115 lines
3.7 KiB
Python
115 lines
3.7 KiB
Python
import logging
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from datetime import datetime
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from pathlib import Path
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import pandas as pd
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import pdfplumber
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from pdf_oralia.pages import charge, locataire, patrimoine
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extract_table_settings = {
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"vertical_strategy": "lines",
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"horizontal_strategy": "text",
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}
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def extract_date(page_text):
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"""Extract date from a page
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:param page_text: text in the page
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:return: the extracted date
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"""
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blocs = page_text.split("\n")
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for b in blocs:
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if "Lyon le" in b:
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words = b.split(" ")
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return datetime.strptime(words[-1], "%d/%m/%Y")
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def extract_building(page_text, buildings=["bloch", "marietton", "servient"]):
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for building in buildings:
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if building in page_text.lower():
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return building
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raise ValueError("Pas d'immeuble trouvé")
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def pdf_extract_tables_lines(pdf):
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loc_sink = locataire.fsm()
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next(loc_sink)
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charge_sink = charge.fsm()
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next(charge_sink)
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patrimoine_sink = patrimoine.fsm()
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next(patrimoine_sink)
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page_number = 1
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for page in pdf.pages:
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page_text = page.extract_text()
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date = extract_date(page_text)
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additionnal_fields = {
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"immeuble": extract_building(page_text),
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"mois": date.strftime("%m"),
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"annee": date.strftime("%Y"),
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}
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for line in page.extract_table(extract_table_settings):
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if locataire.is_it(page_text):
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res = loc_sink.send(line)
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if res:
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res.update(additionnal_fields)
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yield locataire.Line(**res)
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elif charge.is_it(page_text):
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res = charge_sink.send(line)
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if res:
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res.update(additionnal_fields)
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yield charge.Line(**res)
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elif patrimoine.is_it(page_text):
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res = patrimoine_sink.send(line)
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if res:
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res.update(additionnal_fields)
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yield patrimoine.Line(**res)
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else:
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logging.warning(f"Page {page_number} non reconnu. Page ignorée.")
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page_number += 1
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def from_pdf(pdf_file):
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"""Build dataframes one about charges and another on loc"""
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pdf = pdfplumber.open(pdf_file)
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locataire_lines = []
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charge_lines = []
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patrimoine_lines = []
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for line in pdf_extract_tables_lines(pdf):
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if isinstance(line, locataire.Line):
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locataire_lines.append(line)
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elif isinstance(line, charge.Line):
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charge_lines.append(line)
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elif isinstance(line, patrimoine.Line):
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patrimoine_lines.append(line)
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else:
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logging.warning(f"Page {page_number+1} non reconnu. Page ignorée.")
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return (
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pd.DataFrame([c.__dict__ for c in charge_lines]),
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pd.DataFrame([c.__dict__ for c in locataire_lines]),
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pd.DataFrame([c.__dict__ for c in patrimoine_lines]),
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)
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def extract_save(pdf_file, dest):
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"""Extract charge and locataire for pdf_file and put xlsx file in dest"""
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pdf_file = Path(pdf_file)
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xls_charge = Path(dest) / f"{pdf_file.stem.replace(' ', '_')}_charge.xlsx"
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xls_locataire = Path(dest) / f"{pdf_file.stem.replace(' ', '_')}_locataire.xlsx"
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xls_patrimoine = Path(dest) / f"{pdf_file.stem.replace(' ', '_')}_patrimoine.xlsx"
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df_charge, df_loc, df_patrimoine = from_pdf(pdf_file)
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df_charge.to_excel(xls_charge, sheet_name="Charges", index=False)
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logging.info(f"{xls_charge} saved")
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df_loc.to_excel(xls_locataire, sheet_name="Location", index=False)
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logging.info(f"{xls_locataire} saved")
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df_patrimoine.to_excel(xls_patrimoine, sheet_name="Patrimoine", index=False)
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logging.info(f"{xls_patrimoine} saved")
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