labels and stuff

app/services/pull_sheet_service.py

@@ -0,0 +1,83 @@
+from typing import List, Dict
+import pandas as pd
+from datetime import datetime
+from pathlib import Path
+from jinja2 import Environment, FileSystemLoader
+from weasyprint import HTML
+import logging
+
+logger = logging.getLogger(__name__)
+
+class PullSheetService:
+    def __init__(self):
+        self.template_dir = Path("app/data/assets/templates")
+        self.env = Environment(loader=FileSystemLoader(str(self.template_dir)))
+        self.template = self.env.get_template("pull_sheet.html")
+        self.output_dir = Path("app/data/cache/tcgplayer/pull_sheets")
+        self.output_dir.mkdir(parents=True, exist_ok=True)
+        
+    def generate_pull_sheet_pdf(self, csv_path: str) -> str:
+        """Generate a PDF pull sheet from a CSV file.
+        
+        Args:
+            csv_path: Path to the CSV file containing pull sheet data
+            
+        Returns:
+            Path to the generated PDF file
+        """
+        try:
+            # Read and process CSV data
+            items = self._read_and_process_csv(csv_path)
+            
+            # Prepare template data
+            template_data = {
+                'items': items,
+                'generation_date': datetime.now().strftime("%Y-%m-%d %H:%M:%S")
+            }
+            
+            # Render HTML
+            html_content = self.template.render(**template_data)
+            
+            # Generate PDF
+            pdf_path = self.output_dir / f"pull_sheet_{datetime.now().strftime('%Y%m%d_%H%M%S')}.pdf"
+            HTML(string=html_content).write_pdf(str(pdf_path))
+            
+            return str(pdf_path)
+            
+        except Exception as e:
+            logger.error(f"Error generating pull sheet PDF: {str(e)}")
+            raise
+            
+    def _read_and_process_csv(self, csv_path: str) -> List[Dict]:
+        """Read and process CSV data using pandas.
+        
+        Args:
+            csv_path: Path to the CSV file
+            
+        Returns:
+            List of processed items
+        """
+        # Read CSV into pandas DataFrame
+        df = pd.read_csv(csv_path)
+        
+        # Filter out the "Orders Contained in Pull Sheet" row
+        df = df[df['Product Line'] != 'Orders Contained in Pull Sheet:']
+        
+        # Convert Set Release Date to datetime
+        df['Set Release Date'] = pd.to_datetime(df['Set Release Date'], format='%m/%d/%Y %H:%M:%S')
+        
+        # Sort by Set Release Date (descending) and then Product Name (ascending)
+        df = df.sort_values(['Set Release Date', 'Product Name'], ascending=[False, True])
+        
+        # Convert to list of dictionaries
+        items = []
+        for _, row in df.iterrows():
+            items.append({
+                'product_name': row['Product Name'],
+                'condition': row['Condition'],
+                'quantity': str(int(row['Quantity'])),  # Convert to string for template
+                'set': row['Set'],
+                'rarity': row['Rarity']
+            })
+                
+        return items