LgZddlmZddlZddlmZddlmZ d dZdZd dZ d dZ y) ) annotationsN)Version)import_requiredc ^ddlm}|ttttd}|d||||||d|S)aCreate timeseries dataframe with random data Parameters ---------- start : datetime (or datetime-like string) Start of time series end : datetime (or datetime-like string) End of time series dtypes : dict (optional) Mapping of column names to types. Valid types include {float, int, str, 'category'} freq : string String like '2s' or '1H' or '12W' for the time series frequency partition_freq : string String like '1M' or '2Y' to divide the dataframe into partitions seed : int (optional) Randomstate seed kwargs: Keywords to pass down to individual column creation functions. Keywords should be prefixed by the column name and then an underscore. Examples -------- >>> import dask >>> df = dask.datasets.timeseries() >>> df.head() # doctest: +SKIP timestamp id name x y 2000-01-01 00:00:00 967 Jerry -0.031348 -0.040633 2000-01-01 00:00:01 1066 Michael -0.262136 0.307107 2000-01-01 00:00:02 988 Wendy -0.526331 0.128641 2000-01-01 00:00:03 1016 Yvonne 0.620456 0.767270 2000-01-01 00:00:04 998 Ursula 0.684902 -0.463278 >>> df = dask.datasets.timeseries( ... '2000', '2010', ... freq='2h', partition_freq='1D', seed=1, # data frequency ... dtypes={'value': float, 'name': str, 'id': int}, # data types ... id_lam=1000 # control number of items in id column ... ) r)make_timeseries)nameidxy)startendfreqpartition_freqseeddtypes)dask.dataframe.io.demorstrintfloat)r r rrrrkwargsrs -lib/python3.12/site-packages/dask/datasets.py timeseriesr sI`7 ~Su5A    %     cddl}ddlm}m}|d d|iii}}t |j t dkrd|d<nd|d<|d dfd i|} t |D cgc]} | jd i|dc} Scc} w) zdGenerate data for a single partition of a dask bag See Also -------- _make_mimesis rN)FieldSchemarz9.0.0 iterationsschemacSNr)fieldschema_descriptionsrz#_generate_mimesis..\s #5e# dict The schema to use to generate the data npartitions: int records_per_partition: int seed: int, None Seed for random data Returns ------- Dask Bag See Also -------- make_people rN)tokenizelzmimesis-) dask.bagbag dask.baser1randomRandomr)randint enumerater/Bag) r#r npartitionsr+rdbr1 random_state_seedsrr.dsks r _make_mimesisr@`s." KRE==&L7<[7I J7I!\ ! !!W -7IE J  v{$94 D !' 'GAt q %uf6KTRR'  66#t[ )) K  s B-B cBtddd}td|i||||S)aMake a dataset of random people This makes a Dask Bag with dictionary records of randomly generated people. This requires the optional library ``mimesis`` to generate records. Parameters ---------- npartitions : int Number of partitions records_per_partition : int Number of records in each partition seed : int, (optional) Random seed locale : str Language locale, like 'en', 'fr', 'zh', or 'ru' Returns ------- b: Dask Bag r&zWThe mimesis module is required for this function. Try: python -m pip install mimesisc |ddd|d|df|d|d|d |d d |d |d ddS)Nzrandom.randintrx)abz person.namezperson.surnamezperson.occupationzperson.telephonezaddress.addressz address.city)addresscityzpayment.credit_card_numberz#payment.credit_card_expiration_date)numberzexpiration-date)ager occupation telephonerFz credit-cardr)r#s rr%zmake_people..sc%c2}%u-='>?/0-.$%67~AVW89$%JK rlocale)rr@)r:r+rrLr s r make_peoplerMs;* * F  6FK1F r)z 2000-01-01z 2000-01-311s1DNNr") iNen) __future__rr5packaging.versionr dask.utilsrrr/r@rMrrrrUs<" %&    =@U,'*T)r