Source code for param.parameterized

Generic support for objects with full-featured Parameters and

This file comes from the Param library (
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 (providing specialized Parameter types).

import asyncio
import copy
import datetime as dt
import html
import inspect
import logging
import numbers
import operator
import random
import re
import types
import typing
import warnings

# Allow this file to be used standalone if desired, albeit without JSON serialization
    from . import serializer
except ImportError:
    serializer = None

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 ._utils import (
    ParamDeprecationWarning as _ParamDeprecationWarning,
    ParamFutureWarning as _ParamFutureWarning,

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

from inspect import getfullargspec

dt_types = (dt.datetime,
_int_types = (int,)

    import numpy as np
    dt_types = dt_types + (np.datetime64,)
    _int_types = _int_types + (np.integer,)

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
# `` + ".<name>"``)
logger = None
[docs]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( + '.' + 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 = []
[docs]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, for dep in arg_deps) kwargs = {n: getattr(dep.owner, for n, dep in kw_deps.items()} return function(*args, **kwargs)
[docs]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, return value
[docs]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()
[docs]@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
[docs]@_deprecated(extra_msg="Use instead `batch_call_watchers`.") @contextmanager def batch_watch(parameterized, enable=True, run=True): with _batch_call_watchers(parameterized, enable, run): yield
[docs]@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
[docs]@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 except: raise finally: for (p, const) in zip(params, constants): p.constant = const
[docs]@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 except: raise 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() 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 # ( # # Code from six (; version 1.4.1). @_deprecated() 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 = 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( 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=_ParamDeprecationWarning, stacklevel=2, ) return _recursive_repr(fillvalue=fillvalue)
[docs]@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 ='what') path = "."'path') m = re.match(r"(?P<obj>.*)(\.)(?P<attr>.*)", path) obj ='obj') attr ="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,, pobj=inst.param[], 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 is None else _getattrr(, p, None) else: old = Undefined if e.old is None else _getattrr(e.old.param[p], what, None) new = Undefined if is None else _getattrr([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")
[docs]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 (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): # _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
[docs]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: # # # 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 # 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 ): ...
[docs] @_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). """ = 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 serializer is None: raise ImportError('Cannot import needed to generate schema') 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): from .reactive import reactive_ops return reactive_ops(self) @property def label(self): if and self._label is None: return label_formatter( 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,, 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[] 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 = 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=_ParamDeprecationWarning, 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.default) obj._param__private.values[] = val else: _old = obj._param__private.values.get(, 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." % def _set_names(self, attrib_name): if None not in (self.owner, and attrib_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__,,, attrib_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
[docs]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="", 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_update(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 ): ...
[docs] @_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 } equalities.update({dtt: operator.eq for dtt in dt_types}) @classmethod def is_equal(cls, obj1, obj2): for eq_type, eq in cls.equalities.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) != 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) != 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): = 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, else: for sp in extract_dependencies(p): groups[sp.owner].append((pname, 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) 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 == 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,, 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, 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 if shared_parameters._share: param_key = (str(type(self)), 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 not in params: params.append( 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
[docs] @_deprecated(extra_msg="""Use instead `for k,v in p.param.objects().items(): print(f"{}.{k}={repr(v.default)}")`""") 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"{}.{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))
[docs] @_deprecated(extra_msg="Use instead `p.param.default =`") 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)
[docs] def add_parameter(self_, param_name, param_obj): """ Add a new Parameter object into this object's class. Should result in a Parameter equivalent to one declared in the class's source code. """ # 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`") 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
[docs] @_deprecated(extra_msg="Use instead `.param.values()` or `.param['param']`") 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
[docs] def update(self_, arg=Undefined, /, **kwargs): """ For the given dictionary or iterable or set of param=value keyword arguments, sets the corresponding parameter of this object or class to the given value. May also be used as a context manager to temporarily set and then reset parameter values. """ 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: 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
[docs] @_deprecated(extra_msg="Use instead `.param.update`") 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 not args[0] in kwargs and not kwargs: kwargs[args[0]] = args[1] else: raise ValueError("Invalid positional arguments for %s.set_param" % ( 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
[docs] 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: warnings.warn( 'Looking up instance Parameter objects (`.param.objects()`) until ' 'the Parameterized instance has been fully initialized is deprecated and will raise an error in a future version. ' '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.', category=_ParamFutureWarning, stacklevel=2, ) 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
[docs] 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: warnings.warn( 'Triggering watchers on a partially initialized Parameterized instance ' 'is deprecated and will raise an error in a future version. ' 'Ensure you have called super().__init__(**params) in ' 'the Parameterized instance constructor before trying to set up a watcher.', category=_ParamFutureWarning, stacklevel=2, ) 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,, obj=event.obj, cls=event.cls, old=event.old,, type=event_type) def _execute_watcher(self, watcher, events): if watcher.mode == 'args': args, kwargs = events, {} else: args, kwargs = (), { 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.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)
[docs] 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)
[docs] def serialize_parameters(self_, subset=None, 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_parameters(self_or_cls, subset=subset)
[docs] 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)
[docs] def deserialize_parameters(self_, serialization, subset=None, mode='json'): self_or_cls = self_.self_or_cls serializer = Parameter._serializers[mode] return serializer.deserialize_parameters(self_or_cls, serialization, subset=subset)
[docs] 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)
[docs] 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
[docs] @_deprecated(extra_msg=""" Use `.param.values().items()` instead (or `.param.values()` for the common case of `dict(....param.get_param_values())`) """) 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()]
[docs] 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)
[docs] 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)
[docs] 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
[docs] 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
[docs] 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)
[docs] @_deprecated(extra_msg='Use instead `.param.method_dependencies`') 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)
[docs] 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): if name == '_param_watchers': continue 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,, 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: warnings.warn( '(Un)registering a watcher on a partially initialized Parameterized instance ' 'is deprecated and will raise an error in a future version. Ensure ' 'you have called super().__init__(**) in the Parameterized instance ' 'constructor before trying to set up a watcher.', category=_ParamFutureWarning, stacklevel=4, ) 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)
[docs] 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
[docs] 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.')
[docs] 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
[docs] @_deprecated(extra_msg="Use instead `{k:v.default for k,v in p.param.objects().items()}`") 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( if dbprint_prefix and callable(dbprint_prefix): msg = dbprint_prefix() + ": " + msg # pylint: disable-msg=E1102 get_logger(, msg, *args, **kw) # PARAM3_DEPRECATION
[docs] @_deprecated(extra_msg="""Use instead `for k,v in p.param.objects().items(): print(f"{}.{k}={repr(v.default)}")`""") 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"{}.{k}={repr(v.default)}")` """ self = self_.self for name, val in self.param.values().items(): print(f'{}.{name} = {val}')
[docs] 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)
[docs] @_deprecated(extra_msg="Use instead `.param.log(param.MESSAGE, ...)`") 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)
[docs] @_deprecated(extra_msg="Use instead `.param.log(param.VERBOSE, ...)`") 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)
[docs] @_deprecated(extra_msg="Use instead `.param.log(param.DEBUG, ...)`") 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)
[docs] 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()
[docs] 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"{}: 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 not type(name_param) is 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: = name_param.default mcs._param__private.renamed = True else: = 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: = 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 # 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 # 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( elif param.allow_refs is True and in explicit_no_refs: explicit_no_refs.remove( # 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, this is going to raise ' \ 'an error in the future. ' 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}' warnings.warn( msg, category=_ParamFutureWarning, stacklevel=4, ) 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
[docs]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`. 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, 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 def empty_script_repr(*args): # pyflakes:ignore (unused arguments): return None try: # Suppress scriptrepr for objects not yet having a useful string representation import numpy script_repr_reg[random.Random] = empty_script_repr script_repr_reg[numpy.random.RandomState] = empty_script_repr except ImportError: pass # Support added only if those libraries are available 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 = + "()" value_field = 'Value' else: cls = p title = 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)
[docs]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, 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.""")
[docs] 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.__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): return Parameters(self.__class__, self=self) #PARAM3_DEPRECATION @property @_deprecated(extra_msg="Use `inst.param.watchers` instead.", warning_cat=_ParamFutureWarning) def _param_watchers(self): return self._param__private.watchers #PARAM3_DEPRECATION @_param_watchers.setter @_deprecated(extra_msg="Use `inst.param.watchers = ...` instead.", warning_cat=_ParamFutureWarning) def _param_watchers(self, value): self._param__private.watchers = value # '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__} {}>"
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). #
[docs]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 (_).
[docs] 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)
[docs]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__ = 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 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 #'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=_ParamDeprecationWarning, 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__)()