{
  "id": 431119,
  "title": "Problem in loading the dataset",
  "url": "/competitions/rsna-2023-abdominal-trauma-detection/discussion/431119",
  "author_name": "Nisarg Bhatt",
  "post_date": "2023-08-12T05:30:17.626000",
  "votes": 0,
  "comment_count": 1,
  "views": 0,
  "content": "<p>Hi everyone, I am starting with RSNA data, but I can't load the dataset. While running the cell, my personal computer RAM is used fully, although I am running the code in Kaggle. </p>\n<p>Please help me with this, and if you know how this is happening, let me know!</p>",
  "messages": [
    {
      "id": 2386819,
      "postDate": "2023-08-12T07:04:17.073Z",
      "content": "<p>i think you need to  use Downsampling OR Parallel Processing <br>\nThreading Example:<br>\nHere, we'll use the threading module to simulate downloading multiple files concurrently.</p>\n<pre><code>import threading\nimport time\n\ndef download_file(file_name):\n    ()\n    time.()  # Simulating download time\n    ()\n\n __name__ == :\n     = [, , ]\n\n    threads = []\n      in :\n        thread = threading.Thread(target=download_file, =(,))\n        threads.(thread)\n        thread.start()\n\n     thread in threads:\n        thread.()\n\n    ()\n</code></pre>\n<p><a href=\"https://www.kaggle.com/nisargbhatt\" target=\"_blank\">@nisargbhatt</a> </p>",
      "rawMarkdown": "i think you need to  use Downsampling OR Parallel Processing \nThreading Example:\nHere, we'll use the threading module to simulate downloading multiple files concurrently.\n\n```\nimport threading\nimport time\n\ndef download_file(file_name):\n    print(f\"Downloading {file_name}\")\n    time.sleep(2)  # Simulating download time\n    print(f\"{file_name} downloaded\")\n\nif __name__ == \"__main__\":\n    files = [\"file1.txt\", \"file2.txt\", \"file3.txt\"]\n    \n    threads = []\n    for file in files:\n        thread = threading.Thread(target=download_file, args=(file,))\n        threads.append(thread)\n        thread.start()\n    \n    for thread in threads:\n        thread.join()\n    \n    print(\"All downloads completed\")\n```\n@nisargbhatt \n\n ",
      "votes": 1
    },
    {
      "id": 2386679,
      "postDate": "2023-08-12T05:30:17.627Z",
      "content": "<p>Hi everyone, I am starting with RSNA data, but I can't load the dataset. While running the cell, my personal computer RAM is used fully, although I am running the code in Kaggle. </p>\n<p>Please help me with this, and if you know how this is happening, let me know!</p>",
      "rawMarkdown": "Hi everyone, I am starting with RSNA data, but I can't load the dataset. While running the cell, my personal computer RAM is used fully, although I am running the code in Kaggle. \n\nPlease help me with this, and if you know how this is happening, let me know!"
    }
  ],
  "comments": [
    {
      "id": 2386819,
      "author_name": "younan iskander",
      "author_url": "",
      "post_date": "2023-08-12T07:04:17.073000",
      "content": "<p>i think you need to  use Downsampling OR Parallel Processing <br>\nThreading Example:<br>\nHere, we'll use the threading module to simulate downloading multiple files concurrently.</p>\n<pre><code>import threading\nimport time\n\ndef download_file(file_name):\n    ()\n    time.()  # Simulating download time\n    ()\n\n __name__ == :\n     = [, , ]\n\n    threads = []\n      in :\n        thread = threading.Thread(target=download_file, =(,))\n        threads.(thread)\n        thread.start()\n\n     thread in threads:\n        thread.()\n\n    ()\n</code></pre>\n<p><a href=\"https://www.kaggle.com/nisargbhatt\" target=\"_blank\">@nisargbhatt</a> </p>",
      "votes": 1,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "2386819": "i think you need to  use Downsampling OR Parallel Processing \nThreading Example:\nHere, we'll use the threading module to simulate downloading multiple files concurrently.\n\n```\nimport threading\nimport time\n\ndef download_file(file_name):\n    print(f\"Downloading {file_name}\")\n    time.sleep(2)  # Simulating download time\n    print(f\"{file_name} downloaded\")\n\nif __name__ == \"__main__\":\n    files = [\"file1.txt\", \"file2.txt\", \"file3.txt\"]\n    \n    threads = []\n    for file in files:\n        thread = threading.Thread(target=download_file, args=(file,))\n        threads.append(thread)\n        thread.start()\n    \n    for thread in threads:\n        thread.join()\n    \n    print(\"All downloads completed\")\n```\n@nisargbhatt \n\n ",
    "2386679": "Hi everyone, I am starting with RSNA data, but I can't load the dataset. While running the cell, my personal computer RAM is used fully, although I am running the code in Kaggle. \n\nPlease help me with this, and if you know how this is happening, let me know!"
  }
}