a RG5d ã@s0ddlmZdd„Zdd„Zdd„Zdd „Zd S) é)Ú OrderedDictcs`ˆs dgStˆdtƒs:tˆdd…ƒ}‡fdd„|DƒStˆdd…ƒ}‡fdd„|DƒSdS)z¨ >>> from sympy.multipledispatch.utils import expand_tuples >>> expand_tuples([1, (2, 3)]) [(1, 2), (1, 3)] >>> expand_tuples([1, 2]) [(1, 2)] ©réNcsg|]}ˆdf|‘qS©rr)Ú.0Út©ÚLrúX/var/www/html/django/DPS/env/lib/python3.9/site-packages/sympy/multipledispatch/utils.pyÚ óz!expand_tuples..cs$g|]}ˆdD]}|f|‘qqSrr)rrÚitemrrr r r )Ú isinstanceÚtupleÚ expand_tuples)r Úrestrrr rs rcs´t|ƒ‰dd„ˆ ¡Dƒ‰t ‡fdd„|Dƒ¡}g}|r’| ¡\}}| |¡| |d¡D]2}|ˆ|vspJ‚ˆ| |¡ˆ|s\d||<q\q6t‡fdd„|Dƒƒr°t dƒ‚|S) a2 Topological sort algorithm by Kahn [1] - O(nodes + vertices) inputs: edges - a dict of the form {a: {b, c}} where b and c depend on a outputs: L - an ordered list of nodes that satisfy the dependencies of edges >>> from sympy.multipledispatch.utils import _toposort >>> _toposort({1: (2, 3), 2: (3, )}) [1, 2, 3] Closely follows the wikipedia page [2] [1] Kahn, Arthur B. (1962), "Topological sorting of large networks", Communications of the ACM [2] https://en.wikipedia.org/wiki/Toposort#Algorithms cSsi|]\}}|t|ƒ“qSr)Úset)rÚkÚvalrrr Ú ,r z_toposort..c3s|]}|ˆvr|VqdS©Nr©rÚv©Zincoming_edgesrr Ú -r z_toposort..rNc3s|]}ˆ |d¡VqdSr)Úgetrrrr r8r zInput has cycles) Ú reverse_dictÚitemsrÚfromkeysÚpopitemÚappendrÚremoveÚanyÚ ValueError)ÚedgesÚSr ÚnÚ_Úmrrr Ú _toposorts   r)cCs8i}|D]*}||D]}| |tƒ¡|f||<qq|S)a›Reverses direction of dependence dict >>> d = {'a': (1, 2), 'b': (2, 3), 'c':()} >>> reverse_dict(d) # doctest: +SKIP {1: ('a',), 2: ('a', 'b'), 3: ('b',)} :note: dict order are not deterministic. As we iterate on the input dict, it make the output of this function depend on the dict order. So this function output order should be considered as undeterministic. )rr)ÚdÚresultÚkeyrrrr r=s  rcCs8i}|D]*}||ƒ}||vr$g||<|| |¡q|S)aÛ Group a collection by a key function >>> from sympy.multipledispatch.utils import groupby >>> names = ['Alice', 'Bob', 'Charlie', 'Dan', 'Edith', 'Frank'] >>> groupby(len, names) # doctest: +SKIP {3: ['Bob', 'Dan'], 5: ['Alice', 'Edith', 'Frank'], 7: ['Charlie']} >>> iseven = lambda x: x % 2 == 0 >>> groupby(iseven, [1, 2, 3, 4, 5, 6, 7, 8]) # doctest: +SKIP {False: [1, 3, 5, 7], True: [2, 4, 6, 8]} See Also: ``countby`` )r )ÚfuncÚseqr*r r,rrr ÚgroupbySsr/N)Ú collectionsrrr)rr/rrrr Ús $