John DeBovis debovis

## energyProfile.json
{
    "lastAccess": 1344369242137,
    "cookie": {
        "originalMaxAge": 14459999,
        "expires": "2012-08-07T23:55:01.331Z",
        "httpOnly": true,
        "path": "/"
    },
    "gaas": {
        "roles": [

## va.json
{
    "id": 2,
    "slug": "va",
    "sites": [
        {
            "id": 21,
            "parentSlug": null,
            "name": "2011 Crystal Drive",
            "slug": "nnn",
            "status": 2,

## nes.txt
{
  "data": [
    {
      "date": "05/09/2012",
      "nes": {
        "Feeding": 1,
        "Sendgrid": 1,
        "AIDE": 1,
        "Our Local Foods": 1,
        "CPR": 3,

## werkzeugProfiler.py
from werkzeug.contrib.profiler import ProfilerMiddleware

app.config['PROFILE'] = True
app.wsgi_app = ProfilerMiddleware(app.wsgi_app, restrictions=[30])
app.run( host='0.0.0.0', port=8081, threaded=True, debug=debug )

## jsonresponse.py
json_headers = {'Content-type': 'application/json', 'Accept': 'text/plain'}
res = Response(headers=json_headers)
res.set_data(data)
res.status_code = 400
raise abort(res)

## Angular-Material-Muppet-App.markdown

      
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                debovis
                / Angular-Material-Muppet-App.markdown
            
            
              Created
              February 13, 2015 01:03
            
              
                Angular Material Muppet App
              
          
    Angular Material Muppet App

The goal of this app is to show basic Angular.js Material Design components in action together. It can also be used as a starting point if you're looking to try things out.
Forked from Marcy Sutton's Pen Angular Material Basic App.
Forked from Marcy Sutton's Pen Angular Material Basic App.
Forked from Marcy Sutton's Pen Angular Material Basic App.

  
## show_logging.py
import logging
print logging.Logger.manager.loggerDict

## tagged_data.csv

          
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            1

            
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## see_flask_routes.py
with app.app_context():
    output = []
    for rule in app.url_map.iter_rules():
        methods = ','.join(rule.methods)
        line = urllib.unquote("{:50s} {:20s} {}".format(rule.endpoint, methods, rule))
        output.append(line)

    for line in sorted(output):
        print line

## ts_classifer.py
from sklearn.metrics import classification_report
import matplotlib.pylab as plt
import numpy as np

class ts_classifier(object):


    def __init__(self,plotter=False):
        '''
        preds is a list of predictions that will be made.
	{
	"lastAccess": 1344369242137,
	"cookie": {
	"originalMaxAge": 14459999,
	"expires": "2012-08-07T23:55:01.331Z",
	"httpOnly": true,
	"path": "/"
	},
	"gaas": {
	"roles": [
	{
	"id": 2,
	"slug": "va",
	"sites": [
	{
	"id": 21,
	"parentSlug": null,
	"name": "2011 Crystal Drive",
	"slug": "nnn",
	"status": 2,
	{
	"data": [
	{
	"date": "05/09/2012",
	"nes": {
	"Feeding": 1,
	"Sendgrid": 1,
	"AIDE": 1,
	"Our Local Foods": 1,
	"CPR": 3,
	from werkzeug.contrib.profiler import ProfilerMiddleware

	app.config['PROFILE'] = True
	app.wsgi_app = ProfilerMiddleware(app.wsgi_app, restrictions=[30])
	app.run( host='0.0.0.0', port=8081, threaded=True, debug=debug )
	json_headers = {'Content-type': 'application/json', 'Accept': 'text/plain'}
	res = Response(headers=json_headers)
	res.set_data(data)
	res.status_code = 400
	raise abort(res)
	111464203307_10153923391928308	1
	111464203307_10153905709378308	1
	111464203307_10153905658238308	1
	111464203307_10153975624618308	1
	357425591250_10153811029651251	0
	357425591250_10153730759216251	0
	357425591250_10153776969171251	0
	521013254686171_878357745618385	0
	521013254686171_882051175249042	0
	521013254686171_874585225995637	0
	with app.app_context():
	output = []
	for rule in app.url_map.iter_rules():
	methods = ','.join(rule.methods)
	line = urllib.unquote("{:50s} {:20s} {}".format(rule.endpoint, methods, rule))
	output.append(line)

	for line in sorted(output):
	print line
	from sklearn.metrics import classification_report
	import matplotlib.pylab as plt
	import numpy as np

	class ts_classifier(object):


	def __init__(self,plotter=False):
	'''
	preds is a list of predictions that will be made.