3 Ud#@sdZddlZddlmZddlZddljjZddl m Z m Z m Z ddl mZmZmZmZdZeddd Zd d ed feeeeed d dZd efedddZeedddZd ed feeedddZdS)z" data hash pandas / numpy objects N)Optional)is_categorical_dtypeis_extension_array_dtype is_list_like) ABCDataFrame ABCIndexClass ABCMultiIndex ABCSeriesZ0123456789123456) num_itemsc Csy t|}Wn tk r,tjgtjdSXtj|g|}tjd}tj|tjd}xBt|D]6\}}||}||N}||9}|tjd||7}qdW|d|kst d|tjd7}|S)z Parameters ---------- arrays : generator num_items : int Should be the same as CPython's tupleobject.c )dtypeiCBixV4iXBzFed in wrong num_itemsi|) next StopIterationnparrayuint64 itertoolschainZ zeros_like enumerateAssertionError)arraysr firstZmultoutiaZ inverse_irL/var/www/html/virt/lib64/python3.6/site-packages/pandas/core/util/hashing.py_combine_hash_arrayss   rTutf8)indexencodinghash_key categorizec sxddlm}dkrtttr8|tdddSttrptjj ddd}||ddd}ntt rtjj ddd}|rȇfd d dD}t j |g|}t |d }||jddd}nttrbd d jD} tj} |rDfd d dD} | d7} t j | | } dd | D} t | | }||jddd}ntdt|S)aX Return a data hash of the Index/Series/DataFrame. Parameters ---------- 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)SeriesNrF)r copy)r$)rr r$c3s$|]}tjddjVqdS)F)rr r!r"N)hash_pandas_objectr_values).0_)r"r r!objrr esz%hash_pandas_object..css|]\}}t|jVqdS)N) hash_arrayr&)r'r(Zseriesrrrr*tsc3s$|]}tjddjVqdS)F)rr r!r"N)r%rr&)r'r()r"r r!r)rrr*xsr css|] }|VqdS)Nr)r'xrrrr*szUnexpected type for hashing )N)N)pandasr#_default_hash_key isinstancer hash_tuplesrr,r&astyper rrrrritemslencolumns TypeErrortype) r)rr r!r"r#hZ index_iterrhashesr Zindex_hash_generator_hashesr)r"r r!r)rr%7s>           r%)r!csd}ttrgd}nts*tdddlmm}ttsN|jfddt j Dfdd D}t |t }|r|d}|S) a Hash an MultiIndex / list-of-tuples efficiently Parameters ---------- vals : MultiIndex, list-of-tuples, or single tuple encoding : str, default 'utf8' hash_key : str, default _default_hash_key Returns ------- ndarray of hashed values array FTz'must be convertible to a list-of-tuplesr) Categorical MultiIndexcs(g|] }j|j|dddqS)FT)orderedfastpath)codesZlevels)r'level)r;valsrr szhash_tuples..c3s|]}t|dVqdS))r r!N)_hash_categorical)r'cat)r r!rrr*szhash_tuples..) r0tuplerr6r.r;r<r from_tuplesrangeZnlevelsrr4)rAr r!Zis_tupler<r9r8r)r;r r!rArr1s     r1)r r!cCsltj|jj}t|||dd}|j}t|r<|j|j}ntj t|dd}|j rhtj tj j ||<|S)a Hash a Categorical by hashing its categories, and then mapping the codes to the hashes Parameters ---------- c : Categorical encoding : str hash_key : str Returns ------- ndarray of hashed values array, same size as len(c) F)r"r)r )rZasarray categoriesr&r,Zisnar4Ztaker?ZzerosanyZiinformax)cr r!valueshashedmaskresultrrrrCs rC)r r!r"c Cst|dstd|j}t|r,t|||St|rF|j\}}|j}tj|tj rtt tj |dt tj |St |tr|jd}nt|jtjtjfr|jdjddd}nt|jtjr|jdkr|jd |jjjd}n|r2d d lm}m}m}||dd \} } || || dd d} t| ||Sytj|||}Wn0tk rttj|jtjt||}YnX||d?N}|tjd9}||d?N}|tjd9}||d?N}|S)a9 Given a 1d array, return an array of deterministic integers. Parameters ---------- vals : ndarray, Categorical 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 ------- 1d uint64 numpy array of hash values, same length as the vals r zmust pass a ndarray-likeu8i8F)r$ur)r;Index factorize)sortT)r=r>le9z lb&&& ) hasattrr6r rrCrZ_values_for_factorizerZ issubdtypeZ complex128r,realimagr0boolr2 issubclassr7Z datetime64Z timedelta64viewnumberitemsizer.r;rUrVhashingZhash_object_arraystrobjectr) rAr r!r"r r(r;rUrVr?rHrDrrrr,s@          r,)__doc__rtypingrZnumpyrZpandas._libs.hashingZ_libsrcZpandas.core.dtypes.commonrrrZpandas.core.dtypes.genericrrrr r/intrr^rdr%r1rCr,rrrrs"  R+(