167 lines
4.3 KiB
Python
167 lines
4.3 KiB
Python
import numpy as np
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import pandas as pd
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DF_TYPES = {
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"Locataires": str,
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"Période": str,
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"Loyers": float,
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"Taxes": float,
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"Provisions": float,
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"Divers": str,
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"Total": float,
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"Réglés": float,
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"Impayés": float,
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"immeuble": str,
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"mois": str,
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"annee": str,
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"Lot": str,
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"Type": str,
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}
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def is_it(page_text):
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if "SITUATION DES LOCATAIRES" in page_text:
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return True
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return False
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def is_drop(row):
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if "totaux" in row[0].lower():
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return True
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if not any(row):
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return True
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return False
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def extract(table, additionnal_fields: dict = {}):
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"""Turn table to dictionary with additional fields"""
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extracted = []
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header = table[0]
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for row in table[1:]:
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if not is_drop(row):
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r = dict()
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for i, value in enumerate(row):
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if header[i] != "":
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r[header[i]] = value
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for k, v in additionnal_fields.items():
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r[k] = v
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extracted.append(r)
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return extracted
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def join_row(last, next):
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row = {}
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for key in last:
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if last[key] == next[key]:
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row[key] = last[key]
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elif last[key] and next[key]:
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row[key] = f"{last[key]}\n{next[key]}"
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elif last[key]:
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row[key] = last[key]
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elif next[key]:
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row[key] = next[key]
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else:
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row[key] = ""
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return row
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def join_tables(tables):
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joined = tables[0]
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for t in tables[1:]:
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last_row = joined[-1]
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if "totaux" not in last_row["Locataires"].lower():
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first_row = t[0]
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joined_row = join_row(last_row, first_row)
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joined = joined[:-1] + [joined_row] + t[1:]
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else:
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joined += t
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return joined
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def parse_lot(string):
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words = string.split(" ")
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return {"Lot": "{:02d}".format(int(words[1])), "Type": " ".join(words[2:])}
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def clean_type(string):
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if "appartement" in string.lower():
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return string[-2:]
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return string
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def join_row(table):
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joined = []
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for row in table:
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if row["Locataires"].startswith("Lot"):
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row.update(parse_lot(row["Locataires"]))
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row["Locataires"] = ""
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joined.append(row)
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elif row["Locataires"] == "Rappel de Loyer":
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last_row = joined[-1]
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row.update(
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{
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"Lot": last_row["Lot"],
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"Type": last_row["Type"],
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"Locataires": last_row["Locataires"],
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"Divers": "Rappel de Loyer",
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}
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)
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joined.append(row)
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elif row["Locataires"]:
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last_row = joined.pop()
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row_name = row["Locataires"].replace("\n", " ")
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row.update({k: v for k, v in last_row.items() if v})
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row["Locataires"] = last_row["Locataires"] + " " + row_name
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joined.append(row)
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else:
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if row["Période"].startswith("Solde"):
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last_row = joined.pop()
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row.update(
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{
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"Lot": last_row["Lot"],
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"Type": last_row["Type"],
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"Locataires": last_row["Locataires"],
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}
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)
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joined.append(row)
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elif row["Période"].startswith("Du"):
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last_row = joined[-1]
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row.update(
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{
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"Lot": last_row["Lot"],
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"Type": last_row["Type"],
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"Locataires": last_row["Locataires"],
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}
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)
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joined.append(row)
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return joined
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def flat_tables(tables):
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tables_flat = []
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for table in tables:
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tables_flat.extend(table)
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return tables_flat
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def table2df(tables):
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tables = flat_tables(tables)
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joined = join_row(tables)
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df = pd.DataFrame.from_records(joined)
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df["immeuble"] = df["immeuble"].apply(lambda x: x[0].capitalize())
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df["Type"] = df["Type"].apply(clean_type)
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numeric_cols = [k for k, v in DF_TYPES.items() if v == float]
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df[numeric_cols] = df[numeric_cols].replace("", np.nan)
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df = df.drop(df[(df["Locataires"] == "") & (df["Période"] == "")].index)
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return df.astype(DF_TYPES)
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