def seed_locations():
# Load location data from JSON file
with open('data/locations.json') as f:
location_data = json.loads(f.read())
# to create locations
for distance, location in location_data.items():
latitude = location['lat']
longitude = location['lon']
crud.create_location(latitude, longitude, float(distance))
print('Success!')
def get_children():
"""Load children from dataset into database."""
with open("data/finaldata.csv", encoding='utf-8-sig') as children_data:
for r in enumerate(children_data):
data = r[1].split(',')
child_id, age_2021, date_missing, lname, fname, missing_age, city, county, state, gender, ethnicity, latitude, longitude = data
child_instance = crud.create_child(fname=fname, lname=lname, ethnicity=ethnicity, date_missing=date_missing, missing_age=int(missing_age), age_2021=int(age_2021))
location_instance = crud.create_location(child_id=child_instance.child_id, state=state, city=city, county=county)
def seed_cities(filename):
"""Add new sample cities to Location table."""
f = open(filename)
csv_f = csv.reader(f)
for row in csv_f:
city, state, country, lat, lng = row
if crud.get_location_by_name(city) == None:
loc_obj = crud.create_location(city, float(lat), float(lng), city,
city, state)
locs_in_db.append(loc_obj)
print(locs_in_db)
def seed_addresses(filename):
"""Add new sample addresses to Location table."""
f = open(filename)
csv_f = csv.reader(f)
for row in csv_f:
name, address, city, state, zipcode, lat, lng = row
if crud.get_location_by_name(name) == None:
loc_obj = crud.create_location(name, float(lat), float(lng),
address, city, state)
locs_in_db.append(loc_obj)
print(locs_in_db)
def show_user_places():
"""Display places for searched destination"""
place = request.args.get('search_input')
place = place.title()
user = session['user']
itineraries = crud.find_itinerary_by_user_id(user)
place_found = crud.find_location_by_name(place)
print(place_found)
print('*********')
if place_found != None:
('***** PLACE FOUND')
poi_details = []
details = crud.get_place_details(place_found)
print(details)
for detail in details:
poi_details.append({
'xid': detail.xid,
'name': detail.name,
'wikipedia': detail.wikipedia,
'image': detail.image,
'extract': detail.extract
})
else:
('********* going to get coordinates')
location_coord = APIfunctions.get_place_coordinates(place)
('coordinates received')
location = crud.create_location(place)
poi_options = APIfunctions.get_points_of_interests(location_coord)
('list of places retrieved')
poi_details = APIfunctions.get_place_info(poi_options)
('details retrieved')
for poi in poi_details:
xid = poi['xid']
name = poi['name']
wikipedia = poi['wikipedia']
image = poi['image']
extract = poi['extract']
crud.create_place(wikipedia, xid, name, image, extract,
location.id)
# return jsonify({'places': poi_details})
return render_template('search_results.html',
poi_details=poi_details,
place=place,
itineraries=itineraries)
def create_location(pin: str,
latitude: float,
longitude: float,
place_name: str,
admin_name1: str,
db: Session = Depends(get_db)):
return crud.create_location(db=db,
key=pin,
latitude=latitude,
longitude=longitude,
place_name=place_name,
admin_name1=admin_name1)
os.system('createdb plants')
model.connect_to_db(server.app)
model.db.create_all()
with open('data/plants3.json') as f:
plant_data = json.loads(f.read())
# Create locations and lighting conditions, store them in list so we can use them
# to create plants later
crud.create_lighting("Low Light")
crud.create_lighting("Medium Light")
crud.create_lighting("Bright Light")
crud.create_location("North Facing")
crud.create_location("East Facing")
crud.create_location("South Facing")
crud.create_location("West Facing")
# Create plants, store them in list so we can use them
# to create recommendations later
plants_in_db = []
for plant in plant_data:
# Get the name, description, lighting, location, and picture_path from the plant
# dictionary.
plant_name, plant_description, plant_lighting, plant_location, pic_src = (
plant['plant_name'], plant['plant_description'],
plant['plant_lighting'], plant['plant_location'], plant['pic_src'])
light_id = crud.lighting_conversion(plant_lighting)
# lat = res.json()['results'][0]['geometry']['location']['lat']
# lng = res.json()['results'][0]['geometry']['location']['lng']
# crud.create_location_full(real_location=real_location,
# movie_scene=movie_scene,
# imgURL = imgURL,
# movie = movie,
# lat = lat,
# lng = lng
# )
#end of the code
crud.create_location(real_location=real_location,
movie_scene=movie_scene,
imgURL=imgURL,
description=description,
movie=movie,
movie_real_life_scene_img=movie_real_life_scene_img,
movie_scene_img=movie_scene_img)
# # params = {"address":"Dogo Onsen","key":"AIzaSyB-33vlR6YV43rPhaQIU-vZAW0LZcS2qpc"}
# # res = requests.get('https://maps.googleapis.com/maps/api/geocode/json',params = params)
# # print(res.json())
# # pprint(res.json())
# # pprint(res.json()['results'][0]['geometry']['location']['lat'])
for i in range(5):
for episode in episode_data:
#for loop to set up database for episodes table and seeds data into episodes_in_db
season, episode_number, doctor, title, imdb, ep_id, companion, guest_star = (
episode['season'], episode['episode_number'], episode['doctor'],
episode['title'], episode['imdb'], episode['ep_id'],
episode['companion'], episode['guest_star'])
db_episode = crud.create_episode(season, episode_number, doctor, title,
imdb, ep_id, companion, guest_star)
locations_in_db.append(db_episode)
with open('data/dr_who_locations.csv', encoding='utf-8-sig') as csv_file:
fieldnames = ['address', 'longitude', 'latitude', 'ep_id']
location_data = csv.DictReader(csv_file,
fieldnames=fieldnames,
skipinitialspace=True)
#reads and imports Location info from csv file
for location in location_data:
#for loop to set up database for locations table and seeds data into locations_in_db
address, longitude, latitude, ep_id = (location['address'],
location['longitude'],
location['latitude'],
location['ep_id'])
db_location = crud.create_location(address, longitude, latitude, ep_id)
locations_in_db.append(db_location)
# camino_lon = radians(-1.23501836322248)
# return distance_between(lat, lon, camino_lat, camino_lon)
#
# distance_from_last_point = distance(last, us)
# last_camino_distance = camino_distance(last)
# total = last_camino_distance + distance_from_last_point
locations = {}
json_data = open('data/camino.json', 'r').read()
data = json.loads(json_data)
last_lat = radians(43.16366490907967)
last_lon = radians(-1.23501836322248)
distance = 0
create_location(-1.23501836322248, 43.16366490907967, 0) # start of camino
for row in data:
# lon = line[0]
# lat = line[1]
lat = float(row["lat"])
lon = float(row["lon"])
# lon, lat = line.strip().split(", ")
# print(lat, lon)
# approximate radius of earth in km
lat_r = radians(lat)
lon_r = radians(lon)
new_distance = distance_between(last_lat, last_lon, lat_r, lon_r)
