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|
from __future__ import annotations
import collections.abc
import copy
import functools
import itertools
import operator
import random
import re
from collections.abc import Container, Iterable, Mapping
from typing import TYPE_CHECKING, Any, Callable, Dict, TypeVar, Union, overload
import jaraco.text
if TYPE_CHECKING:
from _operator import _SupportsComparison
from _typeshed import SupportsKeysAndGetItem
from typing_extensions import Self
_RangeMapKT = TypeVar('_RangeMapKT', bound=_SupportsComparison)
else:
# _SupportsComparison doesn't exist at runtime,
# but _RangeMapKT is used in RangeMap's superclass' type parameters
_RangeMapKT = TypeVar('_RangeMapKT')
_T = TypeVar('_T')
_VT = TypeVar('_VT')
_Matchable = Union[Callable, Container, Iterable, re.Pattern]
def _dispatch(obj: _Matchable) -> Callable:
# can't rely on singledispatch for Union[Container, Iterable]
# due to ambiguity
# (https://peps.python.org/pep-0443/#abstract-base-classes).
if isinstance(obj, re.Pattern):
return obj.fullmatch
# mypy issue: https://github.com/python/mypy/issues/11071
if not isinstance(obj, Callable): # type: ignore[arg-type]
if not isinstance(obj, Container):
obj = set(obj) # type: ignore[arg-type]
obj = obj.__contains__
return obj # type: ignore[return-value]
class Projection(collections.abc.Mapping):
"""
Project a set of keys over a mapping
>>> sample = {'a': 1, 'b': 2, 'c': 3}
>>> prj = Projection(['a', 'c', 'd'], sample)
>>> dict(prj)
{'a': 1, 'c': 3}
Projection also accepts an iterable or callable or pattern.
>>> iter_prj = Projection(iter('acd'), sample)
>>> call_prj = Projection(lambda k: ord(k) in (97, 99, 100), sample)
>>> pat_prj = Projection(re.compile(r'[acd]'), sample)
>>> prj == iter_prj == call_prj == pat_prj
True
Keys should only appear if they were specified and exist in the space.
Order is retained.
>>> list(prj)
['a', 'c']
Attempting to access a key not in the projection
results in a KeyError.
>>> prj['b']
Traceback (most recent call last):
...
KeyError: 'b'
Use the projection to update another dict.
>>> target = {'a': 2, 'b': 2}
>>> target.update(prj)
>>> target
{'a': 1, 'b': 2, 'c': 3}
Projection keeps a reference to the original dict, so
modifying the original dict may modify the Projection.
>>> del sample['a']
>>> dict(prj)
{'c': 3}
"""
def __init__(self, keys: _Matchable, space: Mapping):
self._match = _dispatch(keys)
self._space = space
def __getitem__(self, key):
if not self._match(key):
raise KeyError(key)
return self._space[key]
def _keys_resolved(self):
return filter(self._match, self._space)
def __iter__(self):
return self._keys_resolved()
def __len__(self):
return len(tuple(self._keys_resolved()))
class Mask(Projection):
"""
The inverse of a :class:`Projection`, masking out keys.
>>> sample = {'a': 1, 'b': 2, 'c': 3}
>>> msk = Mask(['a', 'c', 'd'], sample)
>>> dict(msk)
{'b': 2}
"""
def __init__(self, *args, **kwargs):
super().__init__(*args, **kwargs)
# self._match = compose(operator.not_, self._match)
self._match = lambda key, orig=self._match: not orig(key)
def dict_map(function, dictionary):
"""
Return a new dict with function applied to values of dictionary.
>>> dict_map(lambda x: x+1, dict(a=1, b=2))
{'a': 2, 'b': 3}
"""
return dict((key, function(value)) for key, value in dictionary.items())
class RangeMap(Dict[_RangeMapKT, _VT]):
"""
A dictionary-like object that uses the keys as bounds for a range.
Inclusion of the value for that range is determined by the
key_match_comparator, which defaults to less-than-or-equal.
A value is returned for a key if it is the first key that matches in
the sorted list of keys.
One may supply keyword parameters to be passed to the sort function used
to sort keys (i.e. key, reverse) as sort_params.
Create a map that maps 1-3 -> 'a', 4-6 -> 'b'
>>> r = RangeMap({3: 'a', 6: 'b'}) # boy, that was easy
>>> r[1], r[2], r[3], r[4], r[5], r[6]
('a', 'a', 'a', 'b', 'b', 'b')
Even float values should work so long as the comparison operator
supports it.
>>> r[4.5]
'b'
Notice that the way rangemap is defined, it must be open-ended
on one side.
>>> r[0]
'a'
>>> r[-1]
'a'
One can close the open-end of the RangeMap by using undefined_value
>>> r = RangeMap({0: RangeMap.undefined_value, 3: 'a', 6: 'b'})
>>> r[0]
Traceback (most recent call last):
...
KeyError: 0
One can get the first or last elements in the range by using RangeMap.Item
>>> last_item = RangeMap.Item(-1)
>>> r[last_item]
'b'
.last_item is a shortcut for Item(-1)
>>> r[RangeMap.last_item]
'b'
Sometimes it's useful to find the bounds for a RangeMap
>>> r.bounds()
(0, 6)
RangeMap supports .get(key, default)
>>> r.get(0, 'not found')
'not found'
>>> r.get(7, 'not found')
'not found'
One often wishes to define the ranges by their left-most values,
which requires use of sort params and a key_match_comparator.
>>> r = RangeMap({1: 'a', 4: 'b'},
... sort_params=dict(reverse=True),
... key_match_comparator=operator.ge)
>>> r[1], r[2], r[3], r[4], r[5], r[6]
('a', 'a', 'a', 'b', 'b', 'b')
That wasn't nearly as easy as before, so an alternate constructor
is provided:
>>> r = RangeMap.left({1: 'a', 4: 'b', 7: RangeMap.undefined_value})
>>> r[1], r[2], r[3], r[4], r[5], r[6]
('a', 'a', 'a', 'b', 'b', 'b')
"""
def __init__(
self,
source: (
SupportsKeysAndGetItem[_RangeMapKT, _VT] | Iterable[tuple[_RangeMapKT, _VT]]
),
sort_params: Mapping[str, Any] = {},
key_match_comparator: Callable[[_RangeMapKT, _RangeMapKT], bool] = operator.le,
):
dict.__init__(self, source)
self.sort_params = sort_params
self.match = key_match_comparator
@classmethod
def left(
cls,
source: (
SupportsKeysAndGetItem[_RangeMapKT, _VT] | Iterable[tuple[_RangeMapKT, _VT]]
),
) -> Self:
return cls(
source, sort_params=dict(reverse=True), key_match_comparator=operator.ge
)
def __getitem__(self, item: _RangeMapKT) -> _VT:
sorted_keys = sorted(self.keys(), **self.sort_params)
if isinstance(item, RangeMap.Item):
result = self.__getitem__(sorted_keys[item])
else:
key = self._find_first_match_(sorted_keys, item)
result = dict.__getitem__(self, key)
if result is RangeMap.undefined_value:
raise KeyError(key)
return result
@overload # type: ignore[override] # Signature simplified over dict and Mapping
def get(self, key: _RangeMapKT, default: _T) -> _VT | _T: ...
@overload
def get(self, key: _RangeMapKT, default: None = None) -> _VT | None: ...
def get(self, key: _RangeMapKT, default: _T | None = None) -> _VT | _T | None:
"""
Return the value for key if key is in the dictionary, else default.
If default is not given, it defaults to None, so that this method
never raises a KeyError.
"""
try:
return self[key]
except KeyError:
return default
def _find_first_match_(
self, keys: Iterable[_RangeMapKT], item: _RangeMapKT
) -> _RangeMapKT:
is_match = functools.partial(self.match, item)
matches = filter(is_match, keys)
try:
return next(matches)
except StopIteration:
raise KeyError(item) from None
def bounds(self) -> tuple[_RangeMapKT, _RangeMapKT]:
sorted_keys = sorted(self.keys(), **self.sort_params)
return (sorted_keys[RangeMap.first_item], sorted_keys[RangeMap.last_item])
# some special values for the RangeMap
undefined_value = type('RangeValueUndefined', (), {})()
class Item(int):
"""RangeMap Item"""
first_item = Item(0)
last_item = Item(-1)
def __identity(x):
return x
def sorted_items(d, key=__identity, reverse=False):
"""
Return the items of the dictionary sorted by the keys.
>>> sample = dict(foo=20, bar=42, baz=10)
>>> tuple(sorted_items(sample))
(('bar', 42), ('baz', 10), ('foo', 20))
>>> reverse_string = lambda s: ''.join(reversed(s))
>>> tuple(sorted_items(sample, key=reverse_string))
(('foo', 20), ('bar', 42), ('baz', 10))
>>> tuple(sorted_items(sample, reverse=True))
(('foo', 20), ('baz', 10), ('bar', 42))
"""
# wrap the key func so it operates on the first element of each item
def pairkey_key(item):
return key(item[0])
return sorted(d.items(), key=pairkey_key, reverse=reverse)
class KeyTransformingDict(dict):
"""
A dict subclass that transforms the keys before they're used.
Subclasses may override the default transform_key to customize behavior.
"""
@staticmethod
def transform_key(key): # pragma: nocover
return key
def __init__(self, *args, **kargs):
super().__init__()
# build a dictionary using the default constructs
d = dict(*args, **kargs)
# build this dictionary using transformed keys.
for item in d.items():
self.__setitem__(*item)
def __setitem__(self, key, val):
key = self.transform_key(key)
super().__setitem__(key, val)
def __getitem__(self, key):
key = self.transform_key(key)
return super().__getitem__(key)
def __contains__(self, key):
key = self.transform_key(key)
return super().__contains__(key)
def __delitem__(self, key):
key = self.transform_key(key)
return super().__delitem__(key)
def get(self, key, *args, **kwargs):
key = self.transform_key(key)
return super().get(key, *args, **kwargs)
def setdefault(self, key, *args, **kwargs):
key = self.transform_key(key)
return super().setdefault(key, *args, **kwargs)
def pop(self, key, *args, **kwargs):
key = self.transform_key(key)
return super().pop(key, *args, **kwargs)
def matching_key_for(self, key):
"""
Given a key, return the actual key stored in self that matches.
Raise KeyError if the key isn't found.
"""
try:
return next(e_key for e_key in self.keys() if e_key == key)
except StopIteration as err:
raise KeyError(key) from err
class FoldedCaseKeyedDict(KeyTransformingDict):
"""
A case-insensitive dictionary (keys are compared as insensitive
if they are strings).
>>> d = FoldedCaseKeyedDict()
>>> d['heLlo'] = 'world'
>>> list(d.keys()) == ['heLlo']
True
>>> list(d.values()) == ['world']
True
>>> d['hello'] == 'world'
True
>>> 'hello' in d
True
>>> 'HELLO' in d
True
>>> print(repr(FoldedCaseKeyedDict({'heLlo': 'world'})))
{'heLlo': 'world'}
>>> d = FoldedCaseKeyedDict({'heLlo': 'world'})
>>> print(d['hello'])
world
>>> print(d['Hello'])
world
>>> list(d.keys())
['heLlo']
>>> d = FoldedCaseKeyedDict({'heLlo': 'world', 'Hello': 'world'})
>>> list(d.values())
['world']
>>> key, = d.keys()
>>> key in ['heLlo', 'Hello']
True
>>> del d['HELLO']
>>> d
{}
get should work
>>> d['Sumthin'] = 'else'
>>> d.get('SUMTHIN')
'else'
>>> d.get('OTHER', 'thing')
'thing'
>>> del d['sumthin']
setdefault should also work
>>> d['This'] = 'that'
>>> print(d.setdefault('this', 'other'))
that
>>> len(d)
1
>>> print(d['this'])
that
>>> print(d.setdefault('That', 'other'))
other
>>> print(d['THAT'])
other
Make it pop!
>>> print(d.pop('THAT'))
other
To retrieve the key in its originally-supplied form, use matching_key_for
>>> print(d.matching_key_for('this'))
This
>>> d.matching_key_for('missing')
Traceback (most recent call last):
...
KeyError: 'missing'
"""
@staticmethod
def transform_key(key):
return jaraco.text.FoldedCase(key)
class DictAdapter:
"""
Provide a getitem interface for attributes of an object.
Let's say you want to get at the string.lowercase property in a formatted
string. It's easy with DictAdapter.
>>> import string
>>> print("lowercase is %(ascii_lowercase)s" % DictAdapter(string))
lowercase is abcdefghijklmnopqrstuvwxyz
"""
def __init__(self, wrapped_ob):
self.object = wrapped_ob
def __getitem__(self, name):
return getattr(self.object, name)
class ItemsAsAttributes:
"""
Mix-in class to enable a mapping object to provide items as
attributes.
>>> C = type('C', (dict, ItemsAsAttributes), dict())
>>> i = C()
>>> i['foo'] = 'bar'
>>> i.foo
'bar'
Natural attribute access takes precedence
>>> i.foo = 'henry'
>>> i.foo
'henry'
But as you might expect, the mapping functionality is preserved.
>>> i['foo']
'bar'
A normal attribute error should be raised if an attribute is
requested that doesn't exist.
>>> i.missing
Traceback (most recent call last):
...
AttributeError: 'C' object has no attribute 'missing'
It also works on dicts that customize __getitem__
>>> missing_func = lambda self, key: 'missing item'
>>> C = type(
... 'C',
... (dict, ItemsAsAttributes),
... dict(__missing__ = missing_func),
... )
>>> i = C()
>>> i.missing
'missing item'
>>> i.foo
'missing item'
"""
def __getattr__(self, key):
try:
return getattr(super(), key)
except AttributeError as e:
# attempt to get the value from the mapping (return self[key])
# but be careful not to lose the original exception context.
noval = object()
def _safe_getitem(cont, key, missing_result):
try:
return cont[key]
except KeyError:
return missing_result
result = _safe_getitem(self, key, noval)
if result is not noval:
return result
# raise the original exception, but use the original class
# name, not 'super'.
(message,) = e.args
message = message.replace('super', self.__class__.__name__, 1)
e.args = (message,)
raise
def invert_map(map):
"""
Given a dictionary, return another dictionary with keys and values
switched. If any of the values resolve to the same key, raises
a ValueError.
>>> numbers = dict(a=1, b=2, c=3)
>>> letters = invert_map(numbers)
>>> letters[1]
'a'
>>> numbers['d'] = 3
>>> invert_map(numbers)
Traceback (most recent call last):
...
ValueError: Key conflict in inverted mapping
"""
res = dict((v, k) for k, v in map.items())
if not len(res) == len(map):
raise ValueError('Key conflict in inverted mapping')
return res
class IdentityOverrideMap(dict):
"""
A dictionary that by default maps each key to itself, but otherwise
acts like a normal dictionary.
>>> d = IdentityOverrideMap()
>>> d[42]
42
>>> d['speed'] = 'speedo'
>>> print(d['speed'])
speedo
"""
def __missing__(self, key):
return key
class DictStack(list, collections.abc.MutableMapping):
"""
A stack of dictionaries that behaves as a view on those dictionaries,
giving preference to the last.
>>> stack = DictStack([dict(a=1, c=2), dict(b=2, a=2)])
>>> stack['a']
2
>>> stack['b']
2
>>> stack['c']
2
>>> len(stack)
3
>>> stack.push(dict(a=3))
>>> stack['a']
3
>>> stack['a'] = 4
>>> set(stack.keys()) == set(['a', 'b', 'c'])
True
>>> set(stack.items()) == set([('a', 4), ('b', 2), ('c', 2)])
True
>>> dict(**stack) == dict(stack) == dict(a=4, c=2, b=2)
True
>>> d = stack.pop()
>>> stack['a']
2
>>> d = stack.pop()
>>> stack['a']
1
>>> stack.get('b', None)
>>> 'c' in stack
True
>>> del stack['c']
>>> dict(stack)
{'a': 1}
"""
def __iter__(self):
dicts = list.__iter__(self)
return iter(set(itertools.chain.from_iterable(c.keys() for c in dicts)))
def __getitem__(self, key):
for scope in reversed(tuple(list.__iter__(self))):
if key in scope:
return scope[key]
raise KeyError(key)
push = list.append
def __contains__(self, other):
return collections.abc.Mapping.__contains__(self, other)
def __len__(self):
return len(list(iter(self)))
def __setitem__(self, key, item):
last = list.__getitem__(self, -1)
return last.__setitem__(key, item)
def __delitem__(self, key):
last = list.__getitem__(self, -1)
return last.__delitem__(key)
# workaround for mypy confusion
def pop(self, *args, **kwargs):
return list.pop(self, *args, **kwargs)
class BijectiveMap(dict):
"""
A Bijective Map (two-way mapping).
Implemented as a simple dictionary of 2x the size, mapping values back
to keys.
Note, this implementation may be incomplete. If there's not a test for
your use case below, it's likely to fail, so please test and send pull
requests or patches for additional functionality needed.
>>> m = BijectiveMap()
>>> m['a'] = 'b'
>>> m == {'a': 'b', 'b': 'a'}
True
>>> print(m['b'])
a
>>> m['c'] = 'd'
>>> len(m)
2
Some weird things happen if you map an item to itself or overwrite a
single key of a pair, so it's disallowed.
>>> m['e'] = 'e'
Traceback (most recent call last):
ValueError: Key cannot map to itself
>>> m['d'] = 'e'
Traceback (most recent call last):
ValueError: Key/Value pairs may not overlap
>>> m['e'] = 'd'
Traceback (most recent call last):
ValueError: Key/Value pairs may not overlap
>>> print(m.pop('d'))
c
>>> 'c' in m
False
>>> m = BijectiveMap(dict(a='b'))
>>> len(m)
1
>>> print(m['b'])
a
>>> m = BijectiveMap()
>>> m.update(a='b')
>>> m['b']
'a'
>>> del m['b']
>>> len(m)
0
>>> 'a' in m
False
"""
def __init__(self, *args, **kwargs):
super().__init__()
self.update(*args, **kwargs)
def __setitem__(self, item, value):
if item == value:
raise ValueError("Key cannot map to itself")
overlap = (
item in self
and self[item] != value
or value in self
and self[value] != item
)
if overlap:
raise ValueError("Key/Value pairs may not overlap")
super().__setitem__(item, value)
super().__setitem__(value, item)
def __delitem__(self, item):
self.pop(item)
def __len__(self):
return super().__len__() // 2
def pop(self, key, *args, **kwargs):
mirror = self[key]
super().__delitem__(mirror)
return super().pop(key, *args, **kwargs)
def update(self, *args, **kwargs):
# build a dictionary using the default constructs
d = dict(*args, **kwargs)
# build this dictionary using transformed keys.
for item in d.items():
self.__setitem__(*item)
class FrozenDict(collections.abc.Mapping, collections.abc.Hashable):
"""
An immutable mapping.
>>> a = FrozenDict(a=1, b=2)
>>> b = FrozenDict(a=1, b=2)
>>> a == b
True
>>> a == dict(a=1, b=2)
True
>>> dict(a=1, b=2) == a
True
>>> 'a' in a
True
>>> type(hash(a)) is type(0)
True
>>> set(iter(a)) == {'a', 'b'}
True
>>> len(a)
2
>>> a['a'] == a.get('a') == 1
True
>>> a['c'] = 3
Traceback (most recent call last):
...
TypeError: 'FrozenDict' object does not support item assignment
>>> a.update(y=3)
Traceback (most recent call last):
...
AttributeError: 'FrozenDict' object has no attribute 'update'
Copies should compare equal
>>> copy.copy(a) == a
True
Copies should be the same type
>>> isinstance(copy.copy(a), FrozenDict)
True
FrozenDict supplies .copy(), even though
collections.abc.Mapping doesn't demand it.
>>> a.copy() == a
True
>>> a.copy() is not a
True
"""
__slots__ = ['__data']
def __new__(cls, *args, **kwargs):
self = super().__new__(cls)
self.__data = dict(*args, **kwargs)
return self
# Container
def __contains__(self, key):
return key in self.__data
# Hashable
def __hash__(self):
return hash(tuple(sorted(self.__data.items())))
# Mapping
def __iter__(self):
return iter(self.__data)
def __len__(self):
return len(self.__data)
def __getitem__(self, key):
return self.__data[key]
# override get for efficiency provided by dict
def get(self, *args, **kwargs):
return self.__data.get(*args, **kwargs)
# override eq to recognize underlying implementation
def __eq__(self, other):
if isinstance(other, FrozenDict):
other = other.__data
return self.__data.__eq__(other)
def copy(self):
"Return a shallow copy of self"
return copy.copy(self)
class Enumeration(ItemsAsAttributes, BijectiveMap):
"""
A convenient way to provide enumerated values
>>> e = Enumeration('a b c')
>>> e['a']
0
>>> e.a
0
>>> e[1]
'b'
>>> set(e.names) == set('abc')
True
>>> set(e.codes) == set(range(3))
True
>>> e.get('d') is None
True
Codes need not start with 0
>>> e = Enumeration('a b c', range(1, 4))
>>> e['a']
1
>>> e[3]
'c'
"""
def __init__(self, names, codes=None):
if isinstance(names, str):
names = names.split()
if codes is None:
codes = itertools.count()
super().__init__(zip(names, codes))
@property
def names(self):
return (key for key in self if isinstance(key, str))
@property
def codes(self):
return (self[name] for name in self.names)
class Everything:
"""
A collection "containing" every possible thing.
>>> 'foo' in Everything()
True
>>> import random
>>> random.randint(1, 999) in Everything()
True
>>> random.choice([None, 'foo', 42, ('a', 'b', 'c')]) in Everything()
True
"""
def __contains__(self, other):
return True
class InstrumentedDict(collections.UserDict):
"""
Instrument an existing dictionary with additional
functionality, but always reference and mutate
the original dictionary.
>>> orig = {'a': 1, 'b': 2}
>>> inst = InstrumentedDict(orig)
>>> inst['a']
1
>>> inst['c'] = 3
>>> orig['c']
3
>>> inst.keys() == orig.keys()
True
"""
def __init__(self, data):
super().__init__()
self.data = data
class Least:
"""
A value that is always lesser than any other
>>> least = Least()
>>> 3 < least
False
>>> 3 > least
True
>>> least < 3
True
>>> least <= 3
True
>>> least > 3
False
>>> 'x' > least
True
>>> None > least
True
"""
def __le__(self, other):
return True
__lt__ = __le__
def __ge__(self, other):
return False
__gt__ = __ge__
class Greatest:
"""
A value that is always greater than any other
>>> greatest = Greatest()
>>> 3 < greatest
True
>>> 3 > greatest
False
>>> greatest < 3
False
>>> greatest > 3
True
>>> greatest >= 3
True
>>> 'x' > greatest
False
>>> None > greatest
False
"""
def __ge__(self, other):
return True
__gt__ = __ge__
def __le__(self, other):
return False
__lt__ = __le__
def pop_all(items):
"""
Clear items in place and return a copy of items.
>>> items = [1, 2, 3]
>>> popped = pop_all(items)
>>> popped is items
False
>>> popped
[1, 2, 3]
>>> items
[]
"""
result, items[:] = items[:], []
return result
class FreezableDefaultDict(collections.defaultdict):
"""
Often it is desirable to prevent the mutation of
a default dict after its initial construction, such
as to prevent mutation during iteration.
>>> dd = FreezableDefaultDict(list)
>>> dd[0].append('1')
>>> dd.freeze()
>>> dd[1]
[]
>>> len(dd)
1
"""
def __missing__(self, key):
return getattr(self, '_frozen', super().__missing__)(key)
def freeze(self):
self._frozen = lambda key: self.default_factory()
class Accumulator:
def __init__(self, initial=0):
self.val = initial
def __call__(self, val):
self.val += val
return self.val
class WeightedLookup(RangeMap):
"""
Given parameters suitable for a dict representing keys
and a weighted proportion, return a RangeMap representing
spans of values proportial to the weights:
>>> even = WeightedLookup(a=1, b=1)
[0, 1) -> a
[1, 2) -> b
>>> lk = WeightedLookup(a=1, b=2)
[0, 1) -> a
[1, 3) -> b
>>> lk[.5]
'a'
>>> lk[1.5]
'b'
Adds ``.random()`` to select a random weighted value:
>>> lk.random() in ['a', 'b']
True
>>> choices = [lk.random() for x in range(1000)]
Statistically speaking, choices should be .5 a:b
>>> ratio = choices.count('a') / choices.count('b')
>>> .4 < ratio < .6
True
"""
def __init__(self, *args, **kwargs):
raw = dict(*args, **kwargs)
# allocate keys by weight
indexes = map(Accumulator(), raw.values())
super().__init__(zip(indexes, raw.keys()), key_match_comparator=operator.lt)
def random(self):
lower, upper = self.bounds()
selector = random.random() * upper
return self[selector]
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