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315 lines
8.5 KiB
315 lines
8.5 KiB
import copy
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import operator
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from toolz.compatibility import (map, zip, iteritems, iterkeys, itervalues,
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reduce)
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__all__ = ('merge', 'merge_with', 'valmap', 'keymap', 'itemmap',
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'valfilter', 'keyfilter', 'itemfilter',
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'assoc', 'dissoc', 'assoc_in', 'update_in', 'get_in')
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def _get_factory(f, kwargs):
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factory = kwargs.pop('factory', dict)
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if kwargs:
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raise TypeError("{0}() got an unexpected keyword argument "
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"'{1}'".format(f.__name__, kwargs.popitem()[0]))
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return factory
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def merge(*dicts, **kwargs):
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""" Merge a collection of dictionaries
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>>> merge({1: 'one'}, {2: 'two'})
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{1: 'one', 2: 'two'}
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Later dictionaries have precedence
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>>> merge({1: 2, 3: 4}, {3: 3, 4: 4})
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{1: 2, 3: 3, 4: 4}
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See Also:
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merge_with
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"""
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if len(dicts) == 1 and not isinstance(dicts[0], dict):
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dicts = dicts[0]
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factory = _get_factory(merge, kwargs)
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rv = factory()
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for d in dicts:
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rv.update(d)
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return rv
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def merge_with(func, *dicts, **kwargs):
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""" Merge dictionaries and apply function to combined values
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A key may occur in more than one dict, and all values mapped from the key
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will be passed to the function as a list, such as func([val1, val2, ...]).
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>>> merge_with(sum, {1: 1, 2: 2}, {1: 10, 2: 20})
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{1: 11, 2: 22}
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>>> merge_with(first, {1: 1, 2: 2}, {2: 20, 3: 30}) # doctest: +SKIP
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{1: 1, 2: 2, 3: 30}
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See Also:
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merge
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"""
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if len(dicts) == 1 and not isinstance(dicts[0], dict):
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dicts = dicts[0]
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factory = _get_factory(merge_with, kwargs)
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result = factory()
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for d in dicts:
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for k, v in iteritems(d):
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if k not in result:
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result[k] = [v]
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else:
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result[k].append(v)
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return valmap(func, result, factory)
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def valmap(func, d, factory=dict):
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""" Apply function to values of dictionary
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>>> bills = {"Alice": [20, 15, 30], "Bob": [10, 35]}
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>>> valmap(sum, bills) # doctest: +SKIP
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{'Alice': 65, 'Bob': 45}
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See Also:
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keymap
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itemmap
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"""
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rv = factory()
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rv.update(zip(iterkeys(d), map(func, itervalues(d))))
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return rv
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def keymap(func, d, factory=dict):
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""" Apply function to keys of dictionary
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>>> bills = {"Alice": [20, 15, 30], "Bob": [10, 35]}
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>>> keymap(str.lower, bills) # doctest: +SKIP
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{'alice': [20, 15, 30], 'bob': [10, 35]}
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See Also:
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valmap
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itemmap
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"""
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rv = factory()
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rv.update(zip(map(func, iterkeys(d)), itervalues(d)))
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return rv
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def itemmap(func, d, factory=dict):
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""" Apply function to items of dictionary
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>>> accountids = {"Alice": 10, "Bob": 20}
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>>> itemmap(reversed, accountids) # doctest: +SKIP
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{10: "Alice", 20: "Bob"}
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See Also:
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keymap
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valmap
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"""
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rv = factory()
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rv.update(map(func, iteritems(d)))
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return rv
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def valfilter(predicate, d, factory=dict):
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""" Filter items in dictionary by value
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>>> iseven = lambda x: x % 2 == 0
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>>> d = {1: 2, 2: 3, 3: 4, 4: 5}
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>>> valfilter(iseven, d)
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{1: 2, 3: 4}
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See Also:
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keyfilter
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itemfilter
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valmap
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"""
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rv = factory()
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for k, v in iteritems(d):
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if predicate(v):
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rv[k] = v
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return rv
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def keyfilter(predicate, d, factory=dict):
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""" Filter items in dictionary by key
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>>> iseven = lambda x: x % 2 == 0
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>>> d = {1: 2, 2: 3, 3: 4, 4: 5}
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>>> keyfilter(iseven, d)
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{2: 3, 4: 5}
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See Also:
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valfilter
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itemfilter
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keymap
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"""
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rv = factory()
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for k, v in iteritems(d):
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if predicate(k):
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rv[k] = v
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return rv
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def itemfilter(predicate, d, factory=dict):
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""" Filter items in dictionary by item
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>>> def isvalid(item):
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... k, v = item
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... return k % 2 == 0 and v < 4
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>>> d = {1: 2, 2: 3, 3: 4, 4: 5}
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>>> itemfilter(isvalid, d)
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{2: 3}
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See Also:
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keyfilter
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valfilter
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itemmap
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"""
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rv = factory()
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for item in iteritems(d):
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if predicate(item):
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k, v = item
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rv[k] = v
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return rv
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def assoc(d, key, value, factory=dict):
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""" Return a new dict with new key value pair
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New dict has d[key] set to value. Does not modify the initial dictionary.
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>>> assoc({'x': 1}, 'x', 2)
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{'x': 2}
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>>> assoc({'x': 1}, 'y', 3) # doctest: +SKIP
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{'x': 1, 'y': 3}
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"""
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d2 = factory()
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d2[key] = value
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return merge(d, d2, factory=factory)
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def dissoc(d, *keys):
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""" Return a new dict with the given key(s) removed.
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New dict has d[key] deleted for each supplied key.
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Does not modify the initial dictionary.
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>>> dissoc({'x': 1, 'y': 2}, 'y')
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{'x': 1}
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>>> dissoc({'x': 1, 'y': 2}, 'y', 'x')
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{}
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>>> dissoc({'x': 1}, 'y') # Ignores missing keys
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{'x': 1}
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"""
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d2 = copy.copy(d)
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for key in keys:
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if key in d2:
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del d2[key]
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return d2
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def assoc_in(d, keys, value, factory=dict):
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""" Return a new dict with new, potentially nested, key value pair
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>>> purchase = {'name': 'Alice',
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... 'order': {'items': ['Apple', 'Orange'],
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... 'costs': [0.50, 1.25]},
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... 'credit card': '5555-1234-1234-1234'}
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>>> assoc_in(purchase, ['order', 'costs'], [0.25, 1.00]) # doctest: +SKIP
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{'credit card': '5555-1234-1234-1234',
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'name': 'Alice',
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'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}}
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"""
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return update_in(d, keys, lambda x: value, value, factory)
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def update_in(d, keys, func, default=None, factory=dict):
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""" Update value in a (potentially) nested dictionary
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inputs:
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d - dictionary on which to operate
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keys - list or tuple giving the location of the value to be changed in d
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func - function to operate on that value
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If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the
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original dictionary with v replaced by func(v), but does not mutate the
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original dictionary.
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If k0 is not a key in d, update_in creates nested dictionaries to the depth
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specified by the keys, with the innermost value set to func(default).
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>>> inc = lambda x: x + 1
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>>> update_in({'a': 0}, ['a'], inc)
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{'a': 1}
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>>> transaction = {'name': 'Alice',
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... 'purchase': {'items': ['Apple', 'Orange'],
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... 'costs': [0.50, 1.25]},
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... 'credit card': '5555-1234-1234-1234'}
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>>> update_in(transaction, ['purchase', 'costs'], sum) # doctest: +SKIP
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{'credit card': '5555-1234-1234-1234',
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'name': 'Alice',
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'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}}
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>>> # updating a value when k0 is not in d
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>>> update_in({}, [1, 2, 3], str, default="bar")
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{1: {2: {3: 'bar'}}}
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>>> update_in({1: 'foo'}, [2, 3, 4], inc, 0)
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{1: 'foo', 2: {3: {4: 1}}}
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"""
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assert len(keys) > 0
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k, ks = keys[0], keys[1:]
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if ks:
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return assoc(d, k, update_in(d[k] if (k in d) else factory(),
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ks, func, default, factory),
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factory)
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else:
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innermost = func(d[k]) if (k in d) else func(default)
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return assoc(d, k, innermost, factory)
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def get_in(keys, coll, default=None, no_default=False):
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""" Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys.
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If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless
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``no_default`` is specified, then it raises KeyError or IndexError.
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``get_in`` is a generalization of ``operator.getitem`` for nested data
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structures such as dictionaries and lists.
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>>> transaction = {'name': 'Alice',
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... 'purchase': {'items': ['Apple', 'Orange'],
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... 'costs': [0.50, 1.25]},
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... 'credit card': '5555-1234-1234-1234'}
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>>> get_in(['purchase', 'items', 0], transaction)
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'Apple'
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>>> get_in(['name'], transaction)
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'Alice'
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>>> get_in(['purchase', 'total'], transaction)
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>>> get_in(['purchase', 'items', 'apple'], transaction)
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>>> get_in(['purchase', 'items', 10], transaction)
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>>> get_in(['purchase', 'total'], transaction, 0)
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0
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>>> get_in(['y'], {}, no_default=True)
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Traceback (most recent call last):
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...
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KeyError: 'y'
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See Also:
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itertoolz.get
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operator.getitem
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"""
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try:
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return reduce(operator.getitem, keys, coll)
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except (KeyError, IndexError, TypeError):
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if no_default:
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raise
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return default
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