"""
Generic support for objects with full-featured Parameters and
messaging.

This file comes from the Param library (https://github.com/holoviz/param)
but can be taken out of the param module and used on its own if desired,
either alone (providing basic Parameter support) or with param's
__init__.py (providing specialized Parameter types).
"""

import asyncio
import copy
import datetime as dt
import html
import inspect
import logging
import numbers
import operator
import re
import sys
import types
import typing
import warnings
from inspect import getfullargspec

from collections import defaultdict, namedtuple, OrderedDict
from functools import partial, wraps, reduce
from html import escape
from itertools import chain
from operator import itemgetter, attrgetter
from types import FunctionType, MethodType

from contextlib import contextmanager
from logging import DEBUG, INFO, WARNING, ERROR, CRITICAL

from . import serializer
from ._utils import (
    DEFAULT_SIGNATURE,
    ParamFutureWarning as _ParamFutureWarning,
    Skip,
    _deprecated,
    _deprecate_positional_args,
    _in_ipython,
    _is_auto_name,
    _is_mutable_container,
    _recursive_repr,
    _to_async_gen,
    _validate_error_prefix,
    accept_arguments,
    iscoroutinefunction,
    descendents,
    gen_types,
)

# Ideally setting param_pager would be in __init__.py but param_pager is
# needed on import to create the Parameterized class, so it'd need to precede
# importing parameterized.py in __init__.py which would be a little weird.
if _in_ipython():
    # In case the optional ipython module is unavailable
    try:
        from .ipython import ParamPager, ipython_async_executor as async_executor
        param_pager = ParamPager(metaclass=True)  # Generates param description
    except ModuleNotFoundError:
        from ._utils import async_executor
else:
    from ._utils import async_executor
    param_pager = None


@gen_types
def _dt_types():
    yield dt.datetime
    yield dt.date
    if np := sys.modules.get("numpy"):
        yield np.datetime64

@gen_types
def _int_types():
    yield int
    if np := sys.modules.get("numpy"):
        yield np.integer

VERBOSE = INFO - 1
logging.addLevelName(VERBOSE, "VERBOSE")

# Get the appropriate logging.Logger instance. If `logger` is None, a
# logger named `"param"` will be instantiated. If `name` is set, a descendant
# logger with the name ``"param.<name>"`` is returned (or
# ``logger.name + ".<name>"``)
logger = None
def get_logger(name=None):
    if logger is None:
        root_logger = logging.getLogger('param')
        if not root_logger.handlers:
            root_logger.setLevel(logging.INFO)
            formatter = logging.Formatter(
                fmt='%(levelname)s:%(name)s: %(message)s')
            handler = logging.StreamHandler()
            handler.setFormatter(formatter)
            root_logger.addHandler(handler)
    else:
        root_logger = logger
    if name is None:
        return root_logger
    else:
        return logging.getLogger(root_logger.name + '.' + name)


# Indicates whether warnings should be raised as errors, stopping
# processing.
warnings_as_exceptions = False

docstring_signature = True        # Add signature to class docstrings
docstring_describe_params = True  # Add parameter description to class
                                  # docstrings (requires ipython module)
object_count = 0
warning_count = 0

# Hook to apply to depends and bind arguments to turn them into valid parameters
_reference_transforms = []

def register_reference_transform(transform):
    """
    Appends a transform to extract potential parameter dependencies
    from an object.

    Arguments:
    ---------
    transform: Callable[Any, Any]

    """
    return _reference_transforms.append(transform)

def transform_reference(arg):
    """
    Applies transforms to turn objects which should be treated like
    a parameter reference into a valid reference that can be resolved
    by Param. This is useful for adding handling for depending on objects
    that are not simple Parameters or functions with dependency
    definitions.
    """
    for transform in _reference_transforms:
        if isinstance(arg, Parameter) or hasattr(arg, '_dinfo'):
            break
        arg = transform(arg)
    return arg

def eval_function_with_deps(function):
    """
    Evaluates a function after resolving its dependencies.

    Calls and returns a function after resolving any dependencies
    stored on the _dinfo attribute and passing the resolved values
    as arguments.
    """
    args, kwargs = (), {}
    if hasattr(function, '_dinfo'):
        arg_deps = function._dinfo['dependencies']
        kw_deps = function._dinfo.get('kw', {})
        if kw_deps or any(isinstance(d, Parameter) for d in arg_deps):
            args = (getattr(dep.owner, dep.name) for dep in arg_deps)
            kwargs = {n: getattr(dep.owner, dep.name) for n, dep in kw_deps.items()}
    return function(*args, **kwargs)

def resolve_value(value, recursive=True):
    """Resolves the current value of a dynamic reference."""
    if not recursive:
        pass
    elif isinstance(value, (list, tuple)):
        return type(value)(resolve_value(v) for v in value)
    elif isinstance(value, dict):
        return type(value)((resolve_value(k), resolve_value(v)) for k, v in value.items())
    elif isinstance(value, slice):
        return slice(
            resolve_value(value.start),
            resolve_value(value.stop),
            resolve_value(value.step)
        )
    value = transform_reference(value)
    is_gen = inspect.isgeneratorfunction(value)
    if hasattr(value, '_dinfo') or iscoroutinefunction(value) or is_gen:
        value = eval_function_with_deps(value)
        if is_gen:
            value = _to_async_gen(value)
    elif isinstance(value, Parameter):
        value = getattr(value.owner, value.name)
    return value

def resolve_ref(reference, recursive=False):
    """Resolves all parameters a dynamic reference depends on."""
    if recursive:
        if isinstance(reference, (list, tuple, set)):
            return [r for v in reference for r in resolve_ref(v, recursive)]
        elif isinstance(reference, dict):
            return [r for kv in reference.items() for o in kv for r in resolve_ref(o, recursive)]
        elif isinstance(reference, slice):
            return [r for v in (reference.start, reference.stop, reference.step) for r in resolve_ref(v, recursive)]
    reference = transform_reference(reference)
    if hasattr(reference, '_dinfo'):
        dinfo = getattr(reference, '_dinfo', {})
        args = list(dinfo.get('dependencies', []))
        kwargs = list(dinfo.get('kw', {}).values())
        refs = []
        for arg in (args + kwargs):
            if isinstance(arg, str):
                owner = get_method_owner(reference)
                if arg in owner.param:
                    arg = owner.param[arg]
                elif '.' in arg:
                    path = arg.split('.')
                    arg = owner
                    for attr in path[:-1]:
                        arg = getattr(arg, attr)
                    arg = arg.param[path[-1]]
                else:
                    arg = getattr(owner, arg)
            refs.extend(resolve_ref(arg))
        return refs
    elif isinstance(reference, Parameter):
        return [reference]
    return []

def _identity_hook(obj, val):
    """To be removed when set_hook is removed"""
    return val


class _Undefined:
    """
    Dummy value to signal completely undefined values rather than
    simple None values.
    """

    def __bool__(self):
        # Haven't defined whether Undefined is falsy or truthy,
        # so to avoid subtle bugs raise an error when it
        # is used in a comparison without `is`.
        raise RuntimeError('Use `is` to compare Undefined')

    def __repr__(self):
        return '<Undefined>'


Undefined = _Undefined()


@contextmanager
def logging_level(level):
    """Temporarily modify param's logging level."""
    level = level.upper()
    levels = [DEBUG, INFO, WARNING, ERROR, CRITICAL, VERBOSE]
    level_names = ['DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL', 'VERBOSE']

    if level not in level_names:
        raise Exception(f"Level {level!r} not in {levels!r}")

    param_logger = get_logger()
    logging_level = param_logger.getEffectiveLevel()
    param_logger.setLevel(levels[level_names.index(level)])
    try:
        yield None
    finally:
        param_logger.setLevel(logging_level)


@contextmanager
def _batch_call_watchers(parameterized, enable=True, run=True):
    """
    Internal version of batch_call_watchers, adding control over queueing and running.
    Only actually batches events if enable=True; otherwise a no-op. Only actually
    calls the accumulated watchers on exit if run=True; otherwise they remain queued.
    """
    BATCH_WATCH = parameterized.param._BATCH_WATCH
    parameterized.param._BATCH_WATCH = enable or parameterized.param._BATCH_WATCH
    try:
        yield
    finally:
        parameterized.param._BATCH_WATCH = BATCH_WATCH
        if run and not BATCH_WATCH:
            parameterized.param._batch_call_watchers()


# PARAM3_DEPRECATION
@_deprecated(extra_msg="Use instead `batch_call_watchers`.", warning_cat=_ParamFutureWarning)
@contextmanager
def batch_watch(parameterized, enable=True, run=True):
    with _batch_call_watchers(parameterized, enable, run):
        yield


@contextmanager
def batch_call_watchers(parameterized):
    """
    Context manager to batch events to provide to Watchers on a
    parameterized object.  This context manager queues any events
    triggered by setting a parameter on the supplied parameterized
    object, saving them up to dispatch them all at once when the
    context manager exits.
    """
    BATCH_WATCH = parameterized.param._BATCH_WATCH
    parameterized.param._BATCH_WATCH = True
    try:
        yield
    finally:
        parameterized.param._BATCH_WATCH = BATCH_WATCH
        if not BATCH_WATCH:
            parameterized.param._batch_call_watchers()


@contextmanager
def _syncing(parameterized, parameters):
    old = parameterized._param__private.syncing
    parameterized._param__private.syncing = set(old) | set(parameters)
    try:
        yield
    finally:
        parameterized._param__private.syncing = old


@contextmanager
def edit_constant(parameterized):
    """
    Temporarily set parameters on Parameterized object to constant=False
    to allow editing them.
    """
    params = parameterized.param.objects('existing').values()
    constants = [p.constant for p in params]
    for p in params:
        p.constant = False
    try:
        yield
    finally:
        for (p, const) in zip(params, constants):
            p.constant = const


@contextmanager
def discard_events(parameterized):
    """
    Context manager that discards any events within its scope
    triggered on the supplied parameterized object.
    """
    batch_watch = parameterized.param._BATCH_WATCH
    parameterized.param._BATCH_WATCH = True
    watchers, events = (list(parameterized.param._state_watchers),
                        list(parameterized.param._events))
    try:
        yield
    finally:
        parameterized.param._BATCH_WATCH = batch_watch
        parameterized.param._state_watchers = watchers
        parameterized.param._events = events


def classlist(class_):
    """
    Return a list of the class hierarchy above (and including) the given class.

    Same as `inspect.getmro(class_)[::-1]`
    """
    return inspect.getmro(class_)[::-1]


def get_all_slots(class_):
    """
    Return a list of slot names for slots defined in `class_` and its
    superclasses.
    """
    # A subclass's __slots__ attribute does not contain slots defined
    # in its superclass (the superclass' __slots__ end up as
    # attributes of the subclass).
    all_slots = []
    parent_param_classes = [c for c in classlist(class_)[1::]]
    for c in parent_param_classes:
        if hasattr(c,'__slots__'):
            all_slots+=c.__slots__
    return all_slots


def get_occupied_slots(instance):
    """
    Return a list of slots for which values have been set.

    (While a slot might be defined, if a value for that slot hasn't
    been set, then it's an AttributeError to request the slot's
    value.)
    """
    return [slot for slot in get_all_slots(type(instance))
            if hasattr(instance,slot)]


# PARAM3_DEPRECATION
@_deprecated(warning_cat=_ParamFutureWarning)
def all_equal(arg1,arg2):
    """
    Return a single boolean for arg1==arg2, even for numpy arrays
    using element-wise comparison.

    Uses all(arg1==arg2) for sequences, and arg1==arg2 otherwise.

    If both objects have an '_infinitely_iterable' attribute, they are
    not be zipped together and are compared directly instead.
    """
    if all(hasattr(el, '_infinitely_iterable') for el in [arg1,arg2]):
        return arg1==arg2
    try:
        return all(a1 == a2 for a1, a2 in zip(arg1, arg2))
    except TypeError:
        return arg1==arg2


# PARAM3_DEPRECATION
# The syntax to use a metaclass changed incompatibly between 2 and
# 3. The add_metaclass() class decorator below creates a class using a
# specified metaclass in a way that works on both 2 and 3. For 3, can
# remove this decorator and specify metaclasses in a simpler way
# (https://docs.python.org/3/reference/datamodel.html#customizing-class-creation)
#
# Code from six (https://bitbucket.org/gutworth/six; version 1.4.1).
@_deprecated(warning_cat=_ParamFutureWarning)
def add_metaclass(metaclass):
    """
    Class decorator for creating a class with a metaclass.

    .. deprecated:: 2.0.0
    """
    def wrapper(cls):
        orig_vars = cls.__dict__.copy()
        orig_vars.pop('__dict__', None)
        orig_vars.pop('__weakref__', None)
        for slots_var in orig_vars.get('__slots__', ()):
            orig_vars.pop(slots_var)
        return metaclass(cls.__name__, cls.__bases__, orig_vars)
    return wrapper


class bothmethod:
    """
    'optional @classmethod'

    A decorator that allows a method to receive either the class
    object (if called on the class) or the instance object
    (if called on the instance) as its first argument.
    """

    def __init__(self, method):
        self.method = method

    def __get__(self, instance, owner):
        if instance is None:
            # Class call
            return self.method.__get__(owner)
        else:
            # Instance call
            return self.method.__get__(instance, owner)


def _getattrr(obj, attr, *args):
    def _getattr(obj, attr):
        return getattr(obj, attr, *args)
    return reduce(_getattr, [obj] + attr.split('.'))


def no_instance_params(cls):
    """Disables instance parameters on the class"""
    cls._param__private.disable_instance_params = True
    return cls


def _instantiate_param_obj(paramobj, owner=None):
    """Return a Parameter object suitable for instantiation given the class's Parameter object"""
    # Shallow-copy Parameter object without the watchers
    p = copy.copy(paramobj)
    p.owner = owner

    # Reset watchers since class parameter watcher should not execute
    # on instance parameters
    p.watchers = {}

    # shallow-copy any mutable slot values other than the actual default
    for s in p.__class__._all_slots_:
        v = getattr(p, s)
        if _is_mutable_container(v) and s != "default":
            setattr(p, s, copy.copy(v))
    return p


def _instantiated_parameter(parameterized, param):
    """
    Given a Parameterized object and one of its class Parameter objects,
    return the appropriate Parameter object for this instance, instantiating
    it if need be.
    """
    if (getattr(parameterized._param__private, 'initialized', False) and param.per_instance and
        not getattr(type(parameterized)._param__private, 'disable_instance_params', False)):
        key = param.name

        if key not in parameterized._param__private.params:
            parameterized._param__private.params[key] = _instantiate_param_obj(param, parameterized)

        param = parameterized._param__private.params[key]

    return param


def instance_descriptor(f):
    # If parameter has an instance Parameter, delegate setting
    def _f(self, obj, val):
        # obj is None when the metaclass is setting
        if obj is not None:
            instance_param = obj._param__private.params.get(self.name)
            if instance_param is None:
                instance_param = _instantiated_parameter(obj, self)
            if instance_param is not None and self is not instance_param:
                instance_param.__set__(obj, val)
                return
        return f(self, obj, val)
    return _f


def get_method_owner(method):
    """Gets the instance that owns the supplied method"""
    if not inspect.ismethod(method):
        return None
    if isinstance(method, partial):
        method = method.func
    return method.__self__


# PARAM3_DEPRECATION
def recursive_repr(fillvalue='...'):
    """
    Decorator to make a repr function return fillvalue for a recursive call

    .. deprecated:: 1.12.0
    """
    warnings.warn(
        'recursive_repr has been deprecated and will be removed in a future version.',
        category=_ParamFutureWarning,
        stacklevel=2,
    )
    return _recursive_repr(fillvalue=fillvalue)


@accept_arguments
def output(func, *output, **kw):
    """
    output allows annotating a method on a Parameterized class to
    declare that it returns an output of a specific type. The outputs
    of a Parameterized class can be queried using the
    Parameterized.param.outputs method. By default the output will
    inherit the method name but a custom name can be declared by
    expressing the Parameter type using a keyword argument.

    The simplest declaration simply declares the method returns an
    object without any type guarantees, e.g.:

      @output()

    If a specific parameter type is specified this is a declaration
    that the method will return a value of that type, e.g.:

      @output(param.Number())

    To override the default name of the output the type may be declared
    as a keyword argument, e.g.:

      @output(custom_name=param.Number())

    Multiple outputs may be declared using keywords mapping from output name
    to the type or using tuples of the same format, i.e. these two declarations
    are equivalent:

      @output(number=param.Number(), string=param.String())

      @output(('number', param.Number()), ('string', param.String()))

    output also accepts Python object types which will be upgraded to
    a ClassSelector, e.g.:

      @output(int)
    """
    if output:
        outputs = []
        for i, out in enumerate(output):
            i = i if len(output) > 1 else None
            if isinstance(out, tuple) and len(out) == 2 and isinstance(out[0], str):
                outputs.append(out+(i,))
            elif isinstance(out, str):
                outputs.append((out, Parameter(), i))
            else:
                outputs.append((None, out, i))
    elif kw:
        # (requires keywords to be kept ordered, which was not true in previous versions)
        outputs = [(name, otype, i if len(kw) > 1 else None)
                   for i, (name, otype) in enumerate(kw.items())]
    else:
        outputs = [(None, Parameter(), None)]

    names, processed = [], []
    for name, otype, i in outputs:
        if isinstance(otype, type):
            if issubclass(otype, Parameter):
                otype = otype()
            else:
                from .import ClassSelector
                otype = ClassSelector(class_=otype)
        elif isinstance(otype, tuple) and all(isinstance(t, type) for t in otype):
            from .import ClassSelector
            otype = ClassSelector(class_=otype)
        if not isinstance(otype, Parameter):
            raise ValueError('output type must be declared with a Parameter class, '
                             'instance or a Python object type.')
        processed.append((name, otype, i))
        names.append(name)

    if len(set(names)) != len(names):
        raise ValueError('When declaring multiple outputs each value '
                         'must be unique.')

    _dinfo = getattr(func, '_dinfo', {})
    _dinfo.update({'outputs': processed})

    @wraps(func)
    def _output(*args,**kw):
        return func(*args,**kw)

    _output._dinfo = _dinfo

    return _output


def _parse_dependency_spec(spec):
    """
    Parses param.depends specifications into three components:

    1. The dotted path to the sub-object
    2. The attribute being depended on, i.e. either a parameter or method
    3. The parameter attribute being depended on
    """
    assert spec.count(":")<=1
    spec = spec.strip()
    m = re.match("(?P<path>[^:]*):?(?P<what>.*)", spec)
    what = m.group('what')
    path = "."+m.group('path')
    m = re.match(r"(?P<obj>.*)(\.)(?P<attr>.*)", path)
    obj = m.group('obj')
    attr = m.group("attr")
    return obj or None, attr, what or 'value'


def _params_depended_on(minfo, dynamic=True, intermediate=True):
    """
    Resolves dependencies declared on a Parameterized method.
    Dynamic dependencies, i.e. dependencies on sub-objects which may
    or may not yet be available, are only resolved if dynamic=True.
    By default intermediate dependencies, i.e. dependencies on the
    path to a sub-object are returned. For example for a dependency
    on 'a.b.c' dependencies on 'a' and 'b' are returned as long as
    intermediate=True.

    Returns lists of concrete dependencies on available parameters
    and dynamic dependencies specifications which have to resolved
    if the referenced sub-objects are defined.
    """
    deps, dynamic_deps = [], []
    dinfo = getattr(minfo.method, "_dinfo", {})
    for d in dinfo.get('dependencies', list(minfo.cls.param)):
        ddeps, ddynamic_deps = (minfo.cls if minfo.inst is None else minfo.inst).param._spec_to_obj(d, dynamic, intermediate)
        dynamic_deps += ddynamic_deps
        for dep in ddeps:
            if isinstance(dep, PInfo):
                deps.append(dep)
            else:
                method_deps, method_dynamic_deps = _params_depended_on(dep, dynamic, intermediate)
                deps += method_deps
                dynamic_deps += method_dynamic_deps
    return deps, dynamic_deps


def _resolve_mcs_deps(obj, resolved, dynamic, intermediate=True):
    """
    Resolves constant and dynamic parameter dependencies previously
    obtained using the _params_depended_on function. Existing resolved
    dependencies are updated with a supplied parameter instance while
    dynamic dependencies are resolved if possible.
    """
    dependencies = []
    for dep in resolved:
        if not issubclass(type(obj), dep.cls):
            dependencies.append(dep)
            continue
        inst = obj if dep.inst is None else dep.inst
        dep = PInfo(inst=inst, cls=dep.cls, name=dep.name,
                    pobj=inst.param[dep.name], what=dep.what)
        dependencies.append(dep)
    for dep in dynamic:
        subresolved, _ = obj.param._spec_to_obj(dep.spec, intermediate=intermediate)
        for subdep in subresolved:
            if isinstance(subdep, PInfo):
                dependencies.append(subdep)
            else:
                dependencies += _params_depended_on(subdep, intermediate=intermediate)[0]
    return dependencies


def _skip_event(*events, **kwargs):
    """
    Checks whether a subobject event should be skipped.
    Returns True if all the values on the new subobject
    match the values on the previous subobject.
    """
    what = kwargs.get('what', 'value')
    changed = kwargs.get('changed')
    if changed is None:
        return False
    for e in events:
        for p in changed:
            if what == 'value':
                old = Undefined if e.old is None else _getattrr(e.old, p, None)
                new = Undefined if e.new is None else _getattrr(e.new, p, None)
            else:
                old = Undefined if e.old is None else _getattrr(e.old.param[p], what, None)
                new = Undefined if e.new is None else _getattrr(e.new.param[p], what, None)
            if not Comparator.is_equal(old, new):
                return False
    return True


def extract_dependencies(function):
    """Extract references from a method or function that declares the references."""
    subparameters = list(function._dinfo['dependencies'])+list(function._dinfo['kw'].values())
    params = []
    for p in subparameters:
        if isinstance(p, str):
            owner = get_method_owner(function)
            *subps, p = p.split('.')
            for subp in subps:
                owner = getattr(owner, subp, None)
                if owner is None:
                    raise ValueError('Cannot depend on undefined sub-parameter {p!r}.')
            if p in owner.param:
                pobj = owner.param[p]
                if pobj not in params:
                    params.append(pobj)
            else:
                for sp in extract_dependencies(getattr(owner, p)):
                    if sp not in params:
                        params.append(sp)
        elif p not in params:
            params.append(p)
    return params


# Two callers at the module top level to support pickling.
async def _async_caller(*events, what='value', changed=None, callback=None, function=None):
    if callback:
        callback(*events)
    if not _skip_event or not _skip_event(*events, what=what, changed=changed):
        await function()


def _sync_caller(*events, what='value', changed=None, callback=None, function=None):
    if callback:
        callback(*events)
    if not _skip_event(*events, what=what, changed=changed):
        return function()


def _m_caller(self, method_name, what='value', changed=None, callback=None):
    """
    Wraps a method call adding support for scheduling a callback
    before it is executed and skipping events if a subobject has
    changed but its values have not.
    """
    function = getattr(self, method_name)
    _caller = _async_caller if iscoroutinefunction(function) else _sync_caller
    caller = partial(_caller, what=what, changed=changed, callback=callback, function=function)
    caller._watcher_name = method_name
    return caller


def _add_doc(obj, docstring):
    """Add a docstring to a namedtuple"""
    obj.__doc__ = docstring


PInfo = namedtuple("PInfo", "inst cls name pobj what")
_add_doc(PInfo,
    """
    Object describing something being watched about a Parameter.

    `inst`: Parameterized instance owning the Parameter, or None

    `cls`: Parameterized class owning the Parameter

    `name`: Name of the Parameter being watched

    `pobj`: Parameter object being watched

    `what`: What is being watched on the Parameter (either 'value' or a slot name)
    """)

MInfo = namedtuple("MInfo", "inst cls name method")
_add_doc(MInfo,
    """
    Object describing a Parameterized method being watched.

    `inst`: Parameterized instance owning the method, or None

    `cls`: Parameterized class owning the method

    `name`: Name of the method being watched

    `method`: bound method of the object being watched
    """)

DInfo = namedtuple("DInfo", "spec")
_add_doc(DInfo,
    """
    Object describing dynamic dependencies.
    `spec`: Dependency specification to resolve
    """)

Event = namedtuple("Event", "what name obj cls old new type")
_add_doc(Event,
    """
    Object representing an event that triggers a Watcher.

    `what`: What is being watched on the Parameter (either value or a slot name)

    `name`: Name of the Parameter that was set or triggered

    `obj`: Parameterized instance owning the watched Parameter, or None

    `cls`: Parameterized class owning the watched Parameter

    `old`: Previous value of the item being watched

    `new`: New value of the item being watched

    `type`: `triggered` if this event was triggered explicitly), `changed` if
    the item was set and watching for `onlychanged`, `set` if the item was set,
    or  None if type not yet known
    """)

_Watcher = namedtuple("Watcher", "inst cls fn mode onlychanged parameter_names what queued precedence")

class Watcher(_Watcher):
    """
    Object declaring a callback function to invoke when an Event is
    triggered on a watched item.

    `inst`: Parameterized instance owning the watched Parameter, or
    None

    `cls`: Parameterized class owning the watched Parameter

    `fn`: Callback function to invoke when triggered by a watched
    Parameter

    `mode`: 'args' for param.watch (call `fn` with PInfo object
    positional args), or 'kwargs' for param.watch_values (call `fn`
    with <param_name>:<new_value> keywords)

    `onlychanged`: If True, only trigger for actual changes, not
    setting to the current value

    `parameter_names`: List of Parameters to watch, by name

    `what`: What to watch on the Parameters (either 'value' or a slot
    name)

    `queued`: Immediately invoke callbacks triggered during processing
            of an Event (if False), or queue them up for processing
            later, after this event has been handled (if True)

    `precedence`: A numeric value which determines the precedence of
                  the watcher.  Lower precedence values are executed
                  with higher priority.
    """

    def __new__(cls_, *args, **kwargs):
        """Allows creating Watcher without explicit precedence value."""
        values = dict(zip(cls_._fields, args))
        values.update(kwargs)
        if 'precedence' not in values:
            values['precedence'] = 0
        return super().__new__(cls_, **values)

    def __str__(self):
        cls = type(self)
        attrs = ', '.join([f'{f}={getattr(self, f)!r}' for f in cls._fields])
        return f"{cls.__name__}({attrs})"




class ParameterMetaclass(type):
    """Metaclass allowing control over creation of Parameter classes."""

    def __new__(mcs, classname, bases, classdict):

        # store the class's docstring in __classdoc
        if '__doc__' in classdict:
            classdict['__classdoc']=classdict['__doc__']

        # when asking for help on Parameter *object*, return the doc slot
        classdict['__doc__'] = property(attrgetter('doc'))

        # Compute all slots in order, using a dict later turned into a list
        # as it's the fastest way to get an ordered set in Python
        all_slots = {}
        for bcls in set(chain(*(base.__mro__[::-1] for base in bases))):
            all_slots.update(dict.fromkeys(getattr(bcls, '__slots__', [])))

        # To get the benefit of slots, subclasses must themselves define
        # __slots__, whether or not they define attributes not present in
        # the base Parameter class.  That's because a subclass will have
        # a __dict__ unless it also defines __slots__.
        if '__slots__' not in classdict:
            classdict['__slots__'] = []
        else:
            all_slots.update(dict.fromkeys(classdict['__slots__']))

        classdict['_all_slots_'] = list(all_slots)

        # No special handling for a __dict__ slot; should there be?
        return type.__new__(mcs, classname, bases, classdict)

    def __getattribute__(mcs,name):
        if name=='__doc__':
            # when asking for help on Parameter *class*, return the
            # stored class docstring
            return type.__getattribute__(mcs,'__classdoc')
        else:
            return type.__getattribute__(mcs,name)


class _ParameterBase(metaclass=ParameterMetaclass):
    """
    Base Parameter class used to dynamically update the signature of all
    the Parameters.
    """

    @classmethod
    def _modified_slots_defaults(cls):
        defaults = cls._slot_defaults.copy()
        defaults['label'] = defaults.pop('_label')
        return defaults

    @classmethod
    def __init_subclass__(cls):
        super().__init_subclass__()
        # _update_signature has been tested against the Parameters available
        # in Param, we don't want to break the Parameters created elsewhere
        # so wrapping this in a loose try/except.
        try:
            cls._update_signature()
        except Exception:
            # The super signature has been changed so we need to get the one
            # from the class constructor directly.
            cls.__signature__ = inspect.signature(cls.__init__)

    @classmethod
    def _update_signature(cls):
        defaults = cls._modified_slots_defaults()
        new_parameters = {}

        for i, kls in enumerate(cls.mro()):
            if kls.__name__.startswith('_'):
                continue
            sig = inspect.signature(kls.__init__)
            for pname, parameter in sig.parameters.items():
                if pname == 'self':
                    continue
                if i >= 1 and parameter.default == inspect.Signature.empty:
                    continue
                if parameter.kind in (inspect.Parameter.VAR_KEYWORD, inspect.Parameter.VAR_POSITIONAL):
                    continue
                if getattr(parameter, 'default', None) is Undefined:
                    if pname not in defaults:
                        raise LookupError(
                            f'Argument {pname!r} of Parameter {cls.__name__!r} has no '
                            'entry in _slot_defaults.'
                        )
                    default = defaults[pname]
                    if callable(default) and hasattr(default, 'sig'):
                        default = default.sig
                    new_parameter = parameter.replace(default=default)
                else:
                    new_parameter = parameter
                if i >= 1:
                    new_parameter = new_parameter.replace(kind=inspect.Parameter.KEYWORD_ONLY)
                new_parameters.setdefault(pname, new_parameter)

        def _sorter(p):
            if p.default == inspect.Signature.empty:
                return 0
            else:
                return 1

        new_parameters = sorted(new_parameters.values(), key=_sorter)
        new_sig = sig.replace(parameters=new_parameters)
        cls.__signature__ = new_sig


class Parameter(_ParameterBase):
    """
    An attribute descriptor for declaring parameters.

    Parameters are a special kind of class attribute.  Setting a
    Parameterized class attribute to be a Parameter instance causes
    that attribute of the class (and the class's instances) to be
    treated as a Parameter.  This allows special behavior, including
    dynamically generated parameter values, documentation strings,
    constant and read-only parameters, and type or range checking at
    assignment time.

    For example, suppose someone wants to define two new kinds of
    objects Foo and Bar, such that Bar has a parameter delta, Foo is a
    subclass of Bar, and Foo has parameters alpha, sigma, and gamma
    (and delta inherited from Bar).  She would begin her class
    definitions with something like this::

       class Bar(Parameterized):
           delta = Parameter(default=0.6, doc='The difference between steps.')
           ...
       class Foo(Bar):
           alpha = Parameter(default=0.1, doc='The starting value.')
           sigma = Parameter(default=0.5, doc='The standard deviation.',
                           constant=True)
           gamma = Parameter(default=1.0, doc='The ending value.')
           ...

    Class Foo would then have four parameters, with delta defaulting
    to 0.6.

    Parameters have several advantages over plain attributes:

    1. Parameters can be set automatically when an instance is
       constructed: The default constructor for Foo (and Bar) will
       accept arbitrary keyword arguments, each of which can be used
       to specify the value of a Parameter of Foo (or any of Foo's
       superclasses).  E.g., if a script does this::

           myfoo = Foo(alpha=0.5)

       myfoo.alpha will return 0.5, without the Foo constructor
       needing special code to set alpha.

       If Foo implements its own constructor, keyword arguments will
       still be accepted if the constructor accepts a dictionary of
       keyword arguments (as in ``def __init__(self,**params):``), and
       then each class calls its superclass (as in
       ``super(Foo,self).__init__(**params)``) so that the
       Parameterized constructor will process the keywords.

    2. A Parameterized class need specify only the attributes of a
       Parameter whose values differ from those declared in
       superclasses; the other values will be inherited.  E.g. if Foo
       declares::

        delta = Parameter(default=0.2)

       the default value of 0.2 will override the 0.6 inherited from
       Bar, but the doc will be inherited from Bar.

    3. The Parameter descriptor class can be subclassed to provide
       more complex behavior, allowing special types of parameters
       that, for example, require their values to be numbers in
       certain ranges, generate their values dynamically from a random
       distribution, or read their values from a file or other
       external source.

    4. The attributes associated with Parameters provide enough
       information for automatically generating property sheets in
       graphical user interfaces, allowing Parameterized instances to
       be edited by users.

    Note that Parameters can only be used when set as class attributes
    of Parameterized classes. Parameters used as standalone objects,
    or as class attributes of non-Parameterized classes, will not have
    the behavior described here.
    """

    # Because they implement __get__ and __set__, Parameters are known
    # as 'descriptors' in Python; see "Implementing Descriptors" and
    # "Invoking Descriptors" in the 'Customizing attribute access'
    # section of the Python reference manual:
    # http://docs.python.org/ref/attribute-access.html
    #
    # Overview of Parameters for programmers
    # ======================================
    #
    # Consider the following code:
    #
    #
    # class A(Parameterized):
    #     p = Parameter(default=1)
    #
    # a1 = A()
    # a2 = A()
    #
    #
    # * a1 and a2 share one Parameter object (A.__dict__['p']).
    #
    # * The default (class) value of p is stored in this Parameter
    #   object (A.__dict__['p'].default).
    #
    # * If the value of p is set on a1 (e.g. a1.p=2), a1's value of p
    #   is stored in a1 itself (a1._param__private.values['p'])
    #
    # * When a1.p is requested, a1._param__private.values['p'] is
    #   returned. When a2.p is requested, 'p' is not found in
    #   a1._param__private.values, so A.__dict__['p'].default (i.e. A.p) is
    #   returned instead.
    #
    #
    # Be careful when referring to the 'name' of a Parameter:
    #
    # * A Parameterized class has a name for the attribute which is
    #   being represented by the Parameter ('p' in the example above);
    #   in the code, this is called the 'name'.
    #
    # * When a Parameterized instance has its own local value for a
    #   parameter, it is stored as 'p._param__private.values[X]' where X is the
    #   name of the Parameter


    # So that the extra features of Parameters do not require a lot of
    # overhead, Parameters are implemented using __slots__ (see
    # http://www.python.org/doc/2.4/ref/slots.html).  Instead of having
    # a full Python dictionary associated with each Parameter instance,
    # Parameter instances have an enumerated list (named __slots__) of
    # attributes, and reserve just enough space to store these
    # attributes.  Using __slots__ requires special support for
    # operations to copy and restore Parameters (e.g. for Python
    # persistent storage pickling); see __getstate__ and __setstate__.
    __slots__ = ['name', 'default', 'doc',
                 'precedence', 'instantiate', 'constant', 'readonly',
                 'pickle_default_value', 'allow_None', 'per_instance',
                 'watchers', 'owner', 'allow_refs', 'nested_refs', '_label']

    # Note: When initially created, a Parameter does not know which
    # Parameterized class owns it, nor does it know its names
    # (attribute name, internal name). Once the owning Parameterized
    # class is created, owner, and name are
    # set.

    _serializers = {'json': serializer.JSONSerialization}

    _slot_defaults = dict(
        default=None, precedence=None, doc=None, _label=None, instantiate=False,
        constant=False, readonly=False, pickle_default_value=True, allow_None=False,
        per_instance=True, allow_refs=False, nested_refs=False
    )

    # Parameters can be updated during Parameterized class creation when they
    # are defined multiple times in a class hierarchy. We have to record which
    # Parameter slots require the default value to be re-validated. Any slots
    # in this list do not have to trigger such re-validation.
    _non_validated_slots = ['_label', 'doc', 'name', 'precedence',
                            'constant', 'pickle_default_value',
                            'watchers', 'owner']

    @typing.overload
    def __init__(
        self,
        default=None, *,
        doc=None, label=None, precedence=None, instantiate=False, constant=False,
        readonly=False, pickle_default_value=True, allow_None=False, per_instance=True,
        allow_refs=False, nested_refs=False
    ):
        ...

    @_deprecate_positional_args
    def __init__(self, default=Undefined, *, doc=Undefined, # pylint: disable-msg=R0913
                 label=Undefined, precedence=Undefined,
                 instantiate=Undefined, constant=Undefined, readonly=Undefined,
                 pickle_default_value=Undefined, allow_None=Undefined,
                 per_instance=Undefined, allow_refs=Undefined, nested_refs=Undefined):
        """
        Initialize a new Parameter object and store the supplied attributes:

        default: the owning class's value for the attribute represented
        by this Parameter, which can be overridden in an instance.

        doc: docstring explaining what this parameter represents.

        label: optional text label to be used when this Parameter is
        shown in a listing. If no label is supplied, the attribute name
        for this parameter in the owning Parameterized object is used.

        precedence: a numeric value, usually in the range 0.0 to 1.0,
        which allows the order of Parameters in a class to be defined in
        a listing or e.g. in GUI menus. A negative precedence indicates
        a parameter that should be hidden in such listings.

        instantiate: controls whether the value of this Parameter will
        be deepcopied when a Parameterized object is instantiated (if
        True), or if the single default value will be shared by all
        Parameterized instances (if False). For an immutable Parameter
        value, it is best to leave instantiate at the default of
        False, so that a user can choose to change the value at the
        Parameterized instance level (affecting only that instance) or
        at the Parameterized class or superclass level (affecting all
        existing and future instances of that class or superclass). For
        a mutable Parameter value, the default of False is also appropriate
        if you want all instances to share the same value state, e.g. if
        they are each simply referring to a single global object like
        a singleton. If instead each Parameterized should have its own
        independently mutable value, instantiate should be set to
        True, but note that there is then no simple way to change the
        value of this Parameter at the class or superclass level,
        because each instance, once created, will then have an
        independently instantiated value.

        constant: if true, the Parameter value can be changed only at
        the class level or in a Parameterized constructor call. The
        value is otherwise constant on the Parameterized instance,
        once it has been constructed.

        readonly: if true, the Parameter value cannot ordinarily be
        changed by setting the attribute at the class or instance
        levels at all. The value can still be changed in code by
        temporarily overriding the value of this slot and then
        restoring it, which is useful for reporting values that the
        _user_ should never change but which do change during code
        execution.

        pickle_default_value: whether the default value should be
        pickled. Usually, you would want the default value to be pickled,
        but there are rare cases where that would not be the case (e.g.
        for file search paths that are specific to a certain system).

        per_instance: whether a separate Parameter instance will be
        created for every Parameterized instance. True by default.
        If False, all instances of a Parameterized class will share
        the same Parameter object, including all validation
        attributes (bounds, etc.). See also instantiate, which is
        conceptually similar but affects the Parameter value rather
        than the Parameter object.

        allow_None: if True, None is accepted as a valid value for
        this Parameter, in addition to any other values that are
        allowed. If the default value is defined as None, allow_None
        is set to True automatically.

        allow_refs: if True allows automatically linking parameter
        references to this Parameter, i.e. the parameter value will
        automatically reflect the current value of the reference that
        is passed in.

        nested_refs: if True and allow_refs=True then even nested objects
        such as dictionaries, lists, slices, tuples and sets will be
        inspected for references and will be automatically resolved.

        default, doc, and precedence all default to None, which allows
        inheritance of Parameter slots (attributes) from the owning-class'
        class hierarchy (see ParameterizedMetaclass).
        """
        self.name = None
        self.owner = None
        self.allow_refs = allow_refs
        self.nested_refs = nested_refs
        self.precedence = precedence
        self.default = default
        self.doc = doc
        self.constant = constant is True or readonly is True # readonly => constant
        self.readonly = readonly
        self._label = label
        self._set_instantiate(instantiate)
        self.pickle_default_value = pickle_default_value
        self._set_allow_None(allow_None)
        self.watchers = {}
        self.per_instance = per_instance

    @classmethod
    def serialize(cls, value):
        """Given the parameter value, return a Python value suitable for serialization"""
        return value

    @classmethod
    def deserialize(cls, value):
        """Given a serializable Python value, return a value that the parameter can be set to"""
        return value

    def schema(self, safe=False, subset=None, mode='json'):
        if mode not in  self._serializers:
            raise KeyError(f'Mode {mode!r} not in available serialization formats {list(self._serializers.keys())!r}')
        return self._serializers[mode].param_schema(self.__class__.__name__, self,
                                                    safe=safe, subset=subset)

    @property
    def rx(self):
        """
        The reactive namespace.

        Provides reactive versions of operations that cannot be made reactive through operator overloading, such as
        `.rx.and_` and `.rx.bool`. Calling this namespace (`()`) returns a reactive expression.

        Returns
        -------
        Reactive expression
            The result of calling the reactive namespace is a reactive expression.

        User Guide
        ----------
        https://param.holoviz.org/user_guide/Reactive_Expressions.html#special-methods-on-rx

        Examples
        --------
        Create a Parameterized instance:

        >>> import param
        >>> class P(param.Parameterized):
        ...     a = param.Number()
        >>> p = P(a=1)

        Get the current value:

        >>> a = p.param.a.rx.value

        Call it to get a reactive expression:

        >>> rx_value = p.param.a.rx()

        """
        from .reactive import reactive_ops
        return reactive_ops(self)

    @property
    def label(self):
        if self.name and self._label is None:
            return label_formatter(self.name)
        else:
            return self._label

    @label.setter
    def label(self, val):
        self._label = val

    def _set_allow_None(self, allow_None):
        # allow_None is set following these rules (last takes precedence):
        # 1. to False by default
        # 2. to the value provided in the constructor, if any
        # 3. to True if default is None
        if self.default is None:
            self.allow_None = True
        elif allow_None is not Undefined:
            self.allow_None = allow_None
        else:
            self.allow_None = self._slot_defaults['allow_None']

    def _set_instantiate(self,instantiate):
        """Constant parameters must be instantiated."""
        # instantiate doesn't actually matter for read-only
        # parameters, since they can't be set even on a class.  But
        # having this code avoids needless instantiation.
        if self.readonly:
            self.instantiate = False
        elif instantiate is not Undefined:
            self.instantiate = instantiate
        else:
            # Default value
            self.instantiate = self._slot_defaults['instantiate']

    def __setattr__(self, attribute, value):
        if attribute == 'name':
            name = getattr(self, 'name', None)
            if name is not None and value != name:
                raise AttributeError("Parameter name cannot be modified after "
                                     "it has been bound to a Parameterized.")

        is_slot = attribute in self.__class__._all_slots_
        has_watcher = attribute != "default" and attribute in getattr(self, 'watchers', [])
        if not (is_slot or has_watcher):
            # Return early if attribute is not a slot
            return super().__setattr__(attribute, value)

        # Otherwise get the old value so we can call watcher/on_set
        old = getattr(self, attribute, NotImplemented)
        if is_slot:
            try:
                self._on_set(attribute, old, value)
            except AttributeError:
                pass

        super().__setattr__(attribute, value)
        if has_watcher and old is not NotImplemented:
            self._trigger_event(attribute, old, value)

    def _trigger_event(self, attribute, old, new):
        event = Event(what=attribute, name=self.name, obj=None, cls=self.owner,
                      old=old, new=new, type=None)
        for watcher in self.watchers[attribute]:
            self.owner.param._call_watcher(watcher, event)
        if not self.owner.param._BATCH_WATCH:
            self.owner.param._batch_call_watchers()

    def __getattribute__(self, key):
        """
        Allow slot values to be Undefined in an "unbound" parameter, i.e. one
        that is not (yet) owned by a Parameterized object, in which case their
        value will be retrieved from the _slot_defaults dictionary.
        """
        v = object.__getattribute__(self, key)
        # Safely checks for name (avoiding recursion) to decide if this object is unbound
        if v is Undefined and key != "name" and getattr(self, "name", None) is None:
            try:
                v = self._slot_defaults[key]
            except KeyError as e:
                raise KeyError(
                    f'Slot {key!r} on unbound parameter {self.__class__.__name__!r} '
                    'has no default value defined in `_slot_defaults`'
                ) from e
            if callable(v):
                v = v(self)
        return v

    def _on_set(self, attribute, old, value):
        """
        Can be overridden on subclasses to handle changes when parameter
        attribute is set.
        """

    def _update_state(self):
        """
        Can be overridden on subclasses to update a Parameter state, i.e. slot
        values, after the slot values have been set in the inheritance procedure.
        """

    def __get__(self, obj, objtype): # pylint: disable-msg=W0613
        """
        Return the value for this Parameter.

        If called for a Parameterized class, produce that
        class's value (i.e. this Parameter object's 'default'
        attribute).

        If called for a Parameterized instance, produce that
        instance's value, if one has been set - otherwise produce the
        class's value (default).
        """
        if obj is None: # e.g. when __get__ called for a Parameterized class
            result = self.default
        else:
            # Attribute error when .values does not exist (_ClassPrivate)
            # and KeyError when there's no cached value for this parameter.
            try:
                result = obj._param__private.values[self.name]
            except (AttributeError, KeyError):
                result = self.default
        return result

    @instance_descriptor
    def __set__(self, obj, val):
        """
        Set the value for this Parameter.

        If called for a Parameterized class, set that class's
        value (i.e. set this Parameter object's 'default' attribute).

        If called for a Parameterized instance, set the value of
        this Parameter on that instance (i.e. in the instance's
        `values` dictionary located in the private namespace `_param__private`,
        under the parameter's name).

        If the Parameter's constant attribute is True, only allows
        the value to be set for a Parameterized class or on
        uninitialized Parameterized instances.

        If the Parameter's readonly attribute is True, only allows the
        value to be specified in the Parameter declaration inside the
        Parameterized source code. A read-only parameter also
        cannot be set on a Parameterized class.

        Note that until we support some form of read-only
        object, it is still possible to change the attributes of the
        object stored in a constant or read-only Parameter (e.g. one
        item in a list).
        """
        name = self.name
        if obj is not None and self.allow_refs and obj._param__private.initialized:
            syncing = name in obj._param__private.syncing
            ref, deps, val, is_async = obj.param._resolve_ref(self, val)
            refs = obj._param__private.refs
            if ref is not None:
                self.owner.param._update_ref(name, ref)
            elif name in refs and not syncing:
                del refs[name]
                if name in obj._param__private.async_refs:
                    obj._param__private.async_refs.pop(name).cancel()
            if is_async or val is Undefined:
                return

        # Deprecated Number set_hook called here to avoid duplicating setter
        if hasattr(self, 'set_hook'):
            val = self.set_hook(obj, val)
            if self.set_hook is not _identity_hook:
                # PARAM3_DEPRECATION
                warnings.warn(
                    'Number.set_hook has been deprecated.',
                    category=_ParamFutureWarning,
                    stacklevel=6,
                )

        self._validate(val)

        _old = NotImplemented
        # obj can be None if __set__ is called for a Parameterized class
        if self.constant or self.readonly:
            if self.readonly:
                raise TypeError("Read-only parameter '%s' cannot be modified" % name)
            elif obj is None:
                _old = self.default
                self.default = val
            elif not obj._param__private.initialized:
                _old = obj._param__private.values.get(self.name, self.default)
                obj._param__private.values[self.name] = val
            else:
                _old = obj._param__private.values.get(self.name, self.default)
                if val is not _old:
                    raise TypeError("Constant parameter '%s' cannot be modified" % name)
        else:
            if obj is None:
                _old = self.default
                self.default = val
            else:
                # When setting a Parameter before calling super.
                if not isinstance(obj._param__private, _InstancePrivate):
                    obj._param__private = _InstancePrivate(
                        explicit_no_refs=type(obj)._param__private.explicit_no_refs
                    )
                _old = obj._param__private.values.get(name, self.default)
                obj._param__private.values[name] = val
        self._post_setter(obj, val)

        if obj is not None:
            if not hasattr(obj, '_param__private') or not getattr(obj._param__private, 'initialized', False):
                return
            obj.param._update_deps(name)

        if obj is None:
            watchers = self.watchers.get("value")
        elif name in obj._param__private.watchers:
            watchers = obj._param__private.watchers[name].get('value')
            if watchers is None:
                watchers = self.watchers.get("value")
        else:
            watchers = None

        obj = self.owner if obj is None else obj

        if obj is None or not watchers:
            return

        event = Event(what='value', name=name, obj=obj, cls=self.owner,
                      old=_old, new=val, type=None)

        # Copy watchers here since they may be modified inplace during iteration
        for watcher in sorted(watchers, key=lambda w: w.precedence):
            obj.param._call_watcher(watcher, event)
        if not obj.param._BATCH_WATCH:
            obj.param._batch_call_watchers()

    def _validate_value(self, value, allow_None):
        """Implements validation for parameter value"""

    def _validate(self, val):
        """Implements validation for the parameter value and attributes"""
        self._validate_value(val, self.allow_None)

    def _post_setter(self, obj, val):
        """Called after the parameter value has been validated and set"""

    def __delete__(self,obj):
        raise TypeError("Cannot delete '%s': Parameters deletion not allowed." % self.name)

    def _set_names(self, attrib_name):
        if None not in (self.owner, self.name) and attrib_name != self.name:
            raise AttributeError('The {} parameter {!r} has already been '
                                 'assigned a name by the {} class, '
                                 'could not assign new name {!r}. Parameters '
                                 'may not be shared by multiple classes; '
                                 'ensure that you create a new parameter '
                                 'instance for each new class.'.format(type(self).__name__, self.name,
                                    self.owner.name, attrib_name))
        self.name = attrib_name

    def __getstate__(self):
        """
        All Parameters have slots, not a dict, so we have to support
        pickle and deepcopy ourselves.
        """
        return {slot: getattr(self, slot) for slot in self.__class__._all_slots_}

    def __setstate__(self,state):
        # set values of __slots__ (instead of in non-existent __dict__)
        for k, v in state.items():
            setattr(self, k, v)


# Define one particular type of Parameter that is used in this file
class String(Parameter):
    r"""
    A String Parameter, with a default value and optional regular expression (regex) matching.

    Example of using a regex to implement IPv4 address matching::

      class IPAddress(String):
        '''IPv4 address as a string (dotted decimal notation)'''
       def __init__(self, default="0.0.0.0", allow_None=False, **kwargs):
           ip_regex = r'^((25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)\.){3}(25[0-5]|2[0-4][0-9]|[01]?[0-9][0-9]?)$'
           super(IPAddress, self).__init__(default=default, regex=ip_regex, **kwargs)

    """

    __slots__ = ['regex']

    _slot_defaults = dict(Parameter._slot_defaults, default="", regex=None)

    @typing.overload
    def __init__(
        self,
        default="", *, regex=None,
        doc=None, label=None, precedence=None, instantiate=False, constant=False,
        readonly=False, pickle_default_value=True, allow_None=False, per_instance=True,
        allow_refs=False, nested_refs=False
    ):
        ...

    @_deprecate_positional_args
    def __init__(self, default=Undefined, *, regex=Undefined, **kwargs):
        super().__init__(default=default, **kwargs)
        self.regex = regex
        self._validate(self.default)

    def _validate_regex(self, val, regex):
        if (val is None and self.allow_None):
            return
        if regex is not None and re.match(regex, val) is None:
            raise ValueError(
                f'{_validate_error_prefix(self)} value {val!r} does not '
                f'match regex {regex!r}.'
            )

    def _validate_value(self, val, allow_None):
        if allow_None and val is None:
            return
        if not isinstance(val, str):
            raise ValueError(
                f'{_validate_error_prefix(self)} only takes a string value, '
                f'not value of {type(val)}.'
            )

    def _validate(self, val):
        self._validate_value(val, self.allow_None)
        self._validate_regex(val, self.regex)


class shared_parameters:
    """
    Context manager to share parameter instances when creating
    multiple Parameterized objects of the same type. Parameter default
    values are instantiated once and cached to be reused when another
    Parameterized object of the same type is instantiated.
    Can be useful to easily modify large collections of Parameterized
    objects at once and can provide a significant speedup.
    """

    _share = False
    _shared_cache = {}

    def __enter__(self):
        shared_parameters._share = True

    def __exit__(self, exc_type, exc_val, exc_tb):
        shared_parameters._share = False
        shared_parameters._shared_cache = {}


def as_uninitialized(fn):
    """
    Decorator: call fn with the parameterized_instance's
    initialization flag set to False, then revert the flag.

    (Used to decorate Parameterized methods that must alter
    a constant Parameter.)
    """
    @wraps(fn)
    def override_initialization(self_,*args,**kw):
        parameterized_instance = self_.self
        original_initialized = parameterized_instance._param__private.initialized
        parameterized_instance._param__private.initialized = False
        ret = fn(self_, *args, **kw)
        parameterized_instance._param__private.initialized = original_initialized
        return ret
    return override_initialization


class Comparator:
    """
    Comparator defines methods for determining whether two objects
    should be considered equal. It works by registering custom
    comparison functions, which may either be registed by type or with
    a predicate function. If no matching comparison can be found for
    the two objects the comparison will return False.

    If registered by type the Comparator will check whether both
    objects are of that type and apply the comparison. If the equality
    function is instead registered with a function it will call the
    function with each object individually to check if the comparison
    applies. This is useful for defining comparisons for objects
    without explicitly importing them.

    To use the Comparator simply call the is_equal function.
    """

    equalities = {
        numbers.Number: operator.eq,
        str: operator.eq,
        bytes: operator.eq,
        type(None): operator.eq,
        lambda o: hasattr(o, '_infinitely_iterable'): operator.eq,  # Time
    }
    gen_equalities = {
        _dt_types: operator.eq
    }

    @classmethod
    def is_equal(cls, obj1, obj2):
        equals = cls.equalities.copy()
        for gen, op in cls.gen_equalities.items():
            for t in gen():
                equals[t] = op

        for eq_type, eq in equals.items():
            try:
                are_instances = isinstance(obj1, eq_type) and isinstance(obj2, eq_type)
            except TypeError:
                pass
            else:
                if are_instances:
                    return eq(obj1, obj2)
            if isinstance(eq_type, FunctionType) and eq_type(obj1) and eq_type(obj2):
                return eq(obj1, obj2)
        if isinstance(obj2, (list, set, tuple)):
            return cls.compare_iterator(obj1, obj2)
        elif isinstance(obj2, dict):
            return cls.compare_mapping(obj1, obj2)
        return False

    @classmethod
    def compare_iterator(cls, obj1, obj2):
        if type(obj1) is not type(obj2) or len(obj1) != len(obj2):
            return False
        for o1, o2 in zip(obj1, obj2):
            if not cls.is_equal(o1, o2):
                return False
        return True

    @classmethod
    def compare_mapping(cls, obj1, obj2):
        if type(obj1) is not type(obj2) or len(obj1) != len(obj2): return False
        for k in obj1:
            if k in obj2:
                if not cls.is_equal(obj1[k], obj2[k]):
                    return False
            else:
                return False
        return True


class _ParametersRestorer:
    """Context-manager to handle the reset of parameter values after an update."""

    def __init__(self, *, parameters, restore, refs=None):
        self._parameters = parameters
        self._restore = restore
        self._refs = {} if refs is None else refs

    def __enter__(self):
        return self._restore

    def __exit__(self, exc_type, exc_value, exc_tb):
        try:
            self._parameters._update(dict(self._restore, **self._refs))
        finally:
            self._restore = {}


class Parameters:
    """
    Object that holds the namespace and implementation of Parameterized
    methods as well as any state that is not in __slots__ or the
    Parameters themselves.

    Exists at both the metaclass level (instantiated by the metaclass)
    and at the instance level. Can contain state specific to either the
    class or the instance as necessary.
    """

    def __init__(self_, cls, self=None):
        """
        cls is the Parameterized class which is always set.
        self is the instance if set.
        """
        self_.cls = cls
        self_.self = self

    @property
    def _BATCH_WATCH(self_):
        return self_.self_or_cls._param__private.parameters_state['BATCH_WATCH']

    @_BATCH_WATCH.setter
    def _BATCH_WATCH(self_, value):
        self_.self_or_cls._param__private.parameters_state['BATCH_WATCH'] = value

    @property
    def _TRIGGER(self_):
        return self_.self_or_cls._param__private.parameters_state['TRIGGER']

    @_TRIGGER.setter
    def _TRIGGER(self_, value):
        self_.self_or_cls._param__private.parameters_state['TRIGGER'] = value

    @property
    def _events(self_):
        return self_.self_or_cls._param__private.parameters_state['events']

    @_events.setter
    def _events(self_, value):
        self_.self_or_cls._param__private.parameters_state['events'] = value

    @property
    def _state_watchers(self_):
        return self_.self_or_cls._param__private.parameters_state['watchers']

    @_state_watchers.setter
    def _state_watchers(self_, value):
        self_.self_or_cls._param__private.parameters_state['watchers'] = value

    @property
    def watchers(self_):
        """Dictionary of instance watchers."""
        if self_.self is None:
            raise TypeError('Accessing `.param.watchers` is only supported on a Parameterized instance, not class.')
        return self_.self._param__private.watchers

    @watchers.setter
    def watchers(self_, value):
        if self_.self is None:
            raise TypeError('Setting `.param.watchers` is only supported on a Parameterized instance, not class.')
        self_.self._param__private.watchers = value

    @property
    def self_or_cls(self_):
        return self_.cls if self_.self is None else self_.self

    def __setstate__(self, state):
        # Set old parameters state on Parameterized.parameters_state
        self_, cls = state.get('self'), state.get('cls')
        self_or_cls = self_ if self_ is not None else cls
        for k in self_or_cls._param__private.parameters_state:
            key = '_'+k
            if key in state:
                self_or_cls._param__private.parameters_state[k] = state.pop(key)
        for k, v in state.items():
            setattr(self, k, v)

    def __getitem__(self_, key):
        """Returns the class or instance parameter"""
        inst = self_.self
        if inst is None:
            return self_._cls_parameters[key]
        p = self_.objects(instance=False)[key]
        return _instantiated_parameter(inst, p)

    def __dir__(self_):
        """Adds parameters to dir"""
        return super().__dir__() + list(self_._cls_parameters)

    def __iter__(self_):
        """Iterates over the parameters on this object."""
        yield from self_._cls_parameters

    def __contains__(self_, param):
        return param in self_._cls_parameters

    def __getattr__(self_, attr):
        """Extends attribute access to parameter objects."""
        cls = self_.__dict__.get('cls')
        if cls is None: # Class not initialized
            raise AttributeError

        if attr in self_._cls_parameters:
            return self_.__getitem__(attr)
        elif self_.self is None:
            raise AttributeError(f"type object '{self_.cls.__name__}.param' has no attribute {attr!r}")
        else:
            raise AttributeError(f"'{self_.cls.__name__}.param' object has no attribute {attr!r}")

    @as_uninitialized
    def _set_name(self_, name):
        self_.self.name = name

    @as_uninitialized
    def _generate_name(self_):
        self_._set_name('%s%05d' % (self_.cls.__name__, object_count))

    @as_uninitialized
    def _setup_params(self_, **params):
        """
        Initialize default and keyword parameter values.

        First, ensures that values for all Parameters with 'instantiate=True'
        (typically used for mutable Parameters) are copied directly into each object,
        to ensure that there is an independent copy of the value (to avoid surprising
        aliasing errors). Second, ensures that Parameters with 'constant=True' are
        referenced on the instance, to make sure that setting a constant
        Parameter on the class doesn't affect already created instances. Then
        sets each of the keyword arguments, raising when any of them are not
        defined as parameters.
        """
        self = self_.self
        ## Deepcopy all 'instantiate=True' parameters
        params_to_deepcopy = {}
        params_to_ref = {}
        objects = self_._cls_parameters
        for pname, p in objects.items():
            if p.instantiate and pname != "name":
                params_to_deepcopy[pname] = p
            elif p.constant and pname != 'name':
                params_to_ref[pname] = p

        for p in params_to_deepcopy.values():
            self_._instantiate_param(p)
        for p in params_to_ref.values():
            self_._instantiate_param(p, deepcopy=False)

        ## keyword arg setting
        deps, refs = {}, {}
        for name, val in params.items():
            desc = self_.cls.get_param_descriptor(name)[0] # pylint: disable-msg=E1101
            if not desc:
                raise TypeError(
                    f"{self.__class__.__name__}.__init__() got an unexpected "
                    f"keyword argument {name!r}"
                )

            pobj = objects.get(name)
            if pobj is None or not pobj.allow_refs:
                # Until Parameter.allow_refs=True by default we have to
                # speculatively evaluate a values to check whether they
                # contain a reference and warn the user that the
                # behavior may change in future.
                if name not in self_.cls._param__private.explicit_no_refs:
                    try:
                        ref, _, resolved, _ = self_._resolve_ref(pobj, val)
                    except Exception:
                        ref = None
                    if ref:
                        warnings.warn(
                            f"Parameter {name!r} on {pobj.owner} is being given a valid parameter "
                            f"reference {val} but is implicitly allow_refs=False. "
                            "In future allow_refs will be enabled by default and "
                            f"the reference {val} will be resolved to its underlying "
                            f"value {resolved}. Please explicitly set allow_ref on the "
                            "Parameter definition to declare whether references "
                            "should be resolved or not.",
                            category=_ParamFutureWarning,
                            stacklevel=4,
                        )
                setattr(self, name, val)
                continue

            # Resolve references
            ref, ref_deps, resolved, is_async = self_._resolve_ref(pobj, val)
            if ref is not None:
                refs[name] = ref
                deps[name] = ref_deps
            if not is_async and not (resolved is Undefined or resolved is Skip):
                setattr(self, name, resolved)
        return refs, deps

    def _setup_refs(self_, refs):
        groups = defaultdict(list)
        for pname, subrefs in refs.items():
            for p in subrefs:

                if isinstance(p, Parameter):
                    groups[p.owner].append((pname, p.name))
                else:
                    for sp in extract_dependencies(p):
                        groups[sp.owner].append((pname, sp.name))
        for owner, pnames in groups.items():
            refnames, pnames = zip(*pnames)
            self_.self._param__private.ref_watchers.append((
                refnames,
                owner.param._watch(self_._sync_refs, list(set(pnames)), precedence=-1)
            ))

    def _update_ref(self_, name, ref):
        param_private = self_.self._param__private
        if name in param_private.async_refs:
            param_private.async_refs.pop(name).cancel()
        for _, watcher in param_private.ref_watchers:
            dep_obj = watcher.cls if watcher.inst is None else watcher.inst
            dep_obj.param.unwatch(watcher)
        self_.self._param__private.ref_watchers = []
        refs = dict(self_.self._param__private.refs, **{name: ref})
        deps = {name: resolve_ref(ref, self_[name].nested_refs) for name, ref in refs.items()}
        self_._setup_refs(deps)
        self_.self._param__private.refs = refs

    def _sync_refs(self_, *events):
        updates = {}
        for pname, ref in self_.self._param__private.refs.items():
            # Skip updating value if dependency has not changed
            recursive = self_[pname].nested_refs
            deps = resolve_ref(ref, recursive)
            is_gen = inspect.isgeneratorfunction(ref)
            is_async = iscoroutinefunction(ref) or is_gen
            if not any((dep.owner is e.obj and dep.name == e.name) for dep in deps for e in events) and not is_async:
                continue

            try:
                new_val = resolve_value(ref, recursive)
            except Skip:
                new_val = Undefined
            if new_val is Skip or new_val is Undefined:
                continue
            elif is_async:
                async_executor(partial(self_._async_ref, pname, new_val))
                continue

            updates[pname] = new_val

        with edit_constant(self_.self):
            with _syncing(self_.self, updates):
                self_.update(updates)

    def _resolve_ref(self_, pobj, value):
        is_gen = inspect.isgeneratorfunction(value)
        is_async = iscoroutinefunction(value) or is_gen
        deps = resolve_ref(value, recursive=pobj.nested_refs)
        if not (deps or is_async or is_gen):
            return None, None, value, False
        ref = value
        try:
            value = resolve_value(value, recursive=pobj.nested_refs)
        except Skip:
            value = Undefined
        if is_async:
            async_executor(partial(self_._async_ref, pobj.name, value))
            value = None
        return ref, deps, value, is_async

    async def _async_ref(self_, pname, awaitable):
        if not self_.self._param__private.initialized:
            async_executor(partial(self_._async_ref, pname, awaitable))
            return

        current_task = asyncio.current_task()
        running_task = self_.self._param__private.async_refs.get(pname)
        if running_task is None:
            self_.self._param__private.async_refs[pname] = current_task
        elif current_task is not running_task:
            self_.self._param__private.async_refs[pname].cancel()
        try:
            if isinstance(awaitable, types.AsyncGeneratorType):
                async for new_obj in awaitable:
                    with _syncing(self_.self, (pname,)):
                        self_.update({pname: new_obj})
            else:
                with _syncing(self_.self, (pname,)):
                    try:
                        self_.update({pname: await awaitable})
                    except Skip:
                        pass
        finally:
            # Ensure we clean up but only if the task matches the currrent task
            if self_.self._param__private.async_refs.get(pname) is current_task:
                del self_.self._param__private.async_refs[pname]

    @classmethod
    def _changed(cls, event):
        """
        Predicate that determines whether a Event object has actually
        changed such that old != new.
        """
        return not Comparator.is_equal(event.old, event.new)

    def _instantiate_param(self_, param_obj, dict_=None, key=None, deepcopy=True):
        # deepcopy or store a reference to reference param_obj.default into
        # self._param__private.values (or dict_ if supplied) under the
        # parameter's name (or key if supplied)
        instantiator = copy.deepcopy if deepcopy else lambda o: o
        self = self_.self
        dict_ = dict_ or self._param__private.values
        key = key or param_obj.name
        if shared_parameters._share:
            param_key = (str(type(self)), param_obj.name)
            if param_key in shared_parameters._shared_cache:
                new_object = shared_parameters._shared_cache[param_key]
            else:
                new_object = instantiator(param_obj.default)
                shared_parameters._shared_cache[param_key] = new_object
        else:
            new_object = instantiator(param_obj.default)

        dict_[key] = new_object

        if isinstance(new_object, Parameterized) and deepcopy:
            global object_count
            object_count += 1
            # Writes over name given to the original object;
            # could instead have kept the same name
            new_object.param._generate_name()

    def _update_deps(self_, attribute=None, init=False):
        obj = self_.self
        init_methods = []
        for method, queued, on_init, constant, dynamic in type(obj).param._depends['watch']:
            # On initialization set up constant watchers; otherwise
            # clean up previous dynamic watchers for the updated attribute
            dynamic = [d for d in dynamic if attribute is None or d.spec.split(".")[0] == attribute]
            if init:
                constant_grouped = defaultdict(list)
                for dep in _resolve_mcs_deps(obj, constant, []):
                    constant_grouped[(id(dep.inst), id(dep.cls), dep.what)].append((None, dep))
                for group in constant_grouped.values():
                    self_._watch_group(obj, method, queued, group)
                m = getattr(self_.self, method)
                if on_init and m not in init_methods:
                    init_methods.append(m)
            elif dynamic:
                for w in obj._param__private.dynamic_watchers.pop(method, []):
                    (w.cls if w.inst is None else w.inst).param.unwatch(w)
            else:
                continue

            # Resolve dynamic dependencies one-by-one to be able to trace their watchers
            grouped = defaultdict(list)
            for ddep in dynamic:
                for dep in _resolve_mcs_deps(obj, [], [ddep]):
                    grouped[(id(dep.inst), id(dep.cls), dep.what)].append((ddep, dep))

            for group in grouped.values():
                watcher = self_._watch_group(obj, method, queued, group, attribute)
                obj._param__private.dynamic_watchers[method].append(watcher)
        for m in init_methods:
            m()

    def _resolve_dynamic_deps(self, obj, dynamic_dep, param_dep, attribute):
        """
        If a subobject whose parameters are being depended on changes
        we should only trigger events if the actual parameter values
        of the new object differ from those on the old subobject,
        therefore we accumulate parameters to compare on a subobject
        change event.

        Additionally we need to make sure to notify the parent object
        if a subobject changes so the dependencies can be
        reinitialized so we return a callback which updates the
        dependencies.
        """
        subobj = obj
        subobjs = [obj]
        for subpath in dynamic_dep.spec.split('.')[:-1]:
            subobj = getattr(subobj, subpath.split(':')[0], None)
            subobjs.append(subobj)

        dep_obj = param_dep.cls if param_dep.inst is None else param_dep.inst
        if dep_obj not in subobjs[:-1]:
            return None, None, param_dep.what

        depth = subobjs.index(dep_obj)
        callback = None
        if depth > 0:
            def callback(*events):
                """
                If a subobject changes, we need to notify the main
                object to update the dependencies.
                """
                obj.param._update_deps(attribute)

        p = '.'.join(dynamic_dep.spec.split(':')[0].split('.')[depth+1:])
        if p == 'param':
            subparams = [sp for sp in list(subobjs[-1].param)]
        else:
            subparams = [p]

        if ':' in dynamic_dep.spec:
            what = dynamic_dep.spec.split(':')[-1]
        else:
            what = param_dep.what

        return subparams, callback, what

    def _watch_group(self_, obj, name, queued, group, attribute=None):
        """
        Sets up a watcher for a group of dependencies. Ensures that
        if the dependency was dynamically generated we check whether
        a subobject change event actually causes a value change and
        that we update the existing watchers, i.e. clean up watchers
        on the old subobject and create watchers on the new subobject.
        """
        dynamic_dep, param_dep = group[0]
        dep_obj = param_dep.cls if param_dep.inst is None else param_dep.inst
        params = []
        for _, g in group:
            if g.name not in params:
                params.append(g.name)

        if dynamic_dep is None:
            subparams, callback, what = None, None, param_dep.what
        else:
            subparams, callback, what = self_._resolve_dynamic_deps(
                obj, dynamic_dep, param_dep, attribute)

        mcaller = _m_caller(obj, name, what, subparams, callback)
        return dep_obj.param._watch(
            mcaller, params, param_dep.what, queued=queued, precedence=-1)

    @_recursive_repr()
    def _repr_html_(self_, open=True):
        return _parameterized_repr_html(self_.self_or_cls, open)

    # Classmethods

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="""Use instead `for k,v in p.param.objects().items(): print(f"{p.__class__.name}.{k}={repr(v.default)}")`""", warning_cat=_ParamFutureWarning)
    def print_param_defaults(self_):
        """
        Print the default values of all cls's Parameters.

        .. deprecated:: 1.12.0
            Use instead `for k,v in p.param.objects().items(): print(f"{p.__class__.name}.{k}={repr(v.default)}")`
        """
        cls = self_.cls
        for key,val in cls.__dict__.items():
            if isinstance(val,Parameter):
                print(cls.__name__+'.'+key+ '='+ repr(val.default))

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="Use instead `p.param.default =`", warning_cat=_ParamFutureWarning)
    def set_default(self_,param_name,value):
        """
        Set the default value of param_name.

        Equivalent to setting param_name on the class.

        .. deprecated:: 1.12.0
             Use instead `p.param.default =`
        """
        cls = self_.cls
        setattr(cls,param_name,value)

    def add_parameter(self_, param_name: str, param_obj: Parameter):
        """
        Add a new Parameter object to this class.

        This method allows dynamically adding a Parameter to the class, resulting in behavior equivalent to declaring
        the Parameter in the class's source code.

        Parameters
        ----------
        param_name : str
            The name of the parameter to add.
        param_obj : Parameter
            The Parameter object to add.

        Examples
        --------
        Create a Parameterized class:

        >>> import param
        >>> class P(param.Parameterized):
        ...     a = param.Number()
        ...     b = param.String()
        >>> p = P()

        Add a new parameter to the class `P` via the class namespace `P.param`:

        >>> P.param.add_parameter('c', param.Tuple(default=(1, 2, 3)))
        >>> print(p.c)
        (1, 2, 3)

        Add a new parameter to the class `P` via the instance namespace `p.param`:

        >>> p.param.add_parameter('d', param.Tuple(default=(3, 2, 1)))
        >>> p.d
        (3, 2, 1)

        """
        # Could have just done setattr(cls,param_name,param_obj),
        # which is supported by the metaclass's __setattr__ , but
        # would need to handle the params() cache as well
        # (which is tricky but important for startup speed).
        cls = self_.cls
        type.__setattr__(cls, param_name, param_obj)
        ParameterizedMetaclass._initialize_parameter(cls, param_name, param_obj)
        # delete cached params()
        cls._param__private.params.clear()

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="Use instead `.param.add_parameter`", warning_cat=_ParamFutureWarning)
    def _add_parameter(self_,param_name, param_obj):
        """
        Add a new Parameter object into this object's class.

        .. deprecated :: 1.12.0
        """
        return self_.add_parameter(param_name, param_obj)

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="Use instead `.param.values()` or `.param['param']`", warning_cat=_ParamFutureWarning)
    def params(self_, parameter_name=None):
        """
        Return the Parameters of this class as the
        dictionary {name: parameter_object}

        Includes Parameters from this class and its
        superclasses.

        .. deprecated:: 1.12.0
            Use instead `.param.values()` or `.param['param']`
        """
        pdict = self_.objects(instance='existing')
        if parameter_name is None:
            return pdict
        else:
            return pdict[parameter_name]

    # Bothmethods

    def update(self_, arg=Undefined, /, **kwargs):
        """
        Update multiple parameters of this object or class before triggering events.

        Allows setting the parameters of the object or class using a dictionary, an iterable, or keyword arguments
        in the form of `param=value`. The specified parameters will be updated to the given values.

        This method can also be used as a context manager to temporarily set and then reset parameter values.

        Parameters
        ----------
        **params : dict or iterable or keyword arguments
            The parameters to update, provided as a dictionary, iterable, or keyword arguments in `param=value` format.

        User Guide
        ----------
        https://param.holoviz.org/user_guide/Parameters.html#other-parameterized-methods

        Examples
        --------
        Create a Parameterized class:

        >>> import param
        >>> class P(param.Parameterized):
        ...    a = param.String()
        ...    b = param.String()

        Define the instance:

        >>> p = P(a="0. Hello", b="0. World")

        Use `.update` to update the parameters:

        >>> p.param.update(a="1. Hello", b="2. World")
        >>> p.a, p.b
        ('1. Hello', '1. World')

        Update the parameters temporarily:

        >>> with p.param.update(a="2. Hello", b="2. World"):
        ...     print(p.a, p.b)
        2. Hello 2. World

        >>> p.a, p.b
        ('1. Hello', '1. World')

        Lets see that events are triggered **after** all parameters have been updated

        >>> @param.depends(p.param.a, watch=True)
        ... def print_a_b(a):
        ...     print(p.a, p.b)
        >>> my_param.param.update(a="3. Hello",b="3. World")
        3. Hello 3. World

        """
        refs = {}
        if self_.self is not None:
            private = self_.self._param__private
            params = list(kwargs if arg is Undefined else dict(arg, **kwargs))
            for pname in params:
                if pname in refs:
                    continue
                elif pname in private.refs:
                    refs[pname] = private.refs[pname]
                elif pname in private.async_refs:
                    refs[pname] = private.async_refs[pname]
        restore = dict(self_._update(arg, **kwargs))
        return _ParametersRestorer(parameters=self_, restore=restore, refs=refs)

    def _update(self_, arg=Undefined, /, **kwargs):
        BATCH_WATCH = self_._BATCH_WATCH
        self_._BATCH_WATCH = True
        self_or_cls = self_.self_or_cls
        if arg is not Undefined:
            kwargs = dict(arg, **kwargs)

        trigger_params = [
            k for k in kwargs
            if k in self_ and hasattr(self_[k], '_autotrigger_value')
        ]

        for tp in trigger_params:
            self_[tp]._mode = 'set'

        values = self_.values()
        restore = {k: values[k] for k, v in kwargs.items() if k in values}

        for (k, v) in kwargs.items():
            if k not in self_:
                self_._BATCH_WATCH = False
                raise ValueError(f"{k!r} is not a parameter of {self_.cls.__name__}")
            try:
                setattr(self_or_cls, k, v)
            except Exception:
                self_._BATCH_WATCH = False
                raise

        self_._BATCH_WATCH = BATCH_WATCH
        if not BATCH_WATCH:
            self_._batch_call_watchers()

        for tp in trigger_params:
            p = self_[tp]
            p._mode = 'reset'
            setattr(self_or_cls, tp, p._autotrigger_reset_value)
            p._mode = 'set-reset'
        return restore

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="Use instead `.param.update`", warning_cat=_ParamFutureWarning)
    def set_param(self_, *args,**kwargs):
        """
        For each param=value keyword argument, sets the corresponding
        parameter of this object or class to the given value.

        For backwards compatibility, also accepts
        set_param("param",value) for a single parameter value using
        positional arguments, but the keyword interface is preferred
        because it is more compact and can set multiple values.

        .. deprecated:: 1.12.0
            Use instead `.param.update`
        """
        self_or_cls = self_.self_or_cls
        if args:
            if len(args) == 2 and args[0] not in kwargs and not kwargs:
                kwargs[args[0]] = args[1]
            else:
                raise ValueError("Invalid positional arguments for %s.set_param" %
                                 (self_or_cls.name))
        return self_.update(kwargs)

    @property
    def _cls_parameters(self_):
        """
        Class parameters are cached because they are accessed often,
        and parameters are rarely added (and cannot be deleted)
        """
        cls = self_.cls
        pdict = cls._param__private.params
        if pdict:
            return pdict

        paramdict = {}
        for class_ in classlist(cls):
            for name, val in class_.__dict__.items():
                if isinstance(val, Parameter):
                    paramdict[name] = val

        # We only want the cache to be visible to the cls on which
        # params() is called, so we mangle the name ourselves at
        # runtime (if we were to mangle it now, it would be
        # _Parameterized.__params for all classes).
        # cls._param__private.params[f'_{cls.__name__}__params'] = paramdict
        cls._param__private.params = paramdict
        return paramdict

    def objects(self_, instance=True):
        """
        Returns the Parameters of this instance or class

        If instance=True and called on a Parameterized instance it
        will create instance parameters for all Parameters defined on
        the class. To force class parameters to be returned use
        instance=False. Since classes avoid creating instance
        parameters unless necessary you may also request only existing
        instance parameters to be returned by setting
        instance='existing'.
        """
        if self_.self is not None and not self_.self._param__private.initialized and instance is True:
            raise RuntimeError(
                'Looking up instance Parameter objects (`.param.objects()`) until '
                'the Parameterized instance has been fully initialized is not allowed. '
                'Ensure you have called `super().__init__(**params)` in your Parameterized '
                'constructor before trying to access instance Parameter objects, or '
                'looking up the class Parameter objects with `.param.objects(instance=False)` '
                'may be enough for your use case.',
            )

        pdict = self_._cls_parameters
        if instance and self_.self is not None:
            if instance == 'existing':
                if getattr(self_.self._param__private, 'initialized', False) and self_.self._param__private.params:
                    return dict(pdict, **self_.self._param__private.params)
                return pdict
            else:
                return {k: self_.self.param[k] for k in pdict}
        return pdict

    def trigger(self_, *param_names):
        """
        Trigger watchers for the given set of parameter names. Watchers
        will be triggered whether or not the parameter values have
        actually changed. As a special case, the value will actually be
        changed for a Parameter of type Event, setting it to True so
        that it is clear which Event parameter has been triggered.
        """
        if self_.self is not None and not self_.self._param__private.initialized:
            raise RuntimeError(
                'Triggering watchers on a partially initialized Parameterized instance '
                'is not allowed. Ensure you have called super().__init__(**params) in '
                'the Parameterized instance constructor before trying to set up a watcher.',
            )

        trigger_params = [p for p in self_
                          if hasattr(self_[p], '_autotrigger_value')]
        triggers = {p:self_[p]._autotrigger_value
                    for p in trigger_params if p in param_names}

        events = self_._events
        watchers = self_._state_watchers
        self_._events  = []
        self_._state_watchers = []
        param_values = self_.values()
        params = {name: param_values[name] for name in param_names}
        self_._TRIGGER = True
        self_.update(dict(params, **triggers))
        self_._TRIGGER = False
        self_._events += events
        self_._state_watchers += watchers

    def _update_event_type(self_, watcher, event, triggered):
        """Returns an updated Event object with the type field set appropriately."""
        if triggered:
            event_type = 'triggered'
        else:
            event_type = 'changed' if watcher.onlychanged else 'set'
        return Event(what=event.what, name=event.name, obj=event.obj, cls=event.cls,
                     old=event.old, new=event.new, type=event_type)

    def _execute_watcher(self, watcher, events):
        if watcher.mode == 'args':
            args, kwargs = events, {}
        else:
            args, kwargs = (), {event.name: event.new for event in events}

        if iscoroutinefunction(watcher.fn):
            if async_executor is None:
                raise RuntimeError("Could not execute %s coroutine function. "
                                   "Please register a asynchronous executor on "
                                   "param.parameterized.async_executor, which "
                                   "schedules the function on an event loop." %
                                   watcher.fn)
            async_executor(partial(watcher.fn, *args, **kwargs))
        else:
            try:
                watcher.fn(*args, **kwargs)
            except Skip:
                pass

    def _call_watcher(self_, watcher, event):
        """Invoke the given watcher appropriately given an Event object."""
        if self_._TRIGGER:
            pass
        elif watcher.onlychanged and (not self_._changed(event)):
            return

        if self_._BATCH_WATCH:
            self_._events.append(event)
            if not any(watcher is w for w in self_._state_watchers):
                self_._state_watchers.append(watcher)
        else:
            event = self_._update_event_type(watcher, event, self_._TRIGGER)
            with _batch_call_watchers(self_.self_or_cls, enable=watcher.queued, run=False):
                self_._execute_watcher(watcher, (event,))

    def _batch_call_watchers(self_):
        """
        Batch call a set of watchers based on the parameter value
        settings in kwargs using the queued Event and watcher objects.
        """
        while self_._events:
            event_dict = OrderedDict([((event.name, event.what), event)
                                      for event in self_._events])
            watchers = self_._state_watchers[:]
            self_._events = []
            self_._state_watchers = []

            for watcher in sorted(watchers, key=lambda w: w.precedence):
                events = [self_._update_event_type(watcher, event_dict[(name, watcher.what)],
                                                   self_._TRIGGER)
                          for name in watcher.parameter_names
                          if (name, watcher.what) in event_dict]
                with _batch_call_watchers(self_.self_or_cls, enable=watcher.queued, run=False):
                    self_._execute_watcher(watcher, events)

    def set_dynamic_time_fn(self_,time_fn,sublistattr=None):
        """
        Set time_fn for all Dynamic Parameters of this class or
        instance object that are currently being dynamically
        generated.

        Additionally, sets _Dynamic_time_fn=time_fn on this class or
        instance object, so that any future changes to Dynamic
        Parmeters can inherit time_fn (e.g. if a Number is changed
        from a float to a number generator, the number generator will
        inherit time_fn).

        If specified, sublistattr is the name of an attribute of this
        class or instance that contains an iterable collection of
        subobjects on which set_dynamic_time_fn should be called.  If
        the attribute sublistattr is present on any of the subobjects,
        set_dynamic_time_fn() will be called for those, too.
        """
        self_or_cls = self_.self_or_cls
        self_or_cls._Dynamic_time_fn = time_fn

        if isinstance(self_or_cls,type):
            a = (None,self_or_cls)
        else:
            a = (self_or_cls,)

        for n,p in self_or_cls.param.objects('existing').items():
            if hasattr(p, '_value_is_dynamic'):
                if p._value_is_dynamic(*a):
                    g = self_or_cls.param.get_value_generator(n)
                    g._Dynamic_time_fn = time_fn

        if sublistattr:
            try:
                sublist = getattr(self_or_cls,sublistattr)
            except AttributeError:
                sublist = []

            for obj in sublist:
                obj.param.set_dynamic_time_fn(time_fn,sublistattr)

    def serialize_parameters(self_, subset=None, mode='json'):
        """
        Return the serialized parameters of the Parameterized object.

        Parameters
        ----------
        subset : list, optional
            A list of parameter names to serialize. If None, all parameters will be serialized. Defaults to None.
        mode : str, optional
            The serialization format. By default, only 'json' is supported. Defaults to 'json'.

        Returns
        -------
        Any
            The serialized value.

        User Guide
        ----------
        https://param.holoviz.org/user_guide/Serialization_and_Persistence.html#serializing-with-json

        Examples
        --------
        Create a Parameterized instance and serialize its parameters:

        >>> import param
        >>> class P(param.Parameterized):
        ...     a = param.Number()
        ...     b = param.String()
        >>> p = P(a=1, b="hello")

        Serialize parameters:

        >>> serialized_data = p.param.serialize_parameters()
        >>> print(serialized_data)
        {"name": "P00002", "a": 1, "b": "hello"}

        """
        self_or_cls = self_.self_or_cls
        if mode not in Parameter._serializers:
            raise ValueError(f'Mode {mode!r} not in available serialization formats {list(Parameter._serializers.keys())!r}')
        serializer = Parameter._serializers[mode]
        return serializer.serialize_parameters(self_or_cls, subset=subset)

    def serialize_value(self_, pname, mode='json'):
        self_or_cls = self_.self_or_cls
        if mode not in Parameter._serializers:
            raise ValueError(f'Mode {mode!r} not in available serialization formats {list(Parameter._serializers.keys())!r}')
        serializer = Parameter._serializers[mode]
        return serializer.serialize_parameter_value(self_or_cls, pname)

    def deserialize_parameters(self_, serialization, subset=None, mode='json') -> dict:
        """
        Deserialize the given serialized data. This data can be used to create a
        `Parameterized` object or update the parameters of an existing `Parameterized` object.

        Parameters
        ----------
        serialization : str
            The serialized parameter data as a JSON string.
        subset : list of str, optional
            A list of parameter names to deserialize. If `None`, all parameters will be
            deserialized. Defaults to `None`.
        mode : str, optional
            The serialization format. By default, only 'json' is supported.
            Defaults to 'json'.

        Returns
        -------
        dict
            A dictionary with parameter names as keys and deserialized values.

        User Guide
        ----------
        https://param.holoviz.org/user_guide/Serialization_and_Persistence.html#serializing-with-json

        Examples
        --------
        >>> import param
        >>> class P(param.Parameterized):
        ...     a = param.Number()
        ...     b = param.String()
        ...
        >>> serialized_data = '{"a": 1, "b": "hello"}'
        >>> deserialized_data = P.param.deserialize_parameters(serialized_data)
        >>> print(deserialized_data)
        {'a': 1, 'b': 'hello'}
        >>> instance = P(**deserialized_data)

        """
        self_or_cls = self_.self_or_cls
        serializer = Parameter._serializers[mode]
        return serializer.deserialize_parameters(self_or_cls, serialization, subset=subset)

    def deserialize_value(self_, pname, value, mode='json'):
        self_or_cls = self_.self_or_cls
        if mode not in Parameter._serializers:
            raise ValueError(f'Mode {mode!r} not in available serialization formats {list(Parameter._serializers.keys())!r}')
        serializer = Parameter._serializers[mode]
        return serializer.deserialize_parameter_value(self_or_cls, pname, value)

    def schema(self_, safe=False, subset=None, mode='json'):
        """Returns a schema for the parameters on this Parameterized object."""
        self_or_cls = self_.self_or_cls
        if mode not in Parameter._serializers:
            raise ValueError(f'Mode {mode!r} not in available serialization formats {list(Parameter._serializers.keys())!r}')
        serializer = Parameter._serializers[mode]
        return serializer.schema(self_or_cls, safe=safe, subset=subset)

    # PARAM3_DEPRECATION
    # same as values() but returns list, not dict
    @_deprecated(extra_msg="""
        Use `.param.values().items()` instead (or `.param.values()` for the
        common case of `dict(....param.get_param_values())`)
    """, warning_cat=_ParamFutureWarning)
    def get_param_values(self_, onlychanged=False):
        """
        Return a list of name,value pairs for all Parameters of this
        object.

        When called on an instance with onlychanged set to True, will
        only return values that are not equal to the default value
        (onlychanged has no effect when called on a class).

        .. deprecated:: 1.12.0
            Use `.param.values().items()` instead (or `.param.values()` for the
            common case of `dict(....param.get_param_values())`)
        """
        vals = self_.values(onlychanged)
        return [(k, v) for k, v in vals.items()]

    def values(self_, onlychanged=False):
        """
        Return a dictionary of name,value pairs for the Parameters of this
        object.

        When called on an instance with onlychanged set to True, will
        only return values that are not equal to the default value
        (onlychanged has no effect when called on a class).
        """
        self_or_cls = self_.self_or_cls
        vals = []
        for name, val in self_or_cls.param.objects('existing').items():
            value = self_or_cls.param.get_value_generator(name)
            if name == 'name' and onlychanged and _is_auto_name(self_.cls.__name__, value):
                continue
            if not onlychanged or not Comparator.is_equal(value, val.default):
                vals.append((name, value))

        vals.sort(key=itemgetter(0))
        return dict(vals)

    def force_new_dynamic_value(self_, name): # pylint: disable-msg=E0213
        """
        Force a new value to be generated for the dynamic attribute
        name, and return it.

        If name is not dynamic, its current value is returned
        (i.e. equivalent to getattr(name).
        """
        cls_or_slf = self_.self_or_cls
        param_obj = cls_or_slf.param.objects('existing').get(name)

        if not param_obj:
            return getattr(cls_or_slf, name)

        cls, slf = None, None
        if isinstance(cls_or_slf,type):
            cls = cls_or_slf
        else:
            slf = cls_or_slf

        if not hasattr(param_obj,'_force'):
            return param_obj.__get__(slf, cls)
        else:
            return param_obj._force(slf, cls)

    def get_value_generator(self_,name): # pylint: disable-msg=E0213
        """
        Return the value or value-generating object of the named
        attribute.

        For most parameters, this is simply the parameter's value
        (i.e. the same as getattr()), but Dynamic parameters have
        their value-generating object returned.
        """
        cls_or_slf = self_.self_or_cls
        param_obj = cls_or_slf.param.objects('existing').get(name)

        if not param_obj:
            value = getattr(cls_or_slf,name)

        # CompositeParameter detected by being a Parameter and having 'attribs'
        elif hasattr(param_obj,'attribs'):
            value = [cls_or_slf.param.get_value_generator(a) for a in param_obj.attribs]

        # not a Dynamic Parameter
        elif not hasattr(param_obj,'_value_is_dynamic'):
            value = getattr(cls_or_slf,name)

        # Dynamic Parameter...
        else:
            # TODO: is this always an instance?
            if isinstance(cls_or_slf, Parameterized) and name in cls_or_slf._param__private.values:
                # dealing with object and it's been set on this object
                value = cls_or_slf._param__private.values[name]
            else:
                # dealing with class or isn't set on the object
                value = param_obj.default

        return value

    def inspect_value(self_,name): # pylint: disable-msg=E0213
        """
        Return the current value of the named attribute without modifying it.

        Same as getattr() except for Dynamic parameters, which have their
        last generated value returned.
        """
        cls_or_slf = self_.self_or_cls
        param_obj = cls_or_slf.param.objects('existing').get(name)

        if not param_obj:
            value = getattr(cls_or_slf,name)
        elif hasattr(param_obj,'attribs'):
            value = [cls_or_slf.param.inspect_value(a) for a in param_obj.attribs]
        elif not hasattr(param_obj,'_inspect'):
            value = getattr(cls_or_slf,name)
        else:
            if isinstance(cls_or_slf,type):
                value = param_obj._inspect(None,cls_or_slf)
            else:
                value = param_obj._inspect(cls_or_slf,None)

        return value

    def method_dependencies(self_, name, intermediate=False):
        """
        Given the name of a method, returns a PInfo object for each dependency
        of this method. See help(PInfo) for the contents of these objects.

        By default intermediate dependencies on sub-objects are not
        returned as these are primarily useful for internal use to
        determine when a sub-object dependency has to be updated.
        """
        method = getattr(self_.self_or_cls, name)
        minfo = MInfo(cls=self_.cls, inst=self_.self, name=name,
                      method=method)
        deps, dynamic = _params_depended_on(
            minfo, dynamic=False, intermediate=intermediate)
        if self_.self is None:
            return deps
        return _resolve_mcs_deps(
            self_.self, deps, dynamic, intermediate=intermediate)

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg='Use instead `.param.method_dependencies`', warning_cat=_ParamFutureWarning)
    def params_depended_on(self_, *args, **kwargs):
        """
        Given the name of a method, returns a PInfo object for each dependency
        of this method. See help(PInfo) for the contents of these objects.

        By default intermediate dependencies on sub-objects are not
        returned as these are primarily useful for internal use to
        determine when a sub-object dependency has to be updated.

        .. deprecated: 2.0.0
            Use instead `.param.method_dependencies`
        """
        return self_.method_dependencies(*args, **kwargs)

    def outputs(self_):
        """
        Returns a mapping between any declared outputs and a tuple
        of the declared Parameter type, the output method, and the
        index into the output if multiple outputs are returned.
        """
        outputs = {}
        for cls in classlist(self_.cls):
            for name in dir(cls):
                method = getattr(self_.self_or_cls, name)
                dinfo = getattr(method, '_dinfo', {})
                if 'outputs' not in dinfo:
                    continue
                for override, otype, idx in dinfo['outputs']:
                    if override is not None:
                        name = override
                    outputs[name] = (otype, method, idx)
        return outputs

    def _spec_to_obj(self_, spec, dynamic=True, intermediate=True):
        """
        Resolves a dependency specification into lists of explicit
        parameter dependencies and dynamic dependencies.

        Dynamic dependencies are specifications to be resolved when
        the sub-object whose parameters are being depended on is
        defined.

        During class creation dynamic=False which means sub-object
        dependencies are not resolved. At instance creation and
        whenever a sub-object is set on an object this method will be
        invoked to determine whether the dependency is available.

        For sub-object dependencies we also return dependencies for
        every part of the path, e.g. for a dependency specification
        like "a.b.c" we return dependencies for sub-object "a" and the
        sub-sub-object "b" in addition to the dependency on the actual
        parameter "c" on object "b". This is to ensure that if a
        sub-object is swapped out we are notified and can update the
        dynamic dependency to the new object. Even if a sub-object
        dependency can only partially resolved, e.g. if object "a"
        does not yet have a sub-object "b" we must watch for changes
        to "b" on sub-object "a" in case such a subobject is put in "b".
        """
        if isinstance(spec, Parameter):
            inst = spec.owner if isinstance(spec.owner, Parameterized) else None
            cls = spec.owner if inst is None else type(inst)
            info = PInfo(inst=inst, cls=cls, name=spec.name,
                         pobj=spec, what='value')
            return [] if intermediate == 'only' else [info], []

        obj, attr, what = _parse_dependency_spec(spec)
        if obj is None:
            src = self_.self_or_cls
        elif not dynamic:
            return [], [DInfo(spec=spec)]
        else:
            if not hasattr(self_.self_or_cls, obj.split('.')[1]):
                raise AttributeError(
                    f'Dependency {obj[1:]!r} could not be resolved, {self_.self_or_cls} '
                    f'has no parameter or attribute {obj.split(".")[1]!r}. Ensure '
                    'the object being depended on is declared before calling the '
                    'Parameterized constructor.'
                )

            src = _getattrr(self_.self_or_cls, obj[1::], None)
            if src is None:
                path = obj[1:].split('.')
                deps = []
                # Attempt to partially resolve subobject path to ensure
                # that if a subobject is later updated making the full
                # subobject path available we have to be notified and
                # set up watchers
                if len(path) >= 1 and intermediate:
                    sub_src = None
                    subpath = path
                    while sub_src is None and subpath:
                        subpath = subpath[:-1]
                        sub_src = _getattrr(self_.self_or_cls, '.'.join(subpath), None)
                    if subpath:
                        subdeps, _ = self_._spec_to_obj(
                            '.'.join(path[:len(subpath)+1]), dynamic, intermediate)
                        deps += subdeps
                return deps, [] if intermediate == 'only' else [DInfo(spec=spec)]

        cls, inst = (src, None) if isinstance(src, type) else (type(src), src)
        if attr == 'param':
            deps, dynamic_deps = self_._spec_to_obj(obj[1:], dynamic, intermediate)
            for p in src.param:
                param_deps, param_dynamic_deps = src.param._spec_to_obj(p, dynamic, intermediate)
                deps += param_deps
                dynamic_deps += param_dynamic_deps
            return deps, dynamic_deps
        elif attr in src.param:
            info = PInfo(inst=inst, cls=cls, name=attr,
                         pobj=src.param[attr], what=what)
        elif hasattr(src, attr):
            attr_obj = getattr(src, attr)
            if isinstance(attr_obj, Parameterized):
                return [], []
            elif isinstance(attr_obj, (FunctionType, MethodType)):
                info = MInfo(inst=inst, cls=cls, name=attr,
                             method=attr_obj)
            else:
                raise AttributeError(f"Attribute {attr!r} could not be resolved on {src}.")
        elif getattr(src, "abstract", None):
            return [], [] if intermediate == 'only' else [DInfo(spec=spec)]
        else:
            raise AttributeError(f"Attribute {attr!r} could not be resolved on {src}.")

        if obj is None or not intermediate:
            return [info], []
        deps, dynamic_deps = self_._spec_to_obj(obj[1:], dynamic, intermediate)
        if intermediate != 'only':
            deps.append(info)
        return deps, dynamic_deps

    def _register_watcher(self_, action, watcher, what='value'):
        if self_.self is not None and not self_.self._param__private.initialized:
            raise RuntimeError(
                '(Un)registering a watcher on a partially initialized Parameterized instance '
                'is not allowed. Ensure you have called super().__init__(**) in the '
                'Parameterized instance constructor before trying to set up a watcher.',
            )

        parameter_names = watcher.parameter_names
        for parameter_name in parameter_names:
            if parameter_name not in self_.cls.param:
                raise ValueError("{} parameter was not found in list of "
                                 "parameters of class {}".format(parameter_name, self_.cls.__name__))

            if self_.self is not None and what == "value":
                watchers = self_.self._param__private.watchers
                if parameter_name not in watchers:
                    watchers[parameter_name] = {}
                if what not in watchers[parameter_name]:
                    watchers[parameter_name][what] = []
                getattr(watchers[parameter_name][what], action)(watcher)
            else:
                watchers = self_[parameter_name].watchers
                if what not in watchers:
                    watchers[what] = []
                getattr(watchers[what], action)(watcher)

    def watch(self_, fn, parameter_names, what='value', onlychanged=True, queued=False, precedence=0):
        """
        Register the given callback function `fn` to be invoked for
        events on the indicated parameters.

        `what`: What to watch on each parameter; either the value (by
        default) or else the indicated slot (e.g. 'constant').

        `onlychanged`: By default, only invokes the function when the
        watched item changes, but if `onlychanged=False` also invokes
        it when the `what` item is set to its current value again.

        `queued`: By default, additional watcher events generated
        inside the callback fn are dispatched immediately, effectively
        doing depth-first processing of Watcher events. However, in
        certain scenarios, it is helpful to wait to dispatch such
        downstream events until all events that triggered this watcher
        have been processed. In such cases setting `queued=True` on
        this Watcher will queue up new downstream events generated
        during `fn` until `fn` completes and all other watchers
        invoked by that same event have finished executing),
        effectively doing breadth-first processing of Watcher events.

        `precedence`: Declares a precedence level for the Watcher that
        determines the priority with which the callback is executed.
        Lower precedence levels are executed earlier. Negative
        precedences are reserved for internal Watchers, i.e. those
        set up by param.depends.

        When the `fn` is called, it will be provided the relevant
        Event objects as positional arguments, which allows it to
        determine which of the possible triggering events occurred.

        Returns a Watcher object.

        See help(Watcher) and help(Event) for the contents of those objects.
        """
        if precedence < 0:
            raise ValueError("User-defined watch callbacks must declare "
                             "a positive precedence. Negative precedences "
                             "are reserved for internal Watchers.")
        return self_._watch(fn, parameter_names, what, onlychanged, queued, precedence)

    def _watch(self_, fn, parameter_names, what='value', onlychanged=True, queued=False, precedence=-1):
        parameter_names = tuple(parameter_names) if isinstance(parameter_names, list) else (parameter_names,)
        watcher = Watcher(inst=self_.self, cls=self_.cls, fn=fn, mode='args',
                          onlychanged=onlychanged, parameter_names=parameter_names,
                          what=what, queued=queued, precedence=precedence)
        self_._register_watcher('append', watcher, what)
        return watcher

    def unwatch(self_, watcher):
        """Remove the given Watcher object (from `watch` or `watch_values`) from this object's list."""
        try:
            self_._register_watcher('remove', watcher, what=watcher.what)
        except Exception:
            self_.warning(f'No such watcher {str(watcher)} to remove.')

    def watch_values(self_, fn, parameter_names, what='value', onlychanged=True, queued=False, precedence=0):
        """
        Easier-to-use version of `watch` specific to watching for changes in parameter values.

        Only allows `what` to be 'value', and invokes the callback `fn` using keyword
        arguments <param_name>=<new_value> rather than with a list of Event objects.
        """
        if precedence < 0:
            raise ValueError("User-defined watch callbacks must declare "
                             "a positive precedence. Negative precedences "
                             "are reserved for internal Watchers.")
        assert what == 'value'
        if isinstance(parameter_names, list):
            parameter_names = tuple(parameter_names)
        else:
            parameter_names = (parameter_names,)
        watcher = Watcher(inst=self_.self, cls=self_.cls, fn=fn,
                          mode='kwargs', onlychanged=onlychanged,
                          parameter_names=parameter_names, what=what,
                          queued=queued, precedence=precedence)
        self_._register_watcher('append', watcher, what)
        return watcher

    # Instance methods

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="Use instead `{k:v.default for k,v in p.param.objects().items()}`", warning_cat=_ParamFutureWarning)
    def defaults(self_):
        """
        Return {parameter_name:parameter.default} for all non-constant
        Parameters.

        Note that a Parameter for which instantiate==True has its default
        instantiated.

        .. deprecated:: 1.12.0
            Use instead `{k:v.default for k,v in p.param.objects().items()}`
        """
        self = self_.self
        d = {}
        for param_name, param in self.param.objects('existing').items():
            if param.constant:
                pass
            if param.instantiate:
                self.param._instantiate_param(param, dict_=d, key=param_name)
            d[param_name] = param.default
        return d

    # Designed to avoid any processing unless the print
    # level is high enough, though not all callers of message(),
    # verbose(), debug(), etc are taking advantage of this.
    def __db_print(self_,level,msg,*args,**kw):
        """
        Calls the logger returned by the get_logger() function,
        prepending the result of calling dbprint_prefix() (if any).

        See python's logging module for details.
        """
        self_or_cls = self_.self_or_cls
        if get_logger(name=self_or_cls.name).isEnabledFor(level):

            if dbprint_prefix and callable(dbprint_prefix):
                msg = dbprint_prefix() + ": " + msg  # pylint: disable-msg=E1102

            get_logger(name=self_or_cls.name).log(level, msg, *args, **kw)

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="""Use instead `for k,v in p.param.objects().items(): print(f"{p.__class__.name}.{k}={repr(v.default)}")`""", warning_cat=_ParamFutureWarning)
    def print_param_values(self_):
        """
        Print the values of all this object's Parameters.

        .. deprecated:: 1.12.0
            Use instead `for k,v in p.param.objects().items(): print(f"{p.__class__.name}.{k}={repr(v.default)}")`
        """
        self = self_.self
        for name, val in self.param.values().items():
            print(f'{self.name}.{name} = {val}')

    def warning(self_, msg,*args,**kw):
        """
        Print msg merged with args as a warning, unless module variable
        warnings_as_exceptions is True, then raise an Exception
        containing the arguments.

        See Python's logging module for details of message formatting.
        """
        self_.log(WARNING, msg, *args, **kw)

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="Use instead `.param.log(param.MESSAGE, ...)`", warning_cat=_ParamFutureWarning)
    def message(self_,msg,*args,**kw):
        """
        Print msg merged with args as a message.

        See Python's logging module for details of message formatting.

        .. deprecated:: 1.12.0
            Use instead `.param.log(param.MESSAGE, ...)`
        """
        self_.__db_print(INFO,msg,*args,**kw)

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="Use instead `.param.log(param.VERBOSE, ...)`", warning_cat=_ParamFutureWarning)
    def verbose(self_,msg,*args,**kw):
        """
        Print msg merged with args as a verbose message.

        See Python's logging module for details of message formatting.

        .. deprecated:: 1.12.0
            Use instead `.param.log(param.VERBOSE, ...)`
        """
        self_.__db_print(VERBOSE,msg,*args,**kw)

    # PARAM3_DEPRECATION
    @_deprecated(extra_msg="Use instead `.param.log(param.DEBUG, ...)`", warning_cat=_ParamFutureWarning)
    def debug(self_,msg,*args,**kw):
        """
        Print msg merged with args as a debugging statement.

        See Python's logging module for details of message formatting.

        .. deprecated:: 1.12.0
            Use instead `.param.log(param.DEBUG, ...)`
        """
        self_.__db_print(DEBUG,msg,*args,**kw)

    def log(self_, level, msg, *args, **kw):
        """
        Print msg merged with args as a message at the indicated logging level.

        Logging levels include those provided by the Python logging module
        plus VERBOSE, either obtained directly from the logging module like
        `logging.INFO`, or from parameterized like `param.parameterized.INFO`.

        Supported logging levels include (in order of severity)
        DEBUG, VERBOSE, INFO, WARNING, ERROR, CRITICAL

        See Python's logging module for details of message formatting.
        """
        if level is WARNING:
            if warnings_as_exceptions:
                raise Exception("Warning: " + msg % args)
            else:
                global warning_count
                warning_count+=1
        self_.__db_print(level, msg, *args, **kw)

    # Note that there's no _state_push method on the class, so
    # dynamic parameters set on a class can't have state saved. This
    # is because, to do this, _state_push() would need to be a
    # @bothmethod, but that complicates inheritance in cases where we
    # already have a _state_push() method.
    # (isinstance(g,Parameterized) below is used to exclude classes.)

    def _state_push(self_):
        """
        Save this instance's state.

        For Parameterized instances, this includes the state of
        dynamically generated values.

        Subclasses that maintain short-term state should additionally
        save and restore that state using _state_push() and
        _state_pop().

        Generally, this method is used by operations that need to test
        something without permanently altering the objects' state.
        """
        self = self_.self_or_cls
        if not isinstance(self, Parameterized):
            raise NotImplementedError('_state_push is not implemented at the class level')
        for pname, p in self.param.objects('existing').items():
            g = self.param.get_value_generator(pname)
            if hasattr(g,'_Dynamic_last'):
                g._saved_Dynamic_last.append(g._Dynamic_last)
                g._saved_Dynamic_time.append(g._Dynamic_time)
                # CB: not storing the time_fn: assuming that doesn't
                # change.
            elif hasattr(g,'_state_push') and isinstance(g,Parameterized):
                g._state_push()

    def _state_pop(self_):
        """
        Restore the most recently saved state.

        See _state_push() for more details.
        """
        self = self_.self_or_cls
        if not isinstance(self, Parameterized):
            raise NotImplementedError('_state_pop is not implemented at the class level')
        for pname, p in self.param.objects('existing').items():
            g = self.param.get_value_generator(pname)
            if hasattr(g,'_Dynamic_last'):
                g._Dynamic_last = g._saved_Dynamic_last.pop()
                g._Dynamic_time = g._saved_Dynamic_time.pop()
            elif hasattr(g,'_state_pop') and isinstance(g,Parameterized):
                g._state_pop()

    def pprint(self_, imports=None, prefix=" ", unknown_value='<?>',
               qualify=False, separator=""):
        """
        (Experimental) Pretty printed representation that may be
        evaluated with eval. See pprint() function for more details.
        """
        self = self_.self_or_cls
        if not isinstance(self, Parameterized):
            raise NotImplementedError('pprint is not implemented at the class level')
        # Wrapping the staticmethod _pprint with partial to pass `self` as the `_recursive_repr`
        # decorator expects `self`` to be the pprinted object (not `self_`).
        return partial(self_._pprint, self, imports=imports, prefix=prefix,
                       unknown_value=unknown_value, qualify=qualify, separator=separator)()

    @staticmethod
    @_recursive_repr()
    def _pprint(self, imports=None, prefix=" ", unknown_value='<?>',
               qualify=False, separator=""):
        if imports is None:
            imports = [] # would have been simpler to use a set from the start
        imports[:] = list(set(imports))

        # Generate import statement
        mod = self.__module__
        bits = mod.split('.')
        imports.append("import %s"%mod)
        imports.append("import %s"%bits[0])

        changed_params = self.param.values(onlychanged=script_repr_suppress_defaults)
        values = self.param.values()
        spec = getfullargspec(type(self).__init__)
        if 'self' not in spec.args or spec.args[0] != 'self':
            raise KeyError(f"'{type(self).__name__}.__init__.__signature__' must contain 'self' as its first Parameter.")
        args = spec.args[1:]

        if spec.defaults is not None:
            posargs = spec.args[:-len(spec.defaults)]
            kwargs = dict(zip(spec.args[-len(spec.defaults):], spec.defaults))
        else:
            posargs, kwargs = args, []

        parameters = self.param.objects('existing')
        ordering = sorted(
            sorted(changed_params), # alphanumeric tie-breaker
            key=lambda k: (- float('inf')  # No precedence is lowest possible precendence
                           if parameters[k].precedence is None else
                           parameters[k].precedence))

        arglist, keywords, processed = [], [], []
        for k in args + ordering:
            if k in processed: continue

            # Suppresses automatically generated names.
            if k == 'name' and (values[k] is not None
                                and re.match('^'+self.__class__.__name__+'[0-9]+$', values[k])):
                continue

            value = pprint(values[k], imports, prefix=prefix,settings=[],
                           unknown_value=unknown_value,
                           qualify=qualify) if k in values else None

            if value is None:
                if unknown_value is False:
                    raise Exception(f"{self.name}: unknown value of {k!r}")
                elif unknown_value is None:
                    # i.e. suppress repr
                    continue
                else:
                    value = unknown_value

            # Explicit kwarg (unchanged, known value)
            if (k in kwargs) and (k in values) and kwargs[k] == values[k]: continue

            if k in posargs:
                # value will be unknown_value unless k is a parameter
                arglist.append(value)
            elif (k in kwargs or
                  (hasattr(spec, 'varkw') and (spec.varkw is not None)) or
                  (hasattr(spec, 'keywords') and (spec.keywords is not None))):
                # Explicit modified keywords or parameters in
                # precendence order (if **kwargs present)
                keywords.append(f'{k}={value}')

            processed.append(k)

        qualifier = mod + '.'  if qualify else ''
        arguments = arglist + keywords + (['**%s' % spec.varargs] if spec.varargs else [])
        return qualifier + '{}({})'.format(self.__class__.__name__,  (','+separator+prefix).join(arguments))


class ParameterizedMetaclass(type):
    """
    The metaclass of Parameterized (and all its descendents).

    The metaclass overrides type.__setattr__ to allow us to set
    Parameter values on classes without overwriting the attribute
    descriptor.  That is, for a Parameterized class of type X with a
    Parameter y, the user can type X.y=3, which sets the default value
    of Parameter y to be 3, rather than overwriting y with the
    constant value 3 (and thereby losing all other info about that
    Parameter, such as the doc string, bounds, etc.).

    The __init__ method is used when defining a Parameterized class,
    usually when the module where that class is located is imported
    for the first time.  That is, the __init__ in this metaclass
    initializes the *class* object, while the __init__ method defined
    in each Parameterized class is called for each new instance of
    that class.

    Additionally, a class can declare itself abstract by having an
    attribute __abstract set to True. The 'abstract' attribute can be
    used to find out if a class is abstract or not.
    """

    def __init__(mcs, name, bases, dict_):
        """
        Initialize the class object (not an instance of the class, but
        the class itself).

        Initializes all the Parameters by looking up appropriate
        default values (see __param_inheritance()) and setting
        attrib_names (see _set_names()).
        """
        type.__init__(mcs, name, bases, dict_)

        # Compute which parameters explicitly do not support references
        # This can be removed when Parameter.allow_refs=True by default.
        explicit_no_refs = set()
        for base in bases:
            if issubclass(base, Parameterized):
                explicit_no_refs |= set(base._param__private.explicit_no_refs)

        _param__private = _ClassPrivate(explicit_no_refs=list(explicit_no_refs))
        mcs._param__private = _param__private
        mcs.__set_name(name, dict_)
        mcs._param__parameters = Parameters(mcs)

        # All objects (with their names) of type Parameter that are
        # defined in this class
        parameters = [(n, o) for (n, o) in dict_.items()
                      if isinstance(o, Parameter)]

        for param_name,param in parameters:
            mcs._initialize_parameter(param_name, param)

        # retrieve depends info from methods and store more conveniently
        dependers = [(n, m, m._dinfo) for (n, m) in dict_.items()
                     if hasattr(m, '_dinfo')]

        # Resolve dependencies of current class
        _watch = []
        for name, method, dinfo in dependers:
            watch = dinfo.get('watch', False)
            on_init = dinfo.get('on_init', False)
            minfo = MInfo(cls=mcs, inst=None, name=name,
                          method=method)
            deps, dynamic_deps = _params_depended_on(minfo, dynamic=False)
            if watch:
                _watch.append((name, watch == 'queued', on_init, deps, dynamic_deps))

        # Resolve dependencies in class hierarchy
        _inherited = []
        for cls in classlist(mcs)[:-1][::-1]:
            if not hasattr(cls, '_param__parameters'):
                continue
            for dep in cls.param._depends['watch']:
                method = getattr(mcs, dep[0], None)
                dinfo = getattr(method, '_dinfo', {'watch': False})
                if (not any(dep[0] == w[0] for w in _watch+_inherited)
                    and dinfo.get('watch')):
                    _inherited.append(dep)

        mcs.param._depends = {'watch': _inherited+_watch}

        if docstring_signature:
            mcs.__class_docstring()

    def __set_name(mcs, name, dict_):
        """
        Give Parameterized classes a useful 'name' attribute that is by
        default the class name, unless a class in the hierarchy has defined
        a `name` String Parameter with a defined `default` value, in which case
        that value is used to set the class name.
        """
        name_param = dict_.get("name", None)
        if name_param is not None:
            if type(name_param) is not String:
                raise TypeError(
                    f"Parameterized class {name!r} cannot override "
                    f"the 'name' Parameter with type {type(name_param)}. "
                    "Overriding 'name' is only allowed with a 'String' Parameter."
                )
            if name_param.default:
                mcs.name = name_param.default
                mcs._param__private.renamed = True
            else:
                mcs.name = name
        else:
            classes = classlist(mcs)[::-1]
            found_renamed = False
            for c in classes:
                if hasattr(c, '_param__private') and c._param__private.renamed:
                    found_renamed = True
                    break
            if not found_renamed:
                mcs.name = name

    def __class_docstring(mcs):
        """
        Customize the class docstring with a Parameter table if
        `docstring_describe_params` and the `param_pager` is available.
        """
        if not docstring_describe_params or not param_pager:
            return
        class_docstr = mcs.__doc__ if mcs.__doc__ else ''
        description = param_pager(mcs)
        mcs.__doc__ = class_docstr + '\n' + description

    def _initialize_parameter(mcs, param_name, param):
        # A Parameter has no way to find out the name a
        # Parameterized class has for it
        param._set_names(param_name)
        mcs.__param_inheritance(param_name, param)

    # Should use the official Python 2.6+ abstract base classes; see
    # https://github.com/holoviz/param/issues/84
    def __is_abstract(mcs):
        """
        Return True if the class has an attribute __abstract set to True.
        Subclasses will return False unless they themselves have
        __abstract set to true.  This mechanism allows a class to
        declare itself to be abstract (e.g. to avoid it being offered
        as an option in a GUI), without the "abstract" property being
        inherited by its subclasses (at least one of which is
        presumably not abstract).
        """
        # Can't just do ".__abstract", because that is mangled to
        # _ParameterizedMetaclass__abstract before running, but
        # the actual class object will have an attribute
        # _ClassName__abstract.  So, we have to mangle it ourselves at
        # runtime. Mangling follows description in
        # https://docs.python.org/2/tutorial/classes.html#private-variables-and-class-local-references
        try:
            return getattr(mcs,'_%s__abstract'%mcs.__name__.lstrip("_"))
        except AttributeError:
            return False

    def __get_signature(mcs):
        """
        For classes with a constructor signature that matches the default
        Parameterized.__init__ signature (i.e. ``__init__(self, **params)``)
        this method will generate a new signature that expands the
        parameters. If the signature differs from the default the
        custom signature is returned.
        """
        if mcs._param__private.signature:
            return mcs._param__private.signature
        # allowed_signature must be the signature of Parameterized.__init__
        # Inspecting `mcs.__init__` instead of `mcs` to avoid a recursion error
        if inspect.signature(mcs.__init__) != DEFAULT_SIGNATURE:
            return None
        processed_kws, keyword_groups = set(), []
        for cls in reversed(mcs.mro()):
            keyword_group = []
            for k, v in sorted(cls.__dict__.items()):
                if isinstance(v, Parameter) and k not in processed_kws and not v.readonly:
                    keyword_group.append(k)
                    processed_kws.add(k)
            keyword_groups.append(keyword_group)

        keywords = [el for grp in reversed(keyword_groups) for el in grp]
        mcs._param__private.signature = signature = inspect.Signature([
            inspect.Parameter(k, inspect.Parameter.KEYWORD_ONLY)
            for k in keywords
        ])
        return signature

    __signature__ = property(__get_signature)

    abstract = property(__is_abstract)

    def _get_param(mcs):
        return mcs._param__parameters

    param = property(_get_param)

    def __setattr__(mcs, attribute_name, value):
        """
        Implements 'self.attribute_name=value' in a way that also supports Parameters.

        If there is already a descriptor named attribute_name, and
        that descriptor is a Parameter, and the new value is *not* a
        Parameter, then call that Parameter's __set__ method with the
        specified value.

        In all other cases set the attribute normally (i.e. overwrite
        the descriptor).  If the new value is a Parameter, once it has
        been set we make sure that the value is inherited from
        Parameterized superclasses as described in __param_inheritance().
        """
        # Find out if there's a Parameter called attribute_name as a
        # class attribute of this class - if not, parameter is None.
        parameter,owning_class = mcs.get_param_descriptor(attribute_name)

        if parameter and not isinstance(value,Parameter):
            if owning_class != mcs:
                parameter = copy.copy(parameter)
                parameter.owner = mcs
                type.__setattr__(mcs,attribute_name,parameter)
            mcs.__dict__[attribute_name].__set__(None,value)

        else:
            type.__setattr__(mcs,attribute_name,value)

            if isinstance(value,Parameter):
                mcs.__param_inheritance(attribute_name,value)

    def __param_inheritance(mcs, param_name, param):
        """
        Look for Parameter values in superclasses of this
        Parameterized class.

        Ordinarily, when a Python object is instantiated, attributes
        not given values in the constructor will inherit the value
        given in the object's class, or in its superclasses.  For
        Parameters owned by Parameterized classes, we have implemented
        an additional level of default lookup, should this ordinary
        lookup return only `Undefined`.

        In such a case, i.e. when no non-`Undefined` value was found for a
        Parameter by the usual inheritance mechanisms, we explicitly
        look for Parameters with the same name in superclasses of this
        Parameterized class, and use the first such value that we
        find.

        The goal is to be able to set the default value (or other
        slots) of a Parameter within a Parameterized class, just as we
        can set values for non-Parameter objects in Parameterized
        classes, and have the values inherited through the
        Parameterized hierarchy as usual.

        Note that instantiate is handled differently: if there is a
        parameter with the same name in one of the superclasses with
        instantiate set to True, this parameter will inherit
        instantiate=True.
        """
        # get all relevant slots (i.e. slots defined in all
        # superclasses of this parameter)
        p_type = type(param)
        slots = dict.fromkeys(p_type._all_slots_)

        # note for some eventual future: python 3.6+ descriptors grew
        # __set_name__, which could replace this and _set_names
        setattr(param, 'owner', mcs)
        del slots['owner']

        # backwards compatibility (see Composite parameter)
        if 'objtype' in slots:
            setattr(param, 'objtype', mcs)
            del slots['objtype']

        supers = classlist(mcs)[::-1]

        # Explicitly inherit instantiate from super class and
        # check if type has changed to a more specific or different
        # Parameter type, requiring extra validation
        type_change = False
        for superclass in supers:
            super_param = superclass.__dict__.get(param_name)
            if not isinstance(super_param, Parameter):
                continue
            if super_param.instantiate is True:
                param.instantiate = True
            super_type = type(super_param)
            if not issubclass(super_type, p_type):
                type_change = True
        del slots['instantiate']

        callables, slot_values = {}, {}
        slot_overridden = False
        for slot in slots.keys():
            # Search up the hierarchy until param.slot (which has to
            # be obtained using getattr(param,slot)) is not Undefined,
            # is a new value (using identity) or we run out of classes
            # to search.
            for scls in supers:
                # Class may not define parameter or slot might not be
                # there because could be a more general type of Parameter
                new_param = scls.__dict__.get(param_name)
                if new_param is None or not hasattr(new_param, slot):
                    continue

                new_value = getattr(new_param, slot)
                old_value = slot_values.get(slot, Undefined)
                if new_value is Undefined:
                    continue
                elif new_value is old_value:
                    continue
                elif old_value is Undefined:
                    slot_values[slot] = new_value
                    # If we already know we have to re-validate abort
                    # early to avoid costly lookups
                    if slot_overridden or type_change:
                        break
                else:
                    if slot not in param._non_validated_slots:
                        slot_overridden = True
                    break

            if slot_values.get(slot, Undefined) is Undefined:
                try:
                    default_val = param._slot_defaults[slot]
                except KeyError as e:
                    raise KeyError(
                        f'Slot {slot!r} of parameter {param_name!r} has no '
                        'default value defined in `_slot_defaults`'
                    ) from e
                if callable(default_val):
                    callables[slot] = default_val
                else:
                    slot_values[slot] = default_val
            elif slot == 'allow_refs':
                # Track Parameters that explicitly declared no refs
                explicit_no_refs = mcs._param__private.explicit_no_refs
                if param.allow_refs is False:
                    explicit_no_refs.append(param.name)
                elif param.allow_refs is True and param.name in explicit_no_refs:
                    explicit_no_refs.remove(param.name)

        # Now set the actual slot values
        for slot, value in slot_values.items():
            setattr(param, slot, value)

            # Avoid crosstalk between mutable slot values in different Parameter objects
            if slot != "default":
                v = getattr(param, slot)
                if _is_mutable_container(v):
                    setattr(param, slot, copy.copy(v))

        # Once all the static slots have been filled in, fill in the dynamic ones
        # (which are only allowed to use static values or results are undefined)
        for slot, fn in callables.items():
            setattr(param, slot, fn(param))

        # Once all the slot values have been set, call _update_state for Parameters
        # that need updates to make sure they're set up correctly after inheritance.
        param._update_state()

        # If the type has changed to a more specific or different type
        # or a slot value has been changed validate the default again.

        # Hack: Had to disable re-validation of None values because the
        # automatic appending of an unknown value on Selector opens a whole
        # rabbit hole in regard to the validation.
        if type_change or slot_overridden and param.default is not None:
            try:
                param._validate(param.default)
            # Param has no base validation exception class. Param Parameters raise
            # ValueError, TypeError, OSError exceptions but external Parameters
            # might raise other types of error, so we catch them all.
            except Exception as e:
                msg = f'{_validate_error_prefix(param)} failed to validate its ' \
                      'default value on class creation. '
                parents = ', '.join(klass.__name__ for klass in mcs.__mro__[1:-2])
                if not type_change and slot_overridden:
                    msg += (
                        f'The Parameter is defined with attributes which when '
                        'combined with attributes inherited from its parent '
                        f'classes ({parents}) make it invalid. '
                        'Please fix the Parameter attributes.'
                    )
                elif type_change and not slot_overridden:
                    msg += (
                        f'The Parameter type changed between class {mcs.__name__!r} '
                        f'and one of its parent classes ({parents}) which '
                        f'made it invalid. Please fix the Parameter type.'
                    )
                else:
                    # type_change and slot_overriden is not possible as when
                    # the type changes checking the slots is aborted for
                    # performance reasons.
                    pass
                msg += f'\nValidation failed with:\n{e}'
                raise RuntimeError(msg) from e

    def get_param_descriptor(mcs,param_name):
        """
        Goes up the class hierarchy (starting from the current class)
        looking for a Parameter class attribute param_name. As soon as
        one is found as a class attribute, that Parameter is returned
        along with the class in which it is declared.
        """
        classes = classlist(mcs)
        for c in classes[::-1]:
            attribute = c.__dict__.get(param_name)
            if isinstance(attribute,Parameter):
                return attribute,c
        return None,None



# Whether script_repr should avoid reporting the values of parameters
# that are just inheriting their values from the class defaults.
# Because deepcopying creates a new object, cannot detect such
# inheritance when instantiate = True, so such values will be printed
# even if they are just being copied from the default.
script_repr_suppress_defaults=True


def script_repr(val, imports=None, prefix="\n    ", settings=[],
        qualify=True, unknown_value=None, separator="\n",
        show_imports=True):
    """
    Variant of pprint() designed for generating a (nearly) runnable script.

    The output of script_repr(parameterized_obj) is meant to be a
    string suitable for running using `python file.py`. Not every
    object is guaranteed to have a runnable script_repr
    representation, but it is meant to be a good starting point for
    generating a Python script that (after minor edits) can be
    evaluated to get a newly initialized object similar to the one
    provided.

    The new object will only have the same parameter state, not the
    same internal (attribute) state; the script_repr captures only
    the state of the Parameters of that object and not any other
    attributes it may have.

    If show_imports is True (default), includes import statements
    for each of the modules required for the objects being
    instantiated. This list may not be complete, as it typically
    includes only the imports needed for the Parameterized object
    itself, not for values that may have been supplied to Parameters.

    Apart from show_imports, accepts the same arguments as pprint(),
    so see pprint() for explanations of the arguments accepted. The
    default values of each of these arguments differ from pprint() in
    ways that are more suitable for saving as a separate script than
    for e.g. pretty-printing at the Python prompt.
    """
    if imports is None:
        imports = []

    rep = pprint(val, imports, prefix, settings, unknown_value,
                 qualify, separator)

    imports = list(set(imports))
    imports_str = ("\n".join(imports) + "\n\n") if show_imports else ""

    return imports_str + rep


# PARAM2_DEPRECATION: Remove entirely unused settings argument
def pprint(val,imports=None, prefix="\n    ", settings=[],
           unknown_value='<?>', qualify=False, separator=''):
    """
    Pretty printed representation of a parameterized
    object that may be evaluated with eval.

    Similar to repr except introspection of the constructor (__init__)
    ensures a valid and succinct representation is generated.

    Only parameters are represented (whether specified as standard,
    positional, or keyword arguments). Parameters specified as
    positional arguments are always shown, followed by modified
    parameters specified as keyword arguments, sorted by precedence.

    unknown_value determines what to do where a representation cannot be
    generated for something required to recreate the object. Such things
    include non-parameter positional and keyword arguments, and certain
    values of parameters (e.g. some random state objects).

    Supplying an unknown_value of None causes unrepresentable things
    to be silently ignored. If unknown_value is a string, that
    string will appear in place of any unrepresentable things. If
    unknown_value is False, an Exception will be raised if an
    unrepresentable value is encountered.

    If supplied, imports should be a list, and it will be populated
    with the set of imports required for the object and all of its
    parameter values.

    If qualify is True, the class's path will be included (e.g. "a.b.C()"),
    otherwise only the class will appear ("C()").

    Parameters will be separated by a comma only by default, but the
    separator parameter allows an additional separator to be supplied
    (e.g. a newline could be supplied to have each Parameter appear on a
    separate line).

    Instances of types that require special handling can use the
    script_repr_reg dictionary. Using the type as a key, add a
    function that returns a suitable representation of instances of
    that type, and adds the required import statement. The repr of a
    parameter can be suppressed by returning None from the appropriate
    hook in script_repr_reg.
    """
    if imports is None:
        imports = []

    if isinstance(val,type):
        rep = type_script_repr(val,imports,prefix,settings)

    elif type(val) in script_repr_reg:
        rep = script_repr_reg[type(val)](val,imports,prefix,settings)

    elif isinstance(val, _no_script_repr):
        rep = None

    elif isinstance(val, Parameterized) or (type(val) is type and issubclass(val, Parameterized)):
        rep=val.param.pprint(imports=imports, prefix=prefix+"    ",
                        qualify=qualify, unknown_value=unknown_value,
                        separator=separator)
    else:
        rep=repr(val)

    return rep


# Registry for special handling for certain types in script_repr and pprint
script_repr_reg = {}


# currently only handles list and tuple
def container_script_repr(container,imports,prefix,settings):
    result=[]
    for i in container:
        result.append(pprint(i,imports,prefix,settings))

    ## (hack to get container brackets)
    if isinstance(container,list):
        d1,d2='[',']'
    elif isinstance(container,tuple):
        d1,d2='(',')'
    else:
        raise NotImplementedError
    rep=d1+','.join(result)+d2

    # no imports to add for built-in types

    return rep


@gen_types
def _no_script_repr():
    # Suppress scriptrepr for objects not yet having a useful string representation
    if random := sys.modules.get("random"):
        yield random.Random
    if npr := sys.modules.get("numpy.random"):
        yield npr.RandomState


def function_script_repr(fn,imports,prefix,settings):
    name = fn.__name__
    module = fn.__module__
    imports.append('import %s'%module)
    return module+'.'+name

def type_script_repr(type_,imports,prefix,settings):
    module = type_.__module__
    if module!='__builtin__':
        imports.append('import %s'%module)
    return module+'.'+type_.__name__

script_repr_reg[list] = container_script_repr
script_repr_reg[tuple] = container_script_repr
script_repr_reg[FunctionType] = function_script_repr


#: If not None, the value of this Parameter will be called (using '()')
#: before every call to __db_print, and is expected to evaluate to a
#: string that is suitable for prefixing messages and warnings (such
#: as some indicator of the global state).
dbprint_prefix=None


def truncate(str_, maxlen = 30):
    """Return HTML-safe truncated version of given string"""
    rep = (str_[:(maxlen-2)] + '..') if (len(str_) > (maxlen-2)) else str_
    return html.escape(rep)


def _get_param_repr(key, val, p, vallen=30, doclen=40):
    """HTML representation for a single Parameter object and its value"""
    if isinstance(val, Parameterized) or (type(val) is type and issubclass(val, Parameterized)):
        value = val.param._repr_html_(open=False)
    elif hasattr(val, "_repr_html_"):
        value = val._repr_html_()
    else:
        value = truncate(repr(val), vallen)

    if hasattr(p, 'bounds'):
        if p.bounds is None:
            range_ = ''
        elif hasattr(p,'inclusive_bounds'):
            # Numeric bounds use ( and [ to indicate exclusive and inclusive
            bl,bu = p.bounds
            il,iu = p.inclusive_bounds

            lb = '' if bl is None else ('>=' if il else '>') + str(bl)
            ub = '' if bu is None else ('<=' if iu else '<') + str(bu)
            range_ = lb + (', ' if lb and bu else '') + ub
        else:
            range_ = repr(p.bounds)
    elif hasattr(p, 'objects') and p.objects:
        range_ = ', '.join(list(map(repr, p.objects)))
    elif hasattr(p, 'class_'):
        if isinstance(p.class_, tuple):
            range_ = ' | '.join(kls.__name__ for kls in p.class_)
        else:
            range_ = p.class_.__name__
    elif hasattr(p, 'regex') and p.regex is not None:
        range_ = f'regex({p.regex})'
    else:
        range_ = ''

    if p.readonly:
        range_ = ' '.join(s for s in ['<i>read-only</i>', range_] if s)
    elif p.constant:
        range_ = ' '.join(s for s in ['<i>constant</i>', range_] if s)

    if getattr(p, 'allow_None', False):
        range_ = ' '.join(s for s in ['<i>nullable</i>', range_] if s)

    tooltip = f' class="param-doc-tooltip" data-tooltip="{escape(p.doc.strip())}"' if p.doc else ''

    return (
        f'<tr>'
        f'  <td><p style="margin-bottom: 0px;"{tooltip}>{key}</p></td>'
        f'  <td style="max-width: 200px; text-align:left;">{value}</td>'
        f'  <td style="text-align:left;">{p.__class__.__name__}</td>'
        f'  <td style="max-width: 300px;">{range_}</td>'
        f'</tr>\n'
    )


def _parameterized_repr_html(p, open):
    """HTML representation for a Parameterized object"""
    if isinstance(p, Parameterized):
        cls = p.__class__
        title = cls.name + "()"
        value_field = 'Value'
    else:
        cls = p
        title = cls.name
        value_field = 'Default'

    tooltip_css = """
.param-doc-tooltip{
  position: relative;
  cursor: help;
}
.param-doc-tooltip:hover:after{
  content: attr(data-tooltip);
  background-color: black;
  color: #fff;
  border-radius: 3px;
  padding: 10px;
  position: absolute;
  z-index: 1;
  top: -5px;
  left: 100%;
  margin-left: 10px;
  min-width: 250px;
}
.param-doc-tooltip:hover:before {
  content: "";
  position: absolute;
  top: 50%;
  left: 100%;
  margin-top: -5px;
  border-width: 5px;
  border-style: solid;
  border-color: transparent black transparent transparent;
}
"""
    openstr = " open" if open else ""
    param_values = p.param.values().items()
    contents = "".join(_get_param_repr(key, val, p.param[key])
                       for key, val in param_values)
    return (
        f'<style>{tooltip_css}</style>\n'
        f'<details {openstr}>\n'
        ' <summary style="display:list-item; outline:none;">\n'
        f'  <tt>{title}</tt>\n'
        ' </summary>\n'
        ' <div style="padding-left:10px; padding-bottom:5px;">\n'
        '  <table style="max-width:100%; border:1px solid #AAAAAA;">\n'
        f'   <tr><th style="text-align:left;">Name</th><th style="text-align:left;">{value_field}</th><th style="text-align:left;">Type</th><th>Range</th></tr>\n'
        f'{contents}\n'
        '  </table>\n </div>\n</details>\n'
    )

# _ClassPrivate and _InstancePrivate are the private namespaces of Parameterized
# classes and instance respectively, stored on the `_param__private` attribute.
# They are implemented with slots for performance reasons.

class _ClassPrivate:
    """
    parameters_state: dict
        Dict holding some transient states
    disable_instance_params: bool
        Whether to disable instance parameters
    renamed: bool
        Whethe the class has been renamed by a super class
    params: dict
        Dict of parameter_name:parameter
    """

    __slots__ = [
        'parameters_state',
        'disable_instance_params',
        'renamed',
        'params',
        'initialized',
        'signature',
        'explicit_no_refs',
    ]

    def __init__(
        self,
        parameters_state=None,
        disable_instance_params=False,
        explicit_no_refs=None,
        renamed=False,
        params=None,
    ):
        if parameters_state is None:
            parameters_state = {
                "BATCH_WATCH": False, # If true, Event and watcher objects are queued.
                "TRIGGER": False,
                "events": [], # Queue of batched events
                "watchers": [] # Queue of batched watchers
            }
        self.parameters_state = parameters_state
        self.disable_instance_params = disable_instance_params
        self.renamed = renamed
        self.params = {} if params is None else params
        self.initialized = False
        self.signature = None
        self.explicit_no_refs = [] if explicit_no_refs is None else explicit_no_refs

    def __getstate__(self):
        return {slot: getattr(self, slot) for slot in self.__slots__}

    def __setstate__(self, state):
        for k, v in state.items():
            setattr(self, k, v)


class _InstancePrivate:
    """
    initialized: bool
        Flag that can be tested to see if e.g. constant Parameters can still be set
    parameters_state: dict
        Dict holding some transient states
    dynamic_watchers: defaultdict
        Dynamic watchers
    ref_watchers: list[Watcher]
        Watchers used for internal references
    params: dict
        Dict of parameter_name:parameter
    refs: dict
        Dict of parameter name:reference
    watchers: dict
        Dict of dict:
            parameter_name:
                parameter_attribute (e.g. 'value'): list of `Watcher`s
    values: dict
        Dict of parameter name: value
    """

    __slots__ = [
        'initialized',
        'parameters_state',
        'dynamic_watchers',
        'params',
        'async_refs',
        'refs',
        'ref_watchers',
        'syncing',
        'watchers',
        'values',
        'explicit_no_refs',
    ]

    def __init__(
        self,
        initialized=False,
        parameters_state=None,
        dynamic_watchers=None,
        refs=None,
        params=None,
        watchers=None,
        values=None,
        explicit_no_refs=None
    ):
        self.initialized = initialized
        self.explicit_no_refs = [] if explicit_no_refs is None else explicit_no_refs
        self.syncing = set()
        if parameters_state is None:
            parameters_state = {
                "BATCH_WATCH": False, # If true, Event and watcher objects are queued.
                "TRIGGER": False,
                "events": [], # Queue of batched events
                "watchers": [] # Queue of batched watchers
            }
        self.ref_watchers = []
        self.async_refs = {}
        self.parameters_state = parameters_state
        self.dynamic_watchers = defaultdict(list) if dynamic_watchers is None else dynamic_watchers
        self.params = {} if params is None else params
        self.refs = {} if refs is None else refs
        self.watchers = {} if watchers is None else watchers
        self.values = {} if values is None else values

    def __getstate__(self):
        return {slot: getattr(self, slot) for slot in self.__slots__}

    def __setstate__(self, state):
        for k, v in state.items():
            setattr(self, k, v)


class Parameterized(metaclass=ParameterizedMetaclass):
    """
    Base class for named objects that support Parameters and message
    formatting.

    Automatic object naming: Every Parameterized instance has a name
    parameter.  If the user doesn't designate a name=<str> argument
    when constructing the object, the object will be given a name
    consisting of its class name followed by a unique 5-digit number.

    Automatic parameter setting: The Parameterized __init__ method
    will automatically read the list of keyword parameters.  If any
    keyword matches the name of a Parameter (see Parameter class)
    defined in the object's class or any of its superclasses, that
    parameter in the instance will get the value given as a keyword
    argument.  For example:

    >>> class Foo(Parameterized):
    ...     xx = Parameter(default=1)

    >>> foo = Foo(xx=20)

    in this case foo.xx gets the value 20.

    When initializing a Parameterized instance ('foo' in the example
    above), the values of parameters can be supplied as keyword
    arguments to the constructor (using parametername=parametervalue);
    these values will override the class default values for this one
    instance.

    If no 'name' parameter is supplied, self.name defaults to the
    object's class name with a unique number appended to it.

    Message formatting: Each Parameterized instance has several
    methods for optionally printing output. This functionality is
    based on the standard Python 'logging' module; using the methods
    provided here, wraps calls to the 'logging' module's root logger
    and prepends each message with information about the instance
    from which the call was made. For more information on how to set
    the global logging level and change the default message prefix,
    see documentation for the 'logging' module.
    """

    name = String(default=None, constant=True, doc="""
        String identifier for this object.""")

    def __init__(self, **params):
        global object_count

        # Setting a Parameter value in an __init__ block before calling
        # Parameterized.__init__ (via super() generally) already sets the
        # _InstancePrivate namespace over the _ClassPrivate namespace
        # (see Parameter.__set__) so we shouldn't override it here.
        if not isinstance(self._param__private, _InstancePrivate):
            self._param__private = _InstancePrivate(
                explicit_no_refs=type(self)._param__private.explicit_no_refs
            )

        # Skip generating a custom instance name when a class in the hierarchy
        # has overriden the default of the `name` Parameter.
        if self.param.name.default == self.__class__.__name__:
            self.param._generate_name()
        refs, deps = self.param._setup_params(**params)
        object_count += 1

        self._param__private.initialized = True

        self.param._setup_refs(deps)
        self.param._update_deps(init=True)
        self._param__private.refs = refs

    @property
    def param(self):
        """
        The `.param` namespace for `Parameterized` classes and instances.

        This namespace provides access to powerful methods and properties for managing
        parameters in a `Parameterized` object. It includes utilities for adding parameters,
        updating parameters, debugging, serialization, logging, and more.

        User Guide
        ----------
        For more details on parameter objects and instances, see:
        https://param.holoviz.org/user_guide/Parameters.html#parameter-objects-and-instances

        Examples
        --------
        Basic usage of `.param` in a `Parameterized` class:

        >>> import param
        >>>
        >>> class MyClass(param.Parameterized):
        ...     value = param.Parameter()
        >>>
        >>> my_instance = MyClass(value=0)

        Access the `value` parameter of `my_instance`:

        >>> my_instance.param.value  # the Parameter instance

        Note that this is different from the current `value` of `my_instance`:

        >>> my_instance.value  # the current parameter value
        0

        """
        return Parameters(self.__class__, self=self)

    # 'Special' methods

    def __getstate__(self):
        """
        Save the object's state: return a dictionary that is a shallow
        copy of the object's __dict__ and that also includes the
        object's __slots__ (if it has any).
        """
        # Unclear why this is a copy and not simply state.update(self.__dict__)
        state = self.__dict__.copy()
        for slot in get_occupied_slots(self):
            state[slot] = getattr(self,slot)

        # Note that Parameterized object pickling assumes that
        # attributes to be saved are only in __dict__ or __slots__
        # (the standard Python places to store attributes, so that's a
        # reasonable assumption). (Additionally, class attributes that
        # are Parameters are also handled, even when they haven't been
        # instantiated - see PickleableClassAttributes.)

        return state

    def __setstate__(self, state):
        """
        Restore objects from the state dictionary to this object.

        During this process the object is considered uninitialized.
        """
        explicit_no_refs = type(self)._param__private.explicit_no_refs
        self._param__private = _InstancePrivate(explicit_no_refs=explicit_no_refs)
        self._param__private.initialized = False

        _param__private = state.get('_param__private', None)
        if _param__private is None:
            _param__private = _InstancePrivate(explicit_no_refs=explicit_no_refs)

        # When making a copy the internal watchers have to be
        # recreated and point to the new instance
        if _param__private.watchers:
            param_watchers = _param__private.watchers
            for p, attrs in param_watchers.items():
                for attr, watchers in attrs.items():
                    new_watchers = []
                    for watcher in watchers:
                        watcher_args = list(watcher)
                        if watcher.inst is not None:
                            watcher_args[0] = self
                        fn = watcher.fn
                        if hasattr(fn, '_watcher_name'):
                            watcher_args[2] = _m_caller(self, fn._watcher_name)
                        elif get_method_owner(fn) is watcher.inst:
                            watcher_args[2] = getattr(self, fn.__name__)
                        new_watchers.append(Watcher(*watcher_args))
                    param_watchers[p][attr] = new_watchers

        state.pop('param', None)

        for name,value in state.items():
            setattr(self,name,value)
        self._param__private.initialized = True

    @_recursive_repr()
    def __repr__(self):
        """
        Provide a nearly valid Python representation that could be used to recreate
        the item with its parameters, if executed in the appropriate environment.

        Returns 'classname(parameter1=x,parameter2=y,...)', listing
        all the parameters of this object.
        """
        try:
            settings = [f'{name}={val!r}'
                        for name, val in self.param.values().items()]
        except RuntimeError: # Handle recursion in parameter depth
            settings = []
        return self.__class__.__name__ + "(" + ", ".join(settings) + ")"

    def __str__(self):
        """Return a short representation of the name and class of this object."""
        return f"<{self.__class__.__name__} {self.name}>"


def print_all_param_defaults():
    """Print the default values for all imported Parameters."""
    print("_______________________________________________________________________________")
    print("")
    print("                           Parameter Default Values")
    print("")
    classes = descendents(Parameterized)
    classes.sort(key=lambda x:x.__name__)
    for c in classes:
        c.print_param_defaults()
    print("_______________________________________________________________________________")



# As of Python 2.6+, a fn's **args no longer has to be a
# dictionary. This might allow us to use a decorator to simplify using
# ParamOverrides (if that does indeed make them simpler to use).
# http://docs.python.org/whatsnew/2.6.html
class ParamOverrides(dict):
    """
    A dictionary that returns the attribute of a specified object if
    that attribute is not present in itself.

    Used to override the parameters of an object.
    """

    # NOTE: Attribute names of this object block parameters of the
    # same name, so all attributes of this object should have names
    # starting with an underscore (_).

    def __init__(self,overridden,dict_,allow_extra_keywords=False):
        """

        If allow_extra_keywords is False, then all keys in the
        supplied dict_ must match parameter names on the overridden
        object (otherwise a warning will be printed).

        If allow_extra_keywords is True, then any items in the
        supplied dict_ that are not also parameters of the overridden
        object will be available via the extra_keywords() method.
        """
        # This method should be fast because it's going to be
        # called a lot. This _might_ be faster (not tested):
        #  def __init__(self,overridden,**kw):
        #      ...
        #      dict.__init__(self,**kw)
        self._overridden = overridden
        dict.__init__(self,dict_)

        if allow_extra_keywords:
            self._extra_keywords=self._extract_extra_keywords(dict_)
        else:
            self._check_params(dict_)

    def extra_keywords(self):
        """
        Return a dictionary containing items from the originally
        supplied `dict_` whose names are not parameters of the
        overridden object.
        """
        return self._extra_keywords

    def param_keywords(self):
        """
        Return a dictionary containing items from the originally
        supplied `dict_` whose names are parameters of the
        overridden object (i.e. not extra keywords/parameters).
        """
        return {key: self[key] for key in self if key not in self.extra_keywords()}

    def __missing__(self,name):
        # Return 'name' from the overridden object
        return getattr(self._overridden,name)

    def __repr__(self):
        # As dict.__repr__, but indicate the overridden object
        return dict.__repr__(self)+" overriding params from %s"%repr(self._overridden)

    def __getattr__(self,name):
        # Provide 'dot' access to entries in the dictionary.
        # (This __getattr__ method is called only if 'name' isn't an
        # attribute of self.)
        return self.__getitem__(name)

    def __setattr__(self,name,val):
        # Attributes whose name starts with _ are set on self (as
        # normal), but all other attributes are inserted into the
        # dictionary.
        if not name.startswith('_'):
            self.__setitem__(name,val)
        else:
            dict.__setattr__(self,name,val)

    def get(self, key, default=None):
        try:
            return self[key]
        except KeyError:
            return default

    def __contains__(self, key):
        return key in self.__dict__ or key in self._overridden.param

    def _check_params(self,params):
        """
        Print a warning if params contains something that is not a
        Parameter of the overridden object.
        """
        overridden_object_params = list(self._overridden.param)
        for item in params:
            if item not in overridden_object_params:
                self.param.warning("'%s' will be ignored (not a Parameter).",item)

    def _extract_extra_keywords(self,params):
        """
        Return any items in params that are not also
        parameters of the overridden object.
        """
        extra_keywords = {}
        overridden_object_params = list(self._overridden.param)
        for name, val in params.items():
            if name not in overridden_object_params:
                extra_keywords[name]=val
                # Could remove name from params (i.e. del params[name])
                # so that it's only available via extra_keywords()
        return extra_keywords


# Helper function required by ParameterizedFunction.__reduce__
def _new_parameterized(cls):
    return Parameterized.__new__(cls)


class ParameterizedFunction(Parameterized):
    """
    Acts like a Python function, but with arguments that are Parameters.

    Implemented as a subclass of Parameterized that, when instantiated,
    automatically invokes __call__ and returns the result, instead of
    returning an instance of the class.

    To obtain an instance of this class, call instance().
    """

    __abstract = True

    def __str__(self):
        return self.__class__.__name__+"()"

    @bothmethod
    def instance(self_or_cls,**params):
        """
        Return an instance of this class, copying parameters from any
        existing instance provided.
        """
        if isinstance (self_or_cls,ParameterizedMetaclass):
            cls = self_or_cls
        else:
            p = params
            params = self_or_cls.param.values()
            params.update(p)
            params.pop('name')
            cls = self_or_cls.__class__

        inst=Parameterized.__new__(cls)
        Parameterized.__init__(inst,**params)
        if 'name' in params:  inst.__name__ = params['name']
        else:                 inst.__name__ = self_or_cls.name
        return inst

    def __new__(class_,*args,**params):
        # Create and __call__() an instance of this class.
        inst = class_.instance()
        inst.param._set_name(class_.__name__)
        return inst.__call__(*args,**params)

    def __call__(self,*args,**kw):
        raise NotImplementedError("Subclasses must implement __call__.")

    def __reduce__(self):
        # Control reconstruction (during unpickling and copying):
        # ensure that ParameterizedFunction.__new__ is skipped
        state = ParameterizedFunction.__getstate__(self)
        # Here it's necessary to use a function defined at the
        # module level rather than Parameterized.__new__ directly
        # because otherwise pickle will find .__new__'s module to be
        # __main__. Pretty obscure aspect of pickle.py...
        return (_new_parameterized,(self.__class__,),state)

    def _pprint(self, imports=None, prefix="\n    ",unknown_value='<?>',
                qualify=False, separator=""):
        """
        Same as self.param.pprint, except that X.classname(Y
        is replaced with X.classname.instance(Y
        """
        r = self.param.pprint(imports,prefix,
                              unknown_value=unknown_value,
                              qualify=qualify,separator=separator)
        classname=self.__class__.__name__
        return r.replace(".%s("%classname,".%s.instance("%classname)


class default_label_formatter(ParameterizedFunction):
    """Default formatter to turn parameter names into appropriate widget labels."""

    capitalize = Parameter(default=True, doc="""
        Whether or not the label should be capitalized.""")

    replace_underscores = Parameter(default=True, doc="""
        Whether or not underscores should be replaced with spaces.""")

    overrides = Parameter(default={}, doc="""
        Allows custom labels to be specified for specific parameter
        names using a dictionary where key is the parameter name and the
        value is the desired label.""")

    def __call__(self, pname):
        if pname in self.overrides:
            return self.overrides[pname]
        if self.replace_underscores:
            pname = pname.replace('_',' ')
        if self.capitalize:
            pname = pname[:1].upper() + pname[1:]
        return pname


label_formatter = default_label_formatter


# PARAM3_DEPRECATION: Should be able to remove this; was originally
# adapted from OProperty from
# infinitesque.net/articles/2005/enhancing%20Python's%20property.xhtml
# but since python 2.6 the getter, setter, and deleter attributes of
# a property should provide similar functionality already.
class overridable_property:
    """
    The same as Python's "property" attribute, but allows the accessor
    methods to be overridden in subclasses.

    .. deprecated:: 2.0.0
    """

    # Delays looking up the accessors until they're needed, rather
    # than finding them when the class is first created.

    # Based on the emulation of PyProperty_Type() in Objects/descrobject.c

    def __init__(self, fget=None, fset=None, fdel=None, doc=None):
        warnings.warn(
            message="overridable_property has been deprecated.",
            category=_ParamFutureWarning,
            stacklevel=2,
        )
        self.fget = fget
        self.fset = fset
        self.fdel = fdel
        self.__doc__ = doc

    def __get__(self, obj, objtype=None):
        if obj is None:
            return self
        if self.fget is None:
            raise AttributeError("unreadable attribute")
        if self.fget.__name__ == '<lambda>' or not self.fget.__name__:
            return self.fget(obj)
        else:
            return getattr(obj, self.fget.__name__)()

    def __set__(self, obj, value):
        if self.fset is None:
            raise AttributeError("can't set attribute")
        if self.fset.__name__ == '<lambda>' or not self.fset.__name__:
            self.fset(obj, value)
        else:
            getattr(obj, self.fset.__name__)(value)

    def __delete__(self, obj):
        if self.fdel is None:
            raise AttributeError("can't delete attribute")
        if self.fdel.__name__ == '<lambda>' or not self.fdel.__name__:
            self.fdel(obj)
        else:
            getattr(obj, self.fdel.__name__)()
