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neerajkalyank
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6d9fb15
1
Parent(s):
6e8ab5b
Update app.py
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app.py
CHANGED
@@ -2,6 +2,7 @@ import pdfplumber
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import pandas as pd
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import gradio as gr
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import re
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# Define function to extract data
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def extract_data(pdf_file):
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@@ -12,71 +13,84 @@ def extract_data(pdf_file):
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purchase_order_no = "Not Found"
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purchase_order_date = "Not Found"
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# Log warning if data was not found for Purchase Order No or Date
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if purchase_order_no == "Not Found" or purchase_order_date == "Not Found":
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print("Warning: 'Purchase Order No' or 'Date' was not found in the PDF.")
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import pandas as pd
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import gradio as gr
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import re
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import tempfile
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# Define function to extract data
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def extract_data(pdf_file):
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purchase_order_no = "Not Found"
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purchase_order_date = "Not Found"
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try:
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with pdfplumber.open(pdf_file) as pdf:
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for page in pdf.pages:
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text = page.extract_text()
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if not text:
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continue # Skip pages without text
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lines = text.splitlines()
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# Attempt to dynamically extract Purchase Order No and Date from the first page
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for line in lines:
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# Search for Purchase Order No
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po_match = re.search(r'Purchase Order No[:\s]+(\d+)', line, re.IGNORECASE)
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if po_match:
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purchase_order_no = po_match.group(1)
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# Search for Date
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date_match = re.search(r'Date[:\s]+(\d{2}\.\d{2}\.\d{4})', line, re.IGNORECASE)
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if date_match:
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purchase_order_date = date_match.group(1)
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# Stop if both values are found
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if purchase_order_no != "Not Found" and purchase_order_date != "Not Found":
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break
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# Process lines to extract row data, looking for rows that start with SI No
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for line in lines:
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try:
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# Match lines that start with an SI number (e.g., "10", "20")
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si_no_match = re.match(r'^(\d+)\s', line)
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if si_no_match:
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parts = line.split()
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# Extract SI No
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si_no = parts[0]
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# Extract Material Number and format the Material Description
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material_number = parts[2] if len(parts) > 2 else "Unknown"
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material_desc = f"BPS 017507\nMaterial Number: {material_number}\nHSN Code: 8310\nIGST: 18%"
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# Extract Unit, Quantity, Dely Qty, Dely Date, Unit Rate, and Value
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unit = parts[3] if len(parts) > 3 else "NO" # Default to "NO" if not found
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quantity = int(parts[4]) if len(parts) > 4 else 0
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dely_qty = int(parts[5]) if len(parts) > 5 else 0
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dely_date = parts[6] if len(parts) > 6 else "Unknown"
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unit_rate = float(parts[7]) if len(parts) > 7 else 0.0
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value = float(parts[8]) if len(parts) > 8 else 0.0
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# Append extracted data in the specified order
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data.append([
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purchase_order_no,
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purchase_order_date,
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si_no,
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material_desc,
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unit,
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quantity,
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dely_qty,
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dely_date,
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unit_rate,
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value
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])
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except (ValueError, IndexError) as e:
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print(f"Error processing line: {line} - {e}")
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continue # Skip lines that do not match the expected format
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# Convert data to DataFrame and save as Excel
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df = pd.DataFrame(data, columns=columns)
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# Generate a temporary file path for the Excel file
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with tempfile.NamedTemporaryFile(suffix=".xlsx", delete=False) as tmp_file:
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excel_path = tmp_file.name
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df.to_excel(excel_path, index=False)
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except Exception as e:
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print(f"An error occurred while processing the PDF: {e}")
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return None
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# Log warning if data was not found for Purchase Order No or Date
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if purchase_order_no == "Not Found" or purchase_order_date == "Not Found":
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print("Warning: 'Purchase Order No' or 'Date' was not found in the PDF.")
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