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crawlab
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crawleval

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The dataset viewer is not available for this split.
Cannot extract the features (columns) for the split 'test' of the config 'default' of the dataset.
Error code:   FeaturesError
Exception:    ArrowInvalid
Message:      Schema at index 1 was different: 
4063ed4d7559ba435267610e7387ee4626a076a49fa4951ab17028b95fb2da3e: string
9da4813774a7f9cd796fadc1fc8164d103e06ac2aad6300d0be1368fa6baa4d4: string
fc83dc4a2858af2852bd3dd8da38b4f19742c059eb99557a724e1476d7b944e5: string
0e3bd9383bd0a2bd6260cbf1e9a75e6a6cee5a4c726a55b524553443c87395e6: string
53abbc0de94fb86c4b8074b109a1e5bdb91b496b936a76cba95d83233e6338c1: string
27313d822909b4b9205a224895ec47341d9a641dd921465017ddadca32c8aea3: string
bfb27bd1eb56be78a6e267fc31b3ed76dfe7488dc0473a74eee43a3bc1aef5aa: string
71db2e25d97fd93f5ee3cc181af45d67229e215d90a96773f2894aa585d3e0bb: string
73d2cca7b98d17ea64398ad9422c0aea55cf6dd028e606081abc8dbd9666df67: string
d6b240283bcfd9343b545fc070be40cd077d70f2c0e177a786391b28244896f9: string
74c123aa7c7b802b3fecef041aa087662768456eab92a1b0f216bc2bcf7d918a: string
0e1225f81de37606cd180ef611af6867fa1f7858492c2d3e84b97a18eda26ccb: string
vs
id: string
name: string
description: string
url: string
created_at: string
size: int64
dom_nodes: int64
text_nodes: int64
link_nodes: int64
image_nodes: int64
max_nesting_level: int64
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/split/first_rows.py", line 228, in compute_first_rows_from_streaming_response
                  iterable_dataset = iterable_dataset._resolve_features()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 3339, in _resolve_features
                  features = _infer_features_from_batch(self.with_format(None)._head())
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2096, in _head
                  return next(iter(self.iter(batch_size=n)))
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 2300, in iter
                  for key, example in iterator:
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1856, in __iter__
                  for key, pa_table in self._iter_arrow():
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 1878, in _iter_arrow
                  yield from self.ex_iterable._iter_arrow()
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/iterable_dataset.py", line 504, in _iter_arrow
                  yield new_key, pa.Table.from_batches(chunks_buffer)
                File "pyarrow/table.pxi", line 4116, in pyarrow.lib.Table.from_batches
                File "pyarrow/error.pxi", line 154, in pyarrow.lib.pyarrow_internal_check_status
                File "pyarrow/error.pxi", line 91, in pyarrow.lib.check_status
              pyarrow.lib.ArrowInvalid: Schema at index 1 was different: 
              4063ed4d7559ba435267610e7387ee4626a076a49fa4951ab17028b95fb2da3e: string
              9da4813774a7f9cd796fadc1fc8164d103e06ac2aad6300d0be1368fa6baa4d4: string
              fc83dc4a2858af2852bd3dd8da38b4f19742c059eb99557a724e1476d7b944e5: string
              0e3bd9383bd0a2bd6260cbf1e9a75e6a6cee5a4c726a55b524553443c87395e6: string
              53abbc0de94fb86c4b8074b109a1e5bdb91b496b936a76cba95d83233e6338c1: string
              27313d822909b4b9205a224895ec47341d9a641dd921465017ddadca32c8aea3: string
              bfb27bd1eb56be78a6e267fc31b3ed76dfe7488dc0473a74eee43a3bc1aef5aa: string
              71db2e25d97fd93f5ee3cc181af45d67229e215d90a96773f2894aa585d3e0bb: string
              73d2cca7b98d17ea64398ad9422c0aea55cf6dd028e606081abc8dbd9666df67: string
              d6b240283bcfd9343b545fc070be40cd077d70f2c0e177a786391b28244896f9: string
              74c123aa7c7b802b3fecef041aa087662768456eab92a1b0f216bc2bcf7d918a: string
              0e1225f81de37606cd180ef611af6867fa1f7858492c2d3e84b97a18eda26ccb: string
              vs
              id: string
              name: string
              description: string
              url: string
              created_at: string
              size: int64
              dom_nodes: int64
              text_nodes: int64
              link_nodes: int64
              image_nodes: int64
              max_nesting_level: int64

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CrawlEval

Resources and tools for evaluating the performance and behavior of web crawling systems.

Overview

CrawlEval provides a comprehensive suite of tools and datasets for evaluating web crawling systems, with a particular focus on HTML pattern extraction and content analysis. The project includes:

  1. A curated dataset of web pages with ground truth patterns
  2. Tools for fetching and analyzing web content
  3. Evaluation metrics and benchmarking capabilities

Dataset

The dataset is designed to test and benchmark web crawling systems' ability to extract structured data from HTML. It includes:

  • Raw HTML files with various structures and complexities
  • Ground truth PagePattern JSON files
  • Metadata about each example (query, complexity, etc.)

See the dataset documentation for detailed information about the dataset structure and usage.

Tools

Web Page Fetcher (fetch_webpage.py)

A powerful tool for collecting and analyzing web pages for evaluation purposes.

Key features:

  • Fetches web pages with proper JavaScript rendering using Selenium
  • Extracts and analyzes metadata (DOM structure, nesting levels, etc.)
  • Content deduplication using SHA-256 hashing
  • URL deduplication with normalization
  • Parallel processing of multiple URLs
  • Progress tracking and detailed logging

Usage:

python -m crawleval.fetch_webpage --batch urls.txt [options]

Options:

  • --dir DIR: Base directory for storing data
  • --list-hashes: Display the content hash index
  • --list-urls: Display the URL index
  • --save-results FILE: Save batch processing results to a JSON file
  • --workers N: Number of parallel workers (default: 4)

Contributing

We welcome contributions to improve the dataset and tools. Please see the dataset documentation for guidelines on adding new examples.
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