yolo

output_dataset.parquet

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
-oid sha256:1a670b3dc111fe3c5c2522545ba62b74df0da6beb2b1d413ba574f983728ebdf
+oid sha256:c49abfa2591aac4b75847bb0f31e4ed5581eb94727308af9c5c6c31657d4946c
 size 22475137

par.py

@@ -8,44 +8,45 @@ import base64
 
 def encode_file(file_path):
     """Encode text files or base64 encode image files."""
-    try:
-        if file_path.endswith('.jpg'):
-            with open(file_path, "rb") as image_file:
-                return base64.b64encode(image_file.read()).decode('utf-8')
-        else:
+    if file_path.endswith('.jpg'):
+        with open(file_path, "rb") as image_file:
+            return base64.b64encode(image_file.read()).decode('utf-8')
+    else:
+        try:
             with open(file_path, 'r', encoding='utf-8') as file:
                 return file.read()
-    except UnicodeDecodeError as e:
-        print(f"Error decoding file {file_path}: {e}")
-        return None
+        except UnicodeDecodeError as e:
+            print(f"Error decoding file {file_path}: {e}")
+            return None
 
 def extract_images(markdown_content):
     """Extract PHOTO_IDs from markdown files and return as a list."""
     return re.findall(r'\{\{PHOTO_ID:(\d+)\|WIDTH:\d+\}\}', markdown_content)
 
 def collect_data(directory):
-    data = []
+    data = {}
     image_files = {re.search(r'(\d+)', filename).group(1): filename
                    for filename in os.listdir(directory) if filename.endswith('.jpg')}
 
+    # Iterate over all files in the directory and organize them by problem ID
     for filename in os.listdir(directory):
         problem_id = filename.split('.')[0]
-        if not any(d['Problem ID'] == problem_id for d in data):
-            data.append({'Problem ID': problem_id, 'Images': [], 'in': None, 'out': None, 'cpp': None, 'md': None, 'sol.md': None})
-
-        current_entry = next(item for item in data if item['Problem ID'] == problem_id)
         file_type = filename.split('.')[-1]
         file_path = os.path.join(directory, filename)
+
+        if problem_id not in data:
+            data[problem_id] = {'Problem ID': problem_id, 'Images': [], 'in': None, 'out': None, 'cpp': None, 'md': None, 'sol.md': None}
+
         if file_type in ['in', 'out', 'cpp', 'md', 'sol.md']:
             content = encode_file(file_path)
-            if content is not None:  # Make sure we successfully read the file
-                current_entry[file_type] = content
+            if content is not None:
+                data[problem_id][file_type] = content
                 if file_type in ['md', 'sol.md']:
                     image_ids = extract_images(content)
-                    current_entry['Images'] += [image_files[id] for id in image_ids if id in image_files]
-                    current_entry['Images'] = list(set(current_entry['Images']))  # Remove duplicates if any
+                    data[problem_id]['Images'] += [image_files[id] for id in image_ids if id in image_files]
+                    data[problem_id]['Images'] = list(set(data[problem_id]['Images']))  # Remove duplicates
 
-    return data
+    return list(data.values())
 
 def create_parquet_file(data, output_file):
     df = pd.DataFrame(data)