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Created May 28, 2018 07:56
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DB to dot.ipynb
{
"cells": [
{
"cell_type": "code",
"execution_count": 1,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-28T07:26:39.628000Z",
"start_time": "2018-05-28T07:26:38.656000Z"
}
},
"outputs": [],
"source": [
"import pandas as pd\n",
"import requests"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-28T07:26:41.403000Z",
"start_time": "2018-05-28T07:26:39.631000Z"
}
},
"outputs": [],
"source": [
"auth_headers = {'Authorization': 'Bearer keyYXkjYFw61SeWDk'}\n",
"techs_table = 'https://api.airtable.com/v0/appuaXpFiadmP89sq/Techs'\n",
"r = requests.get(\n",
" techs_table,\n",
" headers=auth_headers)"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-28T07:37:47.951000Z",
"start_time": "2018-05-28T07:37:47.943000Z"
}
},
"outputs": [],
"source": [
"import ast\n",
"d = eval(ast.literal_eval(str(r.content)[1:]))\n",
"rowsD = [x[\"fields\"] for x in d[\"records\"]]"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-28T07:26:41.522000Z",
"start_time": "2018-05-28T07:26:41.499000Z"
}
},
"outputs": [
{
"data": {
"text/html": [
"<div>\n",
"<style>\n",
" .dataframe thead tr:only-child th {\n",
" text-align: right;\n",
" }\n",
"\n",
" .dataframe thead th {\n",
" text-align: left;\n",
" }\n",
"\n",
" .dataframe tbody tr th {\n",
" vertical-align: top;\n",
" }\n",
"</style>\n",
"<table border=\"1\" class=\"dataframe\">\n",
" <thead>\n",
" <tr style=\"text-align: right;\">\n",
" <th></th>\n",
" <th>Field 1</th>\n",
" <th>LongName</th>\n",
" <th>Name</th>\n",
" <th>Other_people_involved</th>\n",
" <th>Owner</th>\n",
" <th>Type</th>\n",
" <th>percentComplete</th>\n",
" <th>precursors</th>\n",
" </tr>\n",
" </thead>\n",
" <tbody>\n",
" <tr>\n",
" <th>15</th>\n",
" <td>31</td>\n",
" <td>Robotic Desk Arrangement</td>\n",
" <td>robDesk</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0%</td>\n",
" <td>AIlayout,lAmp,robSense</td>\n",
" </tr>\n",
" <tr>\n",
" <th>26</th>\n",
" <td>41</td>\n",
" <td>SLAM (Simultanious Location And Mapping)</td>\n",
" <td>SLAM</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0%</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>8</th>\n",
" <td>36</td>\n",
" <td>Sensicorn 2</td>\n",
" <td>sensicorn2</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0%</td>\n",
" <td>mApp,sensicorn1</td>\n",
" </tr>\n",
" <tr>\n",
" <th>3</th>\n",
" <td>10</td>\n",
" <td>Unit Desks</td>\n",
" <td>desks</td>\n",
" <td>NaN</td>\n",
" <td>[recHLT6IoCZXwwtp3]</td>\n",
" <td>NaN</td>\n",
" <td>0%</td>\n",
" <td>NaN</td>\n",
" </tr>\n",
" <tr>\n",
" <th>31</th>\n",
" <td>33</td>\n",
" <td>Robot Mounted Sensing</td>\n",
" <td>robSense</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>NaN</td>\n",
" <td>0%</td>\n",
" <td>basicRobot,sensors,SLAM</td>\n",
" </tr>\n",
" </tbody>\n",
"</table>\n",
"</div>"
],
"text/plain": [
" Field 1 LongName Name \\\n",
"15 31 Robotic Desk Arrangement robDesk \n",
"26 41 SLAM (Simultanious Location And Mapping) SLAM \n",
"8 36 Sensicorn 2 sensicorn2 \n",
"3 10 Unit Desks desks \n",
"31 33 Robot Mounted Sensing robSense \n",
"\n",
" Other_people_involved Owner Type percentComplete \\\n",
"15 NaN NaN NaN 0% \n",
"26 NaN NaN NaN 0% \n",
"8 NaN NaN NaN 0% \n",
"3 NaN [recHLT6IoCZXwwtp3] NaN 0% \n",
"31 NaN NaN NaN 0% \n",
"\n",
" precursors \n",
"15 AIlayout,lAmp,robSense \n",
"26 NaN \n",
"8 mApp,sensicorn1 \n",
"3 NaN \n",
"31 basicRobot,sensors,SLAM "
]
},
"execution_count": 4,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"project_data = pd.DataFrame(rowsD)\n",
"project_data.sample(5)"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-28T07:26:41.529000Z",
"start_time": "2018-05-28T07:26:41.525000Z"
},
"collapsed": true
},
"outputs": [],
"source": [
"node_description_pattern = \"{name} [label=\\\"{longName}\\\"];\"\n",
"edge_pattern = \"{from_node} -> {to_node};\""
]
},
{
"cell_type": "code",
"execution_count": 15,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-28T07:36:39.029000Z",
"start_time": "2018-05-28T07:36:39.005000Z"
}
},
"outputs": [],
"source": [
"node_descriptions = []\n",
"edges = []\n",
"\n",
"for i, row in project_data.iterrows():\n",
" n = node_description_pattern.format(name=row[\"Name\"], longName=row[\"LongName\"])\n",
" node_descriptions.append(n)\n",
" if type(row[\"precursors\"]) is str:\n",
" precursors = row[\"precursors\"].split(\",\")\n",
" for p in precursors:\n",
" e = edge_pattern.format(from_node=row[\"Name\"], to_node=p)\n",
" edges.append(e)"
]
},
{
"cell_type": "code",
"execution_count": 16,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-28T07:36:40.348000Z",
"start_time": "2018-05-28T07:36:40.341000Z"
}
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"digraph G {\n",
" rankdir = \"LR\";\n",
" label = \"Tech Tree of OATMEAL Projects\";\n",
" labelloc = \"t\";\n",
" node [style=filled, color=\"black\", fontcolor=\"white\"];\n",
" \n",
" potPaper [label=\"A Plane of Thrones Paper\"];\n",
" robPaper [label=\"Robotics Papers\"];\n",
" deskSenseDn [label=\"Below Desk Sensing\"];\n",
" desks [label=\"Unit Desks\"];\n",
" deskSenseUp [label=\"Above Desk Sensing\"];\n",
" mApp [label=\"Mobile App\"];\n",
" geoEthno2 [label=\"Geographic/ Ethnographic data 2\"];\n",
" basicBeacon [label=\"iBeacon Awareness\"];\n",
" sensicorn2 [label=\"Sensicorn 2\"];\n",
" geoEthno1 [label=\"Geographic/ Ethnographic data 1\"];\n",
" emailData [label=\"Email Data\"];\n",
" RBTM [label=\"Robotic Building Topology Modification\"];\n",
" basicRobot [label=\"Awareness of Robots\"];\n",
" timeData [label=\"Timesheet Data\"];\n",
" SNA [label=\"Social Network Analysis\"];\n",
" robDesk [label=\"Robotic Desk Arrangement\"];\n",
" Shakedown [label=\"Shakedown data capture\"];\n",
" phone [label=\"Access To Phones\"];\n",
" halo [label=\"Robotic Weaving\"];\n",
" SNAblog [label=\"nan\"];\n",
" SydStudioSeating [label=\"Sydney Studio Seating\"];\n",
" revit2ML [label=\"Revit Layout Extraction\"];\n",
" data [label=\"Data Literacy\"];\n",
" sensicorn1 [label=\"Sensicorn 1\"];\n",
" SydStudioSeating2 [label=\"Better Sydney Studio Seating\"];\n",
" diary [label=\"Diary Studies\"];\n",
" SLAM [label=\"SLAM (Simultanious Location And Mapping)\"];\n",
" bravo [label=\"Bravo Victor November\"];\n",
" pot [label=\"A Plane of Thrones Framework\"];\n",
" deskLoc [label=\"Desk Location\"];\n",
" electron [label=\"Desktop App\"];\n",
" robSense [label=\"Robot Mounted Sensing\"];\n",
" boom [label=\"Distribution Boom\"];\n",
" AIlayout [label=\"AI Layout\"];\n",
" lAmp [label=\"Learning Amplified Seating Plans\"];\n",
" bizCap [label=\"Capturing Business Metrics\"];\n",
" loTraining [label=\"Layout Training Data\"];\n",
" cadd [label=\"Continuous Analysis, Design & Delivery\"];\n",
" geoEthno3 [label=\"Geographic/ Ethnographic data 3\"];\n",
" ShakedownPaper [label=\"Shakedown Paper\"];\n",
" s3 [label=\"S3\"];\n",
" sensors [label=\"Sensor Literacy\"];\n",
" pathVis [label=\"Path Visualisation\"];\n",
" lExp [label=\"Learning Experiment\"];\n",
" systemReef [label=\"Systems Reef\"];\n",
" Shakedown2 [label=\"Shakedown (with stalls) Product\"];\n",
" hardware [label=\"Hardware Design\"];\n",
" BTARATA [label=\"Buildings That Are Right All The Time\"];\n",
" potPaper -> pot;\n",
" potPaper -> revit2ML;\n",
" robPaper -> halo;\n",
" deskSenseUp -> electron;\n",
" deskSenseUp -> s3;\n",
" mApp -> phone;\n",
" geoEthno2 -> geoEthno1;\n",
" geoEthno2 -> deskSenseDn;\n",
" sensicorn2 -> mApp;\n",
" sensicorn2 -> sensicorn1;\n",
" geoEthno1 -> deskLoc;\n",
" geoEthno1 -> deskSenseUp;\n",
" geoEthno1 -> diary;\n",
" RBTM -> robDesk;\n",
" SNA -> emailData;\n",
" SNA -> timeData;\n",
" robDesk -> AIlayout;\n",
" robDesk -> lAmp;\n",
" robDesk -> robSense;\n",
" Shakedown -> sensors;\n",
" halo -> basicRobot;\n",
" SNAblog -> bravo;\n",
" SydStudioSeating -> pot;\n",
" sensicorn1 -> hardware;\n",
" sensicorn1 -> pathVis;\n",
" SydStudioSeating2 -> lAmp;\n",
" SydStudioSeating2 -> SydStudioSeating;\n",
" diary -> electron;\n",
" deskLoc -> basicBeacon;\n",
" deskLoc -> desks;\n",
" robSense -> basicRobot;\n",
" robSense -> sensors;\n",
" robSense -> SLAM;\n",
" boom -> systemReef;\n",
" AIlayout -> loTraining;\n",
" lAmp -> lExp;\n",
" lAmp -> pot;\n",
" lAmp -> SNA;\n",
" cadd -> bizCap;\n",
" cadd -> geoEthno3;\n",
" cadd -> RBTM;\n",
" geoEthno3 -> sensicorn2;\n",
" geoEthno3 -> geoEthno2;\n",
" ShakedownPaper -> Shakedown;\n",
" s3 -> hardware;\n",
" s3 -> sensors;\n",
" sensors -> data;\n",
" lExp -> revit2ML;\n",
" Shakedown2 -> Shakedown;\n",
" BTARATA -> cadd;\n",
"}\n",
"\n"
]
}
],
"source": [
"g = \"\"\"\n",
"digraph G {{\n",
" rankdir = \"LR\";\n",
" label = \"Tech Tree of OATMEAL Projects\";\n",
" labelloc = \"t\";\n",
" node [style=filled, color=\"black\", fontcolor=\"white\"];\n",
" \n",
" {nodes}\n",
" {edges}\n",
"}}\n",
"\"\"\".format(edges=\"\\n \".join(edges), nodes=\"\\n \".join(node_descriptions))\n",
"\n",
"print(g)"
]
},
{
"cell_type": "code",
"execution_count": 23,
"metadata": {
"ExecuteTime": {
"end_time": "2018-05-28T07:44:49.263000Z",
"start_time": "2018-05-28T07:44:49.205000Z"
}
},
"outputs": [
{
"ename": "FileNotFoundError",
"evalue": "[WinError 2] \"dot.exe\" not found in path.",
"output_type": "error",
"traceback": [
"\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
"\u001b[1;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\py35\\lib\\site-packages\\pydot.py\u001b[0m in \u001b[0;36mcreate\u001b[1;34m(self, prog, format, encoding)\u001b[0m\n\u001b[0;32m 1860\u001b[0m \u001b[0mshell\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mFalse\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1861\u001b[1;33m stderr=subprocess.PIPE, stdout=subprocess.PIPE)\n\u001b[0m\u001b[0;32m 1862\u001b[0m \u001b[1;32mexcept\u001b[0m \u001b[0mOSError\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\py35\\lib\\subprocess.py\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, args, bufsize, executable, stdin, stdout, stderr, preexec_fn, close_fds, shell, cwd, env, universal_newlines, startupinfo, creationflags, restore_signals, start_new_session, pass_fds)\u001b[0m\n\u001b[0;32m 675\u001b[0m \u001b[0merrread\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0merrwrite\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 676\u001b[1;33m restore_signals, start_new_session)\n\u001b[0m\u001b[0;32m 677\u001b[0m \u001b[1;32mexcept\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\py35\\lib\\subprocess.py\u001b[0m in \u001b[0;36m_execute_child\u001b[1;34m(self, args, executable, preexec_fn, close_fds, pass_fds, cwd, env, startupinfo, creationflags, shell, p2cread, p2cwrite, c2pread, c2pwrite, errread, errwrite, unused_restore_signals, unused_start_new_session)\u001b[0m\n\u001b[0;32m 956\u001b[0m \u001b[0mcwd\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 957\u001b[1;33m startupinfo)\n\u001b[0m\u001b[0;32m 958\u001b[0m \u001b[1;32mfinally\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mFileNotFoundError\u001b[0m: [WinError 2] The system cannot find the file specified",
"\nDuring handling of the above exception, another exception occurred:\n",
"\u001b[1;31mFileNotFoundError\u001b[0m Traceback (most recent call last)",
"\u001b[1;32m<ipython-input-23-24a4539d4ea6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m 23\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 24\u001b[0m \u001b[1;31m# ok, we are set, let's save our graph into a file\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 25\u001b[1;33m \u001b[0mgraph\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite_png\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'example1_graph.png'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
"\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\py35\\lib\\site-packages\\pydot.py\u001b[0m in \u001b[0;36mnew_method\u001b[1;34m(path, f, prog, encoding)\u001b[0m\n\u001b[0;32m 1671\u001b[0m self.write(\n\u001b[0;32m 1672\u001b[0m \u001b[0mpath\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mf\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mprog\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mprog\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1673\u001b[1;33m encoding=encoding)\n\u001b[0m\u001b[0;32m 1674\u001b[0m \u001b[0mname\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;34m'write_{fmt}'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfmt\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfrmt\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1675\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__setattr__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mname\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnew_method\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\py35\\lib\\site-packages\\pydot.py\u001b[0m in \u001b[0;36mwrite\u001b[1;34m(self, path, prog, format, encoding)\u001b[0m\n\u001b[0;32m 1754\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1755\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m-> 1756\u001b[1;33m \u001b[0ms\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcreate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mprog\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mformat\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mencoding\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mencoding\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1757\u001b[0m \u001b[1;32mwith\u001b[0m \u001b[0mio\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mpath\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'wb'\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1758\u001b[0m \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mwrite\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0ms\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;32m~\\AppData\\Local\\Continuum\\anaconda3\\envs\\py35\\lib\\site-packages\\pydot.py\u001b[0m in \u001b[0;36mcreate\u001b[1;34m(self, prog, format, encoding)\u001b[0m\n\u001b[0;32m 1865\u001b[0m args[1] = '\"{prog}\" not found in path.'.format(\n\u001b[0;32m 1866\u001b[0m prog=prog)\n\u001b[1;32m-> 1867\u001b[1;33m \u001b[1;32mraise\u001b[0m \u001b[0mOSError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m*\u001b[0m\u001b[0margs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m 1868\u001b[0m \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m 1869\u001b[0m \u001b[1;32mraise\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mFileNotFoundError\u001b[0m: [WinError 2] \"dot.exe\" not found in path."
]
}
],
"source": [
"import pydot\n",
"\n",
"graph = pydot.Dot(graph_type='graph')\n",
"for i in range(3):\n",
" # we can get right into action by \"drawing\" edges between the nodes in our graph\n",
" # we do not need to CREATE nodes, but if you want to give them some custom style\n",
" # then I would recomend you to do so... let's cover that later\n",
" # the pydot.Edge() constructor receives two parameters, a source node and a destination\n",
" # node, they are just strings like you can see\n",
" edge = pydot.Edge(\"king\", \"lord%d\" % i)\n",
" # and we obviosuly need to add the edge to our graph\n",
" graph.add_edge(edge)\n",
"\n",
"# now let us add some vassals\n",
"vassal_num = 0\n",
"for i in range(3):\n",
" # we create new edges, now between our previous lords and the new vassals\n",
" # let us create two vassals for each lord\n",
" for j in range(2):\n",
" edge = pydot.Edge(\"lord%d\" % i, \"vassal%d\" % vassal_num)\n",
" graph.add_edge(edge)\n",
" vassal_num += 1\n",
"\n",
"# ok, we are set, let's save our graph into a file\n",
"graph.write_png('example1_graph.png')"
]
},
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"end_time": "2018-05-28T07:46:38.393000Z",
"start_time": "2018-05-28T07:46:38.374000Z"
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