titanic",
      "additionalContextCount": 0,
      "votes": 7863,
      "medal": "gold"
    },
    {
      "position": 10,
      "title": "Titanic Top Solution",
      "url": "https://www.kaggle.com/code/brendan45774/titanic-top-solution",
      "slug": "brendan45774/titanic-top-solution",
      "author": {
        "username": "brendan45774",
        "name": "Brenda N",
        "url": "https://www.kaggle.com/brendan45774",
        "image": "https://storage.googleapis.com/kaggle-avatars/thumbnails/2681031-kg.jpg"
      },
      "coauthors": [],
      "lastUpdated": "Wed Sep 01 2021 16:03:11 GMT+0000 (Coordinated Universal Time)",
      "commentCount": 249,
      "context": "Titanic - Machine Learning from Disaster",
      "additionalContextCount": 2,
      "votes": 2294,
      "medal": "gold"
    }
  ]
}