You are viewing a plain text version of this content. The canonical link for it is here.
Posted to commits@airavata.apache.org by sm...@apache.org on 2016/08/09 18:01:11 UTC
[31/32] airavata-sandbox git commit: Added_Apache
http://git-wip-us.apache.org/repos/asf/airavata-sandbox/blob/2352c0ff/Interacting_with_Airavata_using_ipython_Notebook/Admin-User/.ipynb_checkpoints/Admin User-checkpoint.ipynb
----------------------------------------------------------------------
diff --git a/Interacting_with_Airavata_using_ipython_Notebook/Admin-User/.ipynb_checkpoints/Admin User-checkpoint.ipynb b/Interacting_with_Airavata_using_ipython_Notebook/Admin-User/.ipynb_checkpoints/Admin User-checkpoint.ipynb
new file mode 100644
index 0000000..748fc23
--- /dev/null
+++ b/Interacting_with_Airavata_using_ipython_Notebook/Admin-User/.ipynb_checkpoints/Admin User-checkpoint.ipynb
@@ -0,0 +1,852 @@
+{
+ "cells": [
+ {
+ "cell_type": "code",
+ "execution_count": 1,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "import ConfigParser\n",
+ "import pandas as pd\n",
+ "import datetime\n",
+ "from datetime import datetime\n",
+ "import calendar\n",
+ "import matplotlib.pyplot as plt\n",
+ "%matplotlib inline\n",
+ "conf = ConfigParser.RawConfigParser()\n",
+ "conf.read('cli.properties')\n",
+ "hostName = conf.get('AiravataServer', 'host')\n",
+ "port = conf.get('AiravataServer', 'port')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 2,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "0.16.0\n",
+ "0.16.0\n",
+ "\n",
+ "Welcome to Airavata CLI v0.0.1 - Wirtten in python\n",
+ "\n",
+ "\n",
+ "None\n"
+ ]
+ }
+ ],
+ "source": [
+ "from airavata_cli import AiravataCLI\n",
+ "airavata_cli = AiravataCLI(hostName, int(port))\n",
+ "print(airavata_cli.printVersion())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": false
+ },
+ "source": [
+ "## Making Sure we are connected to the right Gateway"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 3,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[Gateway(gatewayId='Ultrascan_Production', emailAddress=None, domain=None, gatewayName='Ultrascan_Production')]"
+ ]
+ },
+ "execution_count": 3,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "airavata_cli.get_gatewaylist()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "## List of Resources the Gateway uses"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 4,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[('alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-17163b64ef29',\n",
+ " 'alamo.uthscsa.edu'),\n",
+ " ('Jureca_32098185-4396-4c11-afb7-26e991a03476', 'Jureca'),\n",
+ " ('comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975ee035b', 'comet.sdsc.edu'),\n",
+ " ('gordon.sdsc.edu_f9363997-4614-477f-847e-79d262ee8ef7', 'gordon.sdsc.edu'),\n",
+ " ('ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aad1f8310ecf',\n",
+ " 'ls5.tacc.utexas.edu'),\n",
+ " ('stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b146-a201fb89bf12',\n",
+ " 'stampede.tacc.xsede.org')]"
+ ]
+ },
+ "execution_count": 4,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "airavata_cli.computer_resources().items()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 5,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>Id</th>\n",
+ " <th>Name</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-1716...</td>\n",
+ " <td>alamo.uthscsa.edu</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>Jureca_32098185-4396-4c11-afb7-26e991a03476</td>\n",
+ " <td>Jureca</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975e...</td>\n",
+ " <td>comet.sdsc.edu</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>gordon.sdsc.edu_f9363997-4614-477f-847e-79d262...</td>\n",
+ " <td>gordon.sdsc.edu</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
+ " <td>ls5.tacc.utexas.edu</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>5</th>\n",
+ " <td>stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b14...</td>\n",
+ " <td>stampede.tacc.xsede.org</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " Id Name\n",
+ "0 alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-1716... alamo.uthscsa.edu\n",
+ "1 Jureca_32098185-4396-4c11-afb7-26e991a03476 Jureca\n",
+ "2 comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975e... comet.sdsc.edu\n",
+ "3 gordon.sdsc.edu_f9363997-4614-477f-847e-79d262... gordon.sdsc.edu\n",
+ "4 ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa... ls5.tacc.utexas.edu\n",
+ "5 stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b14... stampede.tacc.xsede.org"
+ ]
+ },
+ "execution_count": 5,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "compute_resources = pd.DataFrame(list(airavata_cli.computer_resources().items()), columns=[\"Id\", \"Name\"])\n",
+ "compute_resources"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "## Some other custom functions which can be created"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 6,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[ApplicationInterfaceDescription(applicationName='Ultrascan', applicationInputs=[InputDataObjectType(userFriendlyDescription='Ultrascan HPC Input Tar File', name='Input_Tar_File', dataStaged=False, value='', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=3, inputOrder=1, metaData=''), InputDataObjectType(userFriendlyDescription='Batches for multi-wavelength data processing', name='Parallel_Group_Count', dataStaged=False, value='-mgroupcount=1', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=3, metaData=''), InputDataObjectType(userFriendlyDescription='Wall Clock Limit on the Compute Resource', name='Wall_Time', dataStaged=False, value='-walltime=60', applicationArgument='', isRequired=True, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=2, metaData='')], applicationInterfaceId='Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46
', applicationDescription='Ultrascan Version 3 Interface', applicationOutputs=[OutputDataObjectType(dataMovement=True, name='output', value='output/analysis-results.tar', applicationArgument='', isRequired=True, searchQuery='', location='output', requiredToAddedToCommandLine=False, outputStreaming=False, type=3), OutputDataObjectType(dataMovement=True, name='Ultrascan-Standard-Error', value='', applicationArgument='', isRequired=True, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=5), OutputDataObjectType(dataMovement=True, name='Ultrascan-Standard-Out', value='', applicationArgument='', isRequired=True, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=4)], applicationModules=['Ultrascan_82282f1e-284f-4999-9beb-4620c485b03d']),\n",
+ " ApplicationInterfaceDescription(applicationName='Ultrascan_Unicore', applicationInputs=[InputDataObjectType(userFriendlyDescription='', name='Input', dataStaged=False, value='', applicationArgument='', isRequired=True, standardInput=False, requiredToAddedToCommandLine=False, type=3, inputOrder=1, metaData=''), InputDataObjectType(userFriendlyDescription='', name='mgroupcount', dataStaged=False, value='-mgroupcount 1', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=2, metaData=''), InputDataObjectType(userFriendlyDescription='', name='US3INPUTARG', dataStaged=False, value='', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True, type=0, inputOrder=4, metaData=''), InputDataObjectType(userFriendlyDescription='', name='walltime', dataStaged=False, value='-walltime 60', applicationArgument='', isRequired=False, standardInput=False, requiredToAddedToCommandLine=True,
type=0, inputOrder=3, metaData='')], applicationInterfaceId='Ultrascan_Unicore_0e7f8522-6d75-41ba-8b09-0021e728679a', applicationDescription='Unicore Service', applicationOutputs=[OutputDataObjectType(dataMovement=True, name='Ultrascan-Unicore-Standard-Error', value='', applicationArgument='', isRequired=False, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=5), OutputDataObjectType(dataMovement=True, name='Ultrascan-Unicore-Standard-Out', value='', applicationArgument='', isRequired=False, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=4), OutputDataObjectType(dataMovement=True, name='US3OUT', value='analysis-results.tar', applicationArgument='', isRequired=True, searchQuery='', location='', requiredToAddedToCommandLine=False, outputStreaming=False, type=0)], applicationModules=['Ultrascan_Unicore_2471953d-5d87-4ffc-b0e6-b06c86c6206d'])]"
+ ]
+ },
+ "execution_count": 6,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "airavata_cli.list_of_applications('Ultrascan_Production')"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 7,
+ "metadata": {
+ "collapsed": false,
+ "scrolled": true
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "[ApplicationModule(appModuleName='Ultrascan', appModuleVersion='Ultrascan Application', appModuleId='Ultrascan_82282f1e-284f-4999-9beb-4620c485b03d', appModuleDescription=''),\n",
+ " ApplicationModule(appModuleName='Ultrascan_Unicore', appModuleVersion='', appModuleId='Ultrascan_Unicore_2471953d-5d87-4ffc-b0e6-b06c86c6206d', appModuleDescription='Ultrascan Unicore Application')]"
+ ]
+ },
+ "execution_count": 7,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "airavata_cli.module_descriptions('Ultrascan_Production') "
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": false
+ },
+ "source": [
+ "##Setting the time parameters"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 8,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "start= datetime(2015,7,16,15,10)\n",
+ "end= datetime(2016,7,17,11,59)\n",
+ "fromTime = calendar.timegm(start.timetuple())\n",
+ "toTime = calendar.timegm(end.timetuple())"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "## Getting the list of Experiments executed during the above mentioned period"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 9,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [],
+ "source": [
+ "ds=airavata_cli.experiment_statistics(\"Ultrascan_Production\", fromTime*1000, toTime*1000)\n",
+ "#ds"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 10,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "<div>\n",
+ "<table border=\"1\" class=\"dataframe\">\n",
+ " <thead>\n",
+ " <tr style=\"text-align: right;\">\n",
+ " <th></th>\n",
+ " <th>User Name</th>\n",
+ " <th>Name</th>\n",
+ " <th>Status Update</th>\n",
+ " <th>Resource Host ID</th>\n",
+ " <th>Project ID</th>\n",
+ " <th>Creation Time</th>\n",
+ " <th>Experiment ID</th>\n",
+ " <th>Execution ID</th>\n",
+ " <th>Gateway ID</th>\n",
+ " <th>Experiment Status</th>\n",
+ " </tr>\n",
+ " </thead>\n",
+ " <tbody>\n",
+ " <tr>\n",
+ " <th>0</th>\n",
+ " <td>Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...</td>\n",
+ " <td>US3-AIRA</td>\n",
+ " <td>None</td>\n",
+ " <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
+ " <td>Default_Project_4e1dede8-0925-47e6-b61c-966051...</td>\n",
+ " <td>1468618483000</td>\n",
+ " <td>US3-AIRA_36f4788f-240b-4119-aaed-18926be8165c</td>\n",
+ " <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
+ " <td>Ultrascan_Production</td>\n",
+ " <td>COMPLETED</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>1</th>\n",
+ " <td>Paul_Willard_098ba7b6-274c-9fb4-4915-f7ecc0c7cc1f</td>\n",
+ " <td>US3-AIRA</td>\n",
+ " <td>None</td>\n",
+ " <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
+ " <td>Default_Project_b884d629-32bf-4532-ae76-8366db...</td>\n",
+ " <td>1468616186000</td>\n",
+ " <td>US3-AIRA_408946e3-6104-48b3-a9dc-27ec03f45cb2</td>\n",
+ " <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
+ " <td>Ultrascan_Production</td>\n",
+ " <td>COMPLETED</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>2</th>\n",
+ " <td>Paul_Willard_098ba7b6-274c-9fb4-4915-f7ecc0c7cc1f</td>\n",
+ " <td>US3-AIRA</td>\n",
+ " <td>None</td>\n",
+ " <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
+ " <td>Default_Project_b884d629-32bf-4532-ae76-8366db...</td>\n",
+ " <td>1468615898000</td>\n",
+ " <td>US3-AIRA_270ed9fe-f0f9-4c00-936f-72c994cb2125</td>\n",
+ " <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
+ " <td>Ultrascan_Production</td>\n",
+ " <td>COMPLETED</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>3</th>\n",
+ " <td>Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...</td>\n",
+ " <td>US3-AIRA</td>\n",
+ " <td>None</td>\n",
+ " <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
+ " <td>Default_Project_4e1dede8-0925-47e6-b61c-966051...</td>\n",
+ " <td>1468612459000</td>\n",
+ " <td>US3-AIRA_c23effff-bf70-4d77-968a-5982919eb3a0</td>\n",
+ " <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
+ " <td>Ultrascan_Production</td>\n",
+ " <td>COMPLETED</td>\n",
+ " </tr>\n",
+ " <tr>\n",
+ " <th>4</th>\n",
+ " <td>Daniel_Krzizike_550162c5-88f4-5624-cd19-114778...</td>\n",
+ " <td>US3-AIRA</td>\n",
+ " <td>None</td>\n",
+ " <td>ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa...</td>\n",
+ " <td>Default_Project_4e1dede8-0925-47e6-b61c-966051...</td>\n",
+ " <td>1468612433000</td>\n",
+ " <td>US3-AIRA_2e65cd86-b4f2-4514-99c2-68c6cec880f4</td>\n",
+ " <td>Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46</td>\n",
+ " <td>Ultrascan_Production</td>\n",
+ " <td>COMPLETED</td>\n",
+ " </tr>\n",
+ " </tbody>\n",
+ "</table>\n",
+ "</div>"
+ ],
+ "text/plain": [
+ " User Name Name Status Update \\\n",
+ "0 Daniel_Krzizike_550162c5-88f4-5624-cd19-114778... US3-AIRA None \n",
+ "1 Paul_Willard_098ba7b6-274c-9fb4-4915-f7ecc0c7cc1f US3-AIRA None \n",
+ "2 Paul_Willard_098ba7b6-274c-9fb4-4915-f7ecc0c7cc1f US3-AIRA None \n",
+ "3 Daniel_Krzizike_550162c5-88f4-5624-cd19-114778... US3-AIRA None \n",
+ "4 Daniel_Krzizike_550162c5-88f4-5624-cd19-114778... US3-AIRA None \n",
+ "\n",
+ " Resource Host ID \\\n",
+ "0 ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa... \n",
+ "1 ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa... \n",
+ "2 ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa... \n",
+ "3 ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa... \n",
+ "4 ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aa... \n",
+ "\n",
+ " Project ID Creation Time \\\n",
+ "0 Default_Project_4e1dede8-0925-47e6-b61c-966051... 1468618483000 \n",
+ "1 Default_Project_b884d629-32bf-4532-ae76-8366db... 1468616186000 \n",
+ "2 Default_Project_b884d629-32bf-4532-ae76-8366db... 1468615898000 \n",
+ "3 Default_Project_4e1dede8-0925-47e6-b61c-966051... 1468612459000 \n",
+ "4 Default_Project_4e1dede8-0925-47e6-b61c-966051... 1468612433000 \n",
+ "\n",
+ " Experiment ID \\\n",
+ "0 US3-AIRA_36f4788f-240b-4119-aaed-18926be8165c \n",
+ "1 US3-AIRA_408946e3-6104-48b3-a9dc-27ec03f45cb2 \n",
+ "2 US3-AIRA_270ed9fe-f0f9-4c00-936f-72c994cb2125 \n",
+ "3 US3-AIRA_c23effff-bf70-4d77-968a-5982919eb3a0 \n",
+ "4 US3-AIRA_2e65cd86-b4f2-4514-99c2-68c6cec880f4 \n",
+ "\n",
+ " Execution ID Gateway ID \\\n",
+ "0 Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46 Ultrascan_Production \n",
+ "1 Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46 Ultrascan_Production \n",
+ "2 Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46 Ultrascan_Production \n",
+ "3 Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46 Ultrascan_Production \n",
+ "4 Ultrascan_0ed937f6-26af-4c54-8064-3be082411e46 Ultrascan_Production \n",
+ "\n",
+ " Experiment Status \n",
+ "0 COMPLETED \n",
+ "1 COMPLETED \n",
+ "2 COMPLETED \n",
+ "3 COMPLETED \n",
+ "4 COMPLETED "
+ ]
+ },
+ "execution_count": 10,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "All_Experiments = []\n",
+ "for i in ds.allExperiments:\n",
+ " All_Experiments.append([i.userName, i.name, i.statusUpdateTime, i.resourceHostId, i.projectId, i.creationTime, \n",
+ " i.experimentId, i.executionId, i.gatewayId, i.experimentStatus])\n",
+ "labels = [\"User Name\", \"Name\", \"Status Update\", \"Resource Host ID\", \"Project ID\", \"Creation Time\", \"Experiment ID\", \n",
+ " \"Execution ID\", \"Gateway ID\", \"Experiment Status\"]\n",
+ "df = pd.DataFrame(data=All_Experiments, columns=labels)\n",
+ "df.head()"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 11,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "text/plain": [
+ "(4124, 10)"
+ ]
+ },
+ "execution_count": 11,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "df.shape"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "## Calculating percentage use of resources"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 12,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "ls5_cn = sum([1 for x, row in df.iterrows() if row[3] == 'ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aad1f8310ecf' and row[9] == 'COMPLETED'])\n",
+ "stampede_cn = sum([1 for x, row in df.iterrows() if row[3] == 'stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b146-a201fb89bf12' and row[9] == 'COMPLETED'])\n",
+ "comet_cn = sum([1 for x, row in df.iterrows() if row[3] == 'comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975ee035b' and row[9] == 'COMPLETED'])\n",
+ "gordon_cn= sum([1 for x, row in df.iterrows() if row[3] == 'gordon.sdsc.edu_f9363997-4614-477f-847e-79d262ee8ef7' and row[9] == 'COMPLETED'])\n",
+ "#jureca_cn = sum([1 for x, row in df.iterrows() if row[3] == 'Jureca_32098185-4396-4c11-afb7-26e991a03476' and row[9] == 'COMPLETED'])\n",
+ "alamo_cn = sum([1 for x, row in df.iterrows() if row[3] == 'alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-17163b64ef29' and row[9] == 'COMPLETED'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 13,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAX8AAAD8CAYAAACfF6SlAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nqljrzgBQSg0GdgDXKqVilFLTrPU/ARKs9/4ZeKfAv
p4H0qxltwBDsK7UrfLHF8DbQE2gPzBDRJqd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\nX/NfIiJvAE8BvYGDmCfXFsq8
x3MCpVQ6cBdwl3UfZbGI/GTF0bDQ6g2tzwqQgXlSyVeniJgKHoed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\naZoWhnT
y1zRNC0M6+WuapoUhnfw1TdPCkE7+mqZpYUgnf03TtDCkk7+maVoY0slf0zQtDOnkr2ma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
6UhMjPyU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\nSqyyTxHLL1FKHRGRIHCVUuoLEZkPeIGeQEvgDaXU+SIyAWiulBo
uIk2BL4AmejA+Xfap9ESkCiID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\nJuFdtw7v00/z/B9/cI+IDFJKrbY7Nk1f+Y
ckEXGL2/04bvdqhgy5gFmzdOLXKqyWLeHVV4kaPZpz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\n+V5EqtsdU0Wkk38pE
JE6eDw/cd11ifztb5EY+rBqWllyOOC++3BffTXNPB6W674Ap09nqbMkInG4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\n
/FR1/6NHzZ9//AFLl5qtgwqaOdNsCZSXd3w/hgHZ2Wcfdyi57TZctWvT0enkTrtjCTU6mRVH5GZq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
L7wKf2EbfIHmhIR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\n7I6jLIVf8ocm1A2L3tua9idKQUqKedVu3Vw91mpm374T
SzNVq5qtZlq1aua86abz6NixI61btw6J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\ns2mhJSvrxFYzu3YR3L4dtWcPcui
QeVXu9TqDMTExqnbthpKQ0NRx8cXHSzNVqlSBClqaSU1NZcmS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\nBvmWACNE5E
2gBnAxcBdw7ukGGG7JPwO/Pw/QM3hpxyUkkFflnMBTKfsdVwHdrQcASgnp6cf+n2QC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
6i2Rl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\nx5yRY/lys8XO/PnH1xkwwEzchW8Ip6SYNfyoKMjOhpUrzXULmjkT7r
rLbBGU/43PMMgvKWhAt27k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\nBL/fgd8PmF//16amsjw11Vi7caOx/pNP+NLjy
TvicklGoY5w8fHxx3pJl1ZHuN9++42srKwczqKN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\na5CdAy+rMLkRGrbJH4Dc
3Fl8/nmQvDOdo1kLC4ZBVqc2zGXun8aR+ht3SQ7Vg3ea/Vu0CioHeBtU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\njVn
6mQo8CDwKvIY5A9M/Si/MchUARkJGBoxTSoXtfT6d/AtT6i127TrA99/bHYkWyoYNYzs7jG2c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
/3T4/aNZsWIv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\nZ0hJGc2oUX5WhP1cEeFnyhSIi4M+fQiMGWl8zueOLI5PEZt
OOnmYw7l9zMecx3l48BxbvotdHOQg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\nsrKS+PHHd7jppkyWL7c7JK2sJSeTbv
hZzeqz2k072tGNa1QvUP5SCi2UfAGcC5kr4GWrvn+23eW7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\nMxUVRbBxfOBDP
iy1Us04xomTc4IjQ6j555dAc8i4A9b/AdceVepSnfhDi77yr0BExIlh3EZExBN0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
v+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\n9Ph0a6QxcZCDvYc4VDjFqao06RMBwV976d0K/AU4orCXq6Hwl2vCzJJAI
3AryeRtpNMLyOWaCIIq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\nHFF0c1QGbCo5zm5373X3TqAvmu0N8Ia7H4v6LjYA
iwh3jrwZeM3M3gLuJ+y7mUU4PHVg8tmLJZ+1\nAvhB9PodhFcM2n90iKnZR2QUcvfDZtYCrAYeN7PthNvwAmBm9cDDhH0A58zseaB0Ft7AOv5Bye2B\n+xfKDSf8c9nq7l8sfcLM5nDhDWUM+Jy7H76EryaDRGf+IqOQmd0AZN3918DTQAth+/zAWftYoBvo\nMrMawvb9Szp0ye3bzWxq1GeylrCJ6HXgM2Y2I6pHlZnNJNwVcqqZTYve+4WS42wBvl1S97mX/k3l\nSunMX2R0ugV4yswCIAd8g7DNfrOZnYw6fP8GHAL+SRjcAy42BLD0uTeBX3C+w/d3AGb2ZWBD1M7v\nwLroSuQh4FUz6yGcpTywRvjjwDNm9nfCP5dWQKOAhpiGeorIZdNQzeufmn1ERGJIZ/4iIjGkM38R\nkRhS+IuIxJDCX0QkhhT+IiIxpPAXEYkhhb+ISAwp/EVEYkjhLyISQwp/EZEYUviLiMSQwl9EJIYU\n/iIiMaTwFxGJIYW/iEgMKfxFRGJI4S8iEkMKfxGRGFL4i4jEkMJfRCSGFP4iIjH0P6TMyHgAADaY\nAAAAAElFTkSuQmCC\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x946fba8>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "slices= [ls5_cn,stampede_cn,comet_cn,gordon_cn,alamo_cn]\n",
+ "cols = ['c','m','r','w','y']\n",
+ "Hosts= [\"lonestar\",\"stampede\",\"comet\",\"gordon\" , \"alamo\"]\n",
+ "plt.pie(slices,\n",
+ " labels= Hosts,\n",
+ " colors=cols,\n",
+ " startangle=90,\n",
+ " shadow= False,\n",
+ " autopct='%1.1f%%')\n",
+ "\n",
+ "plt.title('Percentage Use by Resources')\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "##Percentage failed by resources"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 14,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "ls5_fn = sum([1 for x, row in df.iterrows() if row[3] == 'ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aad1f8310ecf' and row[9] == 'FAILED'])\n",
+ "stampede_fn = sum([1 for x, row in df.iterrows() if row[3] == 'stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b146-a201fb89bf12' and row[9] == 'FAILED'])\n",
+ "comet_fn = sum([1 for x, row in df.iterrows() if row[3] == 'comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975ee035b' and row[9] == 'FAILED'])\n",
+ "gordon_fn= sum([1 for x, row in df.iterrows() if row[3] == 'gordon.sdsc.edu_f9363997-4614-477f-847e-79d262ee8ef7' and row[9] == 'FAILED'])\n",
+ "#jureca_fn = sum([1 for x, row in df.iterrows() if row[3] == 'Jureca_32098185-4396-4c11-afb7-26e991a03476' and row[9] == 'FAILED'])\n",
+ "alamo_fn = sum([1 for x, row in df.iterrows() if row[3] == 'alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-17163b64ef29' and row[9] == 'FAILED'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 15,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXIAAAD8CAYAAABq6S8VAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz\nAAALEgAACxIB0t1+/AAAIABJREFUeJzsnXl8E1X3h5+TtE2brmyCguyCgvgCAj8EFcUV911EXzZB\nEUFxhdcNFVFEfV1Q9AUVBQURBRdQwRXFhUVkB2WVXZG9TZvQ5Pz+mKmE2pYCaadJ7sMnn0xm7r1z\nZhq+c3PuueeKqmIwGAyG6MXltAEGg8FgODKMkBsMBkOUY4TcYDAYohwj5AaDwRDlGCE3GAyGKMcI\nucFgMEQ5RsgNjiMiR4nItyKyW0SeKkX5vSJS194eIyKPlrWN9rm6ich35XEug+FQMEJeDojIOhHx\nicgeEdlii4/XabvCEZG1ItLRodPfBPypqpmqes/BCqtquqquK3uzij59JBoRkW9EJNf+TvwpIu+L\nSPVItG2IP4yQlw8KXKiqGUBLoBXwwKE2IiLuSBtWQagDLCvvk4qIk99/Bfra34mGQBrwtIP2HEAM\nf9diEiPk5YcAqOoW4FPgRAARyRCRV0Vks4hsEJEhIiL2sW4iMktE/isifwGD7f29RWSZ3ZtbIiLN\n7f1Hi8h7dg9vtYj0//vkIoNFZKKIvGnXWywiLe1jY4HawMf2sbvt/e/avyB22j3IJmHtVRaRj213\nyGzb7u/Cjh8vIjNEZLuILBeRq4u8KSJjgG7AQPvcHUWktYj8YJ93k4iMEJGEsDohEalfRFv/cH2E\nl7V/CY0UkWkishc4Q0SSRORpEfndvtaRIuIp4e/osu3ZZf8NOtptXyUi8wqd+04RmVJCWwXfiT3A\nB0DzsLoiIoNEZJWIbBORd0Qkyz7mEZFxIvKXfY9mi0g1+9jRIvKhfd9/E5Fe4fc63A0lIh1EZEPY\n57Uicq+ILASyRcQlIrXsXwt/2na8EFa+p30PtovIp
yJSO+zYsyLyh/39WBj+3TFEHiPk5YyIHAtc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\n1gGmiEjB30awRLo61n2sBbwj
IplYv3zut+3Yoaq+QvadXIINhQn/mx4L/F7U98O273kReSbMPgVq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\niMhurPv
fxj5WA3gP2A0sxfK3v2Ufuw6oh3XP38calyhw6Y0DFgHrsMZaSryv9nfqYvt612P10K+x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
rCyoXNlN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\nYcECgjNnkrN5M0keDzOzs5kIfKqqW5220eA8pkce54hICtCJ1NT
uJCV1JDMzRKtWibRqlUzz5tYI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\nn54uP4vI5fa8gUjwPXCxvXxcGnARkA3sFJ
H2dpl/AzNLqH+dvX192P7vgGtFxCUi1YDTgDkRsjmq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\nCsKMGeg998C1PvhJS
5UjBbCCxe+DhBWQcg4MSIV1InJ2GZpqCMO4VsoJETkar/dNMjPbMXhwKo0b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\n
h8suK7vrWLgQ+vSBRjvKJzLlSGgEzAfvsXBXqrVMnNtpm6IJI+SHiIgcQ0rKPC68sCmPPZZCsknF\nHGs0a/bP3vb338N551nb550Hs2YVXVcVQqED97lcEAxa23l5lphPnAiXXw7uMpKrzz5DBw6ELj74\noRwjU46Eo4E5kHoidEmHD0TE5HIuJUbIDwERqUdy8s906VKLvn2TTLKr+GHXLqhc2dquXNn6XBQi\n1kzJPn1g6lRrX0oKtGkDvXtD1aqW62XFCspkSEUVRo9Gn38OedoPoyN/ijIlE/gGvB3grHT4RkQy\nnLYpGjA+8lIiIo1ITv6Bm26qxOWXGwWPc6SYPu6IEVCliiX0d98NdepYPfzOna0XwNNPQ48eMG0a\nzJsHDRrADTccuU2BADz2GDpvLvKpv+IMah4qycAHkHIztJgIc0SknarucNquiowRpFIgIsfj8fxI\n//5GxOOUSpVghy0lO3ZAVlbR5QqGS7Ky4LTTYHmhNedXrrTea9WCmTOtQdNNm6zXkVAQmbJwNqys\nQJEph4sbGA2eG6FeOnxreuYlY0TpIIhIAzyeHxgwoBIXXGDuVxwRHjfRrp01OAnWe1Fukbw8yM21\ntnNzYe5cqFfvwDJjxkDPnpCfv799lwv8/sO3c8MGuPFGyF2LbgsgNQ+/qQqFAM9C0jXQIB2+FBGv\n0zZVVIwwlYCI1CA5eRa33JLJ+edHxYCR4cgZMsTq3W7cCNdeC59+Cl26WG6Qrl1h/nzrM8D27fCf\n/1jbO3daa1z27g233mqJf+vW+9udNQsaN7Z87Glplkvlxhth3z6oX//wbF2wwMqZ0ngHuqGCR6Yc\nDgKMguRO0DQdPjUDoEUjJlyzaEQkk5SUOVx9dT169DD5IKKYpJ7X5/e9dHPCpZc6bUlk+ewz9Lnn\nkK5+GOW0MWVMPnAp5H4HM/fCxaqa77RNFQnTIy8CEUnG653B2WfXpnt3I+KGM
mPOHKuX/+9/w4QJ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\ngsWtK0FEXHi973D99R4j4oaKQEFkSuD32MqZUh7cANIB
jkq1fpAcESLSVUQWisgvIvKmiNQRkS9F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\nEHJEunL88Ykcd9zByxoMEcLvhwc
eQKd+ZEWm9HbaoDjkCiARGolI64MWjmJiXshFxE1y8iP06JHm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\nFlg+/4uBc8
PKfojlO68BZGKFI56EtTROs0hfRBlQGWhoBdzE1JT92FwlJz39atq3j6knrsE5/H54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
jIUJs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\nL+SZv8z1MINpTWunLSpT9rCHZSxjBSvsaJuNob38GfLhc+UQdLmw3D
b1rUFYV8EkqfpYbptojPW9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\ndl4eJCTAxIlw+eVGxCNBWhr73h7j/uuZ/2rfq
bcygNv1fM43fpZyJo002tj/bA5IR7OVrSxjmfzG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\nfAqGKCIhgeBzz7hybr6e
+3mAN3gjFCJUJqfqRCeGM/yAfeMZT0taMpaxtKQl4xlfZF0XLp7jOUYz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\n7Ng
UjjrqsOw0GCLOzJkkPzpczwidHrqDO9xJmJWtjpSZzGQ4w1f58B1/KBoRrRySa0VEnhKRxSKy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
s+7sXp0ZxCDG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\n73nAFYVsfS0sjffFB70+4yMvGUlKGkBGxlBefNFLjRpOm2M
wlJ61a/Hceleofm4NHuMxV2UqO23R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\nd9ocg+HQGTFCPZOnSV/66sVcXGESb3
3ER8GRjNztx3+aqkbNqi/2YOddqnqJI+c3Qn54iEhrPJ7p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\nJAzlsssS6dYty
US2GKKK7GwSb7k9mLFxt2sYw6Qh1ryJ7WznRV7M/YmfcvPI66WqUxy2NG4wQu4Q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
BQ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\n+/Ka0n5uWWsKuTx3y7dmXgS6gZ2Ew20kk22Ewy34/lY8rwnXrcfzotTUO
NTVuTQ2QlNTmObmOE1N\nURoaWF2JRDn4KwvK9+tXzv/7t0f/z5jyPeqVKK8c5+ctc3MF5uZc7t2zLCwYFhcj5PNxwCcaXSQS\nuU8oNIfv32Zp6TLWjgFjwHVr7cLzfl+leinksmEZYxLAC8DWh1Ys9hKx2HZCoW34/lasTQBmdVlr\nHvOa5fPQ6nn5NYRCLpHIfYyZxdq/cd2/KBTuALPAzCPHWWtt7vm8AyJPRiEXEQk47RcTEQk4hVxE\nJOAUchGRgFPIRUQCTiEXEQk4hVxEJOAUchGRgFPIRUQCTiEXEQk4hVxEJOAUchGRgFPIRUQCTiEX\nEQk4hVxEJOAUchGRgFPIRUQCTiEXEQk4hVxEJOAUchGRgFPIRUQCTiEXEQk4hVxEJOAUchGRgFPI\nRUQCTiEXEQk4hVxEJOAUchGRgFPIRUQC7h/zJtHE2H36aAAAAABJRU5ErkJggg==\n",
+ "text/plain": [
+ "<matplotlib.figure.Figure at 0x97d1c88>"
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "slices= [ls5_fn,stampede_fn,comet_fn,gordon_fn,alamo_fn]\n",
+ "cols = ['c','m','r','w','y']\n",
+ "Hosts= [\"lonestar\",\"stampede\",\"comet\",\"gordon\" , \"alamo\"]\n",
+ "plt.pie(slices,\n",
+ " labels= Hosts,\n",
+ " colors=cols,\n",
+ " startangle=90,\n",
+ " shadow= False,\n",
+ " autopct='%1.1f%%')\n",
+ "\n",
+ "plt.title('Percentage failure by Resources')\n",
+ "plt.show()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {
+ "collapsed": true
+ },
+ "source": [
+ "## Percentage cancelled by resources"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 16,
+ "metadata": {
+ "collapsed": true
+ },
+ "outputs": [],
+ "source": [
+ "ls5_xn = sum([1 for x, row in df.iterrows() if row[3] == 'ls5.tacc.utexas.edu_6dd67b08-30e5-4f74-bdd6-aad1f8310ecf' and row[9] == 'CANCELED'])\n",
+ "stampede_xn = sum([1 for x, row in df.iterrows() if row[3] == 'stampede.tacc.xsede.org_bf7958ae-f9d4-468b-b146-a201fb89bf12' and row[9] == 'CANCELED'])\n",
+ "comet_xn = sum([1 for x, row in df.iterrows() if row[3] == 'comet.sdsc.edu_f24b0bba-5230-498d-97e2-46a975ee035b' and row[9] == 'CANCELED'])\n",
+ "gordon_xn= sum([1 for x, row in df.iterrows() if row[3] == 'gordon.sdsc.edu_f9363997-4614-477f-847e-79d262ee8ef7' and row[9] == 'CANCELED'])\n",
+ "#jureca_xn = sum([1 for x, row in df.iterrows() if row[3] == 'Jureca_32098185-4396-4c11-afb7-26e991a03476' and row[9] == 'CANCELED'])\n",
+ "alamo_xn = sum([1 for x, row in df.iterrows() if row[3] == 'alamo.uthscsa.edu_4793b5cc-b991-4e43-b82d-17163b64ef29' and row[9] == 'CANCELED'])"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 17,
+ "metadata": {
+ "collapsed": false
+ },
+ "outputs": [
+ {
+ "data": {
+ "image/png": "iVBORw0KGgoAAAANSUhEUgAAAXcAAAD8CAYAAACMwORRAAAABHNCSVQICAgIfAhkiAAAAAlwSFlz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\nkWtEZIsV3z4RGZuP90ArKKWUfpzjA9gNXG49rwNsB
h6xfn8fmAU4gSrAd8BQa91gIB0YgflF6wD6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\nFHjHWlcX6C8i3QPitmMWGpJF
5HrMUvUCEVkD3KuU2mnFEngOezA/n9XzcV6Q/Wd1Vzbb5fT5WGT9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\n9Rh5vae
PYr5HuzHrtPNKyAqz8fYnzCuQlcCCgNfbby1XSqk1eRwrq+eAriLSzDpOT2AC5lXWHsz3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
DDQlLKwF\nLldbMjIaY7NVpmrVZOrXF+LjPdSrZ1C3LsTEQFhYZLDjzk14ONSsaT4ChFkPwLwSOHECzx9/kLBn\nDwm7d9Pjl19I2bsX4+RJnJGR8ocIW5OSWOv3swXYDGxXSvlK9my08kInd63QRMQDdCAs7ApcrktI\nT0/Abo+iWrVk6tc3rCQu1KsHtWqB3V4h2DEXF8OASpXMx3nnAQHJ3+uFffuI3bOH2D17uPqXX0j8\n9VeMkyexV6woW5KT+Swjg6+B75VSh4J4GloI0cldyzcRcQMXYbdficvVDbu9EfXqpXDhhR6aNLFR\nrx7UqAE2W8gm8cJwOiE+3nxg9lCrAHDiBGzbRputW2m1fj3Dd+7E6fHIccPgu8REVgHfARuUUmnB\ni14rq3Ry13IkIk7MZH45LlcP7PbGxMZ6ad/eTevWdpo2BZcrLM8DadmqWBHat4f27bEBFfx+2LeP\nalu30mPTJq7euJG0Q4dwVKgga0+d4h3gY2CH7rmj5YduUNVOs3quXIjNdgVudzdSUpoRE2Mm8/PP\nt9O8ObhcwQ6zwM61QTWYTp2Cdevgm29I+e47VHo6ycB/U1JYDqxSSp0Idow5EZHdQBul1NFgx1Ie\n6ZJ7OSciVYDeREYOwW5vQ61aXi680EWbNmE0awYeT8G7p2hFJjISOnWCTp1wKQV79uBeu5abv/qK\nXtu346xQQXYkJ/Ouz8cKzCqc0lRaK02xlDs6uZdDIlIVM6HfSnh4K9q2zeDqqz20aQMRETqZl1Ii\nUK8e1KuH9OtHhdRU2LiR5t9/T6PPP2d8WhonwsNlYXo6byiltpZsbPI+EAM4geeUUvMAyWM9InIK\nmA1cA/wBPAQ8AdQB7lZKfWBdUc4G2gLpwL1KqS9K6NTKLF0tU06ISDTQl8jIW0lNbcUFF6Rz1VUR\nXHih2eIXwspytUx+KQXbt8Nnn5H26adk+P0c9nqZ7/OxRCn1a3G
/vohEKaWOW+00a4FOwE9Y1TLZ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\n91JIRGwYxhDCw6cSG+villsiufBCs4+bVm
A6uZ+bw4fhtddOJ/k5VpI/HOy4tNzp5F7KiMgluN3z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\nBi7XD7RrdzkvvOChY
sVgh6RpZY5hwODBhD36KJVcLj4WkeuCHVOo0Mm9EESkOU7nz/Trl8C//+3S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\n
fvzRTIQ33VQ0cZcmLVvC/ffjefxxPhSRxkqpAnwllh+65G4RkT44nXcwZYonJK9ptaDz+czEftVV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
aQQbrcbN4rIOKXU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\n/Bs3onbtwhYebqhq1ar6W7a8yDZxYlf69u1LdHR0mRzK
o3v37s7ly5f3h9CfrSk0k7vH04sOHXQv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\n5Dt37uT6669HRFBKsWvXLqZMmcK
YMWNOb/PUU0/xxhtvICKkp6ezbds2jhw5QkZGBr179+bEiRP8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\njqV9+/YlEn
9hVa5cGa/X686h90qulFI/WlUxG4GDwM/ACWAw8LKIuIBdwJDMXbIc4m5gsYjcBywP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
xyFjG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\nTZ48WU2bNu0Zr9c7LtixFJdQS+5h2GxJrFwZRjZ31GlanvbtwzH8Hn
9MUhTTmGZUo9o/NvHj50M+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\nd4MI3HcfHD4MCxfC3r0wezYkJGS/7w03gMcDh
gF2u7ktwJw58P33EB8PDzxgLvv0Uzh5Evr0KZHT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\nw8fGXTzCUmJUPHAV+D4m96ScX2Ie
<TRUNCATED>