jdZddlmZddlZddlZddlmZmZmZddl Z ddl m Z ddl mZmZerddlmZdd ZejddZejddZdS)z6Common utilities for Numba operations with groupby ops) annotationsN) TYPE_CHECKINGAnyCallable)import_optional_dependency)NumbaUtilErrorjit_user_function)ScalarfuncrreturnNonecTt|stdttj|j}ddg}t|}t||ks|d||krtd|d|j d|dS)a^ Validate user defined function for ops when using Numba with groupby ops. The first signature arguments should include: def f(values, index, ...): ... Parameters ---------- func : function, default False user defined function Returns ------- None Raises ------ NumbaUtilError z5Numba engine can only be used with a single function.valuesindexNz The first z arguments to z must be ) callableNotImplementedErrorlistinspect signature parameterskeyslenr__name__)r udf_signature expected_argsmin_number_argss nC:\Users\Terasoftware\OneDrive\Desktop\faahhh\fyndo\fyndo\venv\Lib\site-packages\pandas/core/groupby/numba_.py validate_udfrs, D>> ! C   *400;@@BBCCMw'M-((O M_, )/) *m ;              Callable[..., Scalar]nopythonboolnogilparallelPCallable[[np.ndarray, np.ndarray, np.ndarray, np.ndarray, int, Any], np.ndarray]ct|trddlntd|||dfd }|S)a Generate a numba jitted agg function specified by values from engine_kwargs. 1. jit the user's function 2. Return a groupby agg function with the jitted function inline Configurations specified in engine_kwargs apply to both the user's function _AND_ the groupby evaluation loop. Parameters ---------- func : function function to be applied to each group and will be JITed nopython : bool nopython to be passed into numba.jit nogil : bool nogil to be passed into numba.jit parallel : bool parallel to be passed into numba.jit Returns ------- Numba function rNnumbar!r#r$r np.ndarrayrbeginend num_columnsintargsrr cpt|t|ksJt|}tj||f} |D]W}|||||} |D])} |||||| f}  | | g|R||| f<*X|SNrnpemptyprangerrr*r+r,r. num_groupsresulti group_indexjgroupr' numba_funcs r group_aggz*generate_numba_agg_func..group_agges5zzSXX%%%%ZZ :{344j)) E EAa3q6 12K\\+.. E EuQx#a&0!34)z%DtDDDq!t  E rrr)rr)r*r)r+r)r,r-r.rr r)r rr'rjit)r r!r#r$r=r'r<s @@rgenerate_numba_agg_funcrA@s|>#4((J4 *733 YYYAABA& rCallable[..., np.ndarray]ct|trddlntd|||dfd }|S)a Generate a numba jitted transform function specified by values from engine_kwargs. 1. jit the user's function 2. Return a groupby transform function with the jitted function inline Configurations specified in engine_kwargs apply to both the user's function _AND_ the groupby evaluation loop. Parameters ---------- func : function function to be applied to each window and will be JITed nopython : bool nopython to be passed into numba.jit nogil : bool nogil to be passed into numba.jit parallel : bool parallel to be passed into numba.jit Returns ------- Numba function rNr'r(rr)rr*r+r,r-r.rr ct|t|ksJt|}tjt||f} |D]e}|||||} |D]7} |||||| f}  | | g|R|||||| f<8f|Sr0r1r5s rgroup_transformz6generate_numba_transform_func..group_transforms5zzSXX%%%%ZZ 3v;; 455j)) U UAa3q6 12K\\+.. U UuQx#a&0!34/9z%/Tt/T/T/TuQx#a&(!+,, U rr>r?)r r!r#r$rEr'r<s @@rgenerate_numba_transform_funcrF|s|>#4((J4 *733 YYYAABA& r)r rr r ) r r r!r"r#r"r$r"r r%) r rBr!r"r#r"r$r"r r%)__doc__ __future__r functoolsrtypingrrrnumpyr2pandas.compat._optionalrpandas.core.util.numba_rr pandas._typingr rcacherArFrrrQs,<<"""""" >>>>>> &%%%%%%$ $ $ $ N 8888v 888888r