def hifld_national():
#['VAL_DATE', 'NAICS_DESC', 'COUNTRY', 'NAICS_CODE', 'UNITS', 'RevGeoFlag', 'SOURCEDATE', 'MHPID', 'WEBSITE', 'VAL_METHOD', 'SOURCE', 'ZIP4', 'STATUS', 'COUNTYFIPS', 'ZIP', '\xef\xbb\xbfX', 'LONGITUDE', 'COUNTY', 'STATE', 'FID', 'Y', 'SIZE', 'CITY', 'YEARBLT', 'NAME', 'ADDRESS2', 'TELEPHONE', 'ADDRESS', 'LATITUDE', 'TYPE']
payload = tpcsv.open_source_csv('source_files/HIFLD_Mobile_Home_Parks.csv')
data = payload[0]
headers = payload[1]
parks = []
for park in data:
if park['NAICS_CODE'] == '721211':
continue
else:
address = park['ADDRESS']
county = park['COUNTY']
state = park['STATE']
zipcode = park['ZIP']
name = park['NAME']
city = park['CITY']
total_lots = park['UNITS']
phone_number = park['TELEPHONE']
website = park['WEBSITE']
info_list = [
str("total_lots:" + total_lots),
str("phone_number:" + phone_number),
str("zipcode:" + zipcode),
str("website:" + website)
]
info = "\n".join(info_list)
geo_location = str(park['LATITUDE']) + ", " + str(park['LONGITUDE'])
information = db.apply_schema(
park_name = name,
park_county = county,
park_address = address,
city = city,
park_info = info,
other_contact_info = phone_number,
geo_location = geo_location,
state = state,
total_lots = total_lots
)
park_a = [information]
parks.append(information)
print " :: {} :: {}".format(information['park_name'], information['geo_location'])
tpcsv.write_source_csv(park_a, "pa_complete.csv")
return parks
def mh_village_PA():
#ID,Name,Address,City,State,Zip,County,"Site Count","Average Monthly Rent","Phone Number","Vacant Sites"
payload = tpcsv.open_source_csv('source_files/PACommunityReport.csv')
data = payload[0]
headers = payload[1]
parks = []
for park in data:
address = park['Address']
county = park['County']
state = park['State']
zipcode = park['Zip']
name = park['Name']
city = park['City']
total_lots = park['Site Count']
avg_rent = park['Average Monthly Rent']
phone_number = park['Phone Number']
vacant_lots = park['Vacant Sites']
info_list = [
str("total_lots:" + total_lots),
str("avg_rent:" + avg_rent),
str("phone_number:" + phone_number),
str("vacant_lots:" + vacant_lots),
str("zipcode:" + zipcode),
]
info = "\n".join(info_list)
geo_location = get_park_geolocation(address, county, state, zipcode)
information = db.apply_schema(
park_name = name,
park_county = county,
park_address = address,
city = city,
park_info = info,
other_contact_info = phone_number,
geo_location = geo_location,
state = state,
total_lots = total_lots
)
park_a = [information]
parks.append(information)
print " :: {} :: {}".format(information['park_name'], information['geo_location'])
tpcsv.write_source_csv(park_a, "pa_complete.csv")
return parks
def get_county_parks(links_array):
base_url = 'http://www.in.gov'
counties = links_array
all_parks = []
index = 1
for count, county_link in enumerate(counties):
county_parks = []
num_counties = len(counties)
print "processing {} of {} counties".format(count + index, num_counties)
br.open(county_link)
soup = BeautifulSoup(br.response().read(), "html.parser")
main_html = soup.find('div', {"id" : "col2content"})
county_name_html = soup.find('div', {"id" : "col2"})
county_parks_html = main_html.find_all("div", style="PADDING-BOTTOM: 0px; PADDING-TOP: 0.5em; PADDING-LEFT: 2em; MARGIN-TOP: 0px; PADDING-RIGHT: 0px")
for park in county_parks_html:
information = {}
park = BeautifulSoup(str(park), "html.parser")
park_name = get_park_name(park)
park_county_name = get_park_county_name(county_name_html)
park_address = get_park_address(park)
park_info = get_park_info(park)
park_features = get_park_features(park)
park_ownerinfo = get_park_ownerinfo(park)
park_managerinfo = get_park_managerinfo(park)
park_geolocation = get_park_geolocation(park_address, park_county_name)
information = db.apply_schema(
park_name = park_name,
park_county = park_county_name,
park_address = park_address,
park_info = park_info,
owner_info = park_ownerinfo,
other_contact_info = park_managerinfo,
geo_location = park_geolocation,
state = 'IN',
total_lots = park_features['total_lots'],
water = park_features['water'],
waste = park_features['waste']
)
county_parks.append(information)
all_parks.append(information)
print " :: {} :: {}".format(information['park_name'], information['geo_location'])
try:
tpcsv.write_source_csv(county_parks, "indiana-test.csv")
except:
print "Error :: could not write {} county".format(park_county_name)
continue
return all_parks
#!/usr/bin/env python
import tpcsv
import tpkml
import data as db
source_file = "ingestion/StClaire.kml"
dest_file = "ingestion/StClaire.csv"
kmlobj = tpkml.kml(source_file)
headers = kmlobj.headers()
layer = kmlobj.layers()
data = kmlobj.data()
for i in data:
print "{} \n\n".format(i)
tpcsv.write_source_csv(data, dest_file, headers)
