Interactive.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "The autoreload extension is already loaded. To reload it, use:\n",
      "  %reload_ext autoreload\n"
     ]
    }
   ],
   "source": [
    "import networkx as nx\n",
    "%load_ext autoreload\n",
    "%autoreload 2\n",
    "from libvis.modules import graph\n",
    "from libvis import Vis"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Starting http at 7000\n",
      "2020-02-23 01:54:59.046 | INFO     | legimens.websocket.server:start_server:33 - Starting ws server at localhost:7700\n"
     ]
    }
   ],
   "source": [
    "vis = Vis()\n",
    "vis.start()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "g = nx.petersen_graph()\n",
    "nx.draw(g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "127.0.0.1 - - [23/Feb/2020 01:57:04] \"GET / HTTP/1.1\" 200 -\n",
      "127.0.0.1 - - [23/Feb/2020 01:57:04] \"GET /index.bundle.js?88613a351091593a22da HTTP/1.1\" 200 -\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-23 01:57:05.091 | INFO     | legimens.App:_handler:79 - New ws connection of / from ::1\n",
      "2020-02-23 01:57:05.099 | INFO     | legimens.App:_handler:91 - Sending root Legi_0x7f292e0064f0\n",
      "2020-02-23 01:57:05.134 | INFO     | legimens.App:_handler:79 - New ws connection of /undefined from ::1\n",
      "2020-02-23 01:57:05.150 | ERROR    | legimens.App:_handle_obj_ref:101 - No child with ref undefined\n",
      "2020-02-23 01:57:05.321 | INFO     | legimens.App:_handler:79 - New ws connection of /Legi_0x7f292e0064f0 from ::1\n",
      "2020-02-23 01:57:05.334 | INFO     | legimens.App:_handle_obj_ref:113 - Yield initial update dict_keys([])\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "127.0.0.1 - - [23/Feb/2020 01:57:05] \"GET /favicon.ico HTTP/1.1\" 200 -\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-23 01:57:25.057 | ERROR    | legimens.App:_handler:94 - Handling <class 'trio_websocket._impl.ConnectionClosed'> error:CloseReason<code=1000, name=NORMAL_CLOSURE, reason=None>\n",
      "2020-02-23 01:57:25.068 | INFO     | legimens.App:_handler:79 - New ws connection of / from ::1\n",
      "2020-02-23 01:57:25.071 | INFO     | legimens.App:_handler:91 - Sending root Legi_0x7f292e0064f0\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "127.0.0.1 - - [23/Feb/2020 01:57:36] \"GET / HTTP/1.1\" 200 -\n",
      "127.0.0.1 - - [23/Feb/2020 01:57:36] \"GET /index.bundle.js?88613a351091593a22da HTTP/1.1\" 200 -\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-23 01:57:36.781 | INFO     | legimens.App:_handler:79 - New ws connection of / from ::1\n",
      "2020-02-23 01:57:36.791 | INFO     | legimens.App:_handler:91 - Sending root Legi_0x7f292e0064f0\n",
      "2020-02-23 01:57:36.825 | INFO     | legimens.App:_handler:79 - New ws connection of /undefined from ::1\n",
      "2020-02-23 01:57:36.836 | ERROR    | legimens.App:_handle_obj_ref:101 - No child with ref undefined\n",
      "2020-02-23 01:57:36.971 | INFO     | legimens.App:_handler:79 - New ws connection of /Legi_0x7f292e0064f0 from ::1\n",
      "2020-02-23 01:57:36.973 | INFO     | legimens.App:_handle_obj_ref:113 - Yield initial update dict_keys([])\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "127.0.0.1 - - [23/Feb/2020 01:57:37] \"GET /favicon.ico HTTP/1.1\" 200 -\n"
     ]
    }
   ],
   "source": [
    "vis.graph = graph(graph=g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-02-23 02:05:30.980 | ERROR    | legimens.App:_handler:94 - Handling <class 'trio_websocket._impl.ConnectionClosed'> error:CloseReason<code=1000, name=NORMAL_CLOSURE, reason=None>\n",
      "2020-02-23 02:05:30.983 | INFO     | legimens.App:_handler:79 - New ws connection of /Legi_0x7f291ada9a90 from ::1\n",
      "sending value to front:  graph {\"directed\": false, \"multigraph\": false, \"graph\": {\"name\": \"Petersen Graph\"}, \"nodes\": [{\"id\": 0}, {\"id\": 1}, {\"id\": 2}, {\"id\": 3}, {\"id\": 4}, {\"id\": 5}, {\"id\": 6}, {\"id\": 7}, {\"id\": 8}, {\"id\": 9}], \"links\": [{\"source\": 0, \"target\": 1}, {\"source\": 0, \"target\": 4}, {\"source\": 0, \"target\": 5}, {\"source\": 1, \"target\": 2}, {\"source\": 1, \"target\": 6}, {\"source\": 2, \"target\": 3}, {\"source\": 2, \"target\": 7}, {\"source\": 3, \"target\": 4}, {\"source\": 3, \"target\": 8}, {\"source\": 4, \"target\": 9}, {\"source\": 5, \"target\": 7}, {\"source\": 5, \"target\": 8}, {\"source\": 6, \"target\": 8}, {\"source\": 6, \"target\": 9}, {\"source\": 7, \"target\": 9}]}\n",
      "2020-02-23 02:05:30.985 | INFO     | legimens.App:_handle_obj_ref:113 - Yield initial update dict_keys(['graph'])\n"
     ]
    }
   ],
   "source": [
    "vis.vars.graph = graph(graph=g)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sending value to front:  graph {\"directed\": false, \"multigraph\": false, \"graph\": {\"name\": \"Frucht Graph\"}, \"nodes\": [{\"id\": 0}, {\"id\": 1}, {\"id\": 2}, {\"id\": 3}, {\"id\": 4}, {\"id\": 5}, {\"id\": 6}, {\"id\": 7}, {\"id\": 8}, {\"id\": 9}, {\"id\": 10}, {\"id\": 11}], \"links\": [{\"source\": 0, \"target\": 1}, {\"source\": 0, \"target\": 6}, {\"source\": 0, \"target\": 7}, {\"source\": 1, \"target\": 2}, {\"source\": 1, \"target\": 7}, {\"source\": 2, \"target\": 3}, {\"source\": 2, \"target\": 8}, {\"source\": 3, \"target\": 4}, {\"source\": 3, \"target\": 9}, {\"source\": 4, \"target\": 5}, {\"source\": 4, \"target\": 9}, {\"source\": 5, \"target\": 6}, {\"source\": 5, \"target\": 10}, {\"source\": 6, \"target\": 10}, {\"source\": 7, \"target\": 11}, {\"source\": 8, \"target\": 11}, {\"source\": 8, \"target\": 9}, {\"source\": 10, \"target\": 11}]}\n"
     ]
    }
   ],
   "source": [
    "g1 = nx.frucht_graph()\n",
    "vis.vars.graph.graph=g1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {},
   "outputs": [],
   "source": [
    "g1.add_nodes_from([12,13])\n",
    "g1.add_edges_from([(1,12),(1,13)])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "sending value to front:  graph {\"directed\": false, \"multigraph\": false, \"graph\": {\"name\": \"Frucht Graph\"}, \"nodes\": [{\"color\": \"red\", \"id\": 0}, {\"color\": \"orange\", \"id\": 1}, {\"id\": 2}, {\"id\": 3}, {\"id\": 4}, {\"id\": 5}, {\"id\": 6}, {\"id\": 7}, {\"id\": 8}, {\"id\": 9}, {\"id\": 10}, {\"id\": 11}, {\"id\": 12}, {\"id\": 13}], \"links\": [{\"source\": 0, \"target\": 1}, {\"source\": 0, \"target\": 6}, {\"source\": 0, \"target\": 7}, {\"source\": 1, \"target\": 2}, {\"source\": 1, \"target\": 7}, {\"source\": 1, \"target\": 6}, {\"source\": 1, \"target\": 12}, {\"source\": 1, \"target\": 13}, {\"source\": 2, \"target\": 3}, {\"source\": 2, \"target\": 8}, {\"source\": 3, \"target\": 4}, {\"source\": 3, \"target\": 9}, {\"source\": 4, \"target\": 5}, {\"source\": 4, \"target\": 9}, {\"source\": 5, \"target\": 6}, {\"source\": 5, \"target\": 10}, {\"source\": 6, \"target\": 10}, {\"source\": 7, \"target\": 11}, {\"source\": 8, \"target\": 11}, {\"source\": 8, \"target\": 9}, {\"source\": 10, \"target\": 11}]}\n"
     ]
    }
   ],
   "source": [
    "vis.vars.graph.graph = g1"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [],
   "source": [
    "g1.nodes[0]['color'] = 'red'\n",
    "g1.nodes[1]['color'] = 'orange'"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Extend Graph with libvis?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 62,
   "metadata": {},
   "outputs": [],
   "source": [
    "\n",
    "from libvis.modules import BaseModule\n",
    "from networkx import Graph"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 86,
   "metadata": {},
   "outputs": [],
   "source": [
    "class ExGraph(Graph, BaseModule):\n",
    "    def __init__(self, *args, **kwargs):\n",
    "        super(Graph, self).__init__()\n",
    "        super(BaseModule, self).__init__()\n",
    "        \n",
    "    def vis_get(self, key):\n",
    "        print('getting',key)\n",
    "        return super().vis_get(key)\n",
    "    def vis_(self, key, value):\n",
    "        print('setting', key, value)\n",
    "        super().vis_set(key, value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 87,
   "metadata": {},
   "outputs": [],
   "source": [
    "g = ExGraph()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 88,
   "metadata": {},
   "outputs": [
    {
     "ename": "RecursionError",
     "evalue": "maximum recursion depth exceeded while calling a Python object",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRecursionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-88-fdc2aea8e2f1>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mg\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madd_nodes_from\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mrange\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;36m10\u001b[0m\u001b[0;34m)\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/usr/lib/python3.8/site-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36madd_nodes_from\u001b[0;34m(self, nodes_for_adding, **attr)\u001b[0m\n\u001b[1;32m    567\u001b[0m             \u001b[0;31m# while pre-2.7.5 ironpython throws on self._adj[n]\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    568\u001b[0m             \u001b[0;32mtry\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 569\u001b[0;31m                 \u001b[0;32mif\u001b[0m \u001b[0mn\u001b[0m \u001b[0;32mnot\u001b[0m \u001b[0;32min\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_node\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    570\u001b[0m                     \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_adj\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madjlist_inner_dict_factory\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    571\u001b[0m                     \u001b[0mattr_dict\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_node\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mn\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mnode_attr_dict_factory\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/side-projects-hobby/hosta/python/legimens/helpers/AttrDict.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m     23\u001b[0m         \u001b[0;31m#object.__getattribute__(self, '__get')(name)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\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     26\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/side-projects-hobby/hosta/python/legimens/helpers/AttrDict.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__getattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\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      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/site-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, n)\u001b[0m\n\u001b[1;32m    470\u001b[0m         \u001b[0mAtlasView\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[0;34m}\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    471\u001b[0m         \"\"\"\n\u001b[0;32m--> 472\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madj\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mn\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    473\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    474\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0madd_node\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_for_adding\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mattr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/site-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36madj\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    365\u001b[0m         \u001b[0mFor\u001b[0m \u001b[0mdirected\u001b[0m \u001b[0mgraphs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m`\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madj\u001b[0m\u001b[0;31m`\u001b[0m \u001b[0mholds\u001b[0m \u001b[0moutgoing\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0msuccessor\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0minfo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    366\u001b[0m         \"\"\"\n\u001b[0;32m--> 367\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mAdjacencyView\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_adj\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    368\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    369\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "... last 4 frames repeated, from the frame below ...\n",
      "\u001b[0;32m~/side-projects-hobby/hosta/python/legimens/helpers/AttrDict.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m     23\u001b[0m         \u001b[0;31m#object.__getattribute__(self, '__get')(name)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\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     26\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded while calling a Python object"
     ]
    }
   ],
   "source": [
    "g.add_nodes_from(range(10))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 89,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{}"
      ]
     },
     "execution_count": 89,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "g"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 90,
   "metadata": {},
   "outputs": [
    {
     "ename": "RecursionError",
     "evalue": "maximum recursion depth exceeded",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mRecursionError\u001b[0m                            Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-90-51bcb6021d79>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m\u001b[0m\n\u001b[0;32m----> 1\u001b[0;31m \u001b[0mg\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m1\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/usr/lib/python3.8/site-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, n)\u001b[0m\n\u001b[1;32m    470\u001b[0m         \u001b[0mAtlasView\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[0;34m}\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    471\u001b[0m         \"\"\"\n\u001b[0;32m--> 472\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madj\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mn\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    473\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    474\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0madd_node\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_for_adding\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mattr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/usr/lib/python3.8/site-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36madj\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m    365\u001b[0m         \u001b[0mFor\u001b[0m \u001b[0mdirected\u001b[0m \u001b[0mgraphs\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;31m \u001b[0m\u001b[0;31m`\u001b[0m\u001b[0mG\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madj\u001b[0m\u001b[0;31m`\u001b[0m \u001b[0mholds\u001b[0m \u001b[0moutgoing\u001b[0m \u001b[0;34m(\u001b[0m\u001b[0msuccessor\u001b[0m\u001b[0;34m)\u001b[0m \u001b[0minfo\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    366\u001b[0m         \"\"\"\n\u001b[0;32m--> 367\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mAdjacencyView\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_adj\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    368\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    369\u001b[0m     \u001b[0;34m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/side-projects-hobby/hosta/python/legimens/helpers/AttrDict.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m     23\u001b[0m         \u001b[0;31m#object.__getattribute__(self, '__get')(name)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     24\u001b[0m         \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m_get\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 25\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0msuper\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0m__getattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mname\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     26\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     27\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m~/side-projects-hobby/hosta/python/legimens/helpers/AttrDict.py\u001b[0m in \u001b[0;36m__getattr__\u001b[0;34m(self, name)\u001b[0m\n\u001b[1;32m      5\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      6\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__getattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mname\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 7\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mname\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      8\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      9\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0m__setattr__\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m  \u001b[0mname\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mvalue\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "... last 4 frames repeated, from the frame below ...\n",
      "\u001b[0;32m/usr/lib/python3.8/site-packages/networkx/classes/graph.py\u001b[0m in \u001b[0;36m__getitem__\u001b[0;34m(self, n)\u001b[0m\n\u001b[1;32m    470\u001b[0m         \u001b[0mAtlasView\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[0;34m}\u001b[0m\u001b[0;34m}\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    471\u001b[0m         \"\"\"\n\u001b[0;32m--> 472\u001b[0;31m         \u001b[0;32mreturn\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0madj\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0mn\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    473\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    474\u001b[0m     \u001b[0;32mdef\u001b[0m \u001b[0madd_node\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mnode_for_adding\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0;34m**\u001b[0m\u001b[0mattr\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mRecursionError\u001b[0m: maximum recursion depth exceeded"
     ]
    }
   ],
   "source": [
    "g[1]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
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