{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 143,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import pyarrow\n",
    "from tqdm import tqdm\n",
    "import os\n",
    "import shutil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "outputs": [
    {
     "data": {
      "text/plain": "'2.0.0rc1'"
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pd.__version__"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "outputs": [
    {
     "ename": "OptionError",
     "evalue": "'You can only set the value of existing options'",
     "output_type": "error",
     "traceback": [
      "\u001B[1;31m---------------------------------------------------------------------------\u001B[0m",
      "\u001B[1;31mOptionError\u001B[0m                               Traceback (most recent call last)",
      "Cell \u001B[1;32mIn[12], line 1\u001B[0m\n\u001B[1;32m----> 1\u001B[0m \u001B[43mpd\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43moptions\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mmode\u001B[49m\u001B[38;5;241;43m.\u001B[39;49m\u001B[43mdtype_backend\u001B[49m \u001B[38;5;241m=\u001B[39m \u001B[38;5;124m'\u001B[39m\u001B[38;5;124mpyarrow\u001B[39m\u001B[38;5;124m'\u001B[39m\n",
      "File \u001B[1;32m~\\.conda\\envs\\MOME_BIGDATA\\lib\\site-packages\\pandas\\_config\\config.py:226\u001B[0m, in \u001B[0;36mDictWrapper.__setattr__\u001B[1;34m(self, key, val)\u001B[0m\n\u001B[0;32m    224\u001B[0m     _set_option(prefix, val)\n\u001B[0;32m    225\u001B[0m \u001B[38;5;28;01melse\u001B[39;00m:\n\u001B[1;32m--> 226\u001B[0m     \u001B[38;5;28;01mraise\u001B[39;00m OptionError(\u001B[38;5;124m\"\u001B[39m\u001B[38;5;124mYou can only set the value of existing options\u001B[39m\u001B[38;5;124m\"\u001B[39m)\n",
      "\u001B[1;31mOptionError\u001B[0m: 'You can only set the value of existing options'"
     ]
    }
   ],
   "source": [
    "# pd.options.mode #= 'pyarrow'"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": 119,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_01\n",
      "D:\\PATSTAT\n"
     ]
    }
   ],
   "source": [
    "import os\n",
    "print(os.getcwd())  # Prints the current working directory\n",
    "\n",
    "workdir_path=r\"D:\\PATSTAT\"\n",
    "os.chdir(workdir_path)\n",
    "print(os.getcwd())"
   ],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [],
   "source": [],
   "metadata": {
    "collapsed": false
   }
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "CONCAT: ['tls201_part01.csv', 'tls201_part02.csv', 'tls201_part03.csv'] TO D:\\PATSTAT\\table_tls201.csv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "1000it [07:12,  2.31it/s]\n",
      "1000it [07:25,  2.25it/s]\n",
      "429it [02:55,  2.44it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deleting\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_01\\tls201_part01.csv\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_01\\tls201_part02.csv\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_01\\tls201_part03.csv\n",
      "MOVE: D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_01\\tls202_part01.csv TO D:\\PATSTAT\\table_tls202.csv\n",
      "MOVE: D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_05\\tls204_part01\\tls204_part01.csv TO D:\\PATSTAT\\table_tls204.csv\n",
      "MOVE: D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_05\\tls205_part01\\tls205_part01.csv TO D:\\PATSTAT\\table_tls205.csv\n",
      "CONCAT: ['tls206_part01.csv', 'tls206_part02.csv'] TO D:\\PATSTAT\\table_tls206.csv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "1000it [07:21,  2.27it/s]\n",
      "715it [05:32,  2.15it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deleting\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_05\\tls206_part01\\tls206_part01.csv\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_05\\tls206_part02\\tls206_part02.csv\n",
      "MOVE: D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_05\\tls207_part01\\tls207_part01.csv TO D:\\PATSTAT\\table_tls207.csv\n",
      "CONCAT: ['tls209_part01.csv', 'tls209_part02.csv'] TO D:\\PATSTAT\\table_tls209.csv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "3200it [07:35,  7.02it/s]\n",
      "3049it [07:15,  7.01it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deleting\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_06\\tls209_part01\\tls209_part01.csv\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_06\\tls209_part02\\tls209_part02.csv\n",
      "MOVE: D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_06\\tls210_part01\\tls210_part01.csv TO D:\\PATSTAT\\table_tls210.csv\n",
      "CONCAT: ['tls211_part01.csv', 'tls211_part02.csv'] TO D:\\PATSTAT\\table_tls211.csv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "2500it [08:45,  4.76it/s]\n",
      "369it [01:23,  4.42it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deleting\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_06\\tls211_part01\\tls211_part01.csv\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_06\\tls211_part02\\tls211_part02.csv\n",
      "CONCAT: ['tls212_part01.csv', 'tls212_part02.csv', 'tls212_part03.csv'] TO D:\\PATSTAT\\table_tls212.csv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "4000it [12:45,  5.23it/s]\n",
      "4000it [12:57,  5.14it/s]\n",
      "1232it [03:54,  5.25it/s]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "deleting\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_06\\tls212_part01\\tls212_part01.csv\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_07\\tls212_part02\\tls212_part02.csv\n",
      "D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_07\\tls212_part03\\tls212_part03.csv\n",
      "MOVE: D:\\PATSTAT\\data_PATSTAT_Global_2022_Autumn_07\\tls214_part01\\tls214_part01.csv TO D:\\PATSTAT\\table_tls214.csv\n",
      "CONCAT: ['tls215_part01.csv', 'tls215_part02.csv', 'tls215_part03.csv'] TO D:\\PATSTAT\\table_tls215.csv\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "8000it [15:10,  8.79it/s]\n",
      "3524it [06:32,  9.30it/s]"
     ]
    }
   ],
   "source": [
    "file_path_dict=dict()\n",
    "\n",
    "# iterate over files in\n",
    "# that directory\n",
    "for root, dirs, files in os.walk(workdir_path):\n",
    "    for filename in files:\n",
    "        if filename.endswith(\".csv\") and not filename.startswith(\"table\"):\n",
    "            path= os.path.join(root, filename)\n",
    "            file_path_dict[filename] = path\n",
    "\n",
    "complete_file_set = set()\n",
    "for fname in file_path_dict.keys():\n",
    "    complete_file_set.add(fname.split(\"_\")[0])\n",
    "complete_file_set = sorted(complete_file_set)\n",
    "\n",
    "for complete_file in complete_file_set:\n",
    "    file_list = [file for file in file_path_dict.keys() if complete_file in file]\n",
    "\n",
    "    outfile_path = os.path.join(workdir_path,\"table_\"+complete_file+\".csv\")\n",
    "    # print(outfile_path,file_list)\n",
    "\n",
    "    if len(file_list)==1:\n",
    "        file_path = file_path_dict.get(file_list[0])\n",
    "        print(\"MOVE:\",file_path ,\"TO\",outfile_path)\n",
    "        shutil.move(file_path, outfile_path)\n",
    "    else:\n",
    "        print(\"CONCAT:\",file_list ,\"TO\",outfile_path)\n",
    "\n",
    "\n",
    "        CHUNK_SIZE = 50000\n",
    "        with_header=True\n",
    "        first_one = True\n",
    "        for csv_file_name in file_list:\n",
    "            csv_file_path = file_path_dict.get(csv_file_name)\n",
    "            chunk_container = pd.read_csv(csv_file_path, chunksize=CHUNK_SIZE,low_memory=False)\n",
    "            for chunk in tqdm(chunk_container):\n",
    "                chunk.to_csv(outfile_path, mode=\"a\", index=False, header=with_header)\n",
    "                with_header=False\n",
    "            first_one = False\n",
    "\n",
    "        print(\"deleting\")\n",
    "        for csv_file_name in file_list:\n",
    "            csv_file_path = file_path_dict.get(csv_file_name)\n",
    "            print(csv_file_path)\n",
    "            os.remove(csv_file_path)"
   ],
   "metadata": {
    "collapsed": false,
    "pycharm": {
     "is_executing": true
    }
   }
  }
 ],
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