U ꥡc"@sddlZddlZddlmZddlmZdZddZddZd d Z e fd d Z e fd dZ e fddZ e fddZe fddZe fddZe fddZddZe fddZde fddZd"d d!ZdS)#N)reduce)Mapping) merge merge_withvalmapkeymapitemmap valfilter keyfilter itemfilterassocdissocassoc_in update_inget_incCs.|dt}|r*td|j|d|S)Nfactoryz,{}() got an unexpected keyword argument '{}'r)popdict TypeErrorformat__name__popitem)fkwargsrr3/tmp/pip-unpacked-wheel-n0vm8il5/toolz/dicttoolz.py _get_factory s  rcOsJt|dkr"t|dts"|d}tt|}|}|D]}||q6|S)z Merge a collection of dictionaries >>> merge({1: 'one'}, {2: 'two'}) {1: 'one', 2: 'two'} Later dictionaries have precedence >>> merge({1: 2, 3: 4}, {3: 3, 4: 4}) {1: 2, 3: 3, 4: 4} See Also: merge_with r)len isinstancerrrupdate)dictsrrrvdrrrrs  rc Ost|dkr"t|dts"|d}tt|}tdd}|D]"}|D]\}}|||qJq>|}|D]\}}||j||<qp|S)a Merge dictionaries and apply function to combined values A key may occur in more than one dict, and all values mapped from the key will be passed to the function as a list, such as func([val1, val2, ...]). >>> merge_with(sum, {1: 1, 2: 2}, {1: 10, 2: 20}) {1: 11, 2: 22} >>> merge_with(first, {1: 1, 2: 2}, {2: 20, 3: 30}) # doctest: +SKIP {1: 1, 2: 2, 3: 30} See Also: merge rrcSsgjSN)appendrrrr>zmerge_with..) rrrrr collections defaultdictitems__self__) funcr!rrvaluesr#kvresultrrrr+s rcCs(|}|t|t|||S)z Apply function to values of dictionary >>> bills = {"Alice": [20, 15, 30], "Bob": [10, 35]} >>> valmap(sum, bills) # doctest: +SKIP {'Alice': 65, 'Bob': 45} See Also: keymap itemmap )r zipkeysmapr-r,r#rr"rrrrIs rcCs(|}|tt||||S)z Apply function to keys of dictionary >>> bills = {"Alice": [20, 15, 30], "Bob": [10, 35]} >>> keymap(str.lower, bills) # doctest: +SKIP {'alice': [20, 15, 30], 'bob': [10, 35]} See Also: valmap itemmap )r r1r3r2r-r4rrrrYs rcCs|}|t|||S)z Apply function to items of dictionary >>> accountids = {"Alice": 10, "Bob": 20} >>> itemmap(reversed, accountids) # doctest: +SKIP {10: "Alice", 20: "Bob"} See Also: keymap valmap )r r3r*r4rrrris rcCs,|}|D]\}}||r|||<q|S)z Filter items in dictionary by value >>> iseven = lambda x: x % 2 == 0 >>> d = {1: 2, 2: 3, 3: 4, 4: 5} >>> valfilter(iseven, d) {1: 2, 3: 4} See Also: keyfilter itemfilter valmap r* predicater#rr"r.r/rrrr ys  r cCs,|}|D]\}}||r|||<q|S)z Filter items in dictionary by key >>> iseven = lambda x: x % 2 == 0 >>> d = {1: 2, 2: 3, 3: 4, 4: 5} >>> keyfilter(iseven, d) {2: 3, 4: 5} See Also: valfilter itemfilter keymap r5r6rrrr s  r cCs0|}|D]}||r|\}}|||<q|S)a Filter items in dictionary by item >>> def isvalid(item): ... k, v = item ... return k % 2 == 0 and v < 4 >>> d = {1: 2, 2: 3, 3: 4, 4: 5} >>> itemfilter(isvalid, d) {2: 3} See Also: keyfilter valfilter itemmap r5)r7r#rr"itemr.r/rrrr s   r cCs|}|||||<|S)z Return a new dict with new key value pair New dict has d[key] set to value. Does not modify the initial dictionary. >>> assoc({'x': 1}, 'x', 2) {'x': 2} >>> assoc({'x': 1}, 'y', 3) # doctest: +SKIP {'x': 1, 'y': 3} )r )r#keyvaluerd2rrrr s  r cOsttt|}|}t|t|dkrH|||D]}||kr2||=q2n(t|}|||D]}||||<q^|S)aB Return a new dict with the given key(s) removed. New dict has d[key] deleted for each supplied key. Does not modify the initial dictionary. >>> dissoc({'x': 1, 'y': 2}, 'y') {'x': 1} >>> dissoc({'x': 1, 'y': 2}, 'y', 'x') {} >>> dissoc({'x': 1}, 'y') # Ignores missing keys {'x': 1} g333333?)rr rr setdifference_update)r#r2rrr;r9 remainingr.rrrr s    r cst||fdd|S)a Return a new dict with new, potentially nested, key value pair >>> purchase = {'name': 'Alice', ... 'order': {'items': ['Apple', 'Orange'], ... 'costs': [0.50, 1.25]}, ... 'credit card': '5555-1234-1234-1234'} >>> assoc_in(purchase, ['order', 'costs'], [0.25, 1.00]) # doctest: +SKIP {'credit card': '5555-1234-1234-1234', 'name': 'Alice', 'order': {'costs': [0.25, 1.00], 'items': ['Apple', 'Orange']}} csSr$r)xr:rrr&r'zassoc_in..)r)r#r2r:rrr@rrs rc Cst|}t|}|}}|||D]@} ||krN||}|} | |n |}} | ||<}| }q(||kr|||||<n ||||<|S)a  Update value in a (potentially) nested dictionary inputs: d - dictionary on which to operate keys - list or tuple giving the location of the value to be changed in d func - function to operate on that value If keys == [k0,..,kX] and d[k0]..[kX] == v, update_in returns a copy of the original dictionary with v replaced by func(v), but does not mutate the original dictionary. If k0 is not a key in d, update_in creates nested dictionaries to the depth specified by the keys, with the innermost value set to func(default). >>> inc = lambda x: x + 1 >>> update_in({'a': 0}, ['a'], inc) {'a': 1} >>> transaction = {'name': 'Alice', ... 'purchase': {'items': ['Apple', 'Orange'], ... 'costs': [0.50, 1.25]}, ... 'credit card': '5555-1234-1234-1234'} >>> update_in(transaction, ['purchase', 'costs'], sum) # doctest: +SKIP {'credit card': '5555-1234-1234-1234', 'name': 'Alice', 'purchase': {'costs': 1.75, 'items': ['Apple', 'Orange']}} >>> # updating a value when k0 is not in d >>> update_in({}, [1, 2, 3], str, default="bar") {1: {2: {3: 'bar'}}} >>> update_in({1: 'foo'}, [2, 3, 4], inc, 0) {1: 'foo', 2: {3: {4: 1}}} )iternextr ) r#r2r,defaultrksr.r"innerr9Zdtemprrrrs "      rFc Cs:zttj||WStttfk r4|r,|YSXdS)a4 Returns coll[i0][i1]...[iX] where [i0, i1, ..., iX]==keys. If coll[i0][i1]...[iX] cannot be found, returns ``default``, unless ``no_default`` is specified, then it raises KeyError or IndexError. ``get_in`` is a generalization of ``operator.getitem`` for nested data structures such as dictionaries and lists. >>> transaction = {'name': 'Alice', ... 'purchase': {'items': ['Apple', 'Orange'], ... 'costs': [0.50, 1.25]}, ... 'credit card': '5555-1234-1234-1234'} >>> get_in(['purchase', 'items', 0], transaction) 'Apple' >>> get_in(['name'], transaction) 'Alice' >>> get_in(['purchase', 'total'], transaction) >>> get_in(['purchase', 'items', 'apple'], transaction) >>> get_in(['purchase', 'items', 10], transaction) >>> get_in(['purchase', 'total'], transaction, 0) 0 >>> get_in(['y'], {}, no_default=True) Traceback (most recent call last): ... KeyError: 'y' See Also: itertoolz.get operator.getitem N)roperatorgetitemKeyError IndexErrorr)r2ZcollrCZ no_defaultrrrr/s r)NF)rFr( functoolsrcollections.abcr__all__rrrrrrrr r r r r rrrrrrrs$          :