from bs4 import BeautifulSoup
import json
import datetime
import pytz

# The URL for the page where the parking lots are listed
data_url = "http://example.com"

# Name of the city, just in case it contains umlauts which this filename shouldn't
city_name = "Sample City"

# Name of this file (without '.py'), sorry for needing this, but it makes things easier
file_name = "Sample_City"


def parse_html(html):
    soup = BeautifulSoup(html)

    # Do everything necessary to scrape the contents of the html
    # into a dictionary of the format specified by the schema.


def get_geodata_for_lot(lot_name):
    geofile = open("./cities/" + file_name + ".geojson")
    geodata = geofile.read()
    geofile.close()
    geodata = json.loads(geodata)

    for feature in geodata["features"]:
        if feature["properties"]["name"] == lot_name:
            return {
                "lon": feature["geometry"]["coordinates"][0],
                "lat": feature["geometry"]["coordinates"][1]
            }
    return []


if __name__ == "__main__":
    file = open("../tests/sample_city.html")
    html_data = file.read()
    file.close()
    parse_html(html_data)

from bs4 import BeautifulSoup
import datetime
import pytz
from geodata import GeoData

# The URL for the page where the parking lots are listed
data_url = "http://example.com"

# Name of the city, just in case it contains umlauts which this filename shouldn't
city_name = "Sample City"

# Name of this file (without '.py'), sorry for needing this, but it makes things easier
file_name = "Sample_City"

# Uncomment the following line if there's geodata in the format of Sample_City.geodata in this directory
# geodata = GeoData(city_name)

def parse_html(html):
    soup = BeautifulSoup(html)

    # Do everything necessary to scrape the contents of the html
    # into a dictionary of the format specified by the schema.

    data = {
        "last_updated": "",
        "lots": []
    }

    print(data)
    return data

# the following is for testing this out, just delete it all when done
if __name__ == "__main__":
    with open("../tests/sample_city.html") as f:
        parse_html(f.read())

Clean up sample city file
Clean up sample city file

  from bs4 import BeautifulSoup
- import json
  import datetime
  import pytz
+ from geodata import GeoData
  
  # The URL for the page where the parking lots are listed
  data_url = "http://example.com"
  
  # Name of the city, just in case it contains umlauts which this filename shouldn't
  city_name = "Sample City"
  
  # Name of this file (without '.py'), sorry for needing this, but it makes things easier
  file_name = "Sample_City"
  
+ # Uncomment the following line if there's geodata in the format of Sample_City.geodata in this directory
+ # geodata = GeoData(city_name)
  
  def parse_html(html):
      soup = BeautifulSoup(html)
  
      # Do everything necessary to scrape the contents of the html
      # into a dictionary of the format specified by the schema.
  
+     data = {
+         "last_updated": "",
+         "lots": []
+     }
  
+     print(data)
+     return data
- def get_geodata_for_lot(lot_name):
-     geofile = open("./cities/" + file_name + ".geojson")
-     geodata = geofile.read()
-     geofile.close()
-     geodata = json.loads(geodata)
  
+ # the following is for testing this out, just delete it all when done
+ if __name__ == "__main__":
+     with open("../tests/sample_city.html") as f:
+         parse_html(f.read())
-     for feature in geodata["features"]:
-         if feature["properties"]["name"] == lot_name:
-             return {
-                 "lon": feature["geometry"]["coordinates"][0],
-                 "lat": feature["geometry"]["coordinates"][1]
-             }
-     return []
  
- 
- if __name__ == "__main__":
-     file = open("../tests/sample_city.html")
-     html_data = file.read()
-     file.close()
-     parse_html(html_data)
- 
Clean up sample city file
## Code Before:
from bs4 import BeautifulSoup
import json
import datetime
import pytz

# The URL for the page where the parking lots are listed
data_url = "http://example.com"

# Name of the city, just in case it contains umlauts which this filename shouldn't
city_name = "Sample City"

# Name of this file (without '.py'), sorry for needing this, but it makes things easier
file_name = "Sample_City"


def parse_html(html):
    soup = BeautifulSoup(html)

    # Do everything necessary to scrape the contents of the html
    # into a dictionary of the format specified by the schema.


def get_geodata_for_lot(lot_name):
    geofile = open("./cities/" + file_name + ".geojson")
    geodata = geofile.read()
    geofile.close()
    geodata = json.loads(geodata)

    for feature in geodata["features"]:
        if feature["properties"]["name"] == lot_name:
            return {
                "lon": feature["geometry"]["coordinates"][0],
                "lat": feature["geometry"]["coordinates"][1]
            }
    return []


if __name__ == "__main__":
    file = open("../tests/sample_city.html")
    html_data = file.read()
    file.close()
    parse_html(html_data)

## Instruction:
Clean up sample city file
## Code After:
from bs4 import BeautifulSoup
import datetime
import pytz
from geodata import GeoData

# The URL for the page where the parking lots are listed
data_url = "http://example.com"

# Name of the city, just in case it contains umlauts which this filename shouldn't
city_name = "Sample City"

# Name of this file (without '.py'), sorry for needing this, but it makes things easier
file_name = "Sample_City"

# Uncomment the following line if there's geodata in the format of Sample_City.geodata in this directory
# geodata = GeoData(city_name)

def parse_html(html):
    soup = BeautifulSoup(html)

    # Do everything necessary to scrape the contents of the html
    # into a dictionary of the format specified by the schema.

    data = {
        "last_updated": "",
        "lots": []
    }

    print(data)
    return data

# the following is for testing this out, just delete it all when done
if __name__ == "__main__":
    with open("../tests/sample_city.html") as f:
        parse_html(f.read())
