Spaces:
Running
Running
Reorganisation of files
Browse files- README.md +4 -0
- app.py +1 -207
- reduce_and_convert_PDF.py +211 -0
README.md
CHANGED
@@ -12,3 +12,7 @@ short_description: Convert CbCR to Excel using camelot and manual treatement
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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---
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Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
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This program accept folder as input and returns a .zip file with the corresponding excel files.
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The file names should include the name "CbCR" followed by the indices of the pages where the CbCR tables are located. If it is splitted on several pages, a dash can be used (for example Acciona_2023_CbCR_176.pdf, or Shell_2023_CbCR_55-57.pdf)
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app.py
CHANGED
@@ -1,214 +1,8 @@
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import gradio as gr
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import os
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import shutil
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import re
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from PyPDF2 import PdfReader, PdfWriter
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import pandas as pd
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import camelot
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import openpyxl
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from openpyxl.utils.dataframe import dataframe_to_rows
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from openpyxl.styles import numbers
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from openpyxl.worksheet.table import Table, TableStyleInfo
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import tempfile
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def extract_pages(pdf_path, start_page, end_page, output_path):
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reader = PdfReader(pdf_path)
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writer = PdfWriter()
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for page_num in range(start_page, end_page + 1):
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if page_num <= len(reader.pages):
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writer.add_page(reader.pages[page_num - 1])
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with open(output_path, 'wb') as output_pdf_file:
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writer.write(output_pdf_file)
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def reduce_pdf(pdf_folder,reduced_pdf_folder):
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if os.path.exists(reduced_pdf_folder):
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shutil.rmtree(reduced_pdf_folder)
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os.makedirs(reduced_pdf_folder)
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for filename in os.listdir(pdf_folder):
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if filename.endswith('.pdf'):
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match = re.search(r'_CbCR_(\d+)(?:-(\d+))?', filename)
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if match:
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start_page = int(match.group(1))
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end_page = int(match.group(2)) if match.group(2) else start_page
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base_name = re.sub(r'_CbCR_\d+(?:-\d+)?\.pdf$', '_CbCR.pdf', filename)
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pdf_path = os.path.join(pdf_folder, filename)
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output_path = os.path.join(reduced_pdf_folder, base_name)
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extract_pages(pdf_path, start_page, end_page, output_path)
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print(f'Processed {filename} -> {base_name}')
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def extract_tables_camelot(pdf_path):
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# Extract tables from the PDF file using Camelot
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tables = camelot.read_pdf(pdf_path, pages='all',flavor='stream')
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return tables
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def get_numeric_count(row):
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# Get the number of numerical values in a row
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return sum(1 for x in row if (pd.notna(pd.to_numeric(x.replace(",", "").strip('()'), errors='coerce')) or x in ['-','–']))
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def convert_to_numeric(value):
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if isinstance(value, str) and value.startswith('(') and value.endswith(')'):
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value = '-' + value[1:-1]
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if all(char.isdigit() or char in '-,.' for char in str(value)):
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cleaned_value = pd.to_numeric(value.replace(',', ''), errors='coerce')
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return cleaned_value
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return value
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def get_headers(dataframes):
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# Get the dataframe columns name
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if len(dataframes) >= 2:
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df_for_columns_names = dataframes[1]
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else:
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df_for_columns_names = dataframes[0]
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for i, row in df_for_columns_names.iterrows():
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numeric_count = get_numeric_count(row)
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if numeric_count >= 2:
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first_numeric_idx = i
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break
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df_for_columns_names = df_for_columns_names.astype(str).where(pd.notna(df_for_columns_names), "")
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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])]
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return new_header
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def clean_dataframe(df,header):
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# Rule : if a row is not numerical, merge it with the next numerical one
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df.columns = header
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first_numeric_idx = None
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for i, row in df.iterrows():
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numeric_count = get_numeric_count(row)
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if numeric_count >= 2:
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first_numeric_idx = i
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break
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df = df.iloc[first_numeric_idx:]
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df = df.reset_index(drop=True)
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merged_rows = []
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buffer = None
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for i in range(len(df)):
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row = df.iloc[i]
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numeric_count = get_numeric_count(row)
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if numeric_count < 2:
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if buffer is None:
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buffer = list(df.iloc[i].copy())
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else:
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buffer = [
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" ".join(filter(lambda x: x not in [None, "None", ""], [buffer[j], df.iloc[i, j]]))
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for j in range(df.shape[1])
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]
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merged_rows.append(i)
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else:
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if buffer is not None:
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df.iloc[i] = [
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" ".join(filter(lambda x: x not in [None, "None", ""], [buffer[j], df.iloc[i, j]]))
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for j in range(df.shape[1])
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]
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buffer = None
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clean_df = df.drop(merged_rows).reset_index(drop=True)
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return clean_df
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def clean_and_concatenate_tables(tables):
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dataframes = [table.df for table in tables]
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for i in range(len(dataframes)):
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df = dataframes[i]
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row_counts = df.apply(lambda row: row.notna().sum() - (row.astype(str) == "").sum(), axis=1)
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col_counts = df.apply(lambda col: col.notna().sum() - (col.astype(str) == "").sum(), axis=0)
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dataframes[i] = df.loc[row_counts >= 1, col_counts >= 3].reset_index(drop = True)
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new_header = get_headers(dataframes)
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cleaned_dfs = []
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for df in dataframes:
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cleaned_dfs.append(clean_dataframe(df,new_header))
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concatenated_df = pd.concat(cleaned_dfs, ignore_index=True)
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return concatenated_df
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def convert_to_excel(reduced_pdf_folder, output_folder):
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if os.path.exists(output_folder):
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shutil.rmtree(output_folder)
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os.makedirs(output_folder)
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for filename in os.listdir(reduced_pdf_folder):
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if filename.endswith('.pdf'):
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pdf_path = os.path.join(reduced_pdf_folder, filename)
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tables = extract_tables_camelot(pdf_path)
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if tables:
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concatenated_df = clean_and_concatenate_tables(tables)
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excel_path = os.path.join(output_folder, filename.replace('.pdf', '.xlsx'))
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for col in concatenated_df.columns:
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if any(str(cell).strip() and not str(cell).strip().startswith('(') for cell in concatenated_df[col]):
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concatenated_df[col] = concatenated_df[col].apply(convert_to_numeric)
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wb = openpyxl.Workbook()
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ws = wb.active
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percentage_cells = []
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# Add the DataFrame data to the worksheet
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for r_idx, r in enumerate(dataframe_to_rows(concatenated_df, index=False, header=True)):
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ws.append(r)
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for c_idx, value in enumerate(r):
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if isinstance(value, str) and value.endswith('%'):
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numeric_value = pd.to_numeric(value.strip('%'), errors='coerce') / 100
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ws.cell(row=r_idx + 1, column=c_idx + 1, value=numeric_value)
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percentage_cells.append((r_idx + 1, c_idx + 1))
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tab = Table(displayName = "Table1",ref=ws.dimensions)
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style = TableStyleInfo(
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name="TableStyleMedium9",
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showFirstColumn=False,
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showLastColumn=False,
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showRowStripes=True,
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showColumnStripes=True
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)
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tab.tableStyleInfo = style
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ws.add_table(tab)
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# Ajuster la largeur des colonnes
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for column_cells in ws.columns:
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length = min(max(len(str(cell.value)) for cell in column_cells),30)
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ws.column_dimensions[column_cells[0].column_letter].width = length + 2
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for row, col in percentage_cells:
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cell = ws.cell(row=row, column=col)
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cell.number_format = numbers.BUILTIN_FORMATS[10]
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wb.save(excel_path)
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print(f'Saved {filename} as Excel file')
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else:
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print(f'No tables found in {filename}')
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shutil.make_archive(base_name="./output", format='zip', root_dir="./outputs")
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def reduce_and_convert(input_folder):
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reduced_pdf_folder = "./reduced_pdf"
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output_folder = './outputs'
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reduce_pdf(input_folder,reduced_pdf_folder)
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convert_to_excel(reduced_pdf_folder, output_folder)
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def clear_gradio_temp(exclude_files):
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temp_dir = tempfile.gettempdir()
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import gradio as gr
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import os
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import shutil
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import tempfile
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from reduce_and_convert_PDF import reduce_and_convert
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def clear_gradio_temp(exclude_files):
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temp_dir = tempfile.gettempdir()
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reduce_and_convert_PDF.py
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1 |
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import os
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2 |
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import shutil
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3 |
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import re
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4 |
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from PyPDF2 import PdfReader, PdfWriter
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5 |
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import pandas as pd
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6 |
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import camelot
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7 |
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import openpyxl
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8 |
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from openpyxl.utils.dataframe import dataframe_to_rows
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9 |
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from openpyxl.styles import numbers
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10 |
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from openpyxl.worksheet.table import Table, TableStyleInfo
|
11 |
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12 |
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def extract_pages(pdf_path, start_page, end_page, output_path):
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13 |
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reader = PdfReader(pdf_path)
|
14 |
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writer = PdfWriter()
|
15 |
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for page_num in range(start_page, end_page + 1):
|
16 |
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if page_num <= len(reader.pages):
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17 |
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writer.add_page(reader.pages[page_num - 1])
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18 |
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19 |
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with open(output_path, 'wb') as output_pdf_file:
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20 |
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writer.write(output_pdf_file)
|
21 |
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22 |
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|
23 |
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def reduce_pdf(pdf_folder,reduced_pdf_folder):
|
24 |
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if os.path.exists(reduced_pdf_folder):
|
25 |
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shutil.rmtree(reduced_pdf_folder)
|
26 |
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os.makedirs(reduced_pdf_folder)
|
27 |
+
|
28 |
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for filename in os.listdir(pdf_folder):
|
29 |
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if filename.endswith('.pdf'):
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30 |
+
match = re.search(r'_CbCR_(\d+)(?:-(\d+))?', filename)
|
31 |
+
if match:
|
32 |
+
start_page = int(match.group(1))
|
33 |
+
end_page = int(match.group(2)) if match.group(2) else start_page
|
34 |
+
base_name = re.sub(r'_CbCR_\d+(?:-\d+)?\.pdf$', '_CbCR.pdf', filename)
|
35 |
+
pdf_path = os.path.join(pdf_folder, filename)
|
36 |
+
output_path = os.path.join(reduced_pdf_folder, base_name)
|
37 |
+
|
38 |
+
extract_pages(pdf_path, start_page, end_page, output_path)
|
39 |
+
print(f'Processed {filename} -> {base_name}')
|
40 |
+
|
41 |
+
|
42 |
+
|
43 |
+
|
44 |
+
|
45 |
+
def extract_tables_camelot(pdf_path):
|
46 |
+
# Extract tables from the PDF file using Camelot
|
47 |
+
tables = camelot.read_pdf(pdf_path, pages='all',flavor='stream')
|
48 |
+
return tables
|
49 |
+
|
50 |
+
def get_numeric_count(row):
|
51 |
+
# Get the number of numerical values in a row
|
52 |
+
return sum(1 for x in row if (pd.notna(pd.to_numeric(x.replace(",", "").strip('()'), errors='coerce')) or x in ['-','–']))
|
53 |
+
|
54 |
+
|
55 |
+
def convert_to_numeric(value):
|
56 |
+
if isinstance(value, str) and value.startswith('(') and value.endswith(')'):
|
57 |
+
value = '-' + value[1:-1]
|
58 |
+
|
59 |
+
if all(char.isdigit() or char in '-,.' for char in str(value)):
|
60 |
+
cleaned_value = pd.to_numeric(value.replace(',', ''), errors='coerce')
|
61 |
+
return cleaned_value
|
62 |
+
return value
|
63 |
+
|
64 |
+
def get_headers(dataframes):
|
65 |
+
# Get the dataframe columns name
|
66 |
+
if len(dataframes) >= 2:
|
67 |
+
df_for_columns_names = dataframes[1]
|
68 |
+
else:
|
69 |
+
df_for_columns_names = dataframes[0]
|
70 |
+
for i, row in df_for_columns_names.iterrows():
|
71 |
+
numeric_count = get_numeric_count(row)
|
72 |
+
if numeric_count >= 2:
|
73 |
+
first_numeric_idx = i
|
74 |
+
break
|
75 |
+
|
76 |
+
df_for_columns_names = df_for_columns_names.astype(str).where(pd.notna(df_for_columns_names), "")
|
77 |
+
|
78 |
+
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])]
|
79 |
+
|
80 |
+
return new_header
|
81 |
+
|
82 |
+
def clean_dataframe(df,header):
|
83 |
+
# Rule : if a row is not numerical, merge it with the next numerical one
|
84 |
+
df.columns = header
|
85 |
+
first_numeric_idx = None
|
86 |
+
for i, row in df.iterrows():
|
87 |
+
numeric_count = get_numeric_count(row)
|
88 |
+
if numeric_count >= 2:
|
89 |
+
first_numeric_idx = i
|
90 |
+
break
|
91 |
+
|
92 |
+
df = df.iloc[first_numeric_idx:]
|
93 |
+
df = df.reset_index(drop=True)
|
94 |
+
|
95 |
+
merged_rows = []
|
96 |
+
buffer = None
|
97 |
+
|
98 |
+
for i in range(len(df)):
|
99 |
+
row = df.iloc[i]
|
100 |
+
numeric_count = get_numeric_count(row)
|
101 |
+
|
102 |
+
if numeric_count < 2:
|
103 |
+
if buffer is None:
|
104 |
+
buffer = list(df.iloc[i].copy())
|
105 |
+
else:
|
106 |
+
buffer = [
|
107 |
+
" ".join(filter(lambda x: x not in [None, "None", ""], [buffer[j], df.iloc[i, j]]))
|
108 |
+
for j in range(df.shape[1])
|
109 |
+
]
|
110 |
+
merged_rows.append(i)
|
111 |
+
else:
|
112 |
+
if buffer is not None:
|
113 |
+
df.iloc[i] = [
|
114 |
+
" ".join(filter(lambda x: x not in [None, "None", ""], [buffer[j], df.iloc[i, j]]))
|
115 |
+
for j in range(df.shape[1])
|
116 |
+
]
|
117 |
+
buffer = None
|
118 |
+
|
119 |
+
clean_df = df.drop(merged_rows).reset_index(drop=True)
|
120 |
+
return clean_df
|
121 |
+
|
122 |
+
|
123 |
+
def clean_and_concatenate_tables(tables):
|
124 |
+
dataframes = [table.df for table in tables]
|
125 |
+
|
126 |
+
for i in range(len(dataframes)):
|
127 |
+
df = dataframes[i]
|
128 |
+
row_counts = df.apply(lambda row: row.notna().sum() - (row.astype(str) == "").sum(), axis=1)
|
129 |
+
col_counts = df.apply(lambda col: col.notna().sum() - (col.astype(str) == "").sum(), axis=0)
|
130 |
+
dataframes[i] = df.loc[row_counts >= 1, col_counts >= 3].reset_index(drop = True)
|
131 |
+
|
132 |
+
new_header = get_headers(dataframes)
|
133 |
+
|
134 |
+
cleaned_dfs = []
|
135 |
+
|
136 |
+
for df in dataframes:
|
137 |
+
cleaned_dfs.append(clean_dataframe(df,new_header))
|
138 |
+
|
139 |
+
concatenated_df = pd.concat(cleaned_dfs, ignore_index=True)
|
140 |
+
return concatenated_df
|
141 |
+
|
142 |
+
|
143 |
+
def convert_to_excel(reduced_pdf_folder, output_folder):
|
144 |
+
if os.path.exists(output_folder):
|
145 |
+
shutil.rmtree(output_folder)
|
146 |
+
os.makedirs(output_folder)
|
147 |
+
|
148 |
+
for filename in os.listdir(reduced_pdf_folder):
|
149 |
+
if filename.endswith('.pdf'):
|
150 |
+
pdf_path = os.path.join(reduced_pdf_folder, filename)
|
151 |
+
tables = extract_tables_camelot(pdf_path)
|
152 |
+
if tables:
|
153 |
+
concatenated_df = clean_and_concatenate_tables(tables)
|
154 |
+
|
155 |
+
excel_path = os.path.join(output_folder, filename.replace('.pdf', '.xlsx'))
|
156 |
+
|
157 |
+
for col in concatenated_df.columns:
|
158 |
+
if any(str(cell).strip() and not str(cell).strip().startswith('(') for cell in concatenated_df[col]):
|
159 |
+
concatenated_df[col] = concatenated_df[col].apply(convert_to_numeric)
|
160 |
+
|
161 |
+
wb = openpyxl.Workbook()
|
162 |
+
ws = wb.active
|
163 |
+
|
164 |
+
percentage_cells = []
|
165 |
+
|
166 |
+
# Add the DataFrame data to the worksheet
|
167 |
+
for r_idx, r in enumerate(dataframe_to_rows(concatenated_df, index=False, header=True)):
|
168 |
+
ws.append(r)
|
169 |
+
for c_idx, value in enumerate(r):
|
170 |
+
if isinstance(value, str) and value.endswith('%'):
|
171 |
+
numeric_value = pd.to_numeric(value.strip('%'), errors='coerce') / 100
|
172 |
+
ws.cell(row=r_idx + 1, column=c_idx + 1, value=numeric_value)
|
173 |
+
percentage_cells.append((r_idx + 1, c_idx + 1))
|
174 |
+
|
175 |
+
tab = Table(displayName = "Table1",ref=ws.dimensions)
|
176 |
+
style = TableStyleInfo(
|
177 |
+
name="TableStyleMedium9",
|
178 |
+
showFirstColumn=False,
|
179 |
+
showLastColumn=False,
|
180 |
+
showRowStripes=True,
|
181 |
+
showColumnStripes=True
|
182 |
+
)
|
183 |
+
tab.tableStyleInfo = style
|
184 |
+
|
185 |
+
ws.add_table(tab)
|
186 |
+
|
187 |
+
# Ajuster la largeur des colonnes
|
188 |
+
for column_cells in ws.columns:
|
189 |
+
length = min(max(len(str(cell.value)) for cell in column_cells),30)
|
190 |
+
ws.column_dimensions[column_cells[0].column_letter].width = length + 2
|
191 |
+
|
192 |
+
for row, col in percentage_cells:
|
193 |
+
cell = ws.cell(row=row, column=col)
|
194 |
+
cell.number_format = numbers.BUILTIN_FORMATS[10]
|
195 |
+
wb.save(excel_path)
|
196 |
+
print(f'Saved {filename} as Excel file')
|
197 |
+
else:
|
198 |
+
print(f'No tables found in {filename}')
|
199 |
+
shutil.make_archive(base_name="./output", format='zip', root_dir="./outputs")
|
200 |
+
|
201 |
+
|
202 |
+
def reduce_and_convert(input_folder):
|
203 |
+
reduced_pdf_folder = "./reduced_pdf"
|
204 |
+
output_folder = './outputs'
|
205 |
+
reduce_pdf(input_folder,reduced_pdf_folder)
|
206 |
+
convert_to_excel(reduced_pdf_folder, output_folder)
|
207 |
+
|
208 |
+
|
209 |
+
if __name__ == "__main__":
|
210 |
+
input_folder = "../example_pdf"
|
211 |
+
reduce_and_convert(input_folder)
|