validabr 0.2.0

Enterprise toolkit for validating, parsing, enriching, and anonymizing Brazilian documents (LGPD-ready)

validabr

The Python library for validating, generating, formatting, and masking Brazilian documents — CPF to CNH to Pix keys.

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Installation

pip install validabr
pip install validabr[django]     # Django validators and form fields
pip install validabr[pydantic]   # Pydantic v2 custom types
pip install validabr[pandas]    # Pandas Series accessor
pip install validabr[polars]     # Polars DataFrame expressions

Core validabr has zero dependencies — stdlib only.

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Supported Documents

Document	Validate	Generate	Format	Parse	Mask
CPF	is_valid_cpf	generate_cpf	format_cpf	parse_cpf	mask_cpf
CNPJ (+ alfanumérico)	is_valid_cnpj	generate_cnpj	format_cnpj	parse_cnpj	mask_cnpj
CNJ	is_valid_cnj	generate_cnj	format_cnj	parse_cnj	—
IE (27 states)	is_valid_ie	generate_ie	format_ie	parse_ie	—
RENAVAM	is_valid_renavam	generate_renavam	format_renavam	parse_renavam	—
Título de Eleitor	is_valid_titulo_eleitor	generate_titulo_eleitor	format_titulo_eleitor	parse_titulo_eleitor	—
CNH	is_valid_cnh	generate_cnh	format_cnh	parse_cnh	—
PIS/PASEP	is_valid_pis	generate_pis	format_pis	parse_pis	—
CEP	is_valid_cep	—	format_cep	parse_cep	—
CNS (SUS)	is_valid_cns	generate_cns	format_cns	parse_cns	—
NFe/CTe/NFC-e (44 digits)	is_valid_nfe	generate_nfe	format_nfe	parse_nfe	—
Chave Pix	classify_pix	—	format_pix	parse_pix	—

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Quick Start

Core API — Validate, Generate, Format, Parse

import validabr

# Validate
validabr.is_valid_cpf("529.982.247-25")        # True
validabr.is_valid_cnpj("11.222.333/0001-81")    # True
validabr.is_valid_ie("110.042.490.114", "SP")   # True

# Generate
validabr.generate_cpf()                          # "52998224725"
validabr.generate_cpf(formatted=True)           # "529.982.247-25"
validabr.generate_ie("MG")                      # "062.107.170.0110"

# Format — idempotent (handles raw or formatted input)
validabr.format_cpf("52998224725")              # "529.982.247-25"
validabr.format_cnpj("11222333000181")          # "11.222.333/0001-81"

# Parse — returns NamedTuple with structured fields
data = validabr.parse_cpf("529.982.247-25")
print(data.root, data.check_digits)            # "52998224" "25"

Bulk Operations

# Same-type batch
validabr.validate_list("cpf", ["529.982.247-25", "000.000.000-00"])  # [True, False]
validabr.generate_list("cnpj", 3, formatted=True)

# Mixed-type batch
validabr.validate_docs([("cpf", "529.982.247-25"), ("cnpj", "11.222.333/0001-81")])  # [True, True]

CLI

validabr validate cpf 529.982.247-25        # exit 0
validabr generate cpf --formatted           # 529.982.247-25
validabr format cpf 52998224725              # 529.982.247-25
validabr parse cpf 529.982.247-25          # {"root": "52998224", "check_digits": "25", ...}
validabr mask cpf 529.982.247-25            # ***.982.247-**

LGPD / Secure — Mask & Redact

from validabr import mask_cpf, mask_cnpj, redact_text, BRDocFilter

mask_cpf("529.982.247-25")    # "***.982.247-**"
mask_cnpj("11.222.333/0001-81")  # "**.222.333/****-**"

# Redact all CPF/CNPJ in free text
redact_text("CPF 529.982.247-25 belongs to João")  # "CPF ***.982.247-** belongs to João"

# Logging filter — attach to any Python logger
import logging
logging.getLogger().addFilter(BRDocFilter())

Data Enrichment

from validabr import enrich_cnpj, enrich_cep

info = enrich_cnpj("11222333000181")
# CNPJEnrichmentData(cnpj='...', razao_social='...', cnae='...', municipio='...', uf='...', ...)

cep = enrich_cep("01310-100")
# CEPEnrichmentData(cep='...', logradouro='...', bairro='...', cidade='...', uf='...')

Pandas

import pandas as pd
import validabr.integrations.pandas  # registers .validabr accessor

df = pd.DataFrame({"cpf": ["529.982.247-25", "000.000.000-00"]})
df["valid"] = df["cpf"].validabr.is_valid_cpf()   # bool Series
df["formatted"] = df["cpf"].validabr.format_cpf()  # str Series
df["masked"] = df["cpf"].validabr.mask_cpf()       # str Series
df["tipo_pix"] = df["pix"].validabr.classify_pix()  # "CPF" | "CNPJ" | "EMAIL" | "PHONE" | ""

Polars

import polars as pl
import validabr.integrations.polars  # registers .validabr on Expr

df = pl.DataFrame({"cpf": ["529.982.247-25", "000.000.000-00"]})
df.select(pl.col("cpf").validabr.is_valid_cpf())   # Expr → [True, False]
df.select(pl.col("cpf").validabr.format_cpf())    # Expr → ["529.982.247-25", ...]
df.select(pl.col("cpf").validabr.mask_cpf())      # Expr → ["***.982.247-**", ...]
df.select(pl.col("pix").validabr.classify_pix())  # Expr → ["CPF", "CNPJ", "EMAIL", "PHONE", ""]

Django

from validabr.integrations.django import CPFField, CNPJField, BRDocumentField

class Person(models.Model):
    cpf = CPFField(unique=True)          # validates + strips formatting on save
    cnpj = CNPJField(blank=True)
    documento = BRDocumentField()          # polymorphic — accepts CPF or CNPJ

Pydantic

from pydantic import BaseModel
from validabr.integrations.pydantic import CPF, CNPJ, IE, CNJ, Renavam, TituloEleitor

class Pessoa(BaseModel):
    cpf: CPF
    cnpj: CNPJ | None = None

class Inscricao(BaseModel):
    ie: IE
    estado: str

p = Pessoa(cpf="529.982.247-25")  # auto-strips to "52998224725"

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License

MIT