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How can I handle large amounts of data scraped from a website?
Divide your data into manageable chunks. Use pagination or batch processing to split up scraping tasks, which reduces the memory load.
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4 Replies
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Store data in compressed formats like Parquet or Avro, which save space and load faster. Pandas and Dask in Python make working with large data easy.
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Consider using a database, like MongoDB or SQLite, for temporary storage. Databases handle large data more efficiently than local memory.
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I stream data directly into a storage solution, like AWS S3 or a similar cloud service, to avoid using up local resources.
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If your script handles data in real-time, try Redis or Kafka for fast data handling without excessive memory usage.
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