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import pdfplumber
import pandas as pd
import re
# Function: Extract Text from PDF
def extract_text_from_pdf(pdf_file):
with pdfplumber.open(pdf_file.name) as pdf:
text = ""
for page in pdf.pages:
text += page.extract_text()
return text
# Function: Parse PO Items
def parse_po_items(text):
"""
Parses purchase order items from the extracted text.
Handles split descriptions across lines and filters unwanted text.
"""
lines = text.splitlines()
data = []
current_item = {}
description_accumulator = []
for line in lines:
# Match the start of an item row
item_match = re.match(r"^(?P<Item>\d+)\s+(?P<Description>.+)", line)
if item_match:
# Save the previous item and start a new one
if current_item:
current_item["Description"] = " ".join(description_accumulator).strip()
data.append(current_item)
description_accumulator = []
current_item = {
"Item": item_match.group("Item"),
"Description": "",
"Qty": "",
"Unit": "",
"Unit Price": "",
"Total Price": "",
}
description_accumulator.append(item_match.group("Description"))
elif current_item:
# Handle additional description lines or split descriptions
description_accumulator.append(line.strip())
# Match Qty, Unit, Unit Price, and Total Price
qty_match = re.search(r"(?P<Qty>\d+)\s+(Nos\.|Set)", line)
if qty_match:
current_item["Qty"] = qty_match.group("Qty")
current_item["Unit"] = qty_match.group(2)
price_match = re.search(r"(?P<UnitPrice>[\d.]+)\s+(?P<TotalPrice>[\d.]+)$", line)
if price_match:
current_item["Unit Price"] = price_match.group("UnitPrice")
current_item["Total Price"] = price_match.group("TotalPrice")
# Save the last item
if current_item:
current_item["Description"] = " ".join(description_accumulator).strip()
data.append(current_item)
if not data:
return None, "No items found. Please check the PDF file format."
df = pd.DataFrame(data)
return df, "Data extracted successfully."
# Function: Save to Excel
def save_to_excel(df, output_path="bhel_extracted_data.xlsx"):
df.to_excel(output_path, index=False)
return output_path
# Main function to process PDF
def process_pdf(file):
try:
text = extract_text_from_pdf(file)
df, status = parse_po_items(text)
if df is not None:
output_path = save_to_excel(df)
return output_path, status
return None, status
except Exception as e:
return None, f"Error during processing: {str(e)}"
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