pydantic-validation

name	pydantic-validation
description	Record-level data validation using Pydantic models. Field validators, model validators, and batch validation patterns.
allowed-tools	Read Write Edit Bash

Pydantic Validation

Audience: Data engineers validating records in ETL pipelines.

Goal: Provide reusable Pydantic patterns for record-level validation.

Scripts

Execute validation functions from scripts/validators.py:

from scripts.validators import (
    UserRecord,
    Customer,
    Order,
    Address,
    validate_records,
    print_validation_errors,
    PositiveInt,
    Email
)

Usage Examples

Basic Model Validation

from scripts.validators import UserRecord

# Validate single record
user = UserRecord(
    id=1,
    email="[e-mail]",
    status="active",
    created_at="2024-01-15",
    age=25
)
print(user.email)  # [e-mail] (lowercased)

Batch Validation

from scripts.validators import validate_records, print_validation_errors

raw_data = [
    {: , : , : , : , : },
    {: -, : , : , : , : },
]

valid, invalid = validate_records(raw_data)
 invalid:
    print_validation_errors(invalid)