o 5cc@sdZddlmZddlZddlZddlmZmZmZddl Z ddl m Z ddl mZddlmZmZdd d ZejdddddZejdddddZdS)z6Common utilities for Numba operations with groupby ops) annotationsN) TYPE_CHECKINGAnyCallable)Scalar)import_optional_dependency)NumbaUtilErrorjit_user_functionfuncrreturnNonecCspt|stdtt|j}ddg}t|}t||ks(|d||kr6td|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_argsrP/var/www/html/gps/gps/lib/python3.10/site-packages/pandas/core/groupby/numba_.py validate_udfs" r)maxsizeCallable[..., Scalar]nopythonboolnogilparallelPCallable[[np.ndarray, np.ndarray, np.ndarray, np.ndarray, int, Any], np.ndarray]cHt||||trddlntdj|||ddfdd }|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 c st|t|ks Jt|}t||f}|D]-}|||||} |D]} |||||| f} | | g|R||| f<q+q|SNrnpemptyprange r rr)r*r+r- num_groupsresulti group_indexjgroupr& numba_funcrr group_aggcs z*generate_numba_agg_func..group_aggr r(rr(r)r(r*r(r+r,r-rr r(r rr&rjit)r r r"r#r<rr:rgenerate_numba_agg_func> r@Callable[..., np.ndarray]cr%)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'r r(rr)r*r+r,r-rr c st|t|ks Jt|}tt||f}|D]3}|||||} |D]!} |||||| f} | | g|R|||||| f<q-q|Sr.r/r3r:rrgroup_transforms (z6generate_numba_transform_func..group_transformr=r>)r r r"r#rCrr:rgenerate_numba_transform_func{rArD)r rr r ) r rr r!r"r!r#r!r r$) r rBr r!r"r!r#r!r r$)__doc__ __future__r functoolsrtypingrrrnumpyr0pandas._typingrpandas.compat._optionalrpandas.core.util.numba_rr r lru_cacher@rDrrrrs     '  <