Mh^SSKJr SSKJr SSKrSSKJr \(aSSKJ r SSjr S Sjr g) ) annotations) TYPE_CHECKINGN) is_list_like) NumpyIndexTc Sn[U5(d [U5eUHn[U5(aM[U5e [U5S:Xa/$[R"SU5[R S9n[R "U5n[R"US:5(a [S5e[R"US5nSUS'USS:wa USU- nO[R"U5n[U5VVs/sH>upr[[R"X&U5[R"XW55PM@ snn$s snnf)a Numpy version of itertools.product. Sometimes faster (for large inputs)... Parameters ---------- X : list-like of list-likes Returns ------- product : list of ndarrays Examples -------- >>> cartesian_product([list('ABC'), [1, 2]]) [array(['A', 'A', 'B', 'B', 'C', 'C'], dtype='$cartesian_product...s*1As)dtypez+Product space too large to allocate arrays!)r TypeErrorr npfromiterintpcumprodany ValueErrorroll zeros_like enumerate tile_compatrepeatprod)Xmsgr lenXcumprodXabis r cartesian_productr& s(. 4C ??n AC.  1v{ ;;**"'' :Dzz$H vvhlFGG !A AaD|q RL8 # MM( #aL   !DA  IIa1  GGADM !   sAEc[U[R5(a[R"X5$[R"[R"[ U55U5nUR U5$)zR Index compat for np.tile. Notes ----- Does not support multi-dimensional `num`. ) isinstancerndarraytilearanger take)arrnumtakers r rrHsQ#rzz""wws   GGBIIc#h' -E 88E?)returnzlist[np.ndarray])r-rr.intr1r) __future__rtypingrnumpyrpandas.core.dtypes.commonrpandas._typingrr&rr0r r9s"" 2*8v r0