Registration Functions

def add_constructor(tag: str, constructor: Callable, Loader=None) -> None:
    """
    Register a constructor for a specific YAML tag.
    
    Parameters:
    - tag: YAML tag to handle (e.g., '!custom', 'tag:yaml.org,2002:python/tuple')
    - constructor: Function that takes (loader, node) and returns Python object
    - Loader: Loader class to register with (defaults to global registration)
    
    The constructor function signature:
    def constructor(loader, node) -> Any
    """

def add_multi_constructor(tag_prefix: str, multi_constructor: Callable, Loader=None) -> None:
    """
    Register a multi-constructor for YAML tags with a common prefix.
    
    Parameters:
    - tag_prefix: YAML tag prefix to handle (e.g., '!python/', 'tag:example.com,2002:')
    - multi_constructor: Function that takes (loader, tag_suffix, node) and returns Python object
    - Loader: Loader class to register with (defaults to global registration)
    
    The multi-constructor function signature:
    def multi_constructor(loader, tag_suffix, node) -> Any
    """

def add_representer(data_type: type, representer: Callable, Dumper=None) -> None:
    """
    Register a representer for a specific Python type.
    
    Parameters:
    - data_type: Python type to handle (e.g., MyClass, datetime.date)
    - representer: Function that takes (dumper, data) and returns YAML node
    - Dumper: Dumper class to register with (defaults to global registration)
    
    The representer function signature:
    def representer(dumper, data) -> Node
    """

def add_multi_representer(data_type: type, multi_representer: Callable, Dumper=None) -> None:
    """
    Register a multi-representer for a type and its subclasses.
    
    Parameters:
    - data_type: Base Python type to handle (will also handle subclasses)
    - multi_representer: Function that takes (dumper, data) and returns YAML node
    - Dumper: Dumper class to register with (defaults to global registration)
    
    The multi-representer function signature:
    def multi_representer(dumper, data) -> Node
    """

def add_implicit_resolver(tag: str, regexp: Pattern[str], first=None, Loader=None, Dumper=None) -> None:
    """
    Register an implicit resolver that assigns tags based on value patterns.
    
    Parameters:
    - tag: YAML tag to assign when pattern matches
    - regexp: Compiled regular expression pattern to match against scalar values
    - first: Set of possible first characters (optimization hint)
    - Loader: Loader class to register with (defaults to global registration)
    - Dumper: Dumper class to register with (defaults to global registration)
    """

def add_path_resolver(tag: str, path: Iterable[Any], kind=None, Loader=None, Dumper=None) -> None:
    """
    Register a path resolver that assigns tags based on document path.
    
    Parameters:
    - tag: YAML tag to assign when path matches
    - path: Sequence describing the path in the document structure
    - kind: Node kind to match (ScalarNode, SequenceNode, MappingNode)
    - Loader: Loader class to register with (defaults to global registration)
    - Dumper: Dumper class to register with (defaults to global registration)
    """

import yaml
import re
from datetime import datetime

# Constructor for custom date format
def date_constructor(loader, node):
    """Construct datetime from custom date format."""
    value = loader.construct_scalar(node)
    return datetime.strptime(value, '%Y-%m-%d %H:%M:%S')

# Register constructor for custom tag
yaml.add_constructor('!datetime', date_constructor, Loader=yaml.SafeLoader)

# Test custom constructor
yaml_input = """
created: !datetime 2024-01-15 14:30:00
modified: !datetime 2024-01-16 09:15:30
"""

data = yaml.load(yaml_input, Loader=yaml.SafeLoader)
print(f"Created: {data['created']} (type: {type(data['created'])})")
print(f"Modified: {data['modified']} (type: {type(data['modified'])})")

import yaml
import importlib

def python_object_constructor(loader, tag_suffix, node):
    """Construct Python objects from module.class notation."""
    if tag_suffix == 'object':
        # Handle !!python/object:module.Class
        class_name = loader.construct_scalar(node)
        module_name, class_name = class_name.rsplit('.', 1)
        module = importlib.import_module(module_name)
        cls = getattr(module, class_name)
        return cls()
    elif tag_suffix == 'apply':
        # Handle !!python/apply:function [args]
        function_name = node.value[0].value
        args = loader.construct_sequence(node.value[1])
        module_name, func_name = function_name.rsplit('.', 1)
        module = importlib.import_module(module_name)
        func = getattr(module, func_name)
        return func(*args)
    else:
        raise yaml.constructor.ConstructorError(
            None, None, f"Unknown python tag suffix: {tag_suffix}", node.start_mark
        )

# Register multi-constructor for python tags
yaml.add_multi_constructor('tag:yaml.org,2002:python/', 
                          python_object_constructor, 
                          Loader=yaml.UnsafeLoader)

# Test (UNSAFE - only for demonstration)
yaml_input = """
date_func: !!python/object:datetime.date
result: !!python/apply:datetime.date [2024, 1, 15]
"""

# This would work with UnsafeLoader (not recommended for untrusted input)
# data = yaml.load(yaml_input, Loader=yaml.UnsafeLoader)

import yaml
from decimal import Decimal

def decimal_representer(dumper, data):
    """Represent Decimal as a scalar with custom tag."""
    return dumper.represent_scalar('!decimal', str(data))

def decimal_constructor(loader, node):
    """Construct Decimal from scalar value."""
    value = loader.construct_scalar(node)
    return Decimal(value)

# Register representer and constructor
yaml.add_representer(Decimal, decimal_representer, Dumper=yaml.SafeDumper)
yaml.add_constructor('!decimal', decimal_constructor, Loader=yaml.SafeLoader)

# Test custom Decimal handling
data = {
    'price': Decimal('19.99'),
    'tax_rate': Decimal('0.0825'),
    'total': Decimal('21.64')
}

yaml_output = yaml.dump(data, Dumper=yaml.SafeDumper)
print("YAML output:")
print(yaml_output)
# Output:
# price: !decimal '19.99'
# tax_rate: !decimal '0.0825'
# total: !decimal '21.64'

loaded_data = yaml.load(yaml_output, Loader=yaml.SafeLoader)
print(f"Loaded price: {loaded_data['price']} (type: {type(loaded_data['price'])})")

import yaml
from pathlib import Path

def path_representer(dumper, data):
    """Represent Path objects as strings with custom tag."""
    return dumper.represent_scalar('!path', str(data))

def path_constructor(loader, node):
    """Construct Path from string value."""
    value = loader.construct_scalar(node)
    return Path(value)

# Register for Path and all its subclasses
yaml.add_multi_representer(Path, path_representer, Dumper=yaml.SafeDumper)
yaml.add_constructor('!path', path_constructor, Loader=yaml.SafeLoader)

# Test with different Path types
from pathlib import WindowsPath, PosixPath

data = {
    'config_file': Path('/etc/myapp/config.yaml'),
    'data_dir': Path('/var/lib/myapp'),
    'log_file': Path('/var/log/myapp.log')
}

yaml_output = yaml.dump(data, Dumper=yaml.SafeDumper)
print("YAML output:")
print(yaml_output)

loaded_data = yaml.load(yaml_output, Loader=yaml.SafeLoader)
print(f"Config file: {loaded_data['config_file']} (type: {type(loaded_data['config_file'])})")

import yaml
import re
from ipaddress import IPv4Address, IPv6Address

# IPv4 address pattern
ipv4_pattern = re.compile(r'^(?:[0-9]{1,3}\.){3}[0-9]{1,3}$')

def ipv4_constructor(loader, node):
    value = loader.construct_scalar(node) 
    return IPv4Address(value)

def ipv4_representer(dumper, data):
    return dumper.represent_scalar('!ipv4', str(data))

# Register IPv4 handling
yaml.add_constructor('!ipv4', ipv4_constructor, Loader=yaml.SafeLoader)
yaml.add_representer(IPv4Address, ipv4_representer, Dumper=yaml.SafeDumper)

# Register implicit resolver - automatically detect IPv4 addresses
yaml.add_implicit_resolver('!ipv4', ipv4_pattern, ['0', '1', '2', '3', '4', '5', '6', '7', '8', '9'],
                          Loader=yaml.SafeLoader, Dumper=yaml.SafeDumper)

# Test automatic IPv4 detection
yaml_input = """
server: 192.168.1.1
database: 10.0.0.5
client: not.an.ip.address
"""

data = yaml.load(yaml_input, Loader=yaml.SafeLoader)
print(f"Server: {data['server']} (type: {type(data['server'])})")
print(f"Database: {data['database']} (type: {type(data['database'])})")
print(f"Client: {data['client']} (type: {type(data['client'])})")

# Dump back to YAML
yaml_output = yaml.dump(data, Dumper=yaml.SafeDumper)
print("\nYAML output:")
print(yaml_output)

import yaml

def special_string_constructor(loader, node):
    """Constructor for special strings in specific locations."""
    value = loader.construct_scalar(node)
    return f"SPECIAL: {value}"

# Register constructor
yaml.add_constructor('!special', special_string_constructor, Loader=yaml.SafeLoader)

# Register path resolver - apply !special tag to strings at specific paths
yaml.add_path_resolver('!special', ['config', 'database', 'password'], str,
                      Loader=yaml.SafeLoader)
yaml.add_path_resolver('!special', ['secrets', None], str,  # Any key under 'secrets'
                      Loader=yaml.SafeLoader)

# Test path-based tag resolution
yaml_input = """
config:
  database:
    host: localhost
    password: secret123  # Will get !special tag
    port: 5432
  app:
    name: MyApp
    debug: true
secrets:
  api_key: abc123      # Will get !special tag
  token: xyz789        # Will get !special tag
normal_password: plain  # Won't get !special tag
"""

data = yaml.load(yaml_input, Loader=yaml.SafeLoader)
print("Loaded data:")
print(f"Database password: {data['config']['database']['password']}")
print(f"API key: {data['secrets']['api_key']}")
print(f"Token: {data['secrets']['token']}")
print(f"Normal password: {data['normal_password']}")

import yaml
from typing import NamedTuple
from enum import Enum

class Priority(Enum):
    LOW = 1
    MEDIUM = 2
    HIGH = 3
    CRITICAL = 4

class Task(NamedTuple):
    title: str
    priority: Priority
    completed: bool = False

# Priority enum handling
def priority_representer(dumper, data):
    return dumper.represent_scalar('!priority', data.name.lower())

def priority_constructor(loader, node):
    value = loader.construct_scalar(node)
    return Priority[value.upper()]

# Task handling  
def task_representer(dumper, data):
    return dumper.represent_mapping('!task', {
        'title': data.title,
        'priority': data.priority,
        'completed': data.completed
    })

def task_constructor(loader, node):
    data = loader.construct_mapping(node)
    return Task(**data)

# Register all custom types
yaml.add_representer(Priority, priority_representer, Dumper=yaml.SafeDumper)
yaml.add_constructor('!priority', priority_constructor, Loader=yaml.SafeLoader)
yaml.add_representer(Task, task_representer, Dumper=yaml.SafeDumper)
yaml.add_constructor('!task', task_constructor, Loader=yaml.SafeLoader)

# Test complete type system
tasks = [
    Task("Fix critical bug", Priority.CRITICAL, False),
    Task("Write documentation", Priority.MEDIUM, True),
    Task("Code review", Priority.HIGH, False)
]

yaml_output = yaml.dump(tasks, Dumper=yaml.SafeDumper)
print("YAML output:")
print(yaml_output)

loaded_tasks = yaml.load(yaml_output, Loader=yaml.SafeLoader)
print("Loaded tasks:")
for task in loaded_tasks:
    print(f"  {task.title}: {task.priority.name} ({'✓' if task.completed else '✗'})")