{
  "id": 193056,
  "title": "List of available modules",
  "url": "/competitions/riiid-test-answer-prediction/discussion/193056",
  "author_name": "",
  "post_date": "2020-10-25T05:59:18.524340Z",
  "votes": 1,
  "comment_count": 1,
  "views": 0,
  "content": "<p>Is there a complete list of python modules and packages (XGBoost, LightGBM, etc.) that are available for import and use in this competition?</p>",
  "messages": [
    {
      "id": "1059455",
      "postDate": "10/25/2020 05:59:18",
      "content": "<p>Is there a complete list of python modules and packages (XGBoost, LightGBM, etc.) that are available for import and use in this competition?</p>",
      "rawMarkdown": "Is there a complete list of python modules and packages (XGBoost, LightGBM, etc.) that are available for import and use in this competition?",
      "votes": null
    },
    {
      "id": "1059584",
      "postDate": "10/25/2020 08:47:21",
      "content": "<p>you can find it, for example, in the <a href=\"https://www.kaggle.com/docs/notebooks#dockerfiles-and-notebooks-versions\" target=\"_blank\">documentation </a> and links from it <a href=\"https://github.com/Kaggle/docker-python\" target=\"_blank\">docker-python</a>, <a href=\"https://github.com/Kaggle/docker-python/blob/master/Dockerfile\" target=\"_blank\">cpu</a>  (<code>pip install xgboost ... pip install lightgbm</code>). This is what is already installed. You can also optionally install the desired module if you add the installation files as a dataset. Example in <a href=\"https://www.kaggle.com/rohanrao/tutorial-on-reading-large-datasets/data\" target=\"_blank\">notebook</a>:</p>\n<pre><code># datatable installation without internet\n!pip install ../input/python-datatable/datatable-0.11.0-cp37-cp37m-manylinux2010_x86_64.whl &gt; /dev/null\n</code></pre>",
      "rawMarkdown": "you can find it, for example, in the [documentation ](https://www.kaggle.com/docs/notebooks#dockerfiles-and-notebooks-versions) and links from it [docker-python](https://github.com/Kaggle/docker-python), [cpu](https://github.com/Kaggle/docker-python/blob/master/Dockerfile)  (`pip install xgboost ... pip install lightgbm`). This is what is already installed. You can also optionally install the desired module if you add the installation files as a dataset. Example in [notebook](https://www.kaggle.com/rohanrao/tutorial-on-reading-large-datasets/data):\n```\n# datatable installation without internet\n!pip install ../input/python-datatable/datatable-0.11.0-cp37-cp37m-manylinux2010_x86_64.whl > /dev/null\n```",
      "votes": null
    }
  ],
  "comments": [
    {
      "id": 1059584,
      "author_name": "sapr3s",
      "author_url": "",
      "post_date": "10/25/2020 08:47:21",
      "content": "<p>you can find it, for example, in the <a href=\"https://www.kaggle.com/docs/notebooks#dockerfiles-and-notebooks-versions\" target=\"_blank\">documentation </a> and links from it <a href=\"https://github.com/Kaggle/docker-python\" target=\"_blank\">docker-python</a>, <a href=\"https://github.com/Kaggle/docker-python/blob/master/Dockerfile\" target=\"_blank\">cpu</a>  (<code>pip install xgboost ... pip install lightgbm</code>). This is what is already installed. You can also optionally install the desired module if you add the installation files as a dataset. Example in <a href=\"https://www.kaggle.com/rohanrao/tutorial-on-reading-large-datasets/data\" target=\"_blank\">notebook</a>:</p>\n<pre><code># datatable installation without internet\n!pip install ../input/python-datatable/datatable-0.11.0-cp37-cp37m-manylinux2010_x86_64.whl &gt; /dev/null\n</code></pre>",
      "votes": null,
      "replies": []
    }
  ],
  "raw_markdown_by_id": {
    "1059455": "Is there a complete list of python modules and packages (XGBoost, LightGBM, etc.) that are available for import and use in this competition?",
    "1059584": "you can find it, for example, in the [documentation ](https://www.kaggle.com/docs/notebooks#dockerfiles-and-notebooks-versions) and links from it [docker-python](https://github.com/Kaggle/docker-python), [cpu](https://github.com/Kaggle/docker-python/blob/master/Dockerfile)  (`pip install xgboost ... pip install lightgbm`). This is what is already installed. You can also optionally install the desired module if you add the installation files as a dataset. Example in [notebook](https://www.kaggle.com/rohanrao/tutorial-on-reading-large-datasets/data):\n```\n# datatable installation without internet\n!pip install ../input/python-datatable/datatable-0.11.0-cp37-cp37m-manylinux2010_x86_64.whl > /dev/null\n```"
  },
  "source": "meta"
}