classno 0.0.4

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Classno

Classno is a lightweight and extensible Python library for data modeling, schema definition, and validation. It provides a clean and intuitive way to define data classes with various features like type validation, immutability, private fields, and automatic type casting.

Key Features

• Type hints validation
• Immutable objects
• Private fields
• Automatic type casting
• Customizable comparison behavior
• Default values and factory functions
• Nested object support
• Slots optimization
• Rich comparison methods

Installation

pip install classno

Basic Usage

Simple Data Class

from classno import Classno, field

class User(Classno):
    name: str
    age: int = 0
    email: str = field(default="")

# Create an instance
user = User(name="John", age=30)

Features Configuration

Features can be enabled by setting the __features__ class attribute:

from classno import Classno, Features

class Config(Classno):
    __features__ = Features.VALIDATION | Features.FROZEN

    host: str
    port: int = 8080

Available features:

• Features.EQ - Enable equality comparison
• Features.ORDER - Enable ordering operations
• Features.HASH - Make instances hashable
• Features.SLOTS - Use slots for memory optimization
• Features.FROZEN - Make instances immutable
• Features.PRIVATE - Enable private field access
• Features.VALIDATION - Enable type validation
• Features.LOSSY_AUTOCAST - Enable automatic type casting

Field Configuration

Fields can be configured using the field() function:

from classno import Classno, field
from datetime import datetime

class Post(Classno):
    title: str
    content: str = ""
    created_at: datetime = field(default_factory=datetime.now)
    metadata: dict = field(default_factory=dict, metadata={"indexed": True})

Type Validation

class ValidatedModel(Classno):
    __features__ = Features.VALIDATION

    numbers: list[int]
    mapping: dict[str, float]

# This will raise TypeError if types don't match
model = ValidatedModel(
    numbers=[1, 2, 3],
    mapping={"a": 1.0, "b": 2.0}
)

Immutable Objects

class ImmutableConfig(Classno):
    __features__ = Features.IMMUTABLE  # Combines FROZEN, SLOTS, and HASH

    host: str
    port: int = 8080

config = ImmutableConfig(host="localhost")
# Attempting to modify will raise an exception
config.port = 9000  # Raises Exception

Private Fields

class PrivateFields(Classno):
    __features__ = Features.PRIVATE

    name: str
    secret: str  # Can only be accessed with _secret prefix for rw, secret for ro

obj = PrivateFields(name="public")
obj._secret = "hidden"  # OK
obj.secret  # OK
obj.secret = "hidden"  # Raises Exception

Nested Objects

class Address(Classno):
    street: str
    city: str

class Person(Classno):
    name: str
    address: Address

# Create nested structure
person = Person(
    name="John",
    address=Address(street="123 Main St", city="Boston")
)

Customization

Custom Comparison Keys

class CustomCompare(Classno):
    __hash_keys__ = {"id"}  # Keys used for hashing
    __eq_keys__ = {"id", "name"}  # Keys used for equality comparison
    __order_keys__ = {"name"}  # Keys used for ordering

    id: int
    name: str
    description: str

Best Practices

1. Use type hints for all fields
2. Enable appropriate features based on your needs
3. Use field() for complex field configurations
4. Consider using Features.SLOTS for better memory usage
5. Enable validation when type safety is important

Error Handling

The library raises appropriate exceptions for:

• Type validation errors
• Missing required fields
• Immutability violations
• Invalid field access
• Incorrect feature combinations

Authors

• Dmitriy Kudryavtsev - author - kuderr