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Fix the styling issues caused by black lib
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fatbuddy authored and dovahcrow committed Apr 3, 2024
1 parent b0756ce commit c7f7880
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1 change: 1 addition & 0 deletions dataprep/__init__.py
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Dataprep let you prepare your data using a single library with a few lines of code.
"""

import logging

DEFAULT_PARTITIONS = 1
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1 change: 1 addition & 0 deletions dataprep/clean/address_utils.py
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"""
Constants used by the clean_address() and validate_address() functions
"""

# pylint: disable=C0301, C0302, E1101

from builtins import zip
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ad_nrt.py
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Clean and validate a DataFrame column containing
Andorra NRT (Número de Registre Tributari, Andorra tax number).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument, E1101, E1133
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_al_nipt.py
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Clean and validate a DataFrame column containing
NIPT (Numri i Identifikimit për Personin e Tatueshëm, Albanian VAT number).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument, E1101, E1133
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ar_cbu.py
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Clean and validate a DataFrame column containing
CBU (Clave Bancaria Uniforme, Argentine bank account number).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument, E1101, E1133
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ar_cuit.py
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Clean and validate a DataFrame column containing
CUIT (Código Único de Identificación Tributaria, Argentinian tax number).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument, E1101, E1133
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ar_dni.py
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Clean and validate a DataFrame column containing
DNI (Documento Nacional de Identidad, Argentinian national identity nr.).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument, E1101, E1133
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_at_uid.py
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Clean and validate a DataFrame column containing
UID (Umsatzsteuer-Identifikationsnummer, Austrian VAT number).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument, E1101, E1133
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_at_vnr.py
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Clean and validate a DataFrame column containing
VNR, SVNR, VSNR (Versicherungsnummer, Austrian social security number).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument, E1101, E1133
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_au_abn.py
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"""
Clean and validate a DataFrame column containing Australian Business Numbers (ABNs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_au_acn.py
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"""
Clean and validate a DataFrame column containing Australian Company Numbers (ACNs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_au_tfn.py
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"""
Clean and validate a DataFrame column containing Australian Tax File Numbers (TFNs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_be_iban.py
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"""
Clean and validate a DataFrame column containing Belgian IBANs.
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_be_vat.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Belgian VAT numbers (VATs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_bg_egn.py
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"""
Clean and validate a DataFrame column containing Bulgarian national identification numbers (EGNs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_bg_pnf.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Bulgarian personal number of a foreigner.
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_bg_vat.py
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"""
Clean and validate a DataFrame column containing Bulgarian VAT numbers (VATs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_bic.py
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"""
Clean and validate a DataFrame column containing ISO 9362 Business identifier codes.
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_bitcoin.py
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"""
Clean and validate a DataFrame column containing Bitcoin Addresses.
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_br_cnpj.py
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"""
Clean and validate a DataFrame column containing CNPJ numbers, Brazilian company identifier.
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_br_cpf.py
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"""
Clean and validate a DataFrame column containing CPF numbers, Brazilian national identifier.
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_by_unp.py
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"""
Clean and validate a DataFrame column containing Belarusian UNP numbers (UNPs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ca_bn.py
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"""
Clean and validate a DataFrame column containing Canadian Business Numbers (BNs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ca_sin.py
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"""
Clean and validate a DataFrame column containing Canadian Social Insurance Numbers(SINs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_casrn.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing CAS Registry Numbers.
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ch_esr.py
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"""
Clean and validate a DataFrame column containing Swiss EinzahlungsSchein mit Referenznummer (ESRs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ch_ssn.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Swiss social security numbers (SSNs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ch_uid.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Swiss business identifiers (UIDs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_ch_vat.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Swiss VAT numbers (VATs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cl_rut.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Chile RUT/RUN numbers (RUTs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cn_ric.py
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"""
Clean and validate a DataFrame column containing Chinese Resident Identity Card Number (RICs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cn_uscc.py
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Clean and validate a DataFrame column containing Chinese Unified Social Credit Code
(China tax number) (USCCs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_co_nit.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Colombian identity codes (NITs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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5 changes: 2 additions & 3 deletions dataprep/clean/clean_country.py
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"""
Clean and validate a DataFrame column containing country names.
"""

from functools import lru_cache
from operator import itemgetter
from os import path
Expand Down Expand Up @@ -371,9 +372,7 @@ def _get_format_if_allowed(input_format: str, allowed_formats: Tuple[str, ...])
return (
"name"
if "name" in allowed_formats
else "official"
if "official" in allowed_formats
else None
else "official" if "official" in allowed_formats else None
)

return input_format if input_format in allowed_formats else None
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cr_cpf.py
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"""
Clean and validate a DataFrame column containing Costa Rica physical person ID number (CPFs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cr_cpj.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Costa Rica tax number (CPJs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cr_cr.py
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"""
Clean and validate a DataFrame column containing Costa Rica foreigners ID number (CRs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cu_ni.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Cuban identity card numbers (NIs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 0 additions & 1 deletion dataprep/clean/clean_currency.py
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Expand Up @@ -50,7 +50,6 @@ def clean_currency(
report: bool = True,
progress: bool = False,
) -> Union[pd.DataFrame, dd.DataFrame]:

"""
Clean, standardize and convert currencies.
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cusip.py
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Clean and validate a DataFrame column containing
CUSIP numbers (financial security identification number).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches, unused-argument
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cy_vat.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Cypriot VAT number (VATs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cz_dic.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Czech VAT number (DICs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_cz_rc.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing Czech birth numbers (RCs).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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1 change: 1 addition & 0 deletions dataprep/clean/clean_date.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing dates and times.
"""

# pylint: disable=too-many-lines
import datetime
from copy import deepcopy
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3 changes: 1 addition & 2 deletions dataprep/clean/clean_date_utils.py
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@@ -1,6 +1,7 @@
"""
Common definitions and classes for the clean_date function.
"""

# pylint: disable-msg=too-many-branches

import datetime
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class ParsedDate:

"""Attributes of a parsed date.
Attributes:
year: Value of year.
Expand Down Expand Up @@ -388,7 +388,6 @@ def _is_leap_year(self) -> bool:


class ParsedTargetFormat:

"""Attributes of a parsed target format.
Attributes:
year_token: Token standing of year.
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1 change: 1 addition & 0 deletions dataprep/clean/clean_de_handelsregisternummer.py
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@@ -1,6 +1,7 @@
"""
Clean and validate a DataFrame column containing German company registry id (handelsregisternummer).
"""

# pylint: disable=too-many-lines, too-many-arguments, too-many-branches
from typing import Any, Union
from operator import itemgetter
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