"""
Functions for working with dictionaries.
The :class:`UDict` is a subclass of :class:`dict` with quality of life
improvements. It contains methods for n-ary key-wise set operations as well as
support for the binary operators in addition to other methods for mapping,
inversion, subdicts, and peeking. It can be accessed via the alias
``ubelt.udict``.
The :class:`SetDict` only contains the key-wise set extensions to dict. It can
be accessed via the alias ``ubelt.sdict``.
The :func:`dict_hist` function counts the number of discrete occurrences of hashable
items. Similarly :func:`find_duplicates` looks for indices of items that occur more
than `k=1` times.
The :func:`map_keys` and :func:`map_values` functions are useful for
transforming the keys and values of a dictionary with less syntax than a dict
comprehension.
The :func:`dict_union`, :func:`dict_isect`, and :func:`dict_diff` functions are
similar to the set equivalents.
The :func:`dzip` function zips two iterables and packs them into a dictionary
where the first iterable is used to generate keys and the second generates
values.
The :func:`group_items` function takes two lists and returns a dict mapping
values in the second list to all items in corresponding locations in the first
list.
The :func:`invert_dict` function swaps keys and values. See the function docs
for details on dealing with unique and non-unique values.
The :func:`ddict` and :func:`odict` functions are alias for the commonly used
:func:`collections.defaultdict` and :func:`collections.OrderedDict` classes.
Related Work:
* Note that Python does support set operations on dictionary **views** [DictView]_ [Pep3106]_, but these methods can be inflexible and often leave you only with keys (and no dictionary subset operation), whereas the ubelt definition of these operations is more straightforward.
* There are several recipes for dictionaries that support set operations [SetDictRecipe1]_ [SetDictRecipe2]_.
* The :moduel:`dictmap` package contains a function similar to :func:`map_values` [GHDictMap]_.
* The :module:`dictdiffer` package contains tools for nested difference operations [PypiDictDiffer]_.
* There are lots of other python dictionary utility libraries [PyPIAddict]_.
References:
.. [PyPIAddict] https://github.com/mewwts/addict
.. [SetDictRecipe1] https://gist.github.com/rossmacarthur/38fa948b175abb512e12c516cc3b936d
.. [SetDictRecipe2] https://code.activestate.com/recipes/577471-setdict/
.. [PypiDictDiffer] https://pypi.org/project/dictdiffer/
.. [DictView] https://docs.python.org/3.0/library/stdtypes.html#dictionary-view-objects
.. [Pep3106] https://peps.python.org/pep-3106/
.. [GHDictMap] https://github.com/ulisesojeda/dictionary_map
"""
import sys
import operator as op
import itertools as it
from collections import OrderedDict
from collections import defaultdict
# from ubelt import util_const
from ubelt import util_list
from ubelt.util_const import NoParam
__all__ = [
'AutoDict',
'AutoOrderedDict',
'dzip',
'ddict',
'dict_hist',
'dict_subset',
'dict_union',
'dict_isect',
'dict_diff',
'find_duplicates',
'group_items',
'invert_dict',
'map_keys',
'map_vals',
'map_values',
'sorted_keys',
'sorted_vals',
'sorted_values',
'odict',
'named_product',
'varied_values',
'SetDict',
'UDict',
'sdict',
'udict',
]
# Expose for convenience
odict = OrderedDict
ddict = defaultdict
# Use an ordered dictionary in < 3.7 as the base
if sys.version_info[0:2] <= (3, 6): # nocover
DictBase = OrderedDict
else: # nocover
DictBase = dict
[docs]def dzip(items1, items2, cls=dict):
"""
Zips elementwise pairs between items1 and items2 into a dictionary.
Values from items2 can be broadcast onto items1.
Args:
items1 (Iterable[KT]): full sequence
items2 (Iterable[VT]):
can either be a sequence of one item or a sequence of equal length
to ``items1``
cls (Type[dict], default=dict): dictionary type to use.
Returns:
Dict[KT, VT]: similar to ``dict(zip(items1, items2))``.
Example:
>>> import ubelt as ub
>>> assert ub.dzip([1, 2, 3], [4]) == {1: 4, 2: 4, 3: 4}
>>> assert ub.dzip([1, 2, 3], [4, 4, 4]) == {1: 4, 2: 4, 3: 4}
>>> assert ub.dzip([], [4]) == {}
"""
try:
len(items1)
except TypeError:
items1 = list(items1)
try:
len(items2)
except TypeError:
items2 = list(items2)
if len(items1) == 0 and len(items2) == 1:
# Corner case:
# allow the first list to be empty and the second list to broadcast a
# value. This means that the equality check won't work for the case
# where items1 and items2 are supposed to correspond, but the length of
# items2 is 1.
items2 = []
if len(items2) == 1 and len(items1) > 1:
items2 = items2 * len(items1)
if len(items1) != len(items2):
raise ValueError('out of alignment len(items1)=%r, len(items2)=%r' % (
len(items1), len(items2)))
return cls(zip(items1, items2))
[docs]def group_items(items, key):
"""
Groups a list of items by group id.
Args:
items (Iterable[VT]): a list of items to group
key (Iterable[KT] | Callable[[VT], KT]):
either a corresponding list of group-ids for each item or
a function used to map each item to a group-id.
Returns:
dict[KT, List[VT]]:
a mapping from each group id to the list of corresponding items
Example:
>>> import ubelt as ub
>>> items = ['ham', 'jam', 'spam', 'eggs', 'cheese', 'banana']
>>> groupids = ['protein', 'fruit', 'protein', 'protein', 'dairy', 'fruit']
>>> id_to_items = ub.group_items(items, groupids)
>>> print(ub.repr2(id_to_items, nl=0))
{'dairy': ['cheese'], 'fruit': ['jam', 'banana'], 'protein': ['ham', 'spam', 'eggs']}
"""
if callable(key):
keyfunc = key
pair_list = ((keyfunc(item), item) for item in items)
else:
pair_list = zip(key, items)
# Initialize a dict of lists
id_to_items = defaultdict(list)
# Insert each item into the correct group
for key, item in pair_list:
id_to_items[key].append(item)
return id_to_items
[docs]def dict_hist(items, weights=None, ordered=False, labels=None):
"""
Builds a histogram of items, counting the number of time each item appears
in the input.
Args:
items (Iterable[T]):
hashable items (usually containing duplicates)
weights (Iterable[float], default=None):
Corresponding weights for each item.
ordered (bool, default=False):
If True the result is ordered by frequency.
labels (Iterable[T], default=None):
Expected labels. Allows this function to pre-initialize the
histogram. If specified the frequency of each label is initialized
to zero and ``items`` can only contain items specified in labels.
Returns:
dict[T, int] :
dictionary where the keys are unique elements from ``items``, and
the values are the number of times the item appears in ``items``.
Example:
>>> import ubelt as ub
>>> items = [1, 2, 39, 900, 1232, 900, 1232, 2, 2, 2, 900]
>>> hist = ub.dict_hist(items)
>>> print(ub.repr2(hist, nl=0))
{1: 1, 2: 4, 39: 1, 900: 3, 1232: 2}
Example:
>>> import ubelt as ub
>>> items = [1, 2, 39, 900, 1232, 900, 1232, 2, 2, 2, 900]
>>> hist1 = ub.dict_hist(items)
>>> hist2 = ub.dict_hist(items, ordered=True)
>>> try:
>>> hist3 = ub.dict_hist(items, labels=[])
>>> except KeyError:
>>> pass
>>> else:
>>> raise AssertionError('expected key error')
>>> weights = [1, 1, 1, 0, 0, 0, 0, 1, 1, 1, 1]
>>> hist4 = ub.dict_hist(items, weights=weights)
>>> print(ub.repr2(hist1, nl=0))
{1: 1, 2: 4, 39: 1, 900: 3, 1232: 2}
>>> print(ub.repr2(hist4, nl=0))
{1: 1, 2: 4, 39: 1, 900: 1, 1232: 0}
"""
if labels is None:
hist_ = defaultdict(lambda: 0)
else:
hist_ = {k: 0 for k in labels}
if weights is None:
weights = it.repeat(1)
# Accumulate frequency
for item, weight in zip(items, weights):
hist_[item] += weight
if ordered:
# Order by value
getval = op.itemgetter(1)
hist = OrderedDict([
(key, value)
for (key, value) in sorted(hist_.items(), key=getval)
])
else:
# Cast to a normal dictionary
hist = dict(hist_)
return hist
[docs]def find_duplicates(items, k=2, key=None):
"""
Find all duplicate items in a list.
Search for all items that appear more than ``k`` times and return a mapping
from each (k)-duplicate item to the positions it appeared in.
Args:
items (Iterable[T]):
hashable items possibly containing duplicates
k (int, default=2):
only return items that appear at least ``k`` times.
key (Callable[[T], Any], default=None):
Returns indices where `key(items[i])` maps to a particular value at
least k times.
Returns:
dict[T, List[int]] :
maps each duplicate item to the indices at which it appears
Notes:
Similar to :func:`more_itertools.duplicates_everseen`,
:func:`more_itertools.duplicates_justseen`.
Example:
>>> import ubelt as ub
>>> items = [0, 0, 1, 2, 3, 3, 0, 12, 2, 9]
>>> duplicates = ub.find_duplicates(items)
>>> # Duplicates are a mapping from each item that occurs 2 or more
>>> # times to the indices at which they occur.
>>> assert duplicates == {0: [0, 1, 6], 2: [3, 8], 3: [4, 5]}
>>> # You can set k=3 if you want to don't mind duplicates but you
>>> # want to find triplicates or quadruplets etc.
>>> assert ub.find_duplicates(items, k=3) == {0: [0, 1, 6]}
Example:
>>> import ubelt as ub
>>> items = [0, 0, 1, 2, 3, 3, 0, 12, 2, 9]
>>> # note: k can less then 2
>>> duplicates = ub.find_duplicates(items, k=0)
>>> print(ub.repr2(duplicates, nl=0))
{0: [0, 1, 6], 1: [2], 2: [3, 8], 3: [4, 5], 9: [9], 12: [7]}
Example:
>>> import ubelt as ub
>>> items = [10, 11, 12, 13, 14, 15, 16]
>>> duplicates = ub.find_duplicates(items, key=lambda x: x // 2)
>>> print(ub.repr2(duplicates, nl=0))
{5: [0, 1], 6: [2, 3], 7: [4, 5]}
"""
# Build mapping from items to the indices at which they appear
duplicates = defaultdict(list)
if key is None:
for count, item in enumerate(items):
duplicates[item].append(count)
else:
for count, item in enumerate(items):
duplicates[key(item)].append(count)
# remove items seen fewer than k times.
for key in list(duplicates.keys()):
if len(duplicates[key]) < k:
del duplicates[key]
duplicates = dict(duplicates)
return duplicates
[docs]def dict_subset(dict_, keys, default=NoParam, cls=OrderedDict):
"""
Get a subset of a dictionary
Args:
dict_ (Dict[KT, VT]): superset dictionary
keys (Iterable[KT]): keys to take from ``dict_``
default (Optional[object] | NoParamType):
if specified uses default if keys are missing.
cls (Type[Dict], default=OrderedDict): type of the returned dictionary.
Returns:
Dict[KT, VT]: subset dictionary
SeeAlso:
:func:`dict_isect` - similar functionality, but ignores missing keys
Example:
>>> import ubelt as ub
>>> dict_ = {'K': 3, 'dcvs_clip_max': 0.2, 'p': 0.1}
>>> keys = ['K', 'dcvs_clip_max']
>>> subdict_ = ub.dict_subset(dict_, keys)
>>> print(ub.repr2(subdict_, nl=0))
{'K': 3, 'dcvs_clip_max': 0.2}
"""
keys = list(keys)
items = util_list.take(dict_, keys, default)
subdict_ = cls(list(zip(keys, items)))
return subdict_
[docs]def dict_union(*args):
"""
Dictionary set extension for ``set.union``
Combines items with from multiple dictionaries. For items with
intersecting keys, dictionaries towards the end of the sequence are given
precedence.
Args:
*args (List[Dict]) : A sequence of dictionaries.
Values are taken from the last
Returns:
Dict | OrderedDict :
OrderedDict if the first argument is an OrderedDict, otherwise dict
Notes:
In Python 3.8+, the bitwise or operator "|" operator performs a similar
operation, but as of 2022-06-01 there is still no public method for
dictionary union (or any other dictionary set operator).
References:
https://stackoverflow.com/questions/38987/merge-two-dict
SeeAlso:
:func:`collections.ChainMap` - a standard python builtin data structure
that provides a view that treats multiple dicts as a single dict.
`<https://docs.python.org/3/library/collections.html#chainmap-objects>`_
Example:
>>> import ubelt as ub
>>> result = ub.dict_union({'a': 1, 'b': 1}, {'b': 2, 'c': 2})
>>> assert result == {'a': 1, 'b': 2, 'c': 2}
>>> ub.dict_union(
>>> ub.odict([('a', 1), ('b', 2)]),
>>> ub.odict([('c', 3), ('d', 4)]))
OrderedDict([('a', 1), ('b', 2), ('c', 3), ('d', 4)])
>>> ub.dict_union()
{}
"""
if not args:
return {}
else:
dictclass = OrderedDict if isinstance(args[0], OrderedDict) else dict
return dictclass(it.chain.from_iterable(d.items() for d in args))
[docs]def dict_diff(*args):
"""
Dictionary set extension for :func:`set.difference`
Constructs a dictionary that contains any of the keys in the first arg,
which are not in any of the following args.
Args:
*args (List[Dict[KT, VT] | Iterable[KT]]) :
A sequence of dictionaries (or sets of keys). The first argument
should always be a dictionary, but the subsequent arguments can
just be sets of keys.
Returns:
Dict[KT, VT] | OrderedDict[KT, VT] :
OrderedDict if the first argument is an OrderedDict, otherwise dict
TODO:
- [ ] Add inplace keyword argument, which modifies the first dictionary
inplace.
Example:
>>> import ubelt as ub
>>> ub.dict_diff({'a': 1, 'b': 1}, {'a'}, {'c'})
{'b': 1}
>>> ub.dict_diff(odict([('a', 1), ('b', 2)]), odict([('c', 3)]))
OrderedDict([('a', 1), ('b', 2)])
>>> ub.dict_diff()
{}
>>> ub.dict_diff({'a': 1, 'b': 2}, {'c'})
"""
if not args:
return {}
else:
first_dict = args[0]
dictclass = OrderedDict if isinstance(first_dict, OrderedDict) else dict
# remove_keys = set.union(*map(set, args[1:]))
# new = dictclass((k, v) for k, v in first_dict.items() if k not in remove_keys)
remove_keys = set.union(*map(set, args[1:]))
new = dictclass((k, first_dict[k]) for k in first_dict.keys() if k not in remove_keys)
return new
[docs]def dict_isect(*args):
"""
Dictionary set extension for :func:`set.intersection`
Constructs a dictionary that contains keys common between all inputs.
The returned values will only belong to the first dictionary.
Args:
*args (List[Dict[KT, VT] | Iterable[KT]]) :
A sequence of dictionaries (or sets of keys). The first argument
should always be a dictionary, but the subsequent arguments can
just be sets of keys.
Returns:
Dict[KT, VT] | OrderedDict[KT, VT] :
OrderedDict if the first argument is an OrderedDict, otherwise dict
Note:
This function can be used as an alternative to :func:`dict_subset`
where any key not in the dictionary is ignored. See the following
example:
>>> import ubelt as ub
>>> # xdoctest: +IGNORE_WANT
>>> ub.dict_isect({'a': 1, 'b': 2, 'c': 3}, ['a', 'c', 'd'])
{'a': 1, 'c': 3}
Example:
>>> import ubelt as ub
>>> ub.dict_isect({'a': 1, 'b': 1}, {'b': 2, 'c': 2})
{'b': 1}
>>> ub.dict_isect(odict([('a', 1), ('b', 2)]), odict([('c', 3)]))
OrderedDict()
>>> ub.dict_isect()
{}
"""
if not args:
return {}
else:
dictclass = OrderedDict if isinstance(args[0], OrderedDict) else dict
common_keys = set.intersection(*map(set, args))
first_dict = args[0]
return dictclass((k, first_dict[k]) for k in first_dict
if k in common_keys)
[docs]def map_values(func, dict_, cls=None):
"""
Apply a function to every value in a dictionary.
Creates a new dictionary with the same keys and modified values.
Args:
func (Callable[[VT], T] | Mapping[VT, T]): a function or indexable object
dict_ (Dict[KT, VT]): a dictionary
cls (type | None): specifies the dict subclassof the result.
if unspecified will be dict or OrderedDict. This behavior may
change.
Returns:
Dict[KT, T]: transformed dictionary
Notes:
Similar to :module:`dictmap.dict_map`
Example:
>>> import ubelt as ub
>>> dict_ = {'a': [1, 2, 3], 'b': []}
>>> newdict = ub.map_values(len, dict_)
>>> assert newdict == {'a': 3, 'b': 0}
Example:
>>> # Can also use an indexable as ``func``
>>> import ubelt as ub
>>> dict_ = {'a': 0, 'b': 1}
>>> func = [42, 21]
>>> newdict = ub.map_values(func, dict_)
>>> assert newdict == {'a': 42, 'b': 21}
>>> print(newdict)
"""
if not hasattr(func, '__call__'):
func = func.__getitem__
keyval_list = [(key, func(val)) for key, val in dict_.items()]
if cls is None:
cls = OrderedDict if isinstance(dict_, OrderedDict) else dict
newdict = cls(keyval_list)
return newdict
map_vals = map_values # backwards compatibility
[docs]def map_keys(func, dict_, cls=None):
"""
Apply a function to every key in a dictionary.
Creates a new dictionary with the same values and modified keys. An error
is raised if the new keys are not unique.
Args:
func (Callable[[KT], T] | Mapping[KT, T]): a function or indexable object
dict_ (Dict[KT, VT]): a dictionary
cls (type | None): specifies the dict subclassof the result.
if unspecified will be dict or OrderedDict. This behavior may
change.
Returns:
Dict[T, VT]: transformed dictionary
Raises:
Exception : if multiple keys map to the same value
Example:
>>> import ubelt as ub
>>> dict_ = {'a': [1, 2, 3], 'b': []}
>>> func = ord
>>> newdict = ub.map_keys(func, dict_)
>>> print(newdict)
>>> assert newdict == {97: [1, 2, 3], 98: []}
>>> dict_ = {0: [1, 2, 3], 1: []}
>>> func = ['a', 'b']
>>> newdict = ub.map_keys(func, dict_)
>>> print(newdict)
>>> assert newdict == {'a': [1, 2, 3], 'b': []}
"""
if not hasattr(func, '__call__'):
func = func.__getitem__
keyval_list = [(func(key), val) for key, val in dict_.items()]
if cls is None:
cls = OrderedDict if isinstance(dict_, OrderedDict) else dict
newdict = cls(keyval_list)
if len(newdict) != len(dict_):
raise Exception('multiple input keys mapped to the same output key')
return newdict
[docs]def sorted_values(dict_, key=None, reverse=False, cls=OrderedDict):
"""
Return an ordered dictionary sorted by its values
Args:
dict_ (Dict[KT, VT]):
dictionary to sort. The values must be of comparable types.
key (Callable[[VT], Any] | None):
If given as a callable, customizes the sorting by ordering using
transformed values.
reverse (bool, default=False):
if True returns in descending order
cls (type): specifies the dict return type
Returns:
OrderedDict[KT, VT]: new dictionary where the values are ordered
Example:
>>> import ubelt as ub
>>> dict_ = {'spam': 2.62, 'eggs': 1.20, 'jam': 2.92}
>>> newdict = sorted_values(dict_)
>>> print(ub.repr2(newdict, nl=0))
{'eggs': 1.2, 'spam': 2.62, 'jam': 2.92}
>>> newdict = sorted_values(dict_, reverse=True)
>>> print(ub.repr2(newdict, nl=0))
{'jam': 2.92, 'spam': 2.62, 'eggs': 1.2}
>>> newdict = sorted_values(dict_, key=lambda x: x % 1.6)
>>> print(ub.repr2(newdict, nl=0))
{'spam': 2.62, 'eggs': 1.2, 'jam': 2.92}
"""
if key is None:
newdict = OrderedDict(sorted(dict_.items(), key=lambda kv: kv[1],
reverse=reverse))
else:
newdict = OrderedDict(sorted(dict_.items(), key=lambda kv: key(kv[1]),
reverse=reverse))
return newdict
sorted_vals = sorted_values # backwards compatibility
[docs]def sorted_keys(dict_, key=None, reverse=False, cls=OrderedDict):
"""
Return an ordered dictionary sorted by its keys
Args:
dict_ (Dict[KT, VT]):
dictionary to sort. The keys must be of comparable types.
key (Callable[[KT], Any] | None):
If given as a callable, customizes the sorting by ordering using
transformed keys.
reverse (bool, default=False):
if True returns in descending order
cls (type): specifies the dict return type
Returns:
OrderedDict[KT, VT]: new dictionary where the keys are ordered
Example:
>>> import ubelt as ub
>>> dict_ = {'spam': 2.62, 'eggs': 1.20, 'jam': 2.92}
>>> newdict = sorted_keys(dict_)
>>> print(ub.repr2(newdict, nl=0))
{'eggs': 1.2, 'jam': 2.92, 'spam': 2.62}
>>> newdict = sorted_keys(dict_, reverse=True)
>>> print(ub.repr2(newdict, nl=0))
{'spam': 2.62, 'jam': 2.92, 'eggs': 1.2}
>>> newdict = sorted_keys(dict_, key=lambda x: sum(map(ord, x)))
>>> print(ub.repr2(newdict, nl=0))
{'jam': 2.92, 'eggs': 1.2, 'spam': 2.62}
"""
if key is None:
newdict = OrderedDict(sorted(dict_.items(), key=lambda kv: kv[0],
reverse=reverse))
else:
newdict = OrderedDict(sorted(dict_.items(), key=lambda kv: key(kv[0]),
reverse=reverse))
return newdict
[docs]def invert_dict(dict_, unique_vals=True, cls=None):
"""
Swaps the keys and values in a dictionary.
Args:
dict_ (Dict[KT, VT]): dictionary to invert
unique_vals (bool, default=True): if False, the values of the new
dictionary are sets of the original keys.
cls (type | None): specifies the dict subclassof the result.
if unspecified will be dict or OrderedDict. This behavior may
change.
Returns:
Dict[VT, KT] | Dict[VT, Set[KT]]:
the inverted dictionary
Note:
The must values be hashable.
If the original dictionary contains duplicate values, then only one of
the corresponding keys will be returned and the others will be
discarded. This can be prevented by setting ``unique_vals=False``,
causing the inverted keys to be returned in a set.
Example:
>>> import ubelt as ub
>>> dict_ = {'a': 1, 'b': 2}
>>> inverted = ub.invert_dict(dict_)
>>> assert inverted == {1: 'a', 2: 'b'}
Example:
>>> import ubelt as ub
>>> dict_ = ub.odict([(2, 'a'), (1, 'b'), (0, 'c'), (None, 'd')])
>>> inverted = ub.invert_dict(dict_)
>>> assert list(inverted.keys())[0] == 'a'
Example:
>>> import ubelt as ub
>>> dict_ = {'a': 1, 'b': 0, 'c': 0, 'd': 0, 'f': 2}
>>> inverted = ub.invert_dict(dict_, unique_vals=False)
>>> assert inverted == {0: {'b', 'c', 'd'}, 1: {'a'}, 2: {'f'}}
"""
if cls is None:
cls = OrderedDict if isinstance(dict_, OrderedDict) else dict
if unique_vals:
# Wonder what byte code is better here?
if cls is dict:
inverted = {val: key for key, val in dict_.items()}
else:
inverted = cls((val, key) for key, val in dict_.items())
else:
# Handle non-unique keys using groups
inverted = defaultdict(set)
for key, value in dict_.items():
inverted[value].add(key)
inverted = cls(inverted)
return inverted
[docs]def named_product(_=None, **basis):
"""
Generates the Cartesian product of the ``basis.values()``, where each
generated item labeled by ``basis.keys()``.
In other words, given a dictionary that maps each "axes" (i.e. some
variable) to its "basis" (i.e. the possible values that it can take),
generate all possible points in that grid (i.e. unique assignments of
variables to values).
Args:
_ (Dict[str, List[VT]] | None, default=None):
Use of this positional argument is not recommend. Instead specify
all arguments as keyword args.
If specified, this should be a dictionary is unioned with the
keyword args. This exists to support ordered dictionaries before
Python 3.6, and may eventually be removed.
basis (Dict[str, List[VT]]):
A dictionary where the keys correspond to "columns" and the values
are a list of possible values that "column" can take.
I.E. each key corresponds to an "axes", the values are the list of
possible values for that "axes".
Yields:
Dict[str, VT] :
a "row" in the "longform" data containing a point in the Cartesian
product.
Note:
This function is similar to :func:`itertools.product`, the only
difference is that the generated items are a dictionary that retains
the input keys instead of an tuple.
This function used to be called "basis_product", but "named_product"
might be more appropriate. This function exists in other places
([minstrel271_namedproduct]_, [pytb_namedproduct]_, and
[Hettinger_namedproduct]_).
References:
.. [minstrel271_namedproduct] https://gist.github.com/minstrel271/d51654af3fa4e6411267
.. [pytb_namedproduct] https://py-toolbox.readthedocs.io/en/latest/modules/itertools.html#
.. [Hettinger_namedproduct] https://twitter.com/raymondh/status/970380630822305792
Example:
>>> # An example use case is looping over all possible settings in a
>>> # configuration dictionary for a grid search over parameters.
>>> import ubelt as ub
>>> basis = {
>>> 'arg1': [1, 2, 3],
>>> 'arg2': ['A1', 'B1'],
>>> 'arg3': [9999, 'Z2'],
>>> 'arg4': ['always'],
>>> }
>>> import ubelt as ub
>>> # sort input data for older python versions
>>> basis = ub.odict(sorted(basis.items()))
>>> got = list(ub.named_product(basis))
>>> print(ub.repr2(got, nl=-1))
[
{'arg1': 1, 'arg2': 'A1', 'arg3': 9999, 'arg4': 'always'},
{'arg1': 1, 'arg2': 'A1', 'arg3': 'Z2', 'arg4': 'always'},
{'arg1': 1, 'arg2': 'B1', 'arg3': 9999, 'arg4': 'always'},
{'arg1': 1, 'arg2': 'B1', 'arg3': 'Z2', 'arg4': 'always'},
{'arg1': 2, 'arg2': 'A1', 'arg3': 9999, 'arg4': 'always'},
{'arg1': 2, 'arg2': 'A1', 'arg3': 'Z2', 'arg4': 'always'},
{'arg1': 2, 'arg2': 'B1', 'arg3': 9999, 'arg4': 'always'},
{'arg1': 2, 'arg2': 'B1', 'arg3': 'Z2', 'arg4': 'always'},
{'arg1': 3, 'arg2': 'A1', 'arg3': 9999, 'arg4': 'always'},
{'arg1': 3, 'arg2': 'A1', 'arg3': 'Z2', 'arg4': 'always'},
{'arg1': 3, 'arg2': 'B1', 'arg3': 9999, 'arg4': 'always'},
{'arg1': 3, 'arg2': 'B1', 'arg3': 'Z2', 'arg4': 'always'}
]
Example:
>>> import ubelt as ub
>>> list(ub.named_product(a=[1, 2, 3]))
[{'a': 1}, {'a': 2}, {'a': 3}]
>>> # xdoctest: +IGNORE_WANT
>>> list(ub.named_product(a=[1, 2, 3], b=[4, 5]))
[{'a': 1, 'b': 4},
{'a': 1, 'b': 5},
{'a': 2, 'b': 4},
{'a': 2, 'b': 5},
{'a': 3, 'b': 4},
{'a': 3, 'b': 5}]
"""
# Handle one positional argument.
if _ is not None:
_basis = _
_basis.update(basis)
basis = _basis
keys = list(basis.keys())
for vals in it.product(*basis.values()):
kw = dict(zip(keys, vals))
yield kw
[docs]def varied_values(longform, min_variations=0, default=NoParam):
"""
Given a list of dictionaries, find the values that differ between them.
Args:
longform (List[Dict[KT, VT]]):
This is longform data, as described in [SeabornLongform]_. It is a
list of dictionaries.
Each item in the list - or row - is a dictionary and can be thought
of as an observation. The keys in each dictionary are the columns.
The values of the dictionary must be hashable. Lists will be
converted into tuples.
min_variations (int, default=0):
"columns" with fewer than ``min_variations`` unique values are
removed from the result.
default (VT | NoParamType):
if specified, unspecified columns are given this value.
Defaults to NoParam.
Returns:
Dict[KT, List[VT]] :
a mapping from each "column" to the set of unique values it took
over each "row". If a column is not specified for each row, it is
assumed to take a `default` value, if it is specified.
Raises:
KeyError: If ``default`` is unspecified and all the rows
do not contain the same columns.
References:
.. [SeabornLongform] https://seaborn.pydata.org/tutorial/data_structure.html#long-form-data
Example:
>>> # An example use case is to determine what values of a
>>> # configuration dictionary were tried in a random search
>>> # over a parameter grid.
>>> import ubelt as ub
>>> longform = [
>>> {'col1': 1, 'col2': 'foo', 'col3': None},
>>> {'col1': 1, 'col2': 'foo', 'col3': None},
>>> {'col1': 2, 'col2': 'bar', 'col3': None},
>>> {'col1': 3, 'col2': 'bar', 'col3': None},
>>> {'col1': 9, 'col2': 'bar', 'col3': None},
>>> {'col1': 1, 'col2': 'bar', 'col3': None},
>>> ]
>>> varied = ub.varied_values(longform)
>>> print('varied = {}'.format(ub.repr2(varied, nl=1)))
varied = {
'col1': {1, 2, 3, 9},
'col2': {'bar', 'foo'},
'col3': {None},
}
Example:
>>> import ubelt as ub
>>> import random
>>> longform = [
>>> {'col1': 1, 'col2': 'foo', 'col3': None},
>>> {'col1': 1, 'col2': [1, 2], 'col3': None},
>>> {'col1': 2, 'col2': 'bar', 'col3': None},
>>> {'col1': 3, 'col2': 'bar', 'col3': None},
>>> {'col1': 9, 'col2': 'bar', 'col3': None},
>>> {'col1': 1, 'col2': 'bar', 'col3': None, 'extra_col': 3},
>>> ]
>>> # Operation fails without a default
>>> import pytest
>>> with pytest.raises(KeyError):
>>> varied = ub.varied_values(longform)
>>> #
>>> # Operation works with a default
>>> varied = ub.varied_values(longform, default='<unset>')
>>> expected = {
>>> 'col1': {1, 2, 3, 9},
>>> 'col2': {'bar', 'foo', (1, 2)},
>>> 'col3': set([None]),
>>> 'extra_col': {'<unset>', 3},
>>> }
>>> print('varied = {!r}'.format(varied))
>>> assert varied == expected
Example:
>>> # xdoctest: +REQUIRES(PY3)
>>> # Random numbers are different in Python2, so skip in that case
>>> import ubelt as ub
>>> import random
>>> num_cols = 11
>>> num_rows = 17
>>> rng = random.Random(0)
>>> # Generate a set of columns
>>> columns = sorted(ub.hash_data(i)[0:8] for i in range(num_cols))
>>> # Generate rows for each column
>>> longform = [
>>> {key: ub.hash_data(key)[0:8] for key in columns}
>>> for _ in range(num_rows)
>>> ]
>>> # Add in some varied values in random positions
>>> for row in longform:
>>> if rng.random() > 0.5:
>>> for key in sorted(row.keys()):
>>> if rng.random() > 0.95:
>>> row[key] = 'special-' + str(rng.randint(1, 32))
>>> varied = ub.varied_values(longform, min_variations=1)
>>> print('varied = {}'.format(ub.repr2(varied, nl=1, sort=True)))
varied = {
'095f3e44': {'8fb4d4c9', 'special-23'},
'365d11a1': {'daa409da', 'special-31', 'special-32'},
'5815087d': {'1b823610', 'special-3'},
'7b54b668': {'349a782c', 'special-10'},
'b8244d02': {'d57bca90', 'special-8'},
'f27b5bf8': {'fa0f90d1', 'special-19'},
}
"""
# Enumerate all defined columns
columns = set()
for row in longform:
if default is NoParam and len(row) != len(columns) and len(columns):
missing = set(columns).symmetric_difference(set(row))
raise KeyError((
'No default specified and not every '
'row contains columns {}').format(missing))
columns.update(row.keys())
# Build up the set of unique values for each column
varied = ddict(set)
for row in longform:
for key in columns:
value = row.get(key, default)
if isinstance(value, list):
value = tuple(value)
varied[key].add(value)
# Remove any column that does not have enough variation
if min_variations > 0:
for key, values in list(varied.items()):
if len(values) <= min_variations:
varied.pop(key)
return varied
[docs]class SetDict(dict):
"""
A dictionary subclass where all set operations are defined.
All of the set operations are defined in a key-wise fashion, that is it is
like performing the operation on sets of keys.
Note:
The SetDict class only defines key-wise set operations. Value-wise or
item-wise operations are in general not hashable and therefore not
supported. A heavier extension would be needed for that.
Example:
>>> import ubelt as ub
>>> primes = ub.sdict({v: f'prime_{v}' for v in [2, 3, 5, 7, 11]})
>>> evens = ub.sdict({v: f'even_{v}' for v in [0, 2, 4, 6, 8, 10]})
>>> odds = ub.sdict({v: f'odd_{v}' for v in [1, 3, 5, 7, 9, 11]})
>>> squares = ub.sdict({v: f'square_{v}' for v in [0, 1, 4, 9]})
>>> div3 = ub.sdict({v: f'div3_{v}' for v in [0, 3, 6, 9]})
>>> # All of the set methods are defined
>>> results1 = {}
>>> results1['ints'] = ints = odds.union(evens)
>>> results1['composites'] = ints.difference(primes)
>>> results1['even_primes'] = evens.intersection(primes)
>>> results1['odd_nonprimes_and_two'] = odds.symmetric_difference(primes)
>>> print('results1 = {}'.format(ub.repr2(results1, nl=2, sort=True)))
results1 = {
'composites': {
0: 'even_0',
1: 'odd_1',
4: 'even_4',
6: 'even_6',
8: 'even_8',
9: 'odd_9',
10: 'even_10',
},
'even_primes': {
2: 'even_2',
},
'ints': {
0: 'even_0',
1: 'odd_1',
2: 'even_2',
3: 'odd_3',
4: 'even_4',
5: 'odd_5',
6: 'even_6',
7: 'odd_7',
8: 'even_8',
9: 'odd_9',
10: 'even_10',
11: 'odd_11',
},
'odd_nonprimes_and_two': {
1: 'odd_1',
2: 'prime_2',
9: 'odd_9',
},
}
>>> # As well as their corresponding binary operators
>>> assert results1['ints'] == odds | evens
>>> assert results1['composites'] == ints - primes
>>> assert results1['even_primes'] == evens & primes
>>> assert results1['odd_nonprimes_and_two'] == odds ^ primes
>>> # These can also be used as classmethods
>>> assert results1['ints'] == ub.sdict.union(odds, evens)
>>> assert results1['composites'] == ub.sdict.difference(ints, primes)
>>> assert results1['even_primes'] == ub.sdict.intersection(evens, primes)
>>> assert results1['odd_nonprimes_and_two'] == ub.sdict.symmetric_difference(odds, primes)
>>> # The narry variants are also implemented
>>> results2 = {}
>>> results2['nary_union'] = ub.sdict.union(primes, div3, odds)
>>> results2['nary_difference'] = ub.sdict.difference(primes, div3, odds)
>>> results2['nary_intersection'] = ub.sdict.intersection(primes, div3, odds)
>>> # Note that the definition of symmetric difference might not be what you think in the nary case.
>>> results2['nary_symmetric_difference'] = ub.sdict.symmetric_difference(primes, div3, odds)
>>> print('results2 = {}'.format(ub.repr2(results2, nl=2, sort=True)))
results2 = {
'nary_difference': {
2: 'prime_2',
},
'nary_intersection': {
3: 'prime_3',
},
'nary_symmetric_difference': {
0: 'div3_0',
1: 'odd_1',
2: 'prime_2',
3: 'odd_3',
6: 'div3_6',
},
'nary_union': {
0: 'div3_0',
1: 'odd_1',
2: 'prime_2',
3: 'odd_3',
5: 'odd_5',
6: 'div3_6',
7: 'odd_7',
9: 'odd_9',
11: 'odd_11',
},
}
Example:
>>> # A neat thing about our implementation is that often the right
>>> # hand side is not required to be a dictionary, just something
>>> # that can be cast to a set.
>>> import ubelt as ub
>>> primes = ub.sdict({2: 'a', 3: 'b', 5: 'c', 7: 'd', 11: 'e'})
>>> assert primes - {2, 3} == {5: 'c', 7: 'd', 11: 'e'}
>>> assert primes & {2, 3} == {2: 'a', 3: 'b'}
>>> # Union does need to have a second dictionary
>>> import pytest
>>> with pytest.raises(AttributeError):
>>> primes | {2, 3}
"""
[docs] def copy(self):
"""
Example:
>>> import ubelt as ub
>>> a = ub.sdict({1: 1, 2: 2, 3: 3})
>>> b = ub.udict({1: 1, 2: 2, 3: 3})
>>> c = a.copy()
>>> d = b.copy()
>>> assert c is not a
>>> assert d is not b
>>> assert d == b
>>> assert c == a
>>> list(map(type, [a, b, c, d]))
>>> assert isinstance(c, ub.sdict)
>>> assert isinstance(d, ub.udict)
"""
return self.__class__(self)
# We could just use the builtin variant for this specific operation
def __or__(self, other):
""" The | union operator """
return self.union(other)
def __and__(self, other):
""" The & intersection operator """
return self.intersection(other)
def __sub__(self, other):
""" The - difference operator """
return self.difference(other)
def __xor__(self, other):
""" The ^ symmetric_difference operator """
return self.symmetric_difference(other)
# - reverse versions
def __ror__(self, other):
"""
Example:
>>> import ubelt as ub
>>> self = ub.sdict({1: 1, 2: 2, 3: 3})
>>> other = {1: 10, 2:20, 4: 40}
>>> d1 = self | other
>>> d2 = other | self
>>> assert isinstance(d1, ub.SetDict), 'should use own type'
>>> assert isinstance(d2, ub.SetDict), 'should promote type'
>>> print(f'd1={d1}')
>>> print(f'd2={d2}')
d1={1: 10, 2: 20, 3: 3, 4: 40}
d2={1: 1, 2: 2, 4: 40, 3: 3}
"""
return SetDict.union(other, self, cls=self.__class__)
def __rand__(self, other):
"""
Example:
>>> import ubelt as ub
>>> self = ub.sdict({1: 1, 2: 2, 3: 3})
>>> other = {1: 10, 2:20, 4: 40}
>>> d1 = self & other
>>> d2 = other & self
>>> assert isinstance(d1, ub.SetDict), 'should use own type'
>>> assert isinstance(d2, ub.SetDict), 'should promote type'
>>> print(f'd1={d1}')
>>> print(f'd2={d2}')
d1={1: 1, 2: 2}
d2={1: 10, 2: 20}
"""
return SetDict.intersection(other, self, cls=self.__class__)
def __rsub__(self, other):
"""
Example:
>>> import ubelt as ub
>>> self = ub.sdict({1: 1, 2: 2, 3: 3})
>>> other = {1: 10, 2:20, 4: 40}
>>> d1 = self - other
>>> d2 = other - self
>>> assert isinstance(d1, ub.SetDict), 'should use own type'
>>> assert isinstance(d2, ub.SetDict), 'should promote type'
>>> print(f'd1={d1}')
>>> print(f'd2={d2}')
d1={3: 3}
d2={4: 40}
"""
return SetDict.difference(other, self, cls=self.__class__)
def __rxor__(self, other):
"""
Example:
>>> import ubelt as ub
>>> self = ub.sdict({1: 1, 2: 2, 3: 3})
>>> other = {1: 10, 2:20, 4: 40}
>>> d1 = self ^ other
>>> d2 = other ^ self
>>> assert isinstance(d1, ub.SetDict), 'should use own type'
>>> assert isinstance(d2, ub.SetDict), 'should promote type'
>>> print(f'd1={d1}')
>>> print(f'd2={d2}')
d1={3: 3, 4: 40}
d2={4: 40, 3: 3}
"""
return SetDict.symmetric_difference(other, self, cls=self.__class__)
# - inplace versions
def __ior__(self, other):
"""
Example:
>>> import ubelt as ub
>>> self = orig_ref = ub.sdict({1: 1, 2: 2, 3: 3})
>>> orig_val = orig_ref.copy()
>>> other = {1: 10, 2:20, 4: 40}
>>> self |= other
>>> print(f'self={self}')
>>> assert self is orig_ref
>>> assert self == (orig_val | other)
self={1: 10, 2: 20, 3: 3, 4: 40}
"""
self.update(other)
return self
def __iand__(self, other):
"""
Example:
>>> import ubelt as ub
>>> self = orig_ref = ub.sdict({1: 1, 2: 2, 3: 3})
>>> orig_val = orig_ref.copy()
>>> other = {1: 10, 2:20, 4: 40}
>>> self &= other
>>> print(f'self={self}')
>>> assert self is orig_ref
>>> assert self == (orig_val & other)
self={1: 1, 2: 2}
"""
result = self.intersection(other)
self.clear()
self.update(result)
return self
def __isub__(self, other):
"""
Example:
>>> import ubelt as ub
>>> self = orig_ref = ub.sdict({1: 1, 2: 2, 3: 3})
>>> orig_val = orig_ref.copy()
>>> other = {1: 10, 2:20}
>>> self -= other
>>> print(f'self={self}')
>>> assert self is orig_ref
>>> assert self == (orig_val - other)
self={3: 3}
>>> import ubelt as ub
>>> self = orig_ref = ub.sdict({1: 1, 2: 2, 3: 3})
>>> orig_val = orig_ref.copy()
>>> other = [1]
>>> self -= other
>>> print(f'self={self}')
>>> assert self is orig_ref
>>> assert self == (orig_val - other)
self={2: 2, 3: 3}
>>> import ubelt as ub
>>> self = orig_ref = ub.sdict({1: 1, 2: 2, 3: 3})
>>> orig_val = orig_ref.copy()
>>> other = {1: 10, 2:20, 4: 40}
>>> self -= other
>>> print(f'self={self}')
>>> assert self is orig_ref
>>> assert self == (orig_val - other)
"""
result = self.difference(other)
self.clear()
self.update(result)
# common = UDict.intersection(self, other)
# for k in common:
# self.pop(k, None)
return self
def __ixor__(self, other):
"""
Example:
>>> import ubelt as ub
>>> self = orig_ref = ub.sdict({1: 1, 2: 2, 3: 3})
>>> orig_val = orig_ref.copy()
>>> other = {1: 10, 2:20, 4: 40}
>>> self ^= other
>>> print(f'self={self}')
>>> assert self is orig_ref
>>> assert self == (orig_val ^ other)
"""
result = self.symmetric_difference(other)
self.clear()
self.update(result)
return self
### Main set operations
[docs] def union(self, *others, cls=None):
"""
Return the key-wise union of two or more dictionaries.
For items with intersecting keys, dictionaries towards the end of the
sequence are given precedence.
Args:
self (SetDict | dict):
if called as a static method this must be provided.
*others : other dictionary like objects that have an ``items``
method. (i.e. it must return an iterable of 2-tuples where the
first item is hashable.)
cls (type):
the desired return dictionary type.
Returns:
dict : whatever the dictionary type of the first argument is
Example:
>>> import ubelt as ub
>>> a = ub.SetDict({k: 'A_' + chr(97 + k) for k in [2, 3, 5, 7]})
>>> b = ub.SetDict({k: 'B_' + chr(97 + k) for k in [2, 4, 0, 7]})
>>> c = ub.SetDict({k: 'C_' + chr(97 + k) for k in [2, 8, 3]})
>>> d = ub.SetDict({k: 'D_' + chr(97 + k) for k in [9, 10, 11]})
>>> e = ub.SetDict({k: 'E_' + chr(97 + k) for k in []})
>>> assert a | b == {2: 'B_c', 3: 'A_d', 5: 'A_f', 7: 'B_h', 4: 'B_e', 0: 'B_a'}
>>> a.union(b)
>>> a | b | c
>>> res = ub.SetDict.union(a, b, c, d, e)
>>> print(ub.repr2(res, sort=1, nl=0, si=1))
{0: B_a, 2: C_c, 3: C_d, 4: B_e, 5: A_f, 7: B_h, 8: C_i, 9: D_j, 10: D_k, 11: D_l}
"""
cls = cls or self.__class__
args = it.chain([self], others)
new = cls(it.chain.from_iterable(d.items() for d in args))
return new
[docs] def intersection(self, *others, cls=None):
"""
Return the key-wise intersection of two or more dictionaries.
All items returned will be from the first dictionary for keys that
exist in all other dictionaries / sets provided.
Args:
self (SetDict | dict):
if called as a static method this must be provided.
*others : other dictionary or set like objects that can
be coerced into a set of keys.
cls (type):
the desired return dictionary type.
Returns:
dict : whatever the dictionary type of the first argument is
Example:
>>> import ubelt as ub
>>> a = ub.SetDict({k: 'A_' + chr(97 + k) for k in [2, 3, 5, 7]})
>>> b = ub.SetDict({k: 'B_' + chr(97 + k) for k in [2, 4, 0, 7]})
>>> c = ub.SetDict({k: 'C_' + chr(97 + k) for k in [2, 8, 3]})
>>> d = ub.SetDict({k: 'D_' + chr(97 + k) for k in [9, 10, 11]})
>>> e = ub.SetDict({k: 'E_' + chr(97 + k) for k in []})
>>> assert a & b == {2: 'A_c', 7: 'A_h'}
>>> a.intersection(b)
>>> a & b & c
>>> res = ub.SetDict.intersection(a, b, c, d, e)
>>> print(ub.repr2(res, sort=1, nl=0, si=1))
{}
"""
cls = cls or self.__class__
isect_keys = set(self.keys())
for v in others:
isect_keys.intersection_update(v)
new = cls((k, self[k]) for k in self if k in isect_keys)
return new
[docs] def difference(self, *others, cls=None):
"""
Return the key-wise difference between this dictionary and one or
more other dictionary / keys.
The returned items will be from the first dictionary, and will only
contain keys that do not appear in any of the other dictionaries /
sets.
Args:
self (SetDict | dict):
if called as a static method this must be provided.
*others : other dictionary or set like objects that can
be coerced into a set of keys.
cls (type):
the desired return dictionary type.
Returns:
dict : whatever the dictionary type of the first argument is
Example:
>>> import ubelt as ub
>>> a = ub.SetDict({k: 'A_' + chr(97 + k) for k in [2, 3, 5, 7]})
>>> b = ub.SetDict({k: 'B_' + chr(97 + k) for k in [2, 4, 0, 7]})
>>> c = ub.SetDict({k: 'C_' + chr(97 + k) for k in [2, 8, 3]})
>>> d = ub.SetDict({k: 'D_' + chr(97 + k) for k in [9, 10, 11]})
>>> e = ub.SetDict({k: 'E_' + chr(97 + k) for k in []})
>>> assert a - b == {3: 'A_d', 5: 'A_f'}
>>> a.difference(b)
>>> a - b - c
>>> res = ub.SetDict.difference(a, b, c, d, e)
>>> print(ub.repr2(res, sort=1, nl=0, si=1))
{5: A_f}
"""
cls = cls or self.__class__
other_keys = set()
for v in others:
other_keys.update(v)
# Looping over original keys is important to maintain partial order.
new = cls((k, self[k]) for k in self.keys() if k not in other_keys)
return new
[docs] def symmetric_difference(self, *others, cls=None):
"""
Return the key-wise symmetric difference between this dictionary and
one or more other dictionaries.
Returns items that are (key-wise) in an odd number of the given
dictionaries. This is consistent with the standard n-ary definition of
symmetric difference [WikiSymDiff]_ and corresponds with the xor
operation.
Args:
self (SetDict | dict):
if called as a static method this must be provided.
*others : other dictionary or set like objects that can
be coerced into a set of keys.
cls (type):
the desired return dictionary type.
Returns:
dict : whatever the dictionary type of the first argument is
References:
.. [WikiSymDiff] https://en.wikipedia.org/wiki/Symmetric_difference
Example:
>>> import ubelt as ub
>>> a = ub.SetDict({k: 'A_' + chr(97 + k) for k in [2, 3, 5, 7]})
>>> b = ub.SetDict({k: 'B_' + chr(97 + k) for k in [2, 4, 0, 7]})
>>> c = ub.SetDict({k: 'C_' + chr(97 + k) for k in [2, 8, 3]})
>>> d = ub.SetDict({k: 'D_' + chr(97 + k) for k in [9, 10, 11]})
>>> e = ub.SetDict({k: 'E_' + chr(97 + k) for k in []})
>>> a ^ b
{3: 'A_d', 5: 'A_f', 4: 'B_e', 0: 'B_a'}
>>> a.symmetric_difference(b)
>>> a - b - c
>>> res = ub.SetDict.symmetric_difference(a, b, c, d, e)
>>> print(ub.repr2(res, sort=1, nl=0, si=1))
{0: B_a, 2: C_c, 4: B_e, 5: A_f, 8: C_i, 9: D_j, 10: D_k, 11: D_l}
"""
cls = cls or self.__class__
new = cls(self) # shallow copy
for d in others:
for k, v in d.items():
if k in new:
new.pop(k)
else:
new[k] = v
return new
sdict = SetDict
# Might need to make these mixins for 3.6
[docs]class UDict(SetDict):
"""
A subclass of dict with ubelt enhancements
This builds on top of :class:`SetDict` which itself is a simple extension
that contains only that extra functionality. The extra invert, map, sorted,
and peek functions are less fundamental and there are at least reasonable
workarounds when they are not available.
The UDict class is a simple subclass of dict that provides the following upgrades:
* set operations - inherited from :class:`SetDict`
+ intersection - find items in common
+ union - merge dicts
+ difference - find items in one but not the other
+ symmetric_difference - find items that appear an odd number of times
* subdict - take a subset with optional default values. (similar to intersection, but the later ignores non-common values)
* inversion -
+ invert - swaps a dictionary keys and values (with options for dealing with duplicates).
* mapping -
+ map_keys - applies a function over each key and keeps the values the same
+ map_values - applies a function over each key and keeps the values the same
* sorting -
+ sorted_keys - returns a dictionary ordered by the keys
+ sorted_values - returns a dictionary ordered by the values
IMO key-wise set operations on dictionaries are fundamentaly and sorely
missing from the stdlib, mapping is super convinient, sorting and inversion
are less common, but still useful to have.
TODO:
- [ ] UbeltDict, UltraDict, not sure what the name is. We may just rename this to Dict,
Example:
>>> import ubelt as ub
>>> a = ub.udict({1: 20, 2: 20, 3: 30, 4: 40})
>>> b = ub.udict({0: 0, 2: 20, 4: 42})
>>> c = ub.udict({3: -1, 5: -1})
>>> # Demo key-wise set operations
>>> assert a & b == {2: 20, 4: 40}
>>> assert a - b == {1: 20, 3: 30}
>>> assert a ^ b == {1: 20, 3: 30, 0: 0}
>>> assert a | b == {1: 20, 2: 20, 3: 30, 4: 42, 0: 0}
>>> # Demo new n-ary set methods
>>> a.union(b, c) == {1: 20, 2: 20, 3: -1, 4: 42, 0: 0, 5: -1}
>>> a.intersection(b, c) == {}
>>> a.difference(b, c) == {1: 20}
>>> a.symmetric_difference(b, c) == {1: 20, 0: 0, 5: -1}
>>> # Demo new quality of life methods
>>> assert a.subdict({2, 4, 6, 8}, default=None) == {8: None, 2: 20, 4: 40, 6: None}
>>> assert a.invert() == {20: 2, 30: 3, 40: 4}
>>> assert a.invert(unique_vals=0) == {20: {1, 2}, 30: {3}, 40: {4}}
>>> assert a.peek_key() == ub.peek(a.keys())
>>> assert a.peek_value() == ub.peek(a.values())
>>> assert a.map_keys(lambda x: x * 10) == {10: 20, 20: 20, 30: 30, 40: 40}
>>> assert a.map_values(lambda x: x * 10) == {1: 200, 2: 200, 3: 300, 4: 400}
"""
[docs] def subdict(self, keys, default=NoParam):
"""
Get a subset of a dictionary
Args:
self (Dict[KT, VT]): dictionary or the implicit instance
keys (Iterable[KT]): keys to take from ``self``
default (Optional[object] | NoParamType):
if specified uses default if keys are missing.
Raises:
KeyError : if a key does not exist and default is not specified
SeeAlso:
:func:`ubelt.util_dict.dict_subset`
:func:`ubelt.UDict.take`
Example:
>>> import ubelt as ub
>>> a = ub.udict({k: 'A_' + chr(97 + k) for k in [2, 3, 5, 7]})
>>> s = a.subdict({2, 5})
>>> print('s = {}'.format(ub.repr2(s, nl=0, sort=1)))
s = {2: 'A_c', 5: 'A_f'}
>>> import pytest
>>> with pytest.raises(KeyError):
>>> s = a.subdict({2, 5, 100})
>>> s = a.subdict({2, 5, 100}, default='DEF')
>>> print('s = {}'.format(ub.repr2(s, nl=0, sort=1)))
s = {2: 'A_c', 5: 'A_f', 100: 'DEF'}
"""
cls = self.__class__
if default is NoParam:
new = cls([(k, self[k]) for k in keys])
else:
new = cls([(k, self.get(k, default)) for k in keys])
return new
[docs] def take(self, keys, default=NoParam):
"""
Get values of an iterable of keys.
Args:
self (Dict[KT, VT]): dictionary or the implicit instance
keys (Iterable[KT]): keys to take from ``self``
default (Optional[object] | NoParamType):
if specified uses default if keys are missing.
Yields:
VT: a selected value within the dictionary
Raises:
KeyError : if a key does not exist and default is not specified
SeeAlso:
:func:`ubelt.util_list.take`
:func:`ubelt.UDict.subdict`
Example:
>>> import ubelt as ub
>>> a = ub.udict({k: 'A_' + chr(97 + k) for k in [2, 3, 5, 7]})
>>> s = list(a.take({2, 5}))
>>> print('s = {}'.format(ub.repr2(s, nl=0, sort=1)))
s = ['A_c', 'A_f']
>>> import pytest
>>> with pytest.raises(KeyError):
>>> s = a.subdict({2, 5, 100})
>>> s = list(a.take({2, 5, 100}, default='DEF'))
>>> print('s = {}'.format(ub.repr2(s, nl=0, sort=1)))
s = ['A_c', 'A_f', 'DEF']
"""
if default is NoParam:
for k in keys:
yield self[k]
else:
for k in keys:
yield self.get(k, default)
[docs] def invert(self, unique_vals=True):
"""
Swaps the keys and values in a dictionary.
Args:
self (Dict[KT, VT]): dictionary or the implicit instance to invert
unique_vals (bool, default=True): if False, the values of the new
dictionary are sets of the original keys.
cls (type | None): specifies the dict subclassof the result.
if unspecified will be dict or OrderedDict. This behavior may
change.
Returns:
Dict[VT, KT] | Dict[VT, Set[KT]]:
the inverted dictionary
Note:
The must values be hashable.
If the original dictionary contains duplicate values, then only one of
the corresponding keys will be returned and the others will be
discarded. This can be prevented by setting ``unique_vals=False``,
causing the inverted keys to be returned in a set.
Example:
>>> import ubelt as ub
>>> inverted = ub.udict({'a': 1, 'b': 2}).invert()
>>> assert inverted == {1: 'a', 2: 'b'}
"""
import ubelt as ub
return ub.invert_dict(self, unique_vals=unique_vals, cls=self.__class__)
[docs] def map_keys(self, func):
"""
Apply a function to every value in a dictionary.
Creates a new dictionary with the same keys and modified values.
Args:
self (Dict[KT, VT]): a dictionary or the implicit instance.
func (Callable[[VT], T] | Mapping[VT, T]): a function or indexable object
Returns:
Dict[KT, T]: transformed dictionary
Example:
>>> import ubelt as ub
>>> new = ub.udict({'a': [1, 2, 3], 'b': []}).map_keys(ord)
>>> assert new == {97: [1, 2, 3], 98: []}
"""
import ubelt as ub
return ub.map_keys(func, self, cls=self.__class__)
[docs] def map_values(self, func):
"""
Apply a function to every value in a dictionary.
Creates a new dictionary with the same keys and modified values.
Args:
self (Dict[KT, VT]): a dictionary or the implicit instance.
func (Callable[[VT], T] | Mapping[VT, T]): a function or indexable object
Returns:
Dict[KT, T]: transformed dictionary
Example:
>>> import ubelt as ub
>>> newdict = ub.udict({'a': [1, 2, 3], 'b': []}).map_values(len)
>>> assert newdict == {'a': 3, 'b': 0}
"""
import ubelt as ub
return ub.map_values(func, self, cls=self.__class__)
[docs] def sorted_keys(self, key=None, reverse=False):
"""
Return an ordered dictionary sorted by its keys
Args:
self (Dict[KT, VT]):
dictionary to sort or the implicit instance.
The keys must be of comparable types.
key (Callable[[KT], Any] | None):
If given as a callable, customizes the sorting by ordering using
transformed keys.
reverse (bool, default=False):
if True returns in descending order
Returns:
OrderedDict[KT, VT]: new dictionary where the keys are ordered
Example:
>>> import ubelt as ub
>>> new = ub.udict({'spam': 2.62, 'eggs': 1.20, 'jam': 2.92}).sorted_keys()
>>> assert new == ub.odict([('eggs', 1.2), ('jam', 2.92), ('spam', 2.62)])
"""
import ubelt as ub
return ub.sorted_keys(self, key=key, reverse=reverse, cls=self.__class__)
[docs] def sorted_values(self, key=None, reverse=False):
"""
Return an ordered dictionary sorted by its values
Args:
self (Dict[KT, VT]):
dictionary to sort or the implicit instance.
The values must be of comparable types.
key (Callable[[VT], Any] | None):
If given as a callable, customizes the sorting by ordering using
transformed values.
reverse (bool, default=False):
if True returns in descending order
Returns:
OrderedDict[KT, VT]: new dictionary where the values are ordered
Example:
>>> import ubelt as ub
>>> new = ub.udict({'spam': 2.62, 'eggs': 1.20, 'jam': 2.92}).sorted_values()
>>> assert new == ub.odict([('eggs', 1.2), ('spam', 2.62), ('jam', 2.92)])
"""
import ubelt as ub
return ub.sorted_values(self, key=key, reverse=reverse, cls=self.__class__)
[docs] def peek_key(self, default=NoParam):
"""
Get the first key in the dictionary
Args:
self (Dict): a dictionary or the implicit instance
default (T | NoParamType): default item to return if the iterable is empty,
otherwise a StopIteration error is raised
Returns:
KT: the first value or the default
Example:
>>> import ubelt as ub
>>> assert ub.udict({1: 2}).peek_key() == 1
"""
import ubelt as ub
return ub.peek(self.keys(), default=default)
[docs] def peek_value(self, default=NoParam):
"""
Get the first value in the dictionary
Args:
self (Dict[KT, VT]): a dictionary or the implicit instance
default (T | NoParamType): default item to return if the iterable is empty,
otherwise a StopIteration error is raised
Returns:
VT: the first value or the default
Example:
>>> import ubelt as ub
>>> assert ub.udict({1: 2}).peek_value() == 2
"""
import ubelt as ub
return ub.peek(self.values(), default=default)
[docs]class AutoDict(UDict):
"""
An infinitely nested default dict of dicts.
Implementation of Perl's autovivification feature that follows
[SO_651794]_.
References:
.. [SO_651794] http://stackoverflow.com/questions/651794/init-dict-of-dicts
Example:
>>> import ubelt as ub
>>> auto = ub.AutoDict()
>>> auto[0][10][100] = None
>>> assert str(auto) == '{0: {10: {100: None}}}'
"""
_base = UDict
def __getitem__(self, key):
try:
# value = super(AutoDict, self).__getitem__(key)
value = self._base.__getitem__(self, key)
except KeyError:
value = self[key] = self.__class__()
return value
[docs] def to_dict(self):
"""
Recursively casts a AutoDict into a regular dictionary. All directly
nested AutoDict values are also converted.
This effectively de-defaults the structure.
Returns:
dict: a copy of this dict without autovivification
Example:
>>> import ubelt as ub
>>> auto = ub.AutoDict()
>>> auto[1] = 1
>>> auto['n1'] = ub.AutoDict()
>>> static = auto.to_dict()
>>> assert not isinstance(static, ub.AutoDict)
>>> assert not isinstance(static['n1'], ub.AutoDict)
Example:
>>> import ubelt as ub
>>> auto = ub.AutoOrderedDict()
>>> auto[0][3] = 3
>>> auto[0][2] = 2
>>> auto[0][1] = 1
>>> assert list(auto[0].values()) == [3, 2, 1]
"""
return self._base(
(key, (value.to_dict() if isinstance(value, AutoDict) else value))
for key, value in self.items())
# DEPRECATED. This is no longer needed. AutoDict is always ordered
if sys.version_info[0:2] <= (3, 6): # nocover
AutoOrderedDict = AutoDict
else: # nocover
AutoOrderedDict = AutoDict
# def __getattr__(key):
# if key == 'AutoOrderedDict':
# import ubelt as ub
# ub.schedule_deprecation(
# modname='ubelt', name='AutoOrderedDict', type='class',
# migration='use AutoDict instead',
# deprecate='1.2.0', error='2.0.0', remove='2.1.0')
# return AutoDict
# else:
# raise AttributeError(key)
udict = UDict