reformat most things

crawler/5_routing.py

@@ -16,19 +16,24 @@ for listing in listings:
         log.info(f"Removed-Skip: Skipping {listing.identifier} is already removed.")
         continue
     if miles > 7:
-        log.info(f"Miles-Skip: Skipping {listing.identifier} as it is {miles} miles away")
+        log.info(
+            f"Miles-Skip: Skipping {listing.identifier} as it is {miles} miles away"
+        )
         continue
     if listing.path_routing_json().exists():
-        log.info(f"Path-Skip: Skipping {listing.identifier} as path routing already exists")
+        log.info(
+            f"Path-Skip: Skipping {listing.identifier} as path routing already exists"
+        )
         continue
     if listing.sqm_ocr is None or listing.sqm_ocr < 30 or listing.sqm_ocr > 200:
-        log.info(f"Floorplan-Skip: Skipping {listing.identifier} as sqm_ocr is {listing.sqm_ocr}")
+        log.info(
+            f"Floorplan-Skip: Skipping {listing.identifier} as sqm_ocr is {listing.sqm_ocr}"
+        )
         continue
     filtered_listings.append(listing)
 
 print(f"Filtered listings from {len(listings)} to {len(filtered_listings)}")
 
-
 for listing in tqdm(filtered_listings):
     lat, long = BROCK_STREET_LAT_LONG
     listing.calculate_route(lat, long, recalculate=False)

crawler/data_access.py

@@ -6,7 +6,6 @@ from rec import floorplan, routing
 import re
 import datetime
 
-
 _DATA_DIR = pathlib.Path("data/rs/")
 
 
@@ -263,25 +262,36 @@ class Listing:
 
     def dict_nicely(self):
         return {
-            "identifier": self.identifier,
+            "identifier":
-            "sqm_ocr": self.sqm_ocr,
+                self.identifier,
-            "price": self.price,
+            "sqm_ocr":
-            "price_per_sqm": self.price_per_sqm,
+                self.sqm_ocr,
-            "url": self.url,
+            "price":
-            "bedrooms": self.bedrooms,
+                self.price,
-            "travel_time_fastest": None
+            "price_per_sqm":
-            if len(self.travel_time) == 0
+                self.price_per_sqm,
-            else self.travel_time[0],
+            "url":
-            "travel_time_second": None
+                self.url,
-            if len(self.travel_time) < 2
+            "bedrooms":
-            else self.travel_time[1],
+                self.bedrooms,
-            "lease_left": self.leaseLeft,
+            "travel_time_fastest":
-            "service_charge": self.serviceCharge,
+                None if len(self.travel_time) == 0 else self.travel_time[0],
-            "development": self.development,
+            "travel_time_second":
-            "tenure_type": self.tenure_type,
+                None if len(self.travel_time) < 2 else self.travel_time[1],
-            "updated_days": self.updateDaysAgo,
+            "lease_left":
-            "status": self.status,
+                self.leaseLeft,
-            "last_seen": self.last_seen,
+            "service_charge":
+                self.serviceCharge,
+            "development":
+                self.development,
+            "tenure_type":
+                self.tenure_type,
+            "updated_days":
+                self.updateDaysAgo,
+            "status":
+                self.status,
+            "last_seen":
+                self.last_seen,
         }
 
 

crawler/rec/db.py

@@ -6,7 +6,6 @@ from sqlalchemy.orm import declarative_base
 engine = create_engine("sqlite:///sqlite.db", echo=True)
 session = Session(engine)
 
-
 Base = declarative_base()
 
 

crawler/rec/floorplan.py

@@ -34,12 +34,16 @@ def calculate_model(image_path):
     estimated_sqm = extract_total_sqm(output)
     return estimated_sqm, output, predictions_tensor
 
+
 def improve_img_for_ocr(img: Image):
     img2 = np.array(img.convert('L'))
     cv2.resize(img2, None, fx=1.2, fy=1.2, interpolation=cv2.INTER_CUBIC)
-    thresh = cv2.adaptiveThreshold(img2,255,cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY,11,2)
+    thresh = cv2.adaptiveThreshold(
+        img2, 255, cv2.ADAPTIVE_THRESH_GAUSSIAN_C, cv2.THRESH_BINARY, 11, 2
+    )
     return Image.fromarray(thresh)
 
+
 def calculate_ocr(image_path):
     img = Image.open(image_path)
     text = pytesseract.image_to_string(img)

crawler/rec/query.py

@@ -2,8 +2,7 @@
 import enum
 from typing import List
 import requests
-# from rec.db import RightmoveListing
+from rec.db import RightmoveListing
-
 import urllib3
 
 urllib3.disable_warnings()
@@ -36,7 +35,10 @@ def detail_query(detail_id: int):
     url = f"https://api.rightmove.co.uk/api/property/{detail_id}"
     response = requests.get(url, params=params, headers=headers, verify=False)
     if response.status_code != 200:
-        raise Exception(f"id: {detail_id}. Status Code: {response.status_code}. Failed due to: {response.text}")
+        raise Exception(
+            f"""id: {detail_id}. Status Code: {response.status_code}."""
+            f"""Failed due to: {response.text}"""
+        )
 
     return response.json()
 

crawler/rec/routing.py

@@ -16,18 +16,34 @@ def transit_route(
     monday9am = nextMonday()
 
     header = {
-        "X-Goog-Api-Key": API_KEY,
+        "X-Goog-Api-Key":
-        "Content-Type": "application/json",
+            API_KEY,
-        "X-Goog-FieldMask": "routes.distanceMeters,routes.duration,routes.staticDuration,routes.legs.steps.distanceMeters,routes.legs.steps.staticDuration,routes.legs.steps.travelMode",
+        "Content-Type":
+            "application/json",
+        "X-Goog-FieldMask":
+            "routes.distanceMeters,routes.duration,routes.staticDuration,routes.legs.steps.distanceMeters,routes.legs.steps.staticDuration,routes.legs.steps.travelMode",
     }
 
     body = {
-        "origin": {
+        "origin":
-            "location": {"latLng": {"latitude": origin_lat, "longitude": origin_lon}}
+            {
-        },
+                "location":
-        "destination": {
+                    {
-            "location": {"latLng": {"latitude": dest_lat, "longitude": dest_lon}}
+                        "latLng": {
-        },
+                            "latitude": origin_lat,
+                            "longitude": origin_lon
+                        }
+                    }
+            },
+        "destination":
+            {
+                "location": {
+                    "latLng": {
+                        "latitude": dest_lat,
+                        "longitude": dest_lon
+                    }
+                }
+            },
         "travelMode": "TRANSIT",
         # "2023-10-15T15:01:23.045123456Z"
         "departureTime": monday9am.strftime("%Y-%m-%dT%H:%M:%S.%fZ"),
@@ -97,7 +113,6 @@ if __name__ == "__main__":
 
     extract_time(d)
 
-
 # if __name__ == "__main__":
 #    origin = 51.5635664310333, -0.1107173751570373 # home
 #    dest = 51.50475678313417, 0.04915321000190009 # london city airport