{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Wall time: 2min 33s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "import pandas as pd\n",
    "\n",
    "dfs = pd.read_csv(\n",
    "    \"../../linux/git_diff.log\",\n",
    "    skip_blank_lines=False,\n",
    "    sep=\"\\n\",\n",
    "    encoding=\"latin-1\",\n",
    "    chunksize=100000,\n",
    "    names=[\"raw\"])\n",
    "df = pd.concat(dfs)\n",
    "df.tail()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 112519384 entries, 0 to 112519383\n",
      "Data columns (total 1 columns):\n",
      "raw    object\n",
      "dtypes: object(1)\n",
      "memory usage: 858.5+ MB\n"
     ]
    }
   ],
   "source": [
    "df.info()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
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   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.4"
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 "nbformat": 4,
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