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    "# Table of Contents\n",
    " <p><div class=\"lev1 toc-item\"><a href=\"#Test-for-Binder-v2\" data-toc-modified-id=\"Test-for-Binder-v2-1\"><span class=\"toc-item-num\">1&nbsp;&nbsp;</span>Test for Binder v2</a></div><div class=\"lev2 toc-item\"><a href=\"#Sys-&amp;-OS-modules\" data-toc-modified-id=\"Sys-&amp;-OS-modules-11\"><span class=\"toc-item-num\">1.1&nbsp;&nbsp;</span>Sys &amp; OS modules</a></div><div class=\"lev2 toc-item\"><a href=\"#Importing-a-file\" data-toc-modified-id=\"Importing-a-file-12\"><span class=\"toc-item-num\">1.2&nbsp;&nbsp;</span>Importing a file</a></div><div class=\"lev2 toc-item\"><a href=\"#Conclusion\" data-toc-modified-id=\"Conclusion-13\"><span class=\"toc-item-num\">1.3&nbsp;&nbsp;</span>Conclusion</a></div>"
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  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Test for Binder v2"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Sys & OS modules"
   ]
  },
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      "Path (sys.path):\n",
      "\n",
      "/usr/lib/python36.zip\n",
      "/usr/lib/python3.6\n",
      "/usr/lib/python3.6/lib-dynload\n",
      "/home/lilian/.local/lib/python3.6/site-packages\n",
      "/usr/local/lib/python3.6/dist-packages\n",
      "/usr/local/lib/python3.6/dist-packages/dot2tex-2.11.dev0-py3.6.egg\n",
      "/usr/local/lib/python3.6/dist-packages/autorun-0.1.dev20171103-py3.6.egg\n",
      "/usr/local/lib/python3.6/dist-packages/sphinxcontrib_cheeseshop-0.2.dev20171103-py3.6.egg\n",
      "/usr/local/lib/python3.6/dist-packages/sphinxcontrib_youtube-1.0.dev20171103-py3.6.egg\n",
      "/usr/local/lib/python3.6/dist-packages/sphinxcontrib_bitbucket-1.0-py3.6.egg\n",
      "/usr/local/lib/python3.6/dist-packages/sphinxcontrib_googleanalytics-0.1.dev20180228-py3.6.egg\n",
      "/usr/local/lib/python3.6/dist-packages/sphinxcontrib_gnuplot-0.1.dev20180308-py3.6.egg\n",
      "/usr/lib/python3/dist-packages\n",
      "/usr/local/lib/python3.6/dist-packages/IPython/extensions\n",
      "/home/lilian/.ipython\n"
     ]
    }
   ],
   "source": [
    "import sys\n",
    "\n",
    "print(\"Path (sys.path):\")\n",
    "for f in sys.path:\n",
    "    print(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os"
   ]
  },
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   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Current directory:\n",
      "/home/lilian/publis/notebooks\n"
     ]
    }
   ],
   "source": [
    "print(\"Current directory:\")\n",
    "print(os.getcwd())"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importing a file\n",
    "\n",
    "I will import [this file](https://github.com/Naereen/notebooks/blob/master/agreg/memoisation.py) from the [agreg/](https://github.com/Naereen/notebooks/tree/master/agreg/) sub-folder."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "3 secondes...\n",
      "13\n",
      "4 secondes...\n",
      "100\n",
      "3 secondes...\n",
      "13\n",
      "0 secondes !\n",
      "13\n",
      "3 secondes...\n",
      "13\n",
      "3 secondes...\n",
      "13\n",
      "4 secondes...\n",
      "100\n",
      "0 secondes !\n",
      "100\n",
      "Test de fibo() non mémoisée :\n",
      "F_0 = 1\n",
      "F_1 = 1\n",
      "F_2 = 2\n",
      "F_3 = 3\n",
      "F_4 = 5\n",
      "F_5 = 8\n",
      "F_6 = 13\n",
      "F_7 = 21\n",
      "F_8 = 34\n",
      "F_9 = 55\n",
      "Test de fibo() mémoisée (plus rapide) :\n",
      "F_0 = 1\n",
      "F_1 = 1\n",
      "F_2 = 2\n",
      "F_3 = 3\n",
      "F_4 = 5\n",
      "F_5 = 8\n",
      "F_6 = 13\n",
      "F_7 = 21\n",
      "F_8 = 34\n",
      "F_9 = 55\n",
      "Test de factorielle() mémoisée :\n",
      "0! = 0\n",
      "1! = 1\n",
      "2! = 2\n",
      "3! = 6\n",
      "4! = 24\n",
      "5! = 120\n",
      "6! = 720\n",
      "7! = 5040\n",
      "8! = 40320\n",
      "9! = 362880\n"
     ]
    }
   ],
   "source": [
    "import agreg.memoisation"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Conclusion"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "It seems to work as wanted."
   ]
  }
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