Example #1
0
def getAddress(id):
    persons = session.query(Person).all()
    intendedPerson = {}
    #intendedPerson;
    for person in persons:
        if (person.id == id):
            intendedPerson = person
            break
    address = session.query(Address).filter_by(
        person_id=intendedPerson.id).first()
    print(address.street_name + ' ' + address.street_number)
    lattitude, longitude = getLatLong(address.street_name +
                                      address.street_number)
    return longitude
Example #2
0
def getAddresses(coor, location, descrip, mapDistance):
	HaveAddress = False
	stopAfter = 5
	iterator = 0
	addressList = []
	businnesCoorList = []
	text = ""
	link = "http://www.yelp.com/search?find_desc=" + str(descrip) + "&find_loc=" + str(location) + "&ns=1&ls=ba0120fc3b21754c"

	while not HaveAddress:
		r = requests.get(link)
		text =  r.text
		#print 'requests.status_code:', r.status_code
		#print '<address> in text:', '<address>' in text
		HaveAddress = '<address>' in text
		iterator = iterator + 1
		if "We've found multiple locations matching your search" in text:
			#print "BE MORE SPECIFIC IN YOUR LOCATION"
			if iterator == stopAfter:
				break

	places = [m.start() for m in re.finditer('<address>', text)]
	#print places


	for place in places:
		#print place
		address = find_between(text[int(place)::], "address", "</address>" )
		address = address.replace("<br>", " ");
		addressList.append(address)




	for address in addressList:
		#print address
		lat = coor[0]
		lng = coor[1]
		currentLatLong = getLatLong.getLatLong(address)
		#print currentLatLong
		if lat - mapDistance < float(currentLatLong[0]) < lat + mapDistance and lng - mapDistance < float(currentLatLong[1]) < lng + mapDistance:
			#print "BUSINESS HERE!"
			businnesCoorList.append(currentLatLong)

	return businnesCoorList
Example #3
0
def processData():
	app.races = []
	app.genders = []
	app.ages = []
	app.acsCodes = []
	allTractsLatLng = []

	app.debug = True
	app.vars = {}
	app.city = []
	app.cityID = ""
	app.races = []
	app.genders = []
	app.ages = []
	app.keys = []
	app.maritalcodes = []
	app.languagecodes = []
	app.incomecodes = []
	app.educationcodes = []
	app.gendercodes = []
	incomedata = []
	maritaldata = []
	languagedata = []
	educationdata = []
	tractAndPop = {}
	blockAndPop = {}

	#A dictionary keyed to Fips that contains a duple of LatLong and then the value for the requested demographic
	listofFips = []
	listofValues = []
	listofAcsValues = []
	listofShades = []
	listofAcsValueShades = []
	listofValueShades = []
	FipsPixelDict = {}
	MegaDict = {}
	ValueDict = {}
	AcsDict = {}
	acstypes = []



	displayingSomething = False

	raceNumbers = {'race AfricanAmerican': 0,'race White' : 1, 'race Latino':2, 'race Asian':3, 'race Hawaiian':4, 'race Other':5,'race NativeAmerican':6,'race Multiracial':7}
	genderNumbers = {'gender Male': 0, 'gender Female': 1}
	ageNumbers = {'age 0':0, 'age 20':1, 'age 30':2, 'age 40':3, 'age 50':4,'age 60':5,'age 70':6,'age 80':7}
	listofRace = []
	listofGenders = []
	listofAges = []

	
	#Get race data
	data = ['race AfricanAmerican','race White', 'race Latino', 'race Asian', 'race Hawaiian', 'race Other','race NativeAmerican','race Multiracial', 'gender Male', 'gender Female', 'age 0', 'age 20', 'age 30', 'age 40', 'age 50','age 60','age 70','age 80']
	data_acs = {('widowed','divorced', 'married', 'nevermarried') : 'marital', ('spanish-notAtAll', 'spanish-notWell','spanish-veryWell', 'asian-notAtAll','asian-notWell', 'asian-veryWell') : 'language', ('less-10', '10to15', '15to20', '20to25', '25to30', '30to35', '35to40', '40to45', '45to50', '50to60', '60to75', '75to100', '100to125', '125to150', '150to200', '200more') : 'income', ('noschool', '12nodiplomaschool','hsgraduateschool', 'somecollegeschool', 'associatesschool', 'bachelorschool', 'mastersschool', 'professionalschool', 'doctorateschool') : 'education'}
	acskeys = data_acs.keys()
	acstypes = []
	#data_display = ['density', 'total']

	for i in range(0, len(data)): 
		app.vars[data[i]] = request.form.get(data[i])

	for i in range(0, len(acskeys)): 
		for j in range(0, len(acskeys[i])):
			lookup = acskeys[i][j]
			if request.form.get(lookup) == 'True':
				app.vars['acs-' + lookup] = request.form.get(lookup), data_acs[acskeys[i]]
				if data_acs[acskeys[i]] not in acstypes:
					acstypes.append(data_acs[acskeys[i]])
			else:
				app.vars['acs-' + lookup] = request.form.get(lookup)

	#app.vars['density'] = request.form.get('density')


	#From name of city requested, get Latitude and Longitude
	latAndLong = getLatLong.getLatLong(str(request.form.get('city')))
	lat = latAndLong[0]
	lng = latAndLong[1]

	#Get list of tracts from that latitude, longitude

	#Note - cast as a string!
	app.cityID = str(getfips.getfips(lat, lng))
	
	#Bool = "true" if app.vars['density'] == 'True' else "false"
	Bool = "false"
	#add each demographic to the corresponding variable list (race, gender and age)
	for demographic in app.vars:
		if "True" in str(app.vars[demographic]):
			data = True
			if "race" in demographic:
				app.races.append(demographic)
			if "gender" in demographic:
				app.genders.append(demographic)
			if "age" in demographic:
				app.ages.append(demographic)
			if "acs" in demographic or "gender" in demographic:
				#Gets acs checked data as well as requested gender
				value = str(app.vars[demographic])
				if 'income' in value:
					app.incomecodes.append(demographic)
				if 'marital' in value:
					app.maritalcodes.append(demographic)
				if 'education' in value:
					app.educationcodes.append(demographic)
				if 'language' in value:
					app.languagecodes.append(demographic)

	# "Remember" race, gender and age numerically in order to pass to new.html
	for race in app.races:
		listofRace.append(raceNumbers[race])
	for gender in app.genders:
		listofGenders.append(genderNumbers[gender])
	for age in app.ages:
		listofAges.append(ageNumbers[age])


	#Print list of demographics for debugging (City should be listed first
	for race in app.races:
		for gender in app.genders:
			for age in app.ages:
				app.keys.append(codes_data.getCodes(codeLookup[race], codeLookup[gender], codeLookup[age]))
	

	newKeys = [val for subl in app.keys for val in subl]
	newKeys.insert(0,"P0010001")

	allTracts, tractAndPop = censusTracts.listTracts(app.cityID)
	#tract = app.cityID
	#For all the tracts in the specified city (county area), sum the number of people in the specified codes
	#Last paramter is 1, so that we get tract data (in the county)

	allTractsLatLng = fromFIPSlisttoLatLong.getLatLngFromFIPS(allTracts)

	iterator = 0
	length = len(allTracts)
	mapDistance = 1.5 / length


	while not displayingSomething:

		for tract in allTracts:
			#Get lat long of tract
			z = 16
			

			if tract is app.cityID or (lat - mapDistance < float(allTractsLatLng[iterator][0]) < lat + mapDistance and lng - mapDistance < float(allTractsLatLng[iterator][1]) < lng + mapDistance):
				displayingSomething = True
				#Get ACS data
				if len(acstypes) > 0:
					if 'income' in acstypes:
						incomedata = getACS.getACSdata(tract, app.incomecodes + app.genders)
					if 'marital' in acstypes:
						maritaldata = getACS.getACSdata(tract, app.maritalcodes + app.genders)
					if 'language' in acstypes:
						languagedata = getACS.getACSdata(tract, app.languagecodes + app.genders)
					if 'education' in acstypes:
						educationdata = getACS.getACSdata(tract, app.educationcodes + app.genders)

				data, tempBlockAndPop = newGetPopDict.getpop(newKeys, tract, 2)
				#Add dictionary of blocks with total population to dictionary block adn Pop

				#JUST ADDED
				def sum_acs(ACSdata):
					acsSum = 0
					for element in ACSdata[1][int(blockGroupIndex)-1]:
							acsSum = acsSum + int(element)
					grouppop = ACSdata[2][int(blockGroupIndex) -1]
					blockpop = tempBlockAndPop[blockFIPS]
					if int(grouppop) == 0:
						newacs = 0
					else:
						newacs = int(acsSum * (float(blockpop) / float(grouppop)))
					return newacs
				
				#For every block in the current tract, get lat and long
				for item in data:
					blockFIPS = tract[0:11] +  item

					if blockFIPS not in listofFips:
						blockGroupIndex = blockFIPS[11:12]
						listofFips.append(blockFIPS)
						try: 
							AcsDict[int(blockFIPS)] = {}
							if 'income' in acstypes:
								AcsDict[int(blockFIPS)][0] = int(sum_acs(incomedata))
							if 'marital' in acstypes:
								AcsDict[int(blockFIPS)][1] = int(sum_acs(maritaldata))
							if 'language' in acstypes:
								AcsDict[int(blockFIPS)][2] = int(sum_acs(languagedata))
							if 'education' in acstypes:
								AcsDict[int(blockFIPS)][3] = int(sum_acs(educationdata))
							
						except NameError: 
							pass	
						ValueDict[int(blockFIPS)] = {}
						ValueDict[int(blockFIPS)][0] = data[item]
						ValueDict[int(blockFIPS)][1] = tempBlockAndPop[blockFIPS]

				#Clear app.vars so subsequent queries can occur
				app.vars = {}
				#Get coordinates from FIPS codes
				
				d2 = fromFIPStoPixels.getLatLngFromFIPS(listofFips, z)
				for k, v in d2.iteritems():
					if FipsPixelDict.has_key(k) == False: 
						FipsPixelDict[k] = v
					elif FipsPixelDict.has_key(k) == True:
						FipsPixelDict[k] += v
				#Load html
					
			iterator = iterator + 1

		mapDistance = mapDistance + 0.01
		iterator = 0

			#print FipsPixelDict
	for k,v in FipsPixelDict.iteritems():
		intermediate =  pixelcoordinates.getblockcoor(v, k[0], k[1], z)
		if len(intermediate.keys()) > 1:
			for k2, v2 in intermediate.iteritems():
				MegaDict[k2] = v2
		else:
			k2 = intermediate.keys()[0]
			v2 = intermediate.values()[0]
			MegaDict[k2] = v2

	#Iterate through listofValues and listofAcsValues to convert them to a shadeValue

	for key, value in ValueDict.iteritems():
		#value2 = TotalDict[key]
		if len(AcsDict.values()) > 0:
			MegaDict[key] = [MegaDict[key], ValueDict[key], AcsDict[key], 0]
		else:
			MegaDict[key] = [MegaDict[key], ValueDict[key], 0]
			
	businesses = []
	if len(request.form.get('business')) is not 0:
		businesses = scrapeYelp.getAddresses([lat, lng], request.form.get('city'), request.form.get('business'), mapDistance)
		#print businesses

	# with open('megaDict.txt', 'wb') as handle:
 #  		pickle.dump(MegaDict, handle)
 #  	with open('latLngZ.txt', 'wb') as handle:
 #  		pickle.dump([lat, lng, z], handle)
 #  	with open('businesses.txt', 'wb') as handle:
 #  		pickle.dump(businesses, handle)


 	defaultValues = "false"
 	fromMain = "false"
	return render_template("new.html", data = MegaDict, lat = lat, lng = lng, z = z, yelpData = businesses, density = Bool, defaultValues = defaultValues, fromMain = fromMain, listofRace = listofRace, listofGenders = listofGenders, listofAges = listofAges)