def extract(self):
self.pdf = PDFContainer(format=self.config.outPDFFormat,
codec=self.config.fileCodec)
if self.pdf.format == "filter":
self.pdf.convertPDFFilter(self.INFilename)
else:
self.pdf.convertPDFAlternative(self.INFilename)
self.tokenizer = nltk.data.load(self.config.sentencesSplitterModel)
self.extractorNer = NERExtractor(self.config)
self.extractorLoc = Location(self.config.minTanimoto)
# extract title
txt = self.pdf.getPages(0, 3)
self.extractTitle(txt)
# extract names
txt = self.pdf.getPages(0, 10)
sents = txt.split('\n') # tokenizer.tokenize(txt)
self.extractName(sents)
# extract locations with coords
txt = self.pdf.getAllPages()
sents = self.tokenizer.tokenize(txt)
self.extractLocation(sents)
# extract key words
self.extractKeyWords(txt)
# extract refs
self.extractRefs(txt)
def test_locking_money(self):
user = UserGetter.get_by_id('xUQeyplJshTzco4vyHHVoytT3FD2')
request = DeliveryRequest(
"id",
"item",
"description\ntext",
origin=Location(name="Odenvägen 1, SE-194 63 Odenslunda, Sweden",
latitude=59.51224,
longitude=17.93536).to_dict(),
destination=Location(name="Rolsmo 1, SE-360 24 Linneryd, Sweden",
latitude=56.64989,
longitude=15.16624).to_dict(),
reward=100,
weight=2,
fragile=True,
status=Status.AVAILABLE,
money_lock=0,
owner=user.to_minified().to_dict(),
assistant=MinifiedUser("", "", "", "").to_dict(),
image_path="")
# ensure enough capital
user.deposit(100)
user_balance = user.balance
self.assertEqual(user.balance, user_balance)
user.lock_delivery_amount(request)
self.assertEqual(user.balance, user_balance - 100)
def __init__(self, uid: str, item: str, description: str, origin: dict,
destination: dict, reward: int, weight: int, fragile: bool,
status: Status, money_lock: int, owner: dict, assistant: dict,
image_path: str, **kwargs):
"""Initializes the delivery list"""
self.uid: str = uid
self.item: str = item
self.description: str = description
self.origin: Location = Location(**origin)
self.destination: Location = Location(**destination)
self.reward: int = reward
self.weight: int = weight
self.fragile: bool = fragile
self.status: Status = status
self.money_lock: int = money_lock
self.owner: MinifiedUser = MinifiedUser(**owner)
if assistant:
self.assistant: MinifiedUser = MinifiedUser(**assistant)
self.image_path: str = image_path
self.weight_text = self._weight_props[weight].text
self.weight_icon = self._weight_props[weight].icon
self.status_text = self._to_text(status)
def test_get_by_id(self):
delivery_request = DeliveryRequestGetter.get_by_id(
u'DLpVc0QmbOHzfDo24Hpp')
expected = DeliveryRequest(
uid='DLpVc0QmbOHzfDo24Hpp',
item='Xbox controller',
description='I AM USED FOR TESTS. DO NOT REMOVE',
origin=Location(name="Odenvägen 1, SE-194 63 Odenslunda, Sweden",
latitude=59.51224,
longitude=17.93536).to_dict(),
destination=Location(name="Rolsmo 1, SE-360 24 Linneryd, Sweden",
latitude=56.64989,
longitude=15.16624).to_dict(),
reward=123,
weight=0,
fragile=False,
status=Status.AVAILABLE,
money_lock=23,
owner=MinifiedUser(
mail="*****@*****.**",
name=
'Travis CI Account - DON\'T DELETE OR YOULL BREAK THE ENTIRE CI WORKFLOW/UNITTESTS REEEEEEEEEEEEEEEEEEEEEEEEE',
phonenumber='0',
uid="xUQeyplJshTzco4vyHHVoytT3FD2").to_dict(),
assistant=dict(),
image_path='')
self.assertDictEqual.__self__.maxDiff = None
self.assertDictEqual(delivery_request.to_dict(), expected.to_dict())
def read_locations(source_file_name: str):
"""Loads locations from the specified CSV file and returns a collection of location instances.
:param source_file_name: The CSV file to load.
"""
with open(source_file_name) as location_file:
location_reader = csv.DictReader(location_file)
output_locations = []
int_fieldnames = [
i for i in location_reader.fieldnames if re.match(r'\d+', i)
]
for row in location_reader:
# Build distance dictionary
my_dists = dict.fromkeys(int_fieldnames, 0)
for ifn in my_dists.keys():
try:
my_dists[ifn] = float(row[ifn])
except ValueError:
my_dists[ifn] = -1
# Add to output
this_row_location = Location(int(row["ID"]), row["Name"],
row["Address"], my_dists)
output_locations.append(this_row_location)
print(
f'Read in {location_reader.line_num} lines from {source_file_name}, '
f'created {len(output_locations)} package objects.')
Location.hub = output_locations[0]
return output_locations
def create_customerorder_list(self, orderinfo_list):
# random generation of customer(s) location
for orderinfo in orderinfo_list:
customer_loc_list = [
Location(self.worldsize * random(), self.worldsize * random())
for i in range(orderinfo["workorder_num"])
]
orderinfo.update({"customer_loc_list": customer_loc_list})
self.workorder_list = orderinfo_list
# create processes that specify arrival statistics and manage processes initiated upon
# workorder arrival
self.arrivalstats_list = [
{
"pid":
x["pid"],
"arrival_obj":
ArrivalStochastics(
env=self.env,
lambd_rate=x["lambd_rate"],
dist_type=x["dist_type"],
customer_loc_list=x["customer_loc_list"],
pid=x["pid"],
producer_action=self.producer_list[self.pindexerGet(
x["pid"])].producer_action)
}
#interrupt_process=self.producer_list[self.pindexerGet(x["pid"])].action_process)}
for x in self.workorder_list
]
def get(self, store_id):
store_bson = self.stores_collection.find_one({"_id": bson.ObjectId(store_id)})
store = StoreModel(str(store_bson['_id']),
store_bson['store_type'],
store_bson['location_quick_name'],
Location(store_bson['location']['type'], store_bson['location']['coordinates']))
return store
def findInImage(self, image):
if image is None or len(image.shape) is not 2:
print('error with image')
return
if len(self.template.shape) is not 2:
print('error with template')
return
image = cv2.normalize(image, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8U)
m = np.float32([(1, 0, self.template.shape[0] / 2),
(0, 1, self.template.shape[1] / 2)])
d = cv2.matchTemplate(image, self.template, cv2.TM_CCORR_NORMED)
d = cv2.warpAffine(d, m, dsize=(image.shape[1], image.shape[0]))
m, M, m_1, M_1 = cv2.minMaxLoc(d)
print(m, M, m_1, M_1)
threshold = self.threshold
if self.variableThreshold:
threshold = M - threshold
locations = []
_, d2 = cv2.threshold(d, threshold, 1, cv2.THRESH_BINARY)
d2 = cv2.normalize(d2, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8U)
d = cv2.normalize(d, None, 0, 255, cv2.NORM_MINMAX, cv2.CV_8U)
contours, hier = cv2.findContours(d2, cv2.RETR_LIST,
cv2.CHAIN_APPROX_SIMPLE)
for cnt in contours:
(x, y, w, h) = cv2.boundingRect(cnt)
locations.append(Location((y, x), size=(h, w)))
return locations, cv2.merge((d2, d, image))
def create_vehicle_list(self, vehicleinfo_list):
self.vehicle_list = [
Vehicle(env=self.env,
vid=x["vid"],
initial_location=Location(x["x"], x["y"]),
capacity=x["capacity"],
velocity=x["velocity"]) for x in vehicleinfo_list
]
def test_from_dict(self):
data = {'name': 'test', 'longitude': 0, 'latitude': 0}
location = Location.from_dict(data)
self.assertEqual(location.name, data['name'])
self.assertEqual(location.latitude, data['latitude'])
self.assertEqual(location.longitude, data['longitude'])
def __init__(
self,
number,
description=None,
lat=None,
lng=None,
level=None,
time=None
):
errors = []
try:
self.number = int(number)
except (TypeError, ValueError):
errors.append({
"number": _("Drop point number is not a number.")
})
else:
if self.number < 1:
errors.append({
"number": _("Drop point number is not positive.")
})
with db.session.no_autoflush:
if db.session.query(DropPoint).get(self.number):
errors.append({
"number": _("That drop point already exists.")
})
if time and not isinstance(time, datetime):
errors.append({
"DropPoint": _("Creation time not a datetime object.")
})
if isinstance(time, datetime) and time > datetime.today():
errors.append({
"DropPoint": _("Creation time in the future.")
})
self.time = time if time else datetime.today()
try:
Location(
self,
time=self.time,
description=description,
lat=lat,
lng=lng,
level=level
)
except ValueError as e:
errors += e.args
if errors:
raise ValueError(*errors)
db.session.add(self)
def get(self):
stores = []
for store_bson in self.stores_collection.find():
#TODO refactor out into mapper
store = Store(str(store_bson['_id']),
store_bson['store_type'],
store_bson['location_quick_name'],
Location(store_bson['location']['type'], store_bson['location']['coordinates']))
stores.append(store)
return stores
def put(self, store_id):
data = request.get_json()
store_bson = self.stores_collection.find_one({'_id': bson.ObjectId(store_id)})
store_bson['location_quick_name'] = data['location_quick_name']
store_bson['location']['coordinates'] = data['location']['coordinates']
self.stores_collection.update_one(store_bson)
store = StoreModel(str(store_bson['_id']),
store_bson['store_type'],
store_bson['location_quick_name'],
Location(store_bson['location']['type'], store_bson['location']['coordinates']))
return store
def test_query(self):
user = UserGetter.get_by_id('xUQeyplJshTzco4vyHHVoytT3FD2')
delivery_requests = DeliveryRequestGetter.query(
u'owner.uid', u'==', u'xUQeyplJshTzco4vyHHVoytT3FD2')
self.assertGreaterEqual(len(delivery_requests),
1,
msg="Expected at least 1 match.")
# Clean up DRs
for dr in delivery_requests:
if not dr.uid == 'DLpVc0QmbOHzfDo24Hpp':
with Firestore.batch('packages') as batch:
batch.delete(dr.uid)
delivery_requests = DeliveryRequestGetter.query(
u'owner.uid', u'==', u'xUQeyplJshTzco4vyHHVoytT3FD2')
self.assertEqual(len(delivery_requests), 1, msg="Expected 1 match.")
expected = DeliveryRequest(
uid='DLpVc0QmbOHzfDo24Hpp',
item='Xbox controller',
description='I AM USED FOR TESTS. DO NOT REMOVE',
origin=Location("Odenvägen 1, SE-194 63 Odenslunda, Sweden",
latitude=59.51224,
longitude=17.93536).to_dict(),
destination=Location("Rolsmo 1, SE-360 24 Linneryd, Sweden",
latitude=56.64989,
longitude=15.16624).to_dict(),
reward=123,
weight=0,
fragile=False,
status=Status.AVAILABLE,
money_lock=23,
owner=user.to_minified().to_dict(),
assistant=dict(),
image_path='')
self.assertDictEqual.__self__.maxDiff = None
self.assertDictEqual(delivery_requests[0].to_dict(),
expected.to_dict())
def test_addition_to_drop_point(self):
dp_number = 3
first_description = "here"
first_lat = -23.5
first_lng = 84
first_level = 3
second_description = "there"
second_lat = 3.14
second_lng = -2.71828
second_level = 2
first_time = datetime.today() - timedelta(hours=2)
second_time = datetime.today() - timedelta(hours=2 - 1)
dp = DropPoint(dp_number,
description=first_description,
lat=first_lat,
lng=first_lng,
level=first_level,
time=first_time)
db.session.commit()
self.assertEqual(len(dp.locations), 1,
"Drop point does not have exactly one location.")
self.assertEqual(
db.session.query(Location).count(), 1,
"Not exactly one location in the database.")
second_location = Location(dp,
description=second_description,
lat=second_lat,
lng=second_lng,
level=second_level,
time=second_time)
db.session.commit()
self.assertEqual(len(dp.locations), 2,
"Drop point does not have exactly two locations.")
self.assertEqual(
db.session.query(Location).count(), 2,
"Not exactly two locations in the database.")
self.assertEqual(
dp.get_current_location(), second_location,
"Current drop point location is not second location.")
self.assertEqual(dp.locations[1].time - dp.locations[0].time,
second_time - first_time,
"Wrong time difference between locations.")
def extract(self):
if self.model.INFilename != "":
from converter.pdfextractor import PDFContainer
import nltk.data
from model.title import extractTitle
from converter.pdfextractor import PDFContainer
from model.location import Location
from config.dictionary import refWords, Coves, Seas, Bays, Islands
from model.keywords import KeywordExtractor
from model.reference import ExtracrReference
from model.ner import NERExtractor
from converter.dataContainer import DataPerson, DataLocation, DataKeyword, DataRef
from converter.load import insertData
#self.model.extract()
self.view.setProgress(0)
self.view.isVisibleProgress(True)
self.model.pdf = PDFContainer(format=self.model.config.outPDFFormat, codec=self.model.config.fileCodec)
if self.model.pdf.format == "filter":
self.model.pdf.convertPDFFilter(self.model.INFilename)
else:
self.model.pdf.convertPDFAlternative(self.model.INFilename)
self.view.setProgress(10)
self.model.tokenizer = nltk.data.load(self.model.config.sentencesSplitterModel)
self.view.setProgress(20)
self.model.extractorNer = NERExtractor(self.model.config)
self.view.setProgress(30)
self.model.extractorLoc = Location(self.model.config.minTanimoto)
self.view.setProgress(40)
# extract title
txt = self.model.pdf.getPages(0, 3)
self.model.extractTitle(txt)
self.view.setProgress(50)
# extract names
txt = self.model.pdf.getPages(0, 10)
sents = txt.split('\n') # tokenizer.tokenize(txt)
self.model.extractName(sents)
self.view.setProgress(60)
# extract locations with coords
txt = self.model.pdf.getAllPages()
sents = self.model.tokenizer.tokenize(txt)
self.model.extractLocation(sents)
self.view.setProgress(70)
# extract key words
self.model.extractKeyWords(txt)
self.view.setProgress(80)
# extract refs
self.model.extractRefs(txt)
self.view.setProgress(90)
#############################
self.view.setProgress(100)
def create_delivery_request():
origin = Location(name="Odenvägen 1, SE-194 63 Odenslunda, Sweden",
latitude=59.51224,
longitude=17.93536).to_dict()
destination = Location(name="Rolsmo 1, SE-360 24 Linneryd, Sweden",
latitude=56.64989,
longitude=15.16624).to_dict()
return DeliveryRequest(
"TEST",
"item",
"This a test, feel free to remove.",
origin,
destination,
reward=10,
weight=2,
fragile=True,
status=Status.AVAILABLE,
money_lock=0,
owner=MinifiedUser("", "", "",
"xUQeyplJshTzco4vyHHVoytT3FD2").to_dict(),
assistant=MinifiedUser("", "", "", "").to_dict(),
image_path="")
def profile_optimization_strategies(routing_method: str,
loc_count: int,
step_size: int = 1):
# Initial data load
locations = read_locations("sample_locations.csv")
if len(locations) < loc_count:
need = loc_count - len(locations)
locations.extend(Location.generate_fake_locations(need))
test_routing_table = None
if routing_method.lower() == "hash":
test_routing_table = RoutingTableHash(
locations) # Build location+location distance lookup hash table
elif routing_method.lower() == "array":
test_routing_table = RoutingTableArray(locations)
else:
raise Exception("Unknown routing table type specified:",
routing_method)
# Testing lots of locations
for count in range(5, loc_count, step_size):
print(f"-- Optimization strategies with {count} locations --")
this_pass_locations = locations[1:count]
optimizer = RouteOptimizer(this_pass_locations, test_routing_table,
locations[0])
if count <= optimizer.bfs_cutoff_slow:
start = time.perf_counter()
route = optimizer.get_optimized_bfs()
elapsed = time.perf_counter() - start
optimizer.print_route_evaluation(
f"Brute force N={len(this_pass_locations) + 1}", route,
elapsed)
else:
print(
"Skipping brute force search due to location count being above",
optimizer.bfs_cutoff_slow)
start = time.perf_counter()
route = optimizer.get_optimized_nn()
elapsed = time.perf_counter() - start
optimizer.print_route_evaluation(
f"Nearest Neighbor N={len(this_pass_locations) + 1}", route,
elapsed)
start = time.perf_counter()
route = optimizer.get_optimized_cpm()
elapsed = time.perf_counter() - start
optimizer.print_route_evaluation(
f"AS Coproximity N={len(this_pass_locations) + 1}", route, elapsed)
exit(0)
def fetch_locations(self):
print('Fetching locations...', flush=True)
self.driver.get(self.url)
has_next = True
iterator_count = 0
locations = []
while has_next:
if iterator_count > 0:
location_elements = self.driver.find_element_by_xpath(
'//*[@id="LOCATION_LIST"]/ul')
location_elements = location_elements.find_elements_by_tag_name(
'li')
else:
location_elements = self.driver.find_elements_by_class_name(
'geo_name')
for e in location_elements:
try:
url = e.find_element_by_tag_name('a').get_attribute('href')
url_text = e.find_element_by_tag_name('a').text
language = get_language_by_url(self.driver.current_url)
if language == 'es':
name = url_text.split(I18N[language]['in'] + ' ')[-1]
elif language == 'en':
name = url_text.split(' Restaurants')[0]
else:
name = ''
locations.append(Location(url, name))
except:
logging.warning('Couldn\'t fetch location.')
pass
if iterator_count > 0:
next_page = ".pgLinks>.sprite-pageNext"
else:
next_page = ".pagination>.next"
try:
has_next = self.driver.execute_script(
'return !document.querySelector("' + next_page +
'").classList.contains("disabled")')
if has_next:
self.driver.execute_script('document.querySelector("' +
next_page + '").click()')
except:
has_next = False
iterator_count += 1
time.sleep(SECONDS_BETWEEN_REQUEST)
return locations
def __init__(self, pid, location=None, production_time=0, worldsize=100.0, env=None, deliverymgr=None):
self._pid = pid
if location is None:
x = random.random()*worldsize
y = random.random()*worldsize
self.location = Location(x,y)
else:
self.location = location
# workorder list for this producer
self._workorder_list = None
self.deliverymgr = deliverymgr
# time required to produce product; if stochastic, indicates mean value
self.production_time = production_time
self.env = env
def test_construction_exceptions(self):
dp = DropPoint(1, lat=0, lng=0, level=1)
with self.assertRaisesRegexp(ValueError, "drop point"):
Location("foo")
time_in_future = datetime.today() + timedelta(hours=1)
with self.assertRaisesRegexp(ValueError, "future"):
Location(dp, time=time_in_future, lat=0, lng=0, level=1)
with self.assertRaisesRegexp(ValueError, "not a datetime"):
Location(dp, time="foo", lat=0, lng=0, level=1)
start_time = datetime.today()
with self.assertRaisesRegexp(ValueError, "older than current"):
Location(dp, time=start_time, lat=0, lng=0, level=1)
db.session.commit()
Location(dp, time=start_time - timedelta(hours=1))
invalid_lat = ("foo", -180, 91, None)
invalid_lng = ("bar", -181, 251.5, None)
invalid_level = ("quux", None)
for lat in invalid_lat:
with self.assertRaisesRegexp(ValueError, "lat"):
Location(dp, lat=lat, lng=0, level=1)
for lng in invalid_lng:
with self.assertRaisesRegexp(ValueError, "lng"):
Location(dp, lat=0, lng=lng, level=1)
for level in invalid_level:
with self.assertRaisesRegexp(ValueError, "level"):
Location(dp, lat=0, lng=0, level=level)
too_long = "a" * (Location.max_description + 1)
with self.assertRaisesRegexp(ValueError, "too long"):
Location(dp, lat=0, lng=0, level=1, description=too_long)
def add_location(self):
'''
Create list_of_locations built of Location objects. Except Vallue Error when data isn't integer.
'''
option = [4, 5]
amount = 1
for row in Territory.list_of_territory:
try:
if self.name == row[4] and int(row[3]) in option:
location = Location(row[4], row[5], amount)
self.list_of_locations.append(location)
amount += 1
except ValueError:
continue
def create_producer_list(self, producerinfo_list=None, producer_num=1):
if producerinfo_list:
self.producer_list = [
Producer(pid=x["pid"],
location=Location(x=x["x"], y=x["y"]),
production_time=x["production_time"],
env=self.env,
deliverymgr=self.deliverymgr)
for x in producerinfo_list
]
else:
for i in range(producer_num):
producer = Producer(i + 1,
worldsize=self.worldsize,
env=self.env)
self.producer_list.append(producer)
self.pindexerGet = lambda x: dict(
(p.pid, i) for i, p in enumerate(self.producer_list)).get(x)
def post(self):
data = request.get_json()
store_bson = self.stores_collection.find_one({
'store_type': data['store_type'],
'location.coordinates': data['location']['coordinates']
})
if store_bson:
return {'message': 'item exists'}, 400
new_store = {
'_id': bson.ObjectId(),
'store_type': data['store_type'],
'location': data['location'],
'location_quick_name': data['location_quick_name']
}
self.stores_collection.insert_one(new_store)
store = Store(str(new_store['_id']),
new_store['store_type'],
new_store['location_quick_name'],
Location(new_store['location']['type'], new_store['location']['coordinates']))
return store
def create_location(token, location_name, detailed_address, lot, lat, province,
city, location_contactss):
"""
创建转运网点
:param token:
:param location_name:
:param detailed_address:
:param lot:
:param lat:
:param province:
:param city:
:return:
"""
user = hgetall(get_token(token))
if (not user) or int(user['role_type']) != cs.USER_ROLE_INFO[u"线路规划专员"]:
return cs.AUTH_ERROR, None
# 生成location_code
location_code = generate_location_code()
try:
location_obj = Location(location_name, location_code, detailed_address,
lot, lat, province, city,
cs.LOCATION_STATUS_INFO[u"启用"])
# 创建网点联系人
if location_contactss:
print location_contactss
for item in location_contactss:
location_contacts = LC(location_code, item['contacts_name'],
item['contacts_telephone'])
db.session.add(location_contacts)
db.session.add(location_obj)
db.session.commit()
return cs.OK, location_code
except:
logger.error("create location err : {}".format(
traceback.format_exc(), ))
raise
finally:
db.session.rollback()
def test_to_dict(self):
location1 = Location('test', 0.0, 0.0)
expected = {'name': 'test', 'longitude': 0, 'latitude': 0}
self.assertDictEqual(location1.to_dict(), expected)
import os, sys
parentPath = os.path.abspath("..")
if parentPath not in sys.path:
sys.path.insert(0, parentPath)
from model.location import Location
def test(expect, output):
if expect == output:
print("OK")
else:
print("ERR", expect, " ", output)
l = Location(0.5)
test(l.isNorm('a'), True)
test(l.isNorm(' '), True)
test(l.isNorm('1'), True)
test(l.isNorm(')'), False)
test(l.normalize('It is a good day.'), 'It is a good day')
test(l.getLoc(['It is a good day.']), 'it is a good day')
test(l.isFuzzyEqual('It is a good day.', 'It is a good night.'), 1.0)
test(l.isFuzzyEqual('It is a good day.', 'It is a bad night.'), 0.0)
test(l.VangerFisher('Morskaya', 'Morskoy'), True)
test(l.VangerFisher('Morskaya', 'Mars'), False)
import pandas as pd
from knowledge import Knowledge
from model.location import Location
df = pd.read_excel('tmp/Danh sách cấp xã.xls')
locations = []
# xã
for i, row in df.iterrows():
if (i > 0) and (i % 1000 == 0):
print(f"Extract {i} entities")
location = Location(name=row["Tên"], level=row["Cấp"])
locations.append(location)
# quận, huyện
level1_entities = df["Quận Huyện"].unique()
for name in level1_entities:
location = Location(name=name, level="Quận Huyện")
locations.append(location)
# tỉnh, thành phố
level0_entities = df["Tỉnh / Thành Phố"].unique()
for name in level0_entities:
location = Location(name=name, level="Tỉnh / Thành Phố")
locations.append(location)
savepath = "data/locations.jl"
Knowledge.save(locations, savepath)
print(f"{len(locations)} entities is saved in {savepath}")
def initialize():
collections = mongo.db.collection_names()
if "locations" not in collections:
col: wrappers.Collection = mongo.db.locations
col.ensure_index([("geo", GEOSPHERE)])
locations = json.load(open("./db/locations.json"))
col: wrappers.Collection = mongo.db.locations
for location in locations:
loc = Location(**location)
col.insert_one(loc.__dict__)
subways = json.load(open("./db/subway.json"))
for subway in subways:
if not subway:
continue
loc = Location(**subway)
col.insert_one(loc.__dict__)
if "rooms" not in collections:
col: wrappers.Collection = mongo.db.rooms
col.create_index("seq", unique=True)
col.ensure_index([("geo", GEOSPHERE)])
col2: wrappers.Collection = mongo.db.room_detail
col2.create_index("seq", unique=True)
col2.ensure_index([("geo", GEOSPHERE)])
db = json.load(open("./db/db.json"))
for key in db:
for key2 in db[key]:
for info in db[key][key2]:
try:
location = info["locs"][0]["loc"]
rooms_info = info["rooms"]
col: wrappers.Collection = mongo.db.rooms
items = []
for rinfo in rooms_info:
rinfo["region_code"] = location["code"]
room = RoomInfo(**rinfo)
items += [room.__dict__]
if items:
col.insert_many(items)
except:
pass
if not items:
continue
col: wrappers.Collection = mongo.db.room_detail
option = [
"침대", "책상", "인터넷", "전자도어락", "세탁기", "에어컨", "옷장", "신발장",
"TV", "냉장고", "가스레인지"
]
detail = []
for item in items:
try:
item["building_floor"] = random.randint(1, 5)
item["floor"] = random.randint(
1, item["building_floor"])
if item["room_type"] < 3:
item["room_count"] = item["room_type"] + 1
item["bath_count"] = 1
item["reg_date"] = "2020.10.04 22:30"
item["building_date"] = "2020.10.04 22:00"
item["maintain_cost"] = random.randint(5, 10)
cnt = random.randint(0, len(option))
item["options"] = random.sample(option, cnt)
del item["_id"]
col.insert_one(item)
detail += [item]
except:
continue
#if detail:
# col.insert_many(detail)
if "security_light" not in collections:
col: wrappers.Collection = mongo.db.security_light
col.ensure_index([("geo", GEOSPHERE)])
db = json.load(open("./db/security_light.json"))
items = []
for item in db["records"]:
if "latitude" in item and "longtitude" in item:
cctv = SecurityLight(**item)
items += [cctv.__dict__]
if items:
col.insert_many(items)
if "cctv" not in collections:
col: wrappers.Collection = mongo.db.cctv
col.ensure_index([("geo", GEOSPHERE)])
db = json.load(open("./db/cctv.json"))
items = []
for item in db["records"]:
if "latitude" in item and "longtitude" in item:
cctv = CCTV(**item)
items += [cctv.__dict__]
if items:
col.insert_many(items)
def test_to_string(self):
location = Location('test', 1.0, -5.0)
expected = 'Location: (1.0, -5.0) test'
self.assertEqual(str(location), expected)
