data_setup.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "data_setup.ipynb",
      "provenance": [],
      "authorship_tag": "ABX9TyM/CbD7QH4mHZA3KykkKG8X",
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "language_info": {
      "name": "python"
    }
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/csralvall/online_game_toxicity/blob/main/data_setup.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "WXi1It0746jr"
      },
      "source": [
        "### Install needed packages"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "z0pxZ7ey5ASX",
        "outputId": "71b09f6f-3bc5-4148-b90d-7ead49621522"
      },
      "source": [
        "!pip install -U pip setuptools wheel wget"
      ],
      "execution_count": 1,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Requirement already satisfied: pip in /usr/local/lib/python3.7/dist-packages (21.3.1)\n",
            "Requirement already satisfied: setuptools in /usr/local/lib/python3.7/dist-packages (59.3.0)\n",
            "Requirement already satisfied: wheel in /usr/local/lib/python3.7/dist-packages (0.37.0)\n",
            "Requirement already satisfied: wget in /usr/local/lib/python3.7/dist-packages (3.2)\n",
            "\u001b[33mWARNING: Running pip as the 'root' user can result in broken permissions and conflicting behaviour with the system package manager. It is recommended to use a virtual environment instead: https://pip.pypa.io/warnings/venv\u001b[0m\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "YsdH2QEr9WkR"
      },
      "source": [
        "### Import needed libraries"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "maXhDvByUuFn"
      },
      "source": [
        "# import libraries\n",
        "from google.colab import drive, files"
      ],
      "execution_count": 2,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "JAypiIGA-CLH"
      },
      "source": [
        "### Mount storage"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "u3mjkCTQWaLo",
        "outputId": "64fbecd0-9720-4cca-82b8-9f5a14f8ad71"
      },
      "source": [
        "# mount google drive unit to save computationally expensive results\n",
        "drive.mount('/content/drive')"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Mounted at /content/drive\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "ambPrm3Ay_FF"
      },
      "source": [
        "### Setup API keys"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "jZV7XOy9-Vtn",
        "colab": {
          "resources": {
            "http://localhost:8080/nbextensions/google.colab/files.js": {
              "data": 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              "ok": true,
              "headers": [
                [
                  "content-type",
                  "application/javascript"
                ]
              ],
              "status": 200,
              "status_text": ""
            }
          },
          "base_uri": "https://localhost:8080/",
          "height": 89
        },
        "outputId": "08c907eb-00f0-4160-dbde-3c1471537317"
      },
      "source": [
        "uploaded = files.upload()\n",
        "\n",
        "# load Kaggle API keys\n",
        "for fn in uploaded.keys():\n",
        "  print('User uploaded file \"{name}\" with length {length} bytes'.format(\n",
        "      name=fn, length=len(uploaded[fn])))"
      ],
      "execution_count": 4,
      "outputs": [
        {
          "output_type": "display_data",
          "data": {
            "text/html": [
              "\n",
              "     <input type=\"file\" id=\"files-55d20ca4-e703-43e5-9917-82892110f2f2\" name=\"files[]\" multiple disabled\n",
              "        style=\"border:none\" />\n",
              "     <output id=\"result-55d20ca4-e703-43e5-9917-82892110f2f2\">\n",
              "      Upload widget is only available when the cell has been executed in the\n",
              "      current browser session. Please rerun this cell to enable.\n",
              "      </output>\n",
              "      <script src=\"/nbextensions/google.colab/files.js\"></script> "
            ],
            "text/plain": [
              "<IPython.core.display.HTML object>"
            ]
          },
          "metadata": {}
        },
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Saving kaggle.json to kaggle.json\n",
            "User uploaded file \"kaggle.json\" with length 65 bytes\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "leLnP_RE-oox"
      },
      "source": [
        "# then move kaggle.json into the folder where the API expects to find it\n",
        "# if it is not already present\n",
        "![[ ! -d \"~/.kaggle\" ]] && mkdir -p ~/.kaggle/ && mv kaggle.json ~/.kaggle/ && chmod 600 ~/.kaggle/kaggle.json"
      ],
      "execution_count": 5,
      "outputs": []
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "6fsPfSXEzFO8"
      },
      "source": [
        "### Download and save dataset in storage"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "-e0ANNpj-u00",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "287df564-e98c-4cdf-a550-1bfbd19600eb"
      },
      "source": [
        "# download dataset if not saved in drive\n",
        "![[ ! -f \"/content/gosuai-dota-2-game-chats.zip\" ]] && kaggle datasets download -d romovpa/gosuai-dota-2-game-chats"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Downloading gosuai-dota-2-game-chats.zip to /content\n",
            " 94% 295M/313M [00:03<00:00, 86.4MB/s]\n",
            "100% 313M/313M [00:04<00:00, 80.4MB/s]\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e02RLlCg-1tP",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "a83cbc6c-7ffc-455f-89b1-37a236654667"
      },
      "source": [
        "# unzip file if it is not already inflated\n",
        "![[ ! -f \"/content/dota2_chat_messages.csv\" ]] && unzip gosuai-dota-2-game-chats.zip"
      ],
      "execution_count": 7,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "Archive:  gosuai-dota-2-game-chats.zip\n",
            "  inflating: dota2_chat_messages.csv  \n",
            "  inflating: sample_messages.txt     \n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "FNzufJsk--Hg",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "39a5f199-c208-42b5-f831-28623472f3d7"
      },
      "source": [
        "# make drive directory if it is not already created\n",
        "%env drive_dir=/content/drive/MyDrive/nlp\n",
        "![[ ! -d $drive_dir ]] && mkdir -p $drive_dir"
      ],
      "execution_count": 8,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: drive_dir=/content/drive/MyDrive/nlp\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "iP3pR23W_BmR",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "ef0c23e2-698e-4942-e9ff-ee76d06e8019"
      },
      "source": [
        "# move downloaded dataset to drive folder if it is not already there\n",
        "%env drive_file=/content/drive/MyDrive/nlp/dota2_chat_messages.csv\n",
        "![[ ! -f $drive_file ]] && mv dota2_chat_messages.csv $drive_file"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "env: drive_file=/content/drive/MyDrive/nlp/dota2_chat_messages.csv\n"
          ]
        }
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iWkOn47OKEmC"
      },
      "source": [
        "### Download and save list of bad words in english (lexicon) in storage"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "H9zeJ-g_KC4j"
      },
      "source": [
        "# get a bad-word list\n",
        "![[ ! -f \"/content/drive/MyDrive/nlp/bad_words.txt\" ]] && wget -O bad_words.txt https://www.cs.cmu.edu/~biglou/resources/bad-words.txt\n",
        "# copy file to drive\n",
        "![[ ! -f \"/content/drive/MyDrive/nlp/bad_words.txt\" ]] && mv /content/bad_words.txt /content/drive/MyDrive/nlp/"
      ],
      "execution_count": 10,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "Oo0yjMHK_O48",
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "outputId": "bf9e9518-dc24-4fd7-e686-016eefffae58"
      },
      "source": [
        "# check google drive folder status\n",
        "!ls /content/drive/MyDrive/nlp"
      ],
      "execution_count": 11,
      "outputs": [
        {
          "output_type": "stream",
          "name": "stdout",
          "text": [
            "bad_words.txt\t\t      fasttext.model.syn1neg.npy\n",
            "bag_of_words.pkl\t      fasttext.model.wv.vectors_ngrams.npy\n",
            "dataframe_with_groups.csv     fasttext.model.wv.vectors_vocab.npy\n",
            "dota2_chat_eng_annotated.csv  ftt_serie.npy\n",
            "dota2_chat_messages.csv       w2v_serie.npy\n",
            "dota2_chat_messages_lang.csv  word2vec.model\n",
            "fasttext.model\n"
          ]
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "vOzqz4pL7NKn"
      },
      "source": [
        ""
      ],
      "execution_count": null,
      "outputs": []
    }
  ]
}