fix: fix types on ParsedData model for KC

README.md

@@ -366,7 +366,7 @@ class ParsedData(BaseModel):
     is_multi_audio: bool = False
     is_multi_subtitle: bool = False
     is_complete: bool = False
-    year: List[int] = []
+    year: int = 0
     resolution: List[str] = []
     quality: List[str] = []
     season: List[int] = []
@@ -376,15 +376,14 @@ class ParsedData(BaseModel):
     subtitles: List[str] = []
     language: List[str] = []
     bitDepth: List[int] = []
-    hdr: str | bool = False
+    hdr: str = ""
     proper: bool = False
     repack: bool = False
     remux: bool = False
     upscaled: bool = False
     remastered: bool = False
     directorsCut: bool = False
     extended: bool = False
-    excess: list = []
 ```
 
 This will continue to grow though as we expand on functionality, so keep checking back for this list!

RTN/models.py

@@ -15,7 +15,7 @@ class ParsedData(BaseModel):
     is_multi_audio: bool = False
     is_multi_subtitle: bool = False
     is_complete: bool = False
-    year: List[int] = []
+    year: int = 0
     resolution: List[str] = []
     quality: List[str] = []
     season: List[int] = []
@@ -25,15 +25,14 @@ class ParsedData(BaseModel):
     subtitles: List[str] = []
     language: List[str] = []
     bitDepth: List[int] = []
-    hdr: str | bool = False
+    hdr: str = ""
     proper: bool = False
     repack: bool = False
     remux: bool = False
     upscaled: bool = False
     remastered: bool = False
     directorsCut: bool = False
     extended: bool = False
-    excess: list = []
 
 
 class BaseRankingModel(BaseModel):

RTN/parser.py

@@ -1,5 +1,5 @@
 from concurrent.futures import ThreadPoolExecutor, as_completed
-from typing import Any, List
+from typing import Any, List, Tuple
 
 import Levenshtein
 import PTN
@@ -99,6 +99,11 @@ def rank(self, raw_title: str, infohash: str) -> Torrent:
             lev_ratio=Levenshtein.ratio(parsed_data.parsed_title.lower(), raw_title.lower()),
         )
 
+    def batch_rank(self, torrents: List[Tuple[str, str]], max_workers: int = 4) -> List[Torrent]:
+        """Ranks a batch of torrents in parallel using multiple threads."""
+        with ThreadPoolExecutor(max_workers=max_workers) as executor:
+            return list(executor.map(lambda t: self.rank(t[0], t[1]), torrents))
+
 
 def parse(raw_title: str) -> ParsedData:
     """
@@ -114,6 +119,7 @@ def parse(raw_title: str) -> ParsedData:
         raise TypeError("The input title must be a non-empty string.")
 
     parsed_dict: dict[str, Any] = PTN.parse(raw_title, coherent_types=True)
+    parsed_dict["year"] = parsed_dict["year"][0] if parsed_dict.get("year") else 0
     extras: dict[str, Any] = parse_extras(raw_title)
     full_data = {**parsed_dict, **extras}  # Merge PTN parsed data with RTN extras.
     full_data["raw_title"] = raw_title

RTN/patterns.py

@@ -221,6 +221,6 @@ def parse_extras(raw_title: str) -> Dict[str, Any]:
         "is_multi_audio": check_pattern(MULTI_AUDIO_COMPILED, raw_title),
         "is_multi_subtitle": check_pattern(MULTI_SUBTITLE_COMPILED, raw_title),
         "is_complete": check_pattern(COMPLETE_SERIES_COMPILED, raw_title),
-        "hdr": check_hdr_dolby_video(raw_title) or False,
+        "hdr": check_hdr_dolby_video(raw_title) or "",
         "episode": extract_episodes(raw_title),
     }

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "rank-torrent-name"
-version = "0.1.4"
+version = "0.1.5"
 description = "Parse Torrents using PTN and Rank them according to your preferences!"
 authors = ["Spoked <dreu.lavelle@gmail.com>"]
 license = "MIT"