Common Crawl

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from nemo_curator.core.client import RayClient
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from nemo_curator.pipeline import Pipeline
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from nemo_curator.stages.text.download import CommonCrawlDownloadExtractStage
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from nemo_curator.stages.text.io.writer import JsonlWriter
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def main():
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    # Initialize Ray client
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    ray_client = RayClient()
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    ray_client.start()
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    # Create pipeline
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    pipeline = Pipeline(
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        name="common_crawl_pipeline",
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        description="Download and process Common Crawl data"
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    )
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    # Add Common Crawl processing stage
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    cc_stage = CommonCrawlDownloadExtractStage(
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        start_snapshot="2020-50",  # YYYY-WW format for CC-MAIN
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        end_snapshot="2020-50",
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        download_dir="./cc_downloads",
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        crawl_type="main",  # or "news"
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        use_aws_to_download=True,  # Faster S3 downloads (requires s5cmd)
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        url_limit=10,  # Limit number of WARC files for testing
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        record_limit=1000,  # Limit records per WARC file
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    )
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    pipeline.add_stage(cc_stage)
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    # Add output writer stage
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    writer = JsonlWriter("./cc_output")
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    pipeline.add_stage(writer)
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    # Run pipeline
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    results = pipeline.run()
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    # Stop Ray client
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    ray_client.stop()
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if __name__ == "__main__":
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    main()

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from nemo_curator.stages.text.io.writer import ParquetWriter
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# Replace the JSONL writer with ParquetWriter
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writer = ParquetWriter("./cc_output_parquet")
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pipeline.add_stage(writer)

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from nemo_curator.stages.text.download.html_extractors import ResiliparseExtractor
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from nemo_curator.stages.text.download.html_extractors import TrafilaturaExtractor
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# Use Resiliparse for extraction
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cc_stage = CommonCrawlDownloadExtractStage(
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    start_snapshot="2020-50",
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    end_snapshot="2020-50",
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    download_dir="./downloads",
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    html_extraction=ResiliparseExtractor(
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        required_stopword_density=0.25,
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        main_content=True
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    )
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)
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# Or use Trafilatura with custom parameters
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cc_stage = CommonCrawlDownloadExtractStage(
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    start_snapshot="2020-50", 
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    end_snapshot="2020-50",
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    download_dir="./downloads",
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    html_extraction=TrafilaturaExtractor(
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        min_extracted_size=200,
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        max_repetitions=3
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    )
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)

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# Define custom stop words for specific languages
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stop_lists = {
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    "ENGLISH": frozenset(["the", "and", "is", "in", "for", "where", "when", "to", "at"]),
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    "SPANISH": frozenset(["el", "la", "de", "que", "y", "en", "un", "es", "se", "no"])
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}
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cc_stage = CommonCrawlDownloadExtractStage(
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    start_snapshot="2020-50",
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    end_snapshot="2020-50", 
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    download_dir="./downloads",
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    stop_lists=stop_lists
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)

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cc_stage = CommonCrawlDownloadExtractStage(
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    start_snapshot="2020-08",  # YYYY-MM format for CC-NEWS
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    end_snapshot="2020-10",
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    download_dir="./news_downloads",
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    crawl_type="news"  # Use CC-NEWS instead of CC-MAIN
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)

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cc_stage = CommonCrawlDownloadExtractStage(
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    start_snapshot="2020-50",
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    end_snapshot="2020-50", 
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    download_dir="/fast_storage/cc_downloads",
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    use_aws_to_download=True,  # Faster S3 downloads
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    verbose=False,  # Reduce logging overhead
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    # Remove limits for full processing
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    # url_limit=None,
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    # record_limit=None
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)