>ie\ddlmZddlZddlmZddlmZ dd Zd Zdd Z ddZ dS)) annotationsN)Version)import_required 2000-01-01 2000-01-311s1dc fddlm}|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_timeseriesN)nameidxy)startendfreqpartition_freqseeddtypes)dask.dataframe.io.demor strintfloat)rrrrrrkwargsr s -lib/python3.11/site-packages/dask/datasets.py timeseriesr sg`766666 ~Su5AA ?   %       c ddl}ddlm}m}|d d|iiic}t |jt dkrdd<nd|d<|d dfd i|  fd t |DS) zdGenerate data for a single partition of a dask bag See Also -------- _make_mimesis rN)FieldSchemarz9.0.0 iterationsschemacSNr)fieldschema_descriptionsrz#_generate_mimesis..\s#5#5e#<#<rc6g|]}jdidS)rr)create).0i create_kwargsr$s r z%_generate_mimesis..]s0 T T T!MFM * *M * *1 - T T Trr)mimesismimesis.schemar r!r __version__range) r'r(records_per_partitionrr0r r! schema_kwargsr.r$s `` @@r_generate_mimesisr6JsNNN,,,,,,,, E % %t %u % %E$&r M=w"##gg&6&666&' l##&' l# V N N<<<<< N N NF T T T T Tu=R7S7S T T TTrc ddlm}ddlm}pit j| fdt |D}d|||z fdt|D}|| |S)a Make a Dask Bag filled with data randomly generated by the mimesis projet Parameters ---------- field: dict keyword arguments to pass to ``mimesis.Field`` schema: Callable[Field] -> dict The schema to use to generate the data npartitions: int records_per_partition: int seed: int, None Seed for random data Returns ------- Dask Bag See Also -------- make_people rN)tokenizec<g|]}ddS)rl)randint)r,_ random_states rr/z!_make_mimesis..}s) J J J!\ ! !!W - - J J Jrzmimesis-c4i|]\}}|ft|fSr)r6)r,r-rr'r r4r$s r z!_make_mimesis..s@    At q %uf6KTR   r) dask.bagbag dask.baser8randomRandomr3 enumerateBag) r'r$ npartitionsr4rdbr8seedsdskr r<s `` ` @@r _make_mimesisrJ`s."""""" KRE=&&L J J J Ju[7I7I J J JE  v{$94 D        ''   C 66#t[ ) ))r encRtddd}td|i||||S)aMake a dataset of random people This makes a Dask Bag with dictionary records of randomly generated people. This requires the optional library ``mimesis`` to generate records. Parameters ---------- npartitions : int Number of partitions records_per_partition : int Number of records in each partition seed : int, (optional) Random seed locale : str Language locale, like 'en', 'fr', 'zh', or 'ru' Returns ------- b: Dask Bag r0zWThe mimesis module is required for this function. Try: python -m pip install mimesisc |d|d|df|d|d|d|dd|d |d d d S) Nz person.agez person.namezperson.surnamezperson.occupationzperson.telephonezaddress.addressz address.city)addresscityzpayment.credit_card_numberz#payment.credit_card_expiration_date)numberzexpiration-date)ager occupation telephonerPz credit-cardr)r's rr)zmake_people..su\""}%%uu-='>'>?e/00U-..$u%677~AVAVWWe899$u%JKK   rlocale)rrJ)rFr4rrVr$s r make_peoplerWsO* *  F  6FK1F  r)rrrr NNr&)rKrLNrM) __future__rrBpackaging.versionr dask.utilsrrr6rJrWrrrr[s"""""" %%%%%%&&&&&&    ====@UUU,'*'*'*'*T))))))r