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generate_dataset.py
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generate_dataset.py
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import collections
import datetime
import io
import json
import random
import re
import string
import sys
import zipfile
from collections.abc import MutableMapping
from pathlib import Path
from random import choice
import polars as pl
from confit import Cli
from confit.utils.random import set_seed
from tqdm import tqdm
import edsnlp
from eds_pseudo.pipes.dates_normalizer.dates_normalizer import DatesNormalizer
from edsnlp.core.registries import registry
collections.MutableMapping = MutableMapping
from babel.dates import format_date # noqa: E402
app = Cli(pretty_exceptions_show_locals=False)
last_names_prefix = [
"Noms",
"Nom",
"Nom de famille",
"Noms de famille",
"Nom de jeune fille",
]
first_names_prefix = [
"Prénoms",
"Prénom",
"Prénom(s)",
]
mail_domains = [
"gmail.com",
"yahoo.com",
"hotmail.com",
"outlook.com",
"apple.com",
"aphp.fr",
"chu.fr",
"chu-lyon.fr",
"chu-montpellier.fr",
"chu-nantes.fr",
"aphm.fr",
"labo-123.fr",
"labo-paris.fr",
"clinique-paris.fr",
"clinique-lyon.fr",
"medicale.fr",
"parisseine.com",
"univ-med.com",
]
titles = [
"Dr",
"Docteur",
"Interne",
"Professeur",
"Pr",
"M",
"Mme",
"Monsieur",
"Madame",
"",
"",
]
label_mapping = {
"ADDRESS": "ADRESSE",
"ADDRESSE": "ADRESSE",
"ADRESSE": "ADRESSE",
"DATE": "DATE",
"BIRTHDATE": "DATE_NAISSANCE",
"DATE_NAISSANCE": "DATE_NAISSANCE",
"NAISSANCE": "DATE_NAISSANCE",
"HOSPITAL": "HOPITAL",
"HOPITAL": "HOPITAL",
"IPP": "IPP",
"MAIL": "MAIL",
"EMAIL": "MAIL",
"NDA": "NDA",
"LASTNAME": "NOM",
"NOM": "NOM",
"FIRSTNAME": "PRENOM",
"PRENOM": "PRENOM",
"SECU": "SECU",
"NSS": "SECU",
"PHONE": "TEL",
"TELEPHONE": "TEL",
"TEL": "TEL",
"CITY": "VILLE",
"VILLE": "VILLE",
"ZIP": "ZIP",
}
hospitals = [
"A. Béclère",
"A. beclere",
"A.CHENEVIER",
"A.CHENEVIER-H.MONDOR",
"A.Chenevier",
"ABC",
"AMBROISE PARE",
"AMBROISE PARÉ",
"ANTOINE BECLERE",
"APR",
"ARMAND TROUSSEAU",
"ARMAND TROUSSEAU-LA ROCHE GUYON",
"AVC",
"AVICENNE",
"Albert\nChenevier",
"Albert Chennevier",
"Albert-Chennevier",
"Ambroise\nParé",
"Ambroise Paré",
"Ambroise paré",
"Américain",
"Antoine\nBéclère",
"Antoine Béclère",
"Antoine-Béclère",
"Armand Briard",
"Armand Trousseau",
"Avicenne",
"BCH",
"BCT",
"BEAUJON",
"BICETRE",
"BICHAT",
"BICHAT - CLAUDE BERNARD",
"BICHAT-CLAUDE BERNARD",
"BICHAT-LOUIS MOURIER",
"BICÊTRE",
"BJN",
"BRT",
"Ballanger",
"Beaujon",
"Beclere",
"Begin",
"Berck",
"Bichat",
"Bicêtre",
"Bluets",
"Bois d'Amour",
"Bouch",
"Bretonneau",
"Broca",
"Béclère",
"Bégin",
"C. BERNARD",
"C. Celton",
"CCH",
"CCL",
"CDS Grand Ouest Massy",
"CDS MARCEL HANRA",
"CDS Municipal Pantin",
"CDS POLYVALENT MIROMESNIL",
"CFX",
"CHB",
"CHIC",
"CHS ROGER PREVOT",
"CLAUDE BERNARD",
"COCHIN",
"COCHIN - SAINT-VINCENT DE PAUL",
"COCHIN SAINT VINCENT DE PAUL",
"CSAPA Murger",
"Caunes",
"Centre Cardiologique\nNord",
"Centre Cardiologique du Nord",
"Centre Charlebourg",
"Centre Europe",
"Centre Hospitalier Sainte-Anne",
"Centre Hospitalier Universitaire Bicêtre",
"Centre Hospitalier Universitaire de Bicêtre",
"Centre hospitalier régional",
"Centre municipla de santé Salavador Allende",
"Charles Foix",
"Charles-Foix",
"Clinique\nde Val D'or",
"Clinique Jeanne d'Arc",
"Clinique Pervenche",
"Clinique Saint-Louis",
"Clinique de Bachaumont",
"Clinique de la Jonquière",
"Clinique des Cèdres",
"Clinique des Jonquières",
"Clinique du Parc",
"Clinique du Parc de Belleville",
"Clinique du Pont de Sèvres",
"Clinique du Val D'Oo",
"Clinique du Val D'or",
"Cochin",
"Cochin-Saint Vincent de Paul",
"Cognacq Jay",
"Corentin Celton",
"Croix Saint Simon",
"Croix St Simon",
"Curie",
"DE BICETRE",
"DE LA SOURCE",
"DE RAMBOUILLET",
"DEBORD BROCA",
"DELAFONTAINE",
"DIACONESSES / CROIX SAINT SIMON",
"DUPUYTREN",
"DeLafontaine",
"Delafontaine",
"Denfert Rochereau",
"E. Rist",
"E.Rist",
"EPS Roger Prévot",
"ERX",
"ESQUIROL",
"EUROPÉEN GEORGES POMPIDOU",
"Edouard Rist",
"Esquirol",
"FERNAND WIDAL",
"FOCH",
"FONDATION A. DE ROTHSCHILD",
"FOUGERE",
"Fernand Vidal",
"Fernand Widal",
"Foch",
"Fondation\nRothschild",
"Fondation Rothschild",
"Fondation Rotschild",
"Fondation St Jean de Dieu",
"Fougère",
"Franco-Britannique",
"Franquefort",
"G GPompidou",
"G.POMPIDOU",
"GONESSE",
"GPompidou",
"Georges Clémenceau",
"Gustave Roussy",
"H.MONDOR",
"HEGP",
"HENRI MONDOR",
"HENRY DUNANT",
"HMN",
"HOPITAL DE BICETRE",
"HTD",
"Hamburger",
"Hendaye",
"Henri\nMondor",
"Henri Ey",
"Henri MONDOR",
"Henri Mondor",
"Henri mondor",
"Hopital de val d'Yerres",
"Hopital privé des peupliers",
"Hotel Dieu",
"Husson mourrier",
"Hôtel Dieu",
"Hôtel-Dieu",
"IGR",
"Institut Curie",
"Ipso Nation",
"JEAN VERDIER",
"JOFFRE DUPUYTREN",
"JVR",
"Jean Verdier",
"KB",
"Kremlin Bicêtre",
"Kremlin-Bicêtre",
"LA ROCHE GUYON",
"LARIBOIS IERE",
"LARIBOISIERE",
"LARIBOISIERE FERNAND WIDAL",
"LARIBOISIÈRE",
"LEON BERARD",
"LMR",
"LOUIS MOURIER",
"LOUIS PASTEUR-LE COUDRAY",
"LPS",
"LRB",
"LUCIE ET RAYMOND AUBRAC",
"La Guisane",
"La Pitié",
"La Pitié\nSalpétrière",
"La Pitié Salpétrière",
"La Roche-Guyon",
"La Roseraie",
"La Salpêtrière",
"La Verrière",
"La pitié",
"Labrouste",
"Laennec",
"Lamalou",
"Larib",
"Lariboisiere",
"Lariboisière",
"Lariboisère",
"Louis Mourier",
"Luchon",
"Léon\nBerard",
"Léon Bérard",
"Léopold Bellan",
"MONDOR",
"Marie Lannelongue",
"Marin de\nHendaye",
"Marin de Hendaye",
"Max Fourestier",
"Mignot",
"Mondor",
"Monfer Meil",
"Mont Louis",
"Montsouris",
"NCH",
"NCK",
"NECKER",
"NECKER - ENFANTS\nMALADES",
"NECKER - ENFANTS MALADES",
"NECKER ENFANTS MALADES",
"Necker",
"Necker Enfants-Malades",
"PARIS 7 – DENIS DIDEROT",
"PARIS OUEST SITE G POMPIDOU",
"PAUL BROUSSE",
"PAUL GUIRAUD",
"PB",
"PBR",
"PERCY",
"PGV",
"PITIE",
"PITIE SALPETRIERE",
"PITIE-LA SALPETRIERE",
"PITIE-SALPETRIERE",
"PITIÉ SALPÊTRIÈRE",
"PRIVE DE L OUEST PARISIEN",
"PSL",
"PVR",
"Paris I",
"Paris Nord",
"Pasteur",
"Paul Brousse",
"Paul Guiraud",
"Percy",
"Pitie",
"Pitié",
"Pitié\nSalpêtrière",
"Pitié Salpetrière",
"Pitié Salpitrière",
"Pitié Salpétrière",
"Pitié Salpétrière Pitié",
"Pitié Salpêtrière",
"Pitié-Salpétrière",
"Pitié-Salpêtrière",
"Pitié-Salpêtrière Charles Foix",
"Pompidou",
"Port Royal",
"Quinze-Vingts",
"RDB",
"RMB",
"RObert DEbre",
"RPC",
"RTH",
"René-Muret",
"RobDeb",
"Robert\nDebré",
"Robert Ballanger",
"Robert Debré",
"Robert-Debré",
"Rothschild",
"Rotschild",
"Rotshild",
"SAINT ANTOINE",
"SAINT LOUIS",
"SAINT REMY",
"SAINT-ANTOINE",
"SAINT-Camille",
"SAINT-LOUIS",
"SAT",
"SLS",
"ST JOSEPH",
"ST LOUIS",
"Saint\nANtoine",
"Saint\nLouis",
"Saint Anne",
"Saint Antoine",
"Saint Camille",
"Saint Joseph",
"Saint Louis",
"Saint Maurice",
"Saint-Antoine",
"Saint-Joseph",
"Saint-Louis",
"Saint-Maurice",
"Saint-Michel",
"Sainte Anne",
"Sainte Camille",
"Sainte Périne",
"Salneuve",
"Salpétrière",
"San Antonio",
"San Salvadour",
"Saujon",
"Simone Veil",
"St ANNE",
"St Antoine",
"St Etienne",
"St Joseph",
"St Louis",
"St Maur",
"St Maurice",
"St antoine",
"St-Louis",
"Stalingrad",
"Ste\nAnne",
"Ste Anne",
"Ste Camille",
"Stell",
"TENON",
"TNN",
"TRS",
"Tenon",
"Tnn",
"Trouseau",
"Trousseau",
"UNIVERSITAIRE\nNECKER-ENFANTS MALADES",
"UNIVERSITAIRE HENRI MONDOR",
"UNIVERSITAIRE NECKER-ENFANTS MALADES",
"Universitaire Necker-Enfants malades",
"Universitaires Paris Centre",
"Universitaires Paris Est",
"Universitaires Paris-Seine-Saint-Denis",
"VAUGIRARD-GABRIEL PALLEZ",
"VCH",
"Val d'Hyères",
"Ville Evrard",
"ambroise paré",
"antoine beclere",
"antony",
"assan",
"avicenne",
"beaujon",
"becelre",
"bichat",
"bjn",
"béclère",
"cap bastille",
"centre cardiologique du Nord",
"charles Foix",
"clinique\nde Nogent",
"clinique Floréal",
"clinique Floréale",
"clinique Jeanne d'Arc",
"clinique Mont Louis",
"clinique Montsouris",
"clinique Saint-Hilaire",
"clinique bizet",
"clinique de\nNogent",
"clinique de Turin",
"clinique de Villepinte",
"clinique de la Porte de saint cloud",
"clinique de saint cloud",
"clinique des Peupliers",
"clinique du Louvre",
"clinique du Saint-Coeur",
"clinique montsouris",
"cochin",
"de la Source",
"des JOCKEYS",
"esquirol",
"fernand widal",
"henri mondor",
"hopital Suisse",
"husson Mourrier",
"hôpital des Bluets",
"hôpital du Val d'Yerres",
"institut Charcot",
"institut Franco-Britannique",
"jean verdi",
"kb",
"la\nPitié",
"la Croix Saint Simon",
"la Pitié",
"la Pitié Salpétrière",
"la Pitié-Salpêtrière",
"la Roche Guyon",
"la pitie",
"la pitié",
"lariboisiere",
"lariboisière",
"mondor",
"paul guiraud",
"paul Guiraud",
"paul guirout",
"pitie salpetriere",
"pitié salpetrière",
"pitié salpétrière",
"psl",
"saint antoine",
"saint louis",
"salpétrière",
"st LOUIS",
"st antoine",
"tenon",
"tnn",
"trousseau",
"universitaire mère-enfant\nRobert Debré",
"vaugirard",
"Émile Roux",
"Émile roux",
]
def generate_fake_phone_number():
# Generating a random country code between 1 and 99
if random.randint(0, 2):
ctry = 33
else:
ctry = random.randint(11, 99)
if random.randint(0, 2):
ctry = f"+{ctry:02}"
else:
ctry = f"({ctry:02})"
# Generating a 10-digit phone number
n = "".join(
[" " if random.randint(0, 2) else "0"]
+ [str(random.randint(1 if i == 2 else 0, 7)) for i in range(9)]
)
# Different types of separators
s1 = random.choice([" ", "-", ".", "", "", ""])
s2 = random.choice([" ", ""])
# Combining country code and number with different formats
formats = [
f"0{n[1:2]}{s1}{n[2:4]}{s1}{n[4:6]}{s1}{n[6:8]}{s1}{n[8:10]}",
f"0{n[1:2]}{s1}{n[2:4]}{s1}{n[4:6]}{s1}{n[6:8]}{s1}{n[8:10]}",
f"{ctry}{s2}{n[:2].strip()}{s2}{n[2:4]}{s2}{n[4:6]}{s2}{n[6:8]}{s2}{n[8:10]}",
]
# Choosing a random format from the formats list
fake_phone = random.choice(formats)
if not random.randint(0, 6):
fake_phone = " ".join([char for char in fake_phone if char != " "])
return fake_phone
def load_insee_deces(path="data/deces-2024-m03.txt"):
path = Path(path)
# download if path doesn't exist
if not path.exists():
import requests
url = "https://www.data.gouv.fr/fr/datasets/r/227743d3-434f-4659-8b0f-6af8b1c802f3"
response = requests.get(url)
path.write_text(response.text)
data = path.read_text()
names = []
cities = []
for line in data.split("\n"):
if not line:
continue
name_portion, rest = line.split("/", 1)
if "*" in name_portion:
last_name, all_first_names = name_portion.split("*")
first_names = tuple(f.strip() for f in all_first_names.split())
last_name = last_name.strip()
if not first_names or not all(first_names) or not last_name:
continue
names.append((first_names, last_name))
city = (
rest.strip()
.lstrip(string.digits)
.replace("B033", "")
.replace("B081", "")
)[:30]
if city.lower().startswith("departement") or "Préfecture" in city:
continue
city = re.sub(r"\d+E(?:R|ME)?\s+ARRONDISSEMENT", "", city)
city = city.strip()
if not city or (set(city) & set(string.digits)):
continue
cities.append(city)
return sorted(names), sorted(cities)
def load_natality(path="data/nat2022.csv", threshold=100):
"""
CSV format exemple:
sexe;preusuel;annais;nombre
1;ABD'ALLAH;2011;6
Parameters
----------
path: str
Path to the CSV file
"""
path = Path(path)
if not path.exists():
import requests
url = "https://www.insee.fr/fr/statistiques/fichier/7633685/nat2022_csv.zip"
print(f"Downloading natality dataset from {url}")
response = requests.get(url)
# unzip and write
with zipfile.ZipFile(io.BytesIO(response.content)) as z:
with z.open(path.name) as f:
path.write_text(f.read().decode("utf-8"))
df = pl.scan_csv(
path,
separator=";",
schema={
"sexe": pl.Int32,
"preusuel": pl.Utf8,
"annais": pl.Utf8,
"nombre": pl.Int32,
},
)
df = df.filter(
(pl.col("preusuel") != "_PRENOMS_RARES") & (pl.col("annais") != "XXXX")
)
df = df.select(
pl.col("preusuel"),
pl.col("annais").cast(pl.Int32).alias("annais"),
pl.col("nombre"),
)
df = df.group_by(["preusuel"]).agg(pl.sum("nombre").alias("nombre"))
df = df.filter(pl.col("nombre") > threshold)
df = df.select(
pl.col("preusuel").alias("prenom"),
(1 / pl.col("nombre") ** 0.25).alias("prob"),
)
df = df.select(pl.col("prenom"), pl.col("prob") / pl.col("prob").sum())
df = df.collect()
firstnames = df["prenom"].to_list()
probs = df["prob"].to_list()
return firstnames, probs
def load_names_and_cities(path="data/deces-2024-m03.txt", nat_names_ratio=0.5):
"""
Names will be:
- part true names (first + last) from the INSEE deceased records
- part randomly sampled firstnames from the natality dataset, merged with
randomly sampled lastnames from the INSEE records
This is because the INSEE dataset is not representative of the general
living population, since it only contains deceased people.
"""
full_names, cities = load_insee_deces(path)
firstnames, probs = load_natality()
n_gen_full_names = int(len(full_names) * nat_names_ratio)
sampled_firstnames = [
(n,) for n in random.choices(firstnames, probs, k=n_gen_full_names)
]
all_lastnames = list(dict.fromkeys(n[1] for n in full_names))
sampled_lastnames = random.choices(all_lastnames, k=n_gen_full_names)
full_names_2 = full_names + list(zip(sampled_firstnames, sampled_lastnames))
return sorted(full_names_2), sorted(cities)
total = 0
def pick_fake_name(names):
global total
total += 1
first_names, last_name = random.choice(names)
if random.randint(0, 2):
first_names = first_names[:1]
num_names_to_use = random.choice([1, 1, 1, 1, 1, 2, 2, 2, 3])
first_names = first_names[:num_names_to_use]
return first_names, (last_name,)
def make_first_name(first_names, case=None):
# Generate abbreviations but avoid ambiguous initials like M.
if (case in ("N", "N.") or case is None and random.randint(0, 3) == 0) and not (
len(first_names) == 1 and first_names[0][0] == "M"
):
first_name_sep = random.choice(["-", ""])
with_dot = random.randint(0, 2) == 0 or case == "N"
first_name = first_name_sep.join(
[f[:1] + ("" if with_dot else ".") for f in first_names[:2]]
)
else:
first_name = " ".join(first_names)
first_name = first_name.title()
first_name = first_name.strip()
if case is not None:
if case.isupper():
return first_name.upper()
if case.islower():
return first_name.lower()
return first_name
def make_last_name(last_name, case=None):
last_name = " ".join(last_name).title()
last_name = last_name.strip()
if case is not None:
if case.isupper():
return last_name.upper()
if case.islower():
return last_name.lower()
return last_name
def pick_city(cities):
city = random.choice(cities)
parts = [p for p in re.split(r"[\s-]+", city) if p]
if random.randint(0, 2):
parts = [p.lower().capitalize() for p in parts]
if random.randint(0, 2):
city = " ".join(parts)
else:
city = "-".join(parts)
return city
def generate_random_mail(fake_names):
# Generate a random email address
first_names, last_name = pick_fake_name(fake_names)
first_name = make_first_name(first_names, "Nn")
last_name = make_last_name(last_name, "Nn")
first_name = re.sub(f"[{re.escape(string.punctuation) + ' '}]", "", first_name)
last_name = re.sub(f"[{re.escape(string.punctuation) + ' '}]", "", last_name)
domain = random.choice(mail_domains)
# Different types of email formats
formats = [
"{first_name}{num1}{sp}{sep}{sp}{last_name}{num2}{sp}@{sp}{domain}",
"{last_name}{num1}{sp}{sep}{sp}{first_name}{num2}{sp}@{sp}{domain}",
]
sp = "" if random.randint(0, 10) else " "
# Choose a random format from the formats list
fake_mail = random.choice(formats).format(
first_name=first_name.lower()[: random.randint(1, len(first_name))],
last_name=last_name.lower()[: random.randint(1, len(last_name))],
domain=domain,
sep=random.choice(["-", ".", "_", "", ""]),
num1=random.choice(["", "", random.randint(0, 99)]),
num2=random.choice(["", "", random.randint(0, 99)]),
sp=sp,
)
if not sp:
fake_mail = fake_mail.replace(" ", "")
fake_mail = fake_mail.strip()
return fake_mail
def generate_random_date(year=None, format=None, allow_missing_parts=False):
# Generate a random date between the years 1900 and 2100
start_date = datetime.date(1970, 1, 1)
end_date = datetime.date(2100, 12, 31)
time_between_dates = end_date - start_date
days_between_dates = time_between_dates.days
random_number_of_days = random.randrange(days_between_dates)
random_date = start_date + datetime.timedelta(days=random_number_of_days)
if year is not None:
random_date = random_date + datetime.timedelta(
days=(year - random_date.year) * 365
)
if format is None:
# List of date formats
formats = [
f"{choice(['dd', 'd'])}/{choice(['MM', 'M'])}/{choice(['YYYY', 'YY'])}",
f"{choice(['dd', 'd'])}-{choice(['MM', 'M'])}-{choice(['YYYY', 'YY'])}",
f"{choice(['dd', 'd'])}.{choice(['MM', 'M'])}.{choice(['YYYY', 'YY'])}",
"dddddddd",
f"EEE{choice([' ', ' ', ', '])}d {choice(['MMM', 'MMMM'])} YYYY",
f"d {choice(['MMM', 'MMMM'])} YYYY",
]
if allow_missing_parts:
formats += [
"dd/MM",
"dd-MM",
"dd.MM",
f"EEE{choice([' ', ' ', ', '])}d {choice(['MMM', 'MMMM'])}",
f"{choice(['MMM', 'MMMM'])} YYYY",
]
# Choose a random format and return the date
format = random.choice(formats)
if format == "dddddddd":
return " ".join(random_date.strftime("%d%m%Y"))
result = format_date(random_date, format=format, locale="fr_FR")
if random.randint(0, 20) == 0 and not (set(result) & set(string.ascii_letters)):
result = " ".join(char for char in result if char != " ")
# Remove dots like "12 sept. 2012"
if "." not in format and random.randint(0, 4):
result = result.replace(".", "")
return result
def generate_fake_nss(year=None):
# 1. Generate a digit for sex (either 1 or 2)
sex = random.choice([1, 2])
# 2. Generate two digits for the year of birth (00-99)
if year is None:
year = str(random.randint(0, 99)).zfill(2)
else:
year = str(year % 100).zfill(2)
# 3. Generate two digits for the month of birth (01-12)
month = str(random.randint(1, 12)).zfill(2)
# 4. Generate two digits for the department of birth (01-95, 98
# for non-metropolitan France) or 99 for births outside of France
department = str(random.choice(list(range(1, 96)) + [98, 99])).zfill(2)
# 5. Generate three digits for the town or borough of birth (001-999)
town = str(random.randint(1, 999)).zfill(3)
# 6. Generate three digits for the order number of the birth certificate (001-999)
order_num = str(random.randint(1, 999)).zfill(3)
# Combine all parts to form the fake NSS
s1, s2, s3, s4, s5 = random.choices(["", " "], k=5)
nss = f"{sex}{s1}{year}{s2}{month}{s3}{department}{s4}{town}{s5}{order_num}"
if random.randint(0, 2):
nss = " ".join([char for char in nss if char != " "])
return nss
def make_dummy_sample(template=None, *, fake_names):
if template is None:
template = random.randint(0, 7)
first_name, last_name = pick_fake_name(fake_names)
first_name = make_first_name(first_name)
last_name = make_last_name(last_name)
title = random.choice(titles)
phone = generate_fake_phone_number()
if random.randint(0, 2):
title = title.upper()
if 0 < len(title) < 4 and random.randint(0, 2):
title = title + "."
if random.randint(0, 3):
title = title + " "
else:
title = title + " "
if template in (0, 1, 2, 3):
if template == 0:
return f"{title}[{first_name}](PRENOM) [{last_name}](NOM)".strip()
elif template == 1:
return f"{title}[{last_name}](NOM) [{first_name}](PRENOM)".strip()
elif template == 2:
tel_trigger = random.choice(
["Tel ", "Secrétariat ", "Téléphone ", "Accueil", "Standard", ""]
)
return (
f"{title}[{first_name}](PRENOM) "
f"[{last_name}](NOM)\n{tel_trigger}[{phone}](TEL)"
).strip()
elif template == 3:
if random.randint(0, 2):
return (
f"{choice(last_names_prefix)}: [{last_name}](NOM)\n"
f"{choice(first_names_prefix)}: [{first_name}](PRENOM)"
).strip()
else:
return (
f"{choice(first_names_prefix)}: [{first_name}](PRENOM)\n"
f"{choice(last_names_prefix)}: [{last_name}](NOM)"
).strip()
elif template > 3:
birth_year = random.randint(1970, 2000)
birth_date = generate_random_date(birth_year)
nss = generate_fake_nss(birth_year)
current_year = max(2000, birth_year) + random.randint(10, 30)
date = generate_random_date(current_year, allow_missing_parts=True)
date_nss_template = random.randint(0, 3)
sep = random.choice([" ", "\n"])
date_nss_str = None
if date_nss_template == 0:
date_nss_str = (
f"[{date}](DATE){sep}[{nss}](SECU){sep}[{birth_date}](BIRTHDATE)"
).strip()
elif date_nss_template == 1:
date_nss_str = (
f"[{date}](DATE){sep}"
f"[{birth_date}](BIRTHDATE){sep}"
f"[{nss}](SECU)"
).strip()
elif date_nss_template == 2:
date_nss_str = (
f"[{birth_date}](BIRTHDATE) "
f"[{date}](DATE){sep}[{nss}](SECU)".strip()
)
elif date_nss_template == 3:
date_nss_str = (
f"[{nss}](SECU){sep}"
f"[{birth_date}](BIRTHDATE){sep}"
f"[{date}](DATE)"
).strip()
if template in (5, 6):
return (
f"{date_nss_str}\n{title}[{last_name}](NOM) "
f"[{first_name}](PRENOM)\n[{phone}](TEL)"
).strip()
else:
return (
f"{title}[{last_name}](NOM) "
f"[{first_name}](PRENOM)\n"
f"[{phone}](TEL)\n{date_nss_str}"
).strip()
def generate_french_zipcode():
# Define metropolitan department codes
metro_departments = list(range(1, 96))
metro_departments.remove(20) # Removing 20 as Corsica is handled separately
dom_departments = [971, 972, 973, 974, 976]
corsica_departments = ["2A", "2B"]
# Randomly choose a department
choice = random.choice([*(("metro",) * 5), "dom", "corsica"])
if choice == "metro":
department = random.choice(metro_departments)
zipcode = f"{department:02d}{random.randint(0, 999):03d}"
elif choice == "dom":
department = random.choice(dom_departments)
zipcode = f"{department}{random.randint(0, 99):02d}"
else: # Corsica
department = random.choice(corsica_departments)
zipcode = f"{department}{random.randint(0, 999):03d}"
# Adding space in the middle for variation
if random.choice([True, False]):
zipcode = f"{zipcode[:2]} {zipcode[2:]}"
return zipcode
def detect_name_format(text):
if text.endswith("."):
return "N."
if len(text) == 1:
return "N"
if text.isupper():
return "NN"
if text.istitle():
return "Nn"
return "Nn"
# noinspection RegExpRedundantEscape
def augment_sample(sample, *, fake_names, fake_cities):
# names = []
normalizer = DatesNormalizer(None, format="java")
mem = {}
last_first_names, last_last_name = None, None
birth_year = random.randint(1970, 2100)
def pick_replacement(match):
nonlocal last_first_names, last_last_name
label = label_mapping[match.group(2).upper()]
text = match.group(1)
if label == "NOM" or label == "PRENOM":
if label == "NOM" and (text.lower() in mem or last_last_name is not None):
if text.lower() not in mem:
mem[text.lower()] = last_last_name
res = make_last_name(mem[text.lower()], detect_name_format(text))
last_last_name = None