Upload 2 files

bin/export_structured_data.py

@@ -14,6 +14,7 @@ T = TypeVar("T")
 
 detector = gcld3.NNetLanguageIdentifier(min_num_bytes=20, max_num_bytes=1000)
 
+
 def batch_iterator(iterator: Iterator[T], batch_size: int = 50) -> Iterator[List[T]]:
     """
     Batch an iterator into an iterator over lists of batch size.
@@ -39,19 +40,31 @@ def process_chunk(chunk: List, extractor: jmespath.parser.ParsedResult) -> List[
                 extracted = [extracted]
 
             try:
-                extracted_str = " ".join(set([ex for ex in extracted if isinstance(ex, str)])).strip()
+                extracted_str = " ".join(
+                    set([ex for ex in extracted if isinstance(ex, str)])
+                ).strip()
             except:
                 print(json.dumps(data, ensure_ascii=False))
                 raise
 
             lang = detector.FindLanguage(extracted_str)
-            data["language"] = lang.language
-            data["language_is_reliable"] = lang.is_reliable
-            data["text_length"] = len(extracted_str)
-            data["data_length"] = len(line)
-            data["text_to_data_ratio"] = len(extracted_str) / len(line)
-
-            results.append(data)
+            url = data["url"]
+            schema_type = data["schema_type"]
+            del data["url"]
+            del data["schema_type"]
+
+            wrapped_data = {
+                "payload": data,
+                "language": lang.language,
+                "language_is_reliable": lang.is_reliable,
+                "text_length": len(extracted_str),
+                "data_length": len(line),
+                "text_to_data_ratio": len(extracted_str) / len(line),
+                "url": url,
+                "schema_type": schema_type,
+            }
+
+            results.append(wrapped_data)
 
     return results
 
@@ -73,9 +86,7 @@ def process_file(
     """
     with smart_open.open(output_file, "wt", encoding="utf-8") as writer:
         for input_file in input_files:
-            with smart_open.open(
-                input_file, "rt", encoding="utf-8"
-            ) as reader:
+            with smart_open.open(input_file, "rt", encoding="utf-8") as reader:
                 with ThreadPoolExecutor(max_workers=num_threads) as executor:
                     for chunk in batch_iterator(tqdm(reader), batch_size=chunk_size):
                         if not chunk:

bin/get_stats.py

@@ -19,8 +19,8 @@ if __name__ == "__main__":
 
     with smart_open.open(args.input_file, "rt", encoding="utf-8") as reader:
         for item in tqdm(map(json.loads, reader)):
-            stats[item["language"]][f"{item['@type']} count"] += 1
-            stats[item["language"]][f"{item['@type']} text length"] += item[
+            stats[item["language"]][f"{item['payload']['@type']} count"] += 1
+            stats[item["language"]][f"{item['payload']['@type']} text length"] += item[
                 "text_length"
             ]