datacheck-kit

A small, zero-dependency toolkit for validating and formatting the kinds of data that show up in almost every form or import script: email addresses, phone numbers, URLs, IBANs, credit card numbers, postal codes and slugs.

It exists because most projects end up copy-pasting the same handful of regexes and checksum functions over and over. This package collects the ones worth reusing into one place, with tests and no runtime dependencies.

This is a Python port of the datacheck-kit npm package — same API surface, adapted to Python conventions (snake_case, None instead of null).

Install

pip install datacheck-kit

Usage

import datacheck_kit as dk

dk.is_valid_email("user@example.com")        # True
dk.normalize_email("  User@Example.COM ")    # "user@example.com"

dk.is_valid_url("example.com")               # False (no protocol)
dk.normalize_url("example.com/path/")        # "https://example.com/path/"

dk.is_valid_phone("+44 20 7123 4567")        # True
dk.format_phone_e164("+44 20 7123 4567")     # "+442071234567"

dk.is_valid_iban("NL91ABNA0417164300")       # True
dk.format_iban("NL91ABNA0417164300")         # "NL91 ABNA 0417 1643 00"

dk.is_valid_card_number("4111 1111 1111 1111")  # True (Luhn check)
dk.mask_card_number("4111111111111111")         # "**** **** **** 1111"

dk.is_valid_postal_code("1011 AB", "NL")     # True
dk.supported_countries()                     # ["NL", "PL", "DE", ...]

dk.slugify("Café Müller & Söhne")            # "cafe-muller-sohne"

API

Email

• is_valid_email(value: str) -> bool
• normalize_email(value: str) -> str | None

URL

• is_valid_url(value: str) -> bool
• normalize_url(value: str) -> str | None

Phone

• is_valid_phone(value: str) -> bool — accepts E.164-style numbers (optional leading +, 8-15 digits, common separators allowed).
• format_phone_e164(value: str) -> str | None

IBAN

• is_valid_iban(value: str) -> bool — validates the mod-97 (ISO 7064) checksum and checks length against the issuing country when known.
• format_iban(value: str) -> str — groups the IBAN into 4-character blocks for display.

Credit card

• is_valid_card_number(value: str) -> bool — Luhn algorithm.
• mask_card_number(value: str) -> str | None — keeps only the last 4 digits visible.

Postal code

• is_valid_postal_code(value: str, country_code: str) -> bool — supports NL, PL, DE, FR, IT, AT, CH, GB, ES, FI, US.
• supported_countries() -> list[str]

Slug

• slugify(value: str) -> str — lower-cases, strips common Latin diacritics, and collapses everything else into hyphens.

Why not a bigger validation library?

Larger packages cover far more ground and are a better fit if you need everything they offer. datacheck-kit is for the common case: you need five or six of these checks, you don't want a dependency tree for them, and you'd rather read the source in a couple of minutes than look up documentation.

Testing

python -m unittest discover -s tests

Uses only the standard library — no test framework dependency required.

License

MIT — see LICENSE.