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)