{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from fn import op, _\n",
    "from itertools import repeat\n",
    "from functools import reduce\n",
    "# from objproxies import LazyProxy\n",
    "import json\n",
    "from copy import deepcopy, copy\n",
    "from pipetools import pipe\n",
    "from functools import partial"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "state_dict = {\n",
    "    's1': 2,\n",
    "    's2': 4,\n",
    "    's3': 300\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "# def pipeline(*steps):\n",
    "#     return reduce(lambda x, y: y(x), list(steps))\n",
    "# def compose(*funcs):\n",
    "#     return lambda x: reduce(lambda f, g: g(f), list(funcs), x)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "# ToDo:\n",
    "# Handle case where Mechanisms have no input. Perhaps the sentinel value of 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "# UI Behavior Mechanisms per Mechanism\n",
    "def b1m1(s):\n",
    "    return s['s1']\n",
    "def b2m1(s):\n",
    "    return s['s1'] * s['s2']\n",
    "\n",
    "def b1m2(s):\n",
    "    return s['s1']\n",
    "def b2m2(s):\n",
    "    return s['s1'] / s['s2']\n",
    "\n",
    "# UI State Mechanisms per Mechanism\n",
    "def s1m1(s, _input):\n",
    "    s['s1'] = s['s1']**2 + _input\n",
    "def s2m1(s, _input):\n",
    "    s['s2'] = s['s2'] + 1 + _input  \n",
    "def s3m1(s, _input):\n",
    "    s['s3'] = s['s3']\n",
    "\n",
    "def s1m2(s, _input):\n",
    "    s['s1'] = s['s1'] + _input\n",
    "def s2m2(s, _input):\n",
    "    s['s2'] = s['s2']\n",
    "def s3m2(s, _input):\n",
    "    s['s3'] = s['s3'] + 1\n",
    "    \n",
    "j = {\n",
    "    \"m1\": {\n",
    "        \"behaviors\": {\n",
    "            \"b1\": b1m1,\n",
    "            \"b2\": b2m1\n",
    "        },\n",
    "        \"states\": {\n",
    "            \"s1\": s1m1,\n",
    "            \"s2\": s2m1,\n",
    "            \"s3\": s3m1\n",
    "        }\n",
    "    },\n",
    "    \"m2\": {\n",
    "        \"behaviors\": {\n",
    "            \"b1\": b1m2,\n",
    "            \"b2\": b2m2\n",
    "        },\n",
    "        \"states\": {\n",
    "            \"s1\": s1m2,\n",
    "            \"s2\": s2m2,\n",
    "            \"s3\": s3m2\n",
    "        }\n",
    "    }\n",
    "}"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {},
   "outputs": [],
   "source": [
    "def generate_configs(j):\n",
    "    return list(\n",
    "        map(\n",
    "            lambda x: (\n",
    "                list(j[x][\"states\"].values()),\n",
    "                list(j[x][\"behaviors\"].values())\n",
    "            ), \n",
    "            j.keys()\n",
    "        )\n",
    "    )\n",
    "\n",
    "def getColResults(s, funcs):\n",
    "    return list(map(lambda f: f(s), funcs))\n",
    "\n",
    "def getBehaviorInput(s, funcs): \n",
    "    return op.foldr(_ + _)(getColResults(s, funcs))\n",
    "\n",
    "def mech_step(sL, state_funcs, behavior_funcs):\n",
    "    in_copy, out_copy, mutatable_copy = deepcopy(sL), deepcopy(sL), deepcopy(sL)\n",
    "    last_in_obj, last_mut_obj = in_copy[-1], mutatable_copy[-1]\n",
    "    \n",
    "    _input = getBehaviorInput(last_in_obj, behavior_funcs)\n",
    "\n",
    "    for f in state_funcs:\n",
    "        f(last_mut_obj, _input)\n",
    "    \n",
    "    out_copy.append(last_mut_obj)\n",
    "    return out_copy\n",
    "\n",
    "def pipeline(states_list, configs):\n",
    "    for config in configs:\n",
    "        s_conf, b_conf = config[0], config[1]\n",
    "        states_list = mech_step(states_list, s_conf, b_conf)\n",
    "    return states_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'s1': 2, 's2': 4, 's3': 300},\n",
       " {'s1': 14, 's2': 15, 's3': 300},\n",
       " {'s1': 28.933333333333334, 's2': 15, 's3': 301}]"
      ]
     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "states_list = [state_dict]\n",
    "configs = generate_configs(j)\n",
    "pipeline(states_list, configs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'s1': 2, 's2': 4, 's3': 300}]"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "states_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[([<function __main__.s1m1(s, _input)>,\n",
       "   <function __main__.s2m1(s, _input)>,\n",
       "   <function __main__.s3m1(s, _input)>],\n",
       "  [<function __main__.b1m1(s)>, <function __main__.b2m1(s)>]),\n",
       " ([<function __main__.s1m2(s, _input)>,\n",
       "   <function __main__.s2m2(s, _input)>,\n",
       "   <function __main__.s3m2(s, _input)>],\n",
       "  [<function __main__.b1m2(s)>, <function __main__.b2m2(s)>])]"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sm1 = [s1m1, s2m1, s3m1]\n",
    "bm1 = [b1m1, b2m1]\n",
    "\n",
    "sm2 = [s1m2, s2m2, s3m2]\n",
    "bm2 = [b1m2, b2m2]\n",
    "\n",
    "configs = [(sm1, bm1), (sm2, bm2)]\n",
    "configs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [],
   "source": [
    "# UI State Mechanisms\n",
    "\n",
    "# s['s1']^2 + (s['s1'] + (s['s1'] * s['s2']))\n",
    "# 14 = 4 + (2 + (2 * 4))\n",
    "def m(sL, s_funcs, b_funcs):\n",
    "    dSL = deepcopy(sL)\n",
    "    in_copy = deepcopy(sL)\n",
    "    out_copy = deepcopy(sL)\n",
    "    s = dSL[-1]\n",
    "    _input = getColInput(in_copy[-1], b_funcs)\n",
    "    \n",
    "#     s['s1'] = s['s1']**2 + _input\n",
    "#     s['s2'] = s['s2'] + 1 + _input\n",
    "    for f in s_funcs:\n",
    "        f(s, _input)\n",
    "    \n",
    "    out_copy.append(s)\n",
    "    return out_copy\n",
    "\n",
    "# s['s1'] + (s['s1'] + (s['s1'] / s['s2']))\n",
    "# 28.9 = 14 + (14 + (14/15))\n",
    "def m2(sL):\n",
    "    dSL = deepcopy(sL)\n",
    "    s = dSL[-1]\n",
    "    _input = getColInput(deepcopy(sL)[-1], [b1m2, b2m2])\n",
    "    \n",
    "    s['s1'] = s['s1'] + _input\n",
    "    s['s2'] = s['s2']\n",
    "    \n",
    "    sL.append(s)\n",
    "    return sL\n",
    "\n",
    "# def s2m1(sL):\n",
    "#     s = deepcopy(sL)[-1]\n",
    "#     s['s2'] = s['s2'] + 1 + getColInput(s, [b1m2, b2m2])\n",
    "#     sL.append(s)\n",
    "#     return sL\n",
    "\n",
    "# def s2m2(sL):\n",
    "#     s = deepcopy(sL)[-1]\n",
    "#     s['s2'] = s['s2']\n",
    "#     sL.append(s)\n",
    "#     return sL"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 152,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'s1': 2, 's2': 4, 's3': 300},\n",
       " {'s1': 14, 's2': 15, 's3': 300},\n",
       " {'s1': 28.933333333333334, 's2': 15, 's3': 300}]"
      ]
     },
     "execution_count": 152,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline3(states_list, configs)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 96,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "s1m1() missing 1 required positional argument: '_input'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m-----------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0mTraceback (most recent call last)",
      "\u001b[0;32m<ipython-input-96-5f9e087e72ee>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      5\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mdSL\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m \u001b[0mpipeline2\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mstates_list\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0ms1m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ms1m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-96-5f9e087e72ee>\u001b[0m in \u001b[0;36mpipeline2\u001b[0;34m(sL, funcs)\u001b[0m\n\u001b[1;32m      2\u001b[0m     \u001b[0mdSL\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mdeepcopy\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msL\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      3\u001b[0m     \u001b[0;32mfor\u001b[0m \u001b[0mf\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mfuncs\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 4\u001b[0;31m         \u001b[0mdSL\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mdSL\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      5\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mdSL\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: s1m1() missing 1 required positional argument: '_input'"
     ]
    }
   ],
   "source": [
    "def pipeline2(sL, funcs):\n",
    "    dSL = deepcopy(sL)\n",
    "    for f in funcs:\n",
    "        dSL = f(dSL)\n",
    "    return dSL\n",
    "\n",
    "pipeline2(states_list, [s1m1, s1m2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 101,
   "metadata": {},
   "outputs": [],
   "source": [
    "state_dict = {\n",
    "    's1': 2,\n",
    "    's2': 4,\n",
    "    's3': 300\n",
    "}\n",
    "# l = [state_dict]\n",
    "# l.append(state_dict)\n",
    "# l\n",
    "# print(s1m1([state_dict]))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 97,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'s1': 2, 's2': 4, 's3': 300}]"
      ]
     },
     "execution_count": 97,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_dict\n",
    "states_list = [state_dict]\n",
    "states_list"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 140,
   "metadata": {
    "collapsed": true
   },
   "outputs": [
    {
     "ename": "TypeError",
     "evalue": "'function' object is not subscriptable",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m-----------\u001b[0m",
      "\u001b[0;31mTypeError\u001b[0mTraceback (most recent call last)",
      "\u001b[0;32m<ipython-input-140-e6d630186e0f>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mpipeline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms1m1\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0ms1m2\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m",
      "\u001b[0;32m<ipython-input-104-17d92fdcc430>\u001b[0m in \u001b[0;36mpipeline\u001b[0;34m(*steps)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mpipeline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcompose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mfuncs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfuncs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-104-17d92fdcc430>\u001b[0m in \u001b[0;36m<lambda>\u001b[0;34m(x, y)\u001b[0m\n\u001b[1;32m      1\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mpipeline\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 2\u001b[0;31m     \u001b[0;32mreturn\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0my\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0msteps\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m      3\u001b[0m \u001b[0;32mdef\u001b[0m \u001b[0mcompose\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m*\u001b[0m\u001b[0mfuncs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0;32mlambda\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mreduce\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;32mlambda\u001b[0m \u001b[0mf\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m:\u001b[0m \u001b[0mg\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mf\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mlist\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mfuncs\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mx\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m<ipython-input-137-dac038f7b2cf>\u001b[0m in \u001b[0;36ms1m2\u001b[0;34m(sL)\u001b[0m\n\u001b[1;32m     17\u001b[0m \u001b[0;31m#     dSL = deepcopy(sL)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     18\u001b[0m \u001b[0;31m#     s = dSL[-1]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 19\u001b[0;31m     \u001b[0ms\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msL\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m-\u001b[0m\u001b[0;36m1\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     20\u001b[0m     \u001b[0ms\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m's1'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0ms\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;34m's1'\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0mgetColInput\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0mb1m2\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mb2m2\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     21\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0msL\u001b[0m \u001b[0;34m+\u001b[0m \u001b[0;34m[\u001b[0m\u001b[0ms\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mTypeError\u001b[0m: 'function' object is not subscriptable"
     ]
    }
   ],
   "source": [
    "pipeline(s1m1, s1m2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 99,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[{'s1': 2, 's2': 4, 's3': 300}]"
      ]
     },
     "execution_count": 99,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pipeline2(states_list, [s1m1, s1m2])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [],
   "source": [
    "# def a(x):\n",
    "#     return x + 1\n",
    "# func = F() >> s1m1 >> s1m1\n",
    "# func(state_dict)\n",
    "def s1_pipe(x): return pipe | s1m1 | s1m2 "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "s1m1 | s1m2"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "s1_pipe(state_dict)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'s1': 2, 's2': 4, 's3': 300}"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "state_dict"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 125,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "6\n"
     ]
    }
   ],
   "source": [
    "from functools import partial\n",
    "\n",
    "def multiply(x,y):\n",
    "        return x * y\n",
    "\n",
    "# create a new function that multiplies by 2\n",
    "dbl = partial(multiply,2)\n",
    "print(dbl(4))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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