B W0d&@sNdZddlmZddlZddlmZmZmZmZm Z ddl Z ddl m Z ddlmZddlmZmZddlmZmZdd lmZmZmZmZerdd lmZmZmZmZd Z d d ddddZ!dde dfdddddddddZ"de fdddddddZ#d dddd!d"d#Z$de dfd$ddddd%d&d'Z%de dfdddddd%d(d)Z&dS)*z" data hash pandas / numpy objects ) annotationsN) TYPE_CHECKINGHashableIterableIteratorcast)lib)hash_object_array) ArrayLikeFrameOrSeriesUnion)is_categorical_dtype is_list_like) ABCDataFrameABCIndex ABCMultiIndex ABCSeries) CategoricalIndex MultiIndexSeriesZ0123456789123456zIterator[np.ndarray]intz np.ndarray)arrays num_itemsreturncCsy t|}Wn tk r,tjgtjdSXt|g|}td}t|td}xBt|D]6\}}||}||N}||9}|td||7}qdW|d|kst d|td7}|S)z Parameters ---------- arrays : Iterator[np.ndarray] num_items : int Returns ------- np.ndarray[uint64] Should be the same as CPython's tupleobject.c )dtypeiCBixV4iXBzFed in wrong num_itemsi|) next StopIterationnparrayuint64 itertoolschainZ zeros_like enumerateAssertionError)rrfirstZmultoutiaZ inverse_ir)J/var/www/html/venv/lib/python3.7/site-packages/pandas/core/util/hashing.pycombine_hash_arrays0s   r+Tutf8zIndex | FrameOrSeriesUnionboolstrz str | Noner)objindexencodinghash_key categorizercsddlm}dkrtttr8|tdddSttrptjj ddd}||ddd}n tt rtjj ddd}|rȇfd d d D}t |g|} t | d }||jddd}nttrjfd d D} tj} |rLfdd d D} | d7} t | | } dd | D} t | | }||jddd}ntdt|S)a~ Return a data hash of the Index/Series/DataFrame. Parameters ---------- obj : Index, Series, or DataFrame index : bool, default True Include the index in the hash (if Series/DataFrame). encoding : str, default 'utf8' Encoding for data & key when strings. hash_key : str, default _default_hash_key Hash_key for string key to encode. categorize : bool, default True Whether to first categorize object arrays before hashing. This is more efficient when the array contains duplicate values. Returns ------- Series of uint64, same length as the object r)rNr F)rcopy)r4)r0rr4c3s$|]}tjddjVqdS)F)r0r1r2r3N)hash_pandas_objectr0_values).0_)r3r1r2r/r)r* sz%hash_pandas_object..)Nc3s"|]\}}t|jVqdS)N) hash_arrayr6)r7r8Zseries)r3r1r2r)r*r9sc3s$|]}tjddjVqdS)F)r0r1r2r3N)r5r0r6)r7r8)r3r1r2r/r)r*r9srcss|] }|VqdS)Nr))r7xr)r)r*r9szUnexpected type for hashing )pandasr_default_hash_key isinstancer hash_tuplesrr;r6astyperr!r"r+r0ritemslencolumns TypeErrortype)r/r0r1r2r3rhZserZ index_iterrhashesrZindex_hash_generator_hashesr))r3r1r2r/r*r5Ps@            r5z+MultiIndex | Iterable[tuple[Hashable, ...]])valsr1r2rcszt|stdddlmm}t|ts6||n|fddtj D}fdd|D}t |t |}|S)a Hash an MultiIndex / listlike-of-tuples efficiently. Parameters ---------- vals : MultiIndex or listlike-of-tuples encoding : str, default 'utf8' hash_key : str, default _default_hash_key Returns ------- ndarray[np.uint64] of hashed values z'must be convertible to a list-of-tuplesr)rrcs(g|] }j|j|dddqS)FT)orderedfastpath)codesZlevels)r7level)rmir)r* szhash_tuples..c3s|]}t|dVqdS))r1r2N)_hash_categorical)r7cat)r1r2r)r*r9szhash_tuples..) r rEr=rrr?r from_tuplesrangeZnlevelsr+rC)rJr1r2rZcat_valsrHrGr))rr1r2rOr*r@s   r@r)rRr1r2rcCsdt|jj}t|||dd}|}t|r<||j}ntj t|dd}| r`t j ||<|S)a Hash a Categorical by hashing its categories, and then mapping the codes to the hashes Parameters ---------- cat : Categorical encoding : str hash_key : str Returns ------- ndarray[np.uint64] of hashed values, same size as len(c) F)r3r )r) rZasarray categoriesr6r;ZisnarCZtakerMZzerosanyrZu8max)rRr1r2valueshashedmaskresultr)r)r*rQs  rQr )rJr1r2r3rcCs\t|dstd|j}t|r6td|}t|||St|tjsN| \}}t ||||S)aK Given a 1d array, return an array of deterministic integers. Parameters ---------- vals : ndarray or ExtensionArray encoding : str, default 'utf8' Encoding for data & key when strings. hash_key : str, default _default_hash_key Hash_key for string key to encode. categorize : bool, default True Whether to first categorize object arrays before hashing. This is more efficient when the array contains duplicate values. Returns ------- ndarray[np.uint64, ndim=1] Hashed values, same length as the vals. rzmust pass a ndarray-liker) hasattrrErr rrQr?rZndarrayZ_values_for_factorize _hash_ndarray)rJr1r2r3rr8r)r)r*r;s     r;c Cst|j}t|tjr4tt|dtt|St|trJ| d}nt |j tj tj frt|dj ddd}nt |j tjr|jdkr|d|jj d}n|rdd lm}m}m}||dd \}} |||| dd d } t| ||Syt|||}Wn.tk r.t| t t||}YnX||d ?N}|td9}||d?N}|td9}||d?N}|S)z! See hash_array.__doc__. u8i8F)r4ur)rr factorize)sortT)rKrLle9z lb&&& )rrZ issubdtypeZ complex128r;realimagr?r-rA issubclassrFZ datetime64Z timedelta64viewnumberitemsizer=rrrbrQr rEr.objectr ) rJr1r2r3rrrrbrMrUrRr)r)r*r\*s2        r\)'__doc__ __future__rr!typingrrrrrnumpyrZ pandas._libsrZpandas._libs.hashingr Zpandas._typingr r Zpandas.core.dtypes.commonr r Zpandas.core.dtypes.genericrrrrr=rrrrr>r+r5r@rQr;r\r)r)r)r*s4    "Y+((