{
  "id": 101722,
  "title": "openbabel problem[Errno 28] No space left on device",
  "url": "/competitions/champs-scalar-coupling/discussion/101722",
  "author_name": "",
  "post_date": "2019-07-28T03:28:20.158016300Z",
  "votes": 2,
  "comment_count": 5,
  "views": 0,
  "content": "<p>Hi, **when I use openbabel and to_csv, the kernel commit failed. If I don't use openbabel,the kernel commit complete.**Do you have the same problem?</p>\n\n<p>I'm having technical error while running kernels on Kaggle. This only happens when I run \"Commit\". \n<strong>[NbConvertApp] ERROR | Kernel died while waiting for execute reply.</strong>\n*<em>line 127, in write f.write(output) OSError: [Errno 28] No space left on device</em>*\nWhen I run \"Commit\", I can see that the disk usage has soared from 266.3MB/4.9GB to 4.9GB/4.9GB, then the kernel crashes.\nHow can I solve this problem?</p>",
  "messages": [
    {
      "id": "585769",
      "postDate": "07/28/2019 03:28:20",
      "content": "<p>Hi, **when I use openbabel and to_csv, the kernel commit failed. If I don't use openbabel,the kernel commit complete.**Do you have the same problem?</p>\n\n<p>I'm having technical error while running kernels on Kaggle. This only happens when I run \"Commit\". \n<strong>[NbConvertApp] ERROR | Kernel died while waiting for execute reply.</strong>\n*<em>line 127, in write f.write(output) OSError: [Errno 28] No space left on device</em>*\nWhen I run \"Commit\", I can see that the disk usage has soared from 266.3MB/4.9GB to 4.9GB/4.9GB, then the kernel crashes.\nHow can I solve this problem?</p>",
      "rawMarkdown": "Hi, **when I use openbabel and to_csv, the kernel commit failed. If I don't use openbabel,the kernel commit complete.**Do you have the same problem?\n\nI'm having technical error while running kernels on Kaggle. This only happens when I run \"Commit\". \n**[NbConvertApp] ERROR | Kernel died while waiting for execute reply.**\n**line 127, in write f.write(output) OSError: [Errno 28] No space left on device**\nWhen I run \"Commit\", I can see that the disk usage has soared from 266.3MB/4.9GB to 4.9GB/4.9GB, then the kernel crashes.\nHow can I solve this problem?",
      "votes": null
    },
    {
      "id": "585944",
      "postDate": "07/28/2019 11:26:07",
      "content": "<p>save less info or use a more compact format than csv.</p>",
      "rawMarkdown": "save less info or use a more compact format than csv.",
      "votes": null
    },
    {
      "id": "585956",
      "postDate": "07/28/2019 11:50:55",
      "content": "<p>I second <a href=\"/cpmpml\">@cpmpml</a> </p>\n\n<p>Use pickle or HDF5...\nmuch more compact and way faster to save and read back than csv. </p>",
      "rawMarkdown": "I second @cpmpml \n\nUse pickle or HDF5...\nmuch more compact and way faster to save and read back than csv.",
      "votes": null
    },
    {
      "id": "586042",
      "postDate": "07/28/2019 13:38:05",
      "content": "<p>Thank you very much, I solved the problem with to_hdf</p>",
      "rawMarkdown": "Thank you very much, I solved the problem with to_hdf",
      "votes": null
    },
    {
      "id": "586428",
      "postDate": "07/29/2019 06:47:56",
      "content": "<p>Another, a bit hairy solution, would be to split the kernel into more parts. You can then use more memory but need to import output from more kernels.</p>",
      "rawMarkdown": "Another, a bit hairy solution, would be to split the kernel into more parts. You can then use more memory but need to import output from more kernels.",
      "votes": null
    },
    {
      "id": "859003",
      "postDate": "05/24/2020 03:37:34",
      "content": "<p>hi, could you explain how to do this? importing/exporting from kernels i mean</p>",
      "rawMarkdown": "hi, could you explain how to do this? importing/exporting from kernels i mean",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 585944,
      "author_name": "cpmpml",
      "author_url": "",
      "post_date": "07/28/2019 11:26:07",
      "content": "<p>save less info or use a more compact format than csv.</p>",
      "votes": null,
      "replies": []
    },
    {
      "id": 585956,
      "author_name": "serigne",
      "author_url": "",
      "post_date": "07/28/2019 11:50:55",
      "content": "<p>I second <a href=\"/cpmpml\">@cpmpml</a> </p>\n\n<p>Use pickle or HDF5...\nmuch more compact and way faster to save and read back than csv. </p>",
      "votes": null,
      "replies": [
        {
          "id": 586042,
          "author_name": "firstbloody",
          "author_url": "",
          "post_date": "07/28/2019 13:38:05",
          "content": "<p>Thank you very much, I solved the problem with to_hdf</p>",
          "votes": null,
          "replies": []
        }
      ]
    },
    {
      "id": 586428,
      "author_name": "somnambwl",
      "author_url": "",
      "post_date": "07/29/2019 06:47:56",
      "content": "<p>Another, a bit hairy solution, would be to split the kernel into more parts. You can then use more memory but need to import output from more kernels.</p>",
      "votes": null,
      "replies": [
        {
          "id": 859003,
          "author_name": "tochibedford",
          "author_url": "",
          "post_date": "05/24/2020 03:37:34",
          "content": "<p>hi, could you explain how to do this? importing/exporting from kernels i mean</p>",
          "votes": null,
          "replies": []
        }
      ]
    }
  ],
  "raw_markdown_by_id": {
    "585769": "Hi, **when I use openbabel and to_csv, the kernel commit failed. If I don't use openbabel,the kernel commit complete.**Do you have the same problem?\n\nI'm having technical error while running kernels on Kaggle. This only happens when I run \"Commit\". \n**[NbConvertApp] ERROR | Kernel died while waiting for execute reply.**\n**line 127, in write f.write(output) OSError: [Errno 28] No space left on device**\nWhen I run \"Commit\", I can see that the disk usage has soared from 266.3MB/4.9GB to 4.9GB/4.9GB, then the kernel crashes.\nHow can I solve this problem?",
    "585944": "save less info or use a more compact format than csv.",
    "585956": "I second @cpmpml \n\nUse pickle or HDF5...\nmuch more compact and way faster to save and read back than csv.",
    "586042": "Thank you very much, I solved the problem with to_hdf",
    "586428": "Another, a bit hairy solution, would be to split the kernel into more parts. You can then use more memory but need to import output from more kernels.",
    "859003": "hi, could you explain how to do this? importing/exporting from kernels i mean"
  },
  "source": "meta"
}