import gradio as gr from pathlib import Path import os import shutil import re from PyPDF2 import PdfReader, PdfWriter import pandas as pd import camelot import openpyxl from openpyxl.utils.dataframe import dataframe_to_rows from openpyxl.styles import numbers from openpyxl.worksheet.table import Table, TableStyleInfo def extract_pages(pdf_path, start_page, end_page, output_path): reader = PdfReader(pdf_path) writer = PdfWriter() for page_num in range(start_page, end_page + 1): if page_num <= len(reader.pages): writer.add_page(reader.pages[page_num - 1]) with open(output_path, 'wb') as output_pdf_file: writer.write(output_pdf_file) def reduce_pdf(pdf_folder,reduced_pdf_folder): if not os.path.exists(reduced_pdf_folder): os.makedirs(reduced_pdf_folder) for filename in os.listdir(pdf_folder): if filename.endswith('.pdf'): match = re.search(r'(\d+)-(\d+)', filename) if match: start_page = int(match.group(1)) end_page = int(match.group(2)) base_name = re.sub(r'_\d+-\d+\.pdf$', '.pdf', filename) pdf_path = os.path.join(pdf_folder, filename) output_path = os.path.join(reduced_pdf_folder, base_name) extract_pages(pdf_path, start_page, end_page, output_path) print(f'Processed {filename} -> {base_name}') def extract_tables_camelot(pdf_path): # Extract tables from the PDF file using Camelot tables = camelot.read_pdf(pdf_path, pages='all',flavor='stream') return tables def get_numeric_count(row): # Get the number of numerical values in a row return sum(1 for x in row if (pd.notna(pd.to_numeric(x.replace(",", "").strip('()'), errors='coerce')) or x in ['-','–'])) def convert_to_numeric(value): if isinstance(value, str) and value.startswith('(') and value.endswith(')'): value = '-' + value[1:-1] if all(char.isdigit() or char in '-,.' for char in str(value)): cleaned_value = pd.to_numeric(value.replace(',', ''), errors='coerce') return cleaned_value return value def get_headers(dataframes): # Get the dataframe columns name if len(dataframes) >= 2: df_for_columns_names = dataframes[1] else: df_for_columns_names = dataframes[0] for i, row in df_for_columns_names.iterrows(): numeric_count = get_numeric_count(row) if numeric_count >= 2: first_numeric_idx = i break df_for_columns_names = df_for_columns_names.astype(str).where(pd.notna(df_for_columns_names), "") new_header = [" ".join(filter(None, df_for_columns_names.iloc[:first_numeric_idx, col].values)) for col in range(df_for_columns_names.shape[1])] return new_header def clean_dataframe(df,header): # Rule : if a row is not numerical, merge it with the next numerical one df.columns = header first_numeric_idx = None for i, row in df.iterrows(): numeric_count = get_numeric_count(row) if numeric_count >= 2: first_numeric_idx = i break df = df.iloc[first_numeric_idx:] df = df.reset_index(drop=True) merged_rows = [] buffer = None for i in range(len(df)): row = df.iloc[i] numeric_count = get_numeric_count(row) if numeric_count < 2: if buffer is None: buffer = list(df.iloc[i].copy()) else: buffer = [ " ".join(filter(lambda x: x not in [None, "None", ""], [buffer[j], df.iloc[i, j]])) for j in range(df.shape[1]) ] merged_rows.append(i) else: if buffer is not None: df.iloc[i] = [ " ".join(filter(lambda x: x not in [None, "None", ""], [buffer[j], df.iloc[i, j]])) for j in range(df.shape[1]) ] buffer = None clean_df = df.drop(merged_rows).reset_index(drop=True) return clean_df def clean_and_concatenate_tables(tables): dataframes = [table.df for table in tables] for i in range(len(dataframes)): df = dataframes[i] row_counts = df.apply(lambda row: row.notna().sum() - (row.astype(str) == "").sum(), axis=1) col_counts = df.apply(lambda col: col.notna().sum() - (col.astype(str) == "").sum(), axis=0) dataframes[i] = df.loc[row_counts >= 1, col_counts >= 3].reset_index(drop = True) new_header = get_headers(dataframes) cleaned_dfs = [] for df in dataframes: cleaned_dfs.append(clean_dataframe(df,new_header)) concatenated_df = pd.concat(cleaned_dfs, ignore_index=True) return concatenated_df def convert_to_excel(reduced_pdf_folder, output_folder): if not os.path.exists(output_folder): os.makedirs(output_folder) for filename in os.listdir(reduced_pdf_folder): if filename.endswith('.pdf'): pdf_path = os.path.join(reduced_pdf_folder, filename) tables = extract_tables_camelot(pdf_path) if tables: concatenated_df = clean_and_concatenate_tables(tables) excel_path = os.path.join(output_folder, filename.replace('.pdf', '.xlsx')) for col in concatenated_df.columns: concatenated_df[col] = concatenated_df[col].apply(convert_to_numeric) wb = openpyxl.Workbook() ws = wb.active percentage_cells = [] # Add the DataFrame data to the worksheet for r_idx, r in enumerate(dataframe_to_rows(concatenated_df, index=False, header=True)): ws.append(r) for c_idx, value in enumerate(r): if isinstance(value, str) and value.endswith('%'): numeric_value = pd.to_numeric(value.strip('%'), errors='coerce') / 100 ws.cell(row=r_idx + 1, column=c_idx + 1, value=numeric_value) percentage_cells.append((r_idx + 1, c_idx + 1)) tab = Table(displayName = "Table1",ref=ws.dimensions) style = TableStyleInfo( name="TableStyleMedium9", showFirstColumn=False, showLastColumn=False, showRowStripes=True, showColumnStripes=True ) tab.tableStyleInfo = style ws.add_table(tab) # Ajuster la largeur des colonnes for column_cells in ws.columns: length = min(max(len(str(cell.value)) for cell in column_cells),30) ws.column_dimensions[column_cells[0].column_letter].width = length + 2 for row, col in percentage_cells: cell = ws.cell(row=row, column=col) cell.number_format = numbers.BUILTIN_FORMATS[10] wb.save(excel_path) print(f'Saved {filename} as Excel file') else: print(f'No tables found in {filename}') shutil.make_archive(base_name="./output", format='zip', root_dir="./outputs") def reduce_and_convert(input_folder): reduced_pdf_folder = "./reduced_pdf" output_folder = './outputs' reduce_pdf(input_folder,reduced_pdf_folder) convert_to_excel(reduced_pdf_folder, output_folder) def ui(input_folder): zip_path = reduce_and_convert(input_folder) zip_path = "./output.zip" return zip_path with gr.Blocks() as appli: gr.Markdown("## PDF Reduction & Conversion Tool") input_folder = gr.Textbox(label="Enter Input Folder Path") process_button = gr.Button("Process Files") download_link = gr.File(label="Download Processed Zip") process_button.click(fn=ui, inputs=input_folder, outputs=download_link) appli.launch()