Add vehicle color parsing

encar_scraper/encar.py

@@ -420,11 +420,20 @@ class EncarMapper:
         return self._clean_base_model_name(translated)
 
     def _translate_color(self, color_raw: str) -> str:
-        value = self._as_str(color_raw)
+        value = re.sub(r"\s+", "", self._as_str(color_raw))
         if not value:
             return "other"
         return COLOR_TRANSLATIONS.get(value, self._translate_text(value).lower() or "other")
 
+    def apply_batch_color(self, record: CarRecord, vehicle_data: dict[str, Any]) -> None:
+        spec = vehicle_data.get("spec")
+        if not isinstance(spec, dict):
+            return
+
+        color_raw = self._as_str(spec.get("colorName") or spec.get("customColor") or "")
+        if color_raw:
+            record.color = self._translate_color(color_raw)
+
     def _to_float(self, value: Any) -> float | None:
         if value is None:
             return None
@@ -1500,24 +1509,33 @@ class EncarScraper:
         for i in range(0, len(tasks), BATCH_VEHICLES_CHUNK_SIZE):
             chunks.append(tasks[i:i + BATCH_VEHICLES_CHUNK_SIZE])
 
-        def _fetch_chunk(chunk: list[tuple[int, str]]) -> list[tuple[int, list[ImageRecord]]]:
+        def _fetch_chunk(chunk: list[tuple[int, str]]) -> list[tuple[int, list[ImageRecord], dict[str, Any]]]:
             ids_str = ",".join(vid for _, vid in chunk)
-            path = f"/v1/readside/vehicles?vehicleIds={ids_str}&include=PHOTOS"
-            for attempt in range(2):
+            path = f"/v1/readside/vehicles?vehicleIds={ids_str}&include=SPEC,PHOTOS"
+            for attempt in range(3):
                 try:
                     resp = pool.request("GET", path, timeout=15, retries=False)
                     if resp.status == 200:
                         if not resp.data:
-                            return [(ri, []) for ri, _ in chunk]
+                            return [(ri, [], {}) for ri, _ in chunk]
                         vehicles = json.loads(resp.data.decode("utf-8", errors="ignore"))
-                        # Маппим по vehicleId, а не по индексу — API может пропускать удалённые ID
                         id_to_rec: dict[str, int] = {vid: ri for ri, vid in chunk}
-                        result: list[tuple[int, list[ImageRecord]]] = []
-                        for vehicle_data in vehicles:
+                        result: list[tuple[int, list[ImageRecord], dict[str, Any]]] = []
+                        matched_record_indexes: set[int] = set()
+                        for vehicle_position, vehicle_data in enumerate(vehicles):
                             vid = str(vehicle_data.get("vehicleId") or vehicle_data.get("id") or "")
-                            rec_idx = id_to_rec.get(vid)
+                            rec_idx = None
+                            if vehicle_position < len(chunk):
+                                positional_rec_idx = chunk[vehicle_position][0]
+                                if positional_rec_idx not in matched_record_indexes:
+                                    rec_idx = positional_rec_idx
+                            if rec_idx is None:
+                                rec_idx = id_to_rec.get(vid)
                             if rec_idx is None:
                                 continue
+                            if rec_idx in matched_record_indexes:
+                                continue
+                            matched_record_indexes.add(rec_idx)
                             photos_raw = vehicle_data.get("photos") or []
                             images: list[ImageRecord] = []
                             seen_paths: set[str] = set()
@@ -1535,28 +1553,28 @@ class EncarScraper:
                                     order_index=order,
                                 ))
                             images.sort(key=lambda x: x.order_index)
-                            result.append((rec_idx, images))
+                            result.append((rec_idx, images, vehicle_data))
                         return result
                     if resp.status in (429, 503):
                         time.sleep(1 + attempt * 2)
                         continue
-                    return [(ri, []) for ri, _ in chunk]
+                    return [(ri, [], {}) for ri, _ in chunk]
                 except json.JSONDecodeError:
-                    return [(ri, []) for ri, _ in chunk]
+                    return [(ri, [], {}) for ri, _ in chunk]
                 except Exception as exc:
                     logger.debug("Batch photo chunk error (attempt %d): %s", attempt + 1, exc)
-                    if attempt < 1:
+                    if attempt < 2:
                         time.sleep(1)
-            return [(ri, []) for ri, _ in chunk]
+            return [(ri, [], {}) for ri, _ in chunk]
 
-        results: dict[int, list[ImageRecord]] = {}
+        results: dict[int, tuple[list[ImageRecord], dict[str, Any]]] = {}
         with ThreadPoolExecutor(max_workers=30) as executor:
             futures = {executor.submit(_fetch_chunk, ch): ch for ch in chunks}
             for future in as_completed(futures):
                 try:
-                    for rec_idx, images in future.result():
-                        if images:
-                            results[rec_idx] = images
+                    for rec_idx, images, vehicle_data in future.result():
+                        if vehicle_data:
+                            results[rec_idx] = (images, vehicle_data)
                 except Exception as exc:
                     logger.warning("Batch photo future failed: %s", exc)
 
@@ -1565,7 +1583,10 @@ class EncarScraper:
         fallback_count = 0
         for rec_idx, item in probe_tasks:
             if rec_idx in results:
-                records[rec_idx].images = results[rec_idx]
+                images, vehicle_data = results[rec_idx]
+                if images:
+                    records[rec_idx].images = images
+                self.car_mapper.apply_batch_color(records[rec_idx], vehicle_data)
                 api_ok += 1
             else:
                 fallback_count += 1