Saravanan666/pypi-org huggingface dataset:
Package: datetime_tzutils
datetime_tzutilsWhat is datetime_tzutilsA handful of small utility methods I find useful for dealing withdatetime.datetimeobjects and timezones. Some of these are just a couple of lines but they're easy to
get wrong so I find it useful to package them into a tested module. I also find it
makes code more readable and less repetitive.datetime_tzutils is a pure Python module with no dependencies.Includes:datetime_has_tz(dt: datetime.datetime) -> bool: returns True if the datetime has a timezonedatetime_naive_to_local(dt: datetime.datetime) -> datetime.datetime: converts a naive datetime to the local timezonedatetime_naive_to_utc(dt: datetime.datetime) -> datetime.datetime: converts a naive datetime to UTCdatetime_remove_tz(dt: datetime.datetime) -> datetime.datetime:: removes the timezone from a datetimedatetime_to_new_tz(dt: datetime.datetime, offset) -> datetime.datetime: converts a datetime to a new timezonedatetime_tz_to_utc(dt: datetime.datetime) -> datetime.datetime: converts a datetime with a timezone to UTCdatetime_utc_to_local(dt: datetime.datetime) -> datetime.datetime: converts a UTC datetime to the local timezoneget_local_tz(dt: datetime.datetime) -> datetime.tzinfo: returns the local timezone for a given datetimeutc_offset_seconds(dt: datetime.datetime) -> int: returns the UTC offset in seconds for a given datetimeInstallationpip install datetime_tzutilsSynopsis>>>importdatetime_tzutils>>>importdatetime>>>dt=datetime.datetime(2019,12,1)>>>datetime_tzutils.get_local_tz(dt)datetime.timezone(datetime.timedelta(days=-1,seconds=57600),'PST')>>>datetime_tzutils.datetime_has_tz(dt)False>>>dt=datetime_tzutils.datetime_naive_to_local(dt)>>>dtdatetime.datetime(2019,12,1,0,0,tzinfo=datetime.timezone(datetime.timedelta(days=-1,seconds=57600),'PST'))>>>datetime_tzutils.datetime_has_tz(dt)True>>>utc=datetime_tzutils.datetime_tz_to_utc(dt)>>>utcdatetime.datetime(2019,12,1,8,0,tzinfo=datetime.timezone.utc)>>>dt=datetime_tzutils.datetime_remove_tz(dt)>>>dtdatetime.datetime(2019,12,1,0,0)>>>utc=datetime_tzutils.datetime_naive_to_utc(dt)>>>utcdatetime.datetime(2019,12,1,0,0,tzinfo=datetime.timezone.utc)>>>local=datetime_tzutils.datetime_utc_to_local(utc)>>>localdatetime.datetime(2019,11,30,16,0,tzinfo=datetime.timezone(datetime.timedelta(days=-1,seconds=57600),'PST'))>>>Source CodeThe source code is available onGitHubTestingdatetime_tzutils has been tested with Python 3.9, 3.10, and 3.11 on Linux, macOS, and Windows.100% test coverage withpytest:pip install -r requirements_dev.txtpython -m pytest --cov=datetime_tzutils --cov-report=term-missingContributingContributions are welcome. Please open an issue or submit a pull request.The tests are written with pytest and require a couple of extra packages. Install them with:pip install -r requirements_dev.txtLicenseMIT License
Package: datetimeutc
datetimeutcA Python datetime wrapper so we can forget about timezonesA lightweight datetime utility library which wraps around the standarddatetimemodule, with features from dateutil and pytz.Its purpose is to minimize the effort to convert datetime to/from UTC, a task I found myself doing too often while scaling web services and apps internationally.This wrapper is designed under these datetime philosophy:datetime should always be timezone awaredatetime should always be handled and stored in UTC timedatetime should always default to UTC timedatetime should not contain server local timetimezone conversions should be done on client sideInstall$ pip install datetimeutcUsageThe library provides thinly wrappers of datetime classes, e.g. datetime, date, and time.Instances of these class are created with timezone awareness in UTC time. Users can also pass inNoneor other timezone, which the library will automatically converts into UTC time.>>> from datetimeutc import Datetime, Date, Time
>>> import pytz
>>> d = Datetime(2016, 3, 21, 9, 20, 40)
Datetime(2016, 3, 21, 9, 20, 40, tzinfo=<UTC>)
>>> Datetime(2016, 3, 21, 9, 20, 40, tzinfo=pytz.timezone('US/Eastern'))
Datetime(2016, 3, 21, 14, 16, 40, tzinfo=<UTC>)Functions of datetime are all supported.>>> from datetimeutc import Datetime, Date, Time
>>> Datetime.now()
Datetime(2016, 3, 21, 9, 20, 40, 816025, tzinfo=<UTC>)
>>> Datetime.now().dst()
datetime.timedelta(0)
>>> Datetime.now().timetuple()
time.struct_time(tm_year=2016, tm_mon=3, tm_mday=21, tm_hour=9, tm_min=7, tm_sec=47, tm_wday=0, tm_yday=81, tm_isdst=0)
>>> Datetime.now().toordinal()
736044
>>> Datetime.now().isoweekday()
1
>>> Datetime.now().isoformat()
'2016-03-21T09:08:17.488494+00:00'
>>> Datetime.strptime('2016-03-21','%Y-%m-%d')
Datetime(2016, 3, 21, 0, 0, tzinfo=<UTC>)
>>> datetimeutc.Datetime(2016, 3, 21, 9, 20, 40).astimezone(pytz.timezone('US/Eastern'))
datetime.datetime(2016, 3, 21, 5, 20, 40, tzinfo=<DstTzInfo 'US/Eastern' EDT-1 day, 20:00:00 DST>)UtilitiesOther datetime functions are available for common tasks, e.g. converting to/from javascript timestamp>>> import datetimeutc, datetime
>>> datetimeutc.to_utc(datetime.datetime.now())
datetime.datetime(2016, 3, 21, 9, 31, 8, 455166, tzinfo=<UTC>)
>>> d = datetimeutc.Datetime(2016, 3, 21, 9, 20, 40)
>>> d
Datetime(2016, 3, 21, 9, 20, 40, tzinfo=<UTC>)
>>> d.timestamp
1458552040
>>> d.jstimestamp
1458552040000.0
>>> datetimeutc.Datetime.from_jstimestamp(d.jstimestamp)
Datetime(2016, 3, 21, 9, 20, 40, tzinfo=<UTC>)
Package: datetimex
datetimex-说明文档简述这是一个适用于中文时间字符串格式化的Python库.
可以实现格式化一些中文带有时间的字符串,格式化后将数字结果返回.
即：【中文时间】　>　【数字时间】环境依赖Python 3.x必须成功安装Python、pip等,并且正确配置环境变量,否则该库可能无法正常工作.安装pip3 install datetimex使用import datetimex

test = datetimex.gettime('明天早上七点半')
test2 = datetimex.gettime('两天前的晚上十一点四十五分')

print(test)
print(test2)

结果如下：

('20181214495PM045543', '20181215496AM073000')
('20181214495PM045543', '20181212493PM114500')

gettime方法返回值为一个元组,其中第一项为当前时间，第二项为格式化后的时间.
两个字符串长度均为19,其中：
1~4位代表年份,5~6位代表月份,7~8位代表日,
9~10位代表周数(一年内所在的第几周),
11位代表星期几(星期天为一周的第一天,为0),
12~13位代表上下午
14~15位代表时，16~17位代表分,18~19位代表秒

上面两句代码得到的结果，表示：
在2018年12月14日,也是该年第49周的星期五的下午四点五十五分四十三秒执行的程序,分别传入“明天早上七点半”和“两天前的晚上十一点四十五分”,
执行结果分别返回的是:
2018年12月15日，也是该年的第49周星期六的早上7点30分，
2018年12月12日，该年的第49周星期三的晚上11点45分效果图
Package: date_to
date_to - The easy date converterConvert any date to another with just one friendly functiondate_to()will convert your dates between datetime objects, unix timestamps, and strings. No more boilerplate and headaches of trying to keep track of your dates and their (lack) of timezones.date_to()utilises the dateparser library for string parsing, enablingmany kinds of string representationsof time to be converted into machine interpretable dates.
All output dates are rounded to second precision.Default timezone conversion is to UTC. If you wish to convert your date to another timezone, simply provide the abbreviation of your desired timezone for the optionaltimezone=keyword argument.InstallationThedate_tolibrary is available onPyPiand easily installed using pip:pipinstalldate_toBasic Usefromdate_toimportdate_tosome_date="2001-09-11 17:20 EDT"a=date_to(some_date)b=date_to(some_date,"date")c=date_to(some_date,str,timezone="JST")d=date_to(some_date,to_type=int)print(a,type(a))print(b,type(b))print(c,type(c))print(d,type(d))Output:2001-09-11 21:20:00+00:00 <class 'datetime.datetime'>
2001-09-11 21:20:00+00:00 <class 'datetime.datetime'>
2001-09-12T06:20:00+09:00 <class 'str'>
1000243200 <class 'int'>Acceptedto_typeInputsimportdatetimeasdtaccepted_object_inputs=str|int|float|dt.datetime|dt.dateaccepted_string_inputs={"str":["str","string","text",],"int":["int","timestamp","epoch","unix","float",],"date":["datetime.datetime","datetime","date","dt","dt.datetime","dt.date",],}Parse SettingsIf you wish to change the string parse conversion behaviour you can add adictof keyword arguments to the function'sparser_settings=optional keyword argument. Please refer to thedateparser documentationfor possible settings.DEFAULT_SETTINGS={"TIMEZONE":"UTC","PREFER_DAY_OF_MONTH":"first","RETURN_AS_TIMEZONE_AWARE":True,}
Package: date-tools
date_toolsAuthor: Henin Roland Karkadadate_toolsprovides an integrated collection of date utilities to help you guess the date format of any given date string/listInstallation:$ pip install date-toolsUsage:guess_date_format()-> Expects a single date/ List of dates$ from date_tools import date_guessera) Single date:Example 1: $ date_guesser.guess_date_format("22/03/2018")
Output: '%d/%m/%Y'Example 2: $ date_guesser.guess_date_format("14 03 18")
Output: '%d %m %y'Example 3: $ date_guesser.guess_date_format("13-Mar-2018")
Output: '%d-%b-%Y'Example 4: $ date_guesser.guess_date_format("31/March/18")
Output: '%d/%B/%y'Example 5: $ date_guesser.guess_date_format("22/03/2018")
Output: '%d/%m/%Y'Example 6: $ date_guesser.guess_date_format("31 03 2017")
Output: '%d %m %Y'Example 7: $ date_guesser.guess_date_format("03/2018")
Output: '%m/%Y'Example 8: $ date_guesser.guess_date_format("March/2018")
Output: '%B/%Y'b) List of dates:Example 1: $ date_guesser.guess_date_format(["02 March 2018", "12 May 2018","10 December 2018", "22/03/1988"])
Output: '%d %B %Y' --> Returned as '%d %B %Y' was the date format matched with majority of the itemsExtra Details can be found in the example folderContributing to date_toolsIf you want to contribute code todate_tools, please take a look atCONTRIBUTING.md.
Package: datetransform
datetransformFeature engineering for datesInstallationdatetransformrequires Python 3.5+.pipinstalldatetransformExample Usagefromdatetransform.transformimportadd_date_featuresimportpandasaspddf=pd.read_csv('someFile.csv')df=add_date_features(df,date_field_name='dateCol')# This dataframe now contains additional date features.
Package: datetype
DateTypeA WorkaroundDateType is aworkaround for this
bugto demonstrate that we could
have a type-checking-time wrapper fordatetimethat doesn't change (or almost
doesn't change) the implementation, but fixes up two very annoying behaviors of
the stdlibdatetimemodule:adatetimenow won't type-check as adate- it still inherits at runtime
(the implementation is, after all, not changed) but it doesn't inherit at
type-time.there are separate types for naive and awaredatetimes.There's a very small bit of implementation glue (concrete@classmethods for
construction on theNaiveandAwaretypes, and a few functions that do
runtime checks to convert to/from stdlib types).
Package: dateutil-br
Dateutil-brImplementation to python-dateutil with to Pt-br language. "(>_<)"This implementation rewrites the constants used in thedateutillibrary's date parse.You can see the repositorypypion:https://pypi.org/project/dateutil-br/Installpipinstalldateutil-brUsage Exemples>>>fromdateutil_brimportBrParserInfo,parser>>>print(parser(BrParserInfo()).parse('08/04/2018'))"2018-04-08 00:00:00">>>print(parser(BrParserInfo()).parse('10 de abril de 2018'))"2018-04-10 00:00:00">>>print(parser(BrParserInfo()).parse('15 horas e 13 min de 10 de abril de 2018'))"2018-04-10 15:13:00"MaintainerThis code is sustained by Magrathea Labs, in the repositoryhttps://github.com/magrathealabs/dateutil-brLicenseThe package is available as open source under the terms of the MIT License.
Package: dateutils
dateutilsThe main purpose of this package is to provide more complex arithmetic
operations on dates/times. Heavy use is made of the relativedelta type from
Labix's dateutil library. Much of this package is just a light wrapper on top
of this with some added features such as range generation and business day
calculation.InstallationYou should install dateutils with pip:pip install dateutilsOtherwise, you'll have to download the package and run:python setup.py installIf you install it this way then you will also have to install all necessary
dependencies manually.
Package: dateUts
Sql UtsInstallationpipinstalldateUtsUsagesqlToDatefromdateUtsimportsqlToDateresult=sqlToDate('1991-12-23')print(result)datetime.datetime(1991,12,23,0,0)dateToSqlfromdateUtsimportdateToSqlfromdatetimeimportdatetimetoday=datetime.now()result=dateToSql(today)print(result)'2022-05-25'nowfromdateUtsimportnownow1=now()now2=now(fmt='%Y-%d-%m')now3=now(fmt='sql')print(now1)print(now2)print(now3)datetime.datetime(2022,5,25,18,57,5,710329)'2022-05-25''2022-25-05'todayfromdateUtsimporttodaytoday1=today()today2=today(fmt='%Y-%d-%m')today3=today(fmt='sql')today4=today(fmt='sql',addDays=1)today5=today(fmt='sql',addDays=-1)print(today1)print(today2)print(today3)print(today4)print(today5)datetime.datetime(2022,5,25,18,57,5,710329)'2022-05-25''2022-25-05''2022-25-06''2022-25-04'yesterdayfromdateUtsimportyesterdayystd1=yesterday()ystd2=yesterday(fmt='%Y-%d-%m')ystd3=yesterday(fmt='sql')print(ystd1)print(ystd2)print(ystd3)datetime.datetime(2022,5,24,18,57,5,710329)'2022-24-05''2022-05-24'dateRangefromdateUtsimportsqlToDate,dateRangestart=sqlToDate('2022-05-01')end=sqlToDate('2022-05-03')range1=dateRange(start,end)range2=dateRange(start,end,fmt='sql')print(range1)print(range2)[datetime.datetime(2022,5,1,0,0),datetime.datetime(2022,5,2,0,0),datetime.datetime(2022,5,3,0,0)]['2022-05-01','2022-05-02','2022-05-03']dateAddfromdateUtsimportsqlToDate,dateToSql,dateAddmydate=sqlToDate('2022-05-02')mydate_plus1_day=dateAdd(mydate,1,'day')mydate_less1_day=dateAdd(mydate,-1,'day')mydate_plus1_yer=dateAdd(mydate,1,'year')print(dateToSql(mydate))print(dateToSql(mydate_plus1_day))print(dateToSql(mydate_less1_day))print(dateToSql(mydate_plus1_yer))'2022-05-02''2022-05-03''2022-05-01''2023-05-02'lastWorkingDatefromdateUtsimportlastWorkingDate#Assuming today as '2022-05-25'dt=lastWorkingDate(fmt='sql')print(dt)#Assuming today as '2022-05-23'dt=lastWorkingDate(fmt='sql')print(dt)'2022-05-24''2022-05-20'nextWorkingDatefromdateUtsimportnextWorkingDate#Assuming today as '2023-01-20'dt=nextWorkingDate(fmt='sql')print(dt)#Assuming today as '2023-01-19'dt=nextWorkingDate(fmt='sql')print(dt)'2023-01-23''2023-01-20'DateMatchfromdateUtsimportdateMatchdt=dateMatch('2022-01-01','sql')print(dt)dt=dateMatch('2022-01-01','%Y-%m-%d')print(dt)TrueTrueIsWeekend#Preteend today is sundayfromdateUtsimporttoday,tomorrowdt=today()print(dt.is_weekend())dt=tomorrow()print(dt.is_weekend())TrueFalseInterval#Preteend today is sundayfromdateUtsimporttoday,tomorrowprint(interval(today(),tomorrow().date,in_days=True))print(interval(today(),tomorrow().date,in_minutes=True))print(interval(today(),tomorrow().date,in_seconds=True))1.01440.086400.0Change Log0.0.1 (2022-06-10)First Release0.0.2 (2022-06-10)Required libs0.0.3 (2022-06-11)TblUts0.0.4 (2022-07-20)Adjustment at sqlToDate function0.0.5 (2022-05-25)Readme details0.0.9 (2022-08-18)DateMatch0.1.0 (2022-10-03)Add Hours,Minutes and Seconds0.1.1 (2023-01-18)Next Working Day0.1.2 (2023-04-20)is_weeekend0.1.6 (2023-04-26)fmt bug date adjust0.2.3 (2023-07-11)interval0.2.4 (2023-09-25)different formats outputs0.2.5 (2023-09-25)fix getFormat
Package: dateweek
DateWeekDateWeek is a Python package for working with w-sat weeks.UsagefromdateweekimportDateWeekfromdatetimeimportdatetime# Creating a DateWeek object for the current weekcurrent_week=DateWeek.current_week()# Creating a DateWeek object for a specific weekweek=DateWeek(2020,1)# Creating a DateWeek object from a datetimeweek=DateWeek.from_datetime(datetime(2020,1,1))# Creating a DateWeek object from a stringweek=DateWeek.from_str("2020-01-01")# Getting the first day and last day of the weekfirst_day,last_day=week.first_day,week.last_day# Finding the previous weekprevious_week=current_week-1# Finding the next weeknext_week=current_week+1DevelopmentCondacondaenvcreate-fenvironment.yml
condaactivatedateweek
pipinstall-e.
pipinstall-e.[dev]pipinstall-e.[unittest]
Package: dathost
Welcome to Dathost’s unofficial python wrapper!This is a unofficial asynchronous & synchronous wrapper for Dathost’s API.Features:Full API coverage.Asynchronous & synchronous support.Easy to use with an object oriented design.100% test coverage.InstallPip:pip3 install dathostGit:pip3 install git+https://github.com/WardPearce/dathost.gitDocumentationDocumentationThanks toEncode for creating HTTPX
Package: dathostpython
This is a python wrapper for the dathost API.Installationpip3installdathostpythonBasic usagefromdathostpython.wrapperimportdathostdathost=dathost("email","password")# List servers and all their detailsprint(dathost.servers())# Start a serverdathost.start("server id")# Stop a serverdathost.stop("server id")# Duplicate a serverdathost.duplicate("server id")# Duplicate a server and print its idprint(dathost.duplicate("server id")["id"])# Delete a serverdathost.delete("server id")# Retrieve a file from the serverdathost.getFile("server id","path/to/file.txt")# Retrieve info on a serverprint(dathost.info("server id"))# Edit a server value# Multiple values can be passed, for example:# dathost.edit("570e1dadcde5f5xxxxxxxxxx", csgo_settings__rcon = "Bob", name = "Bob")## Note:# For parameters with "." in them, replace the "." with "__".# A full list of parameters can be found at https://dathost.net/api#!/default/put_game_server_itemdathost.edit("server id",parameter="value")# List files in a directory# The final 2 parameters (Hide default files and show file sizes) are optionaldathost.files("server id","path/to/dir/",True,True)# Sync the files between the local cache and the gameserverdathost.sync("server id")
Package: datim
datim 2.0.1Data as an image.InstallationUsageChangelogDetailsLicenseInstallationpip install datimAlternatively, installdatim[optional]and get progress bar support.Usagedatim has four commands:datimimdatdatimpimdatpdatimandimdatcheck whether the compiled variant of datim is installed.
If unavailable, it will fallback to the pure Python variant of datim.datimpandimdatpexclusivelyuse the pure Python variant of the module.$ datim
usage: datim [-h] [-o] [-np] [-nc] [-na] input output

(compiled) turns any file into an image

positional arguments:
  input               input file path
  output              output file path

optional arguments:
  -h, --help          show this help message and exit
  -o, --overwrite     overwrite without confirmation
  -np, --no-progress  do not use tqdm
  -nc, --no-compress  do not compress data
  -na, --no-alpha     do not use alpha channel$ imdat
usage: imdat [-h] [-o] [-np] [-nc] [-na] input output

(compiled) turns previously converted images into the original file

positional arguments:
  input               input file path
  output              output file path

optional arguments:
  -h, --help          show this help message and exit
  -o, --overwrite     overwrite without confirmation
  -np, --no-progress  do not use tqdm
  -nc, --no-compress  do not compress data
  -na, --no-alpha     do not use alpha channelDetailsAn image created by datim is made up by the following:[header][data][trailing random data][header] -> "<length of [data] hex array encoded in base15 hex>F"This is made up of a base15 hex array (0-E) denoting the length of the
(compressed) data hex array. It is then suffixed with a hexF, acting as a
delimiter betweeen the[header]and[data]section. This method of
storing the data hex array was chosen as to not use the alpha layer, which
would increase the resulting image file size.[data]The (compressed) data is expressed naturally as its hexidecimal counterparts.[trailing 0s]After the[data]hex array are trailing0s. Before 2.0.0, trailing data
were randomly generated for cosmetic purposes, but was removed due for
performance.Licensedatim is unlicensed withThe Unlicense.
Package: datime
datimePython package with convenience functions for dates, times, and intervalsUsagepretty_duration_shortUse the functionpretty_duration_shortto convert a whole number of seconds to a string that indicates the number of
hours, minutes, and seconds in the provided duration.>>>importdatime>>>datime.pretty_duration_short(59)'59s'>>>datime.pretty_duration_short(256)'4m16s'>>>datime.pretty_duration_short(60*60)'1h0m0s'>>>datime.pretty_duration_short(4096)'1h8m16s'>>>datime.pretty_duration_short(2**17)'36h24m32s'
Package: dating
A Python 3 library for handling date ranges and time periods in a
business context, based on Arrow.Install with:$ pip install datingDateTimeRangeTheDateTimeRangeclass defines a range between two points in time.
To use:from dating.ranges import DateTimeRange

date_range = DateTimeRange.from_strings('2017-01-15', '2017-03-15')ordate_time_range = DateTimeRange.from_strings('2017-01-15T10:25:00', '2017-01-16T07:30:00')
Package: datlib
datlibThis is a python package containing useful classes and functions of data structures and algorithms.InstallationRun the following to install:'''pythonpip install datlib'''UsageThere are many modules inside this package.###1. rangeQueries moduleThis module contains a class name SegmentTree.
  The constructor of the class takes following arguments :

  (a) A function **combine**
      This takes two arguments a and b. This function takes care of 
      the combination of the values of child nodes into a parent node.


  (b) A variable **identityVal**

      An identity value for filling the empty nodes in the segment tree
      array and for the case when the query is completely outside the 
      range.

  (c) A list **l**

      This contains the list for which you have to make the SegmentTree.

  You can make the segment tree in following way : 

  '''python

     from rangeQueries import SegmentTree
     def combine(a,b):
         return a+b

     l = [1,2,3,4,5,6,7,8]
     identityVal = 0
     s = SegmentTree(l,identityVal,combine)

  '''

  You can call following methods on your segment tree :

  (a) query(qs,qe)

      This method will take two parameters qs and qe. And will perform 
      query for the range.

  (b) pointUpdate(val,qi)

      This method will take two parameters qi and val,where qi is the 
      index of the given list **l** on which we will update the value
      to **val**.This will update the your segment tree.

  (c) rangeUpdate(qs,qe,val)

      This method will take three parameters qs,qe and val.This method
      will update the values to **val** from index **qs** to **qe**.
      This will update the your segment tree.###2. numbertheory moduleThis module contains following functions :
  Here **n** is the number.

  (a) primefactors(n)

      This function will return all the prime factors of a number.

  (b) chkPrime(n)

      This function will check if a number is prime or not.

  (c) divisors(n)

      This function will return all the divisors of a number.

  (d) powerModulo(x,y,M)

      This function will calculate x^y modulo M.###3. graphs moduleThis module contains following functions :


  (a)  bfs(start,graph)

       This function will take two arguments start and graph.
       Start is the source node which can be a tuple,number or a string.
       graph is a dictionary which contains the adjacency list of the nodes.
       This function will return a dictionary containing distance of all the
       nodes from the source node.

  (b) dfs(start, graph)

      This function will take two arguments start and graph.
      Start is the source node which can be a tuple,number or a string.
      graph is a dictionary which contains the adjacency list of the nodes.
      This function will contain a set of all the nodes that can be reched
      from start.
Package: datomizer
Datomizer pip packageWelcome to Datomize python clientDatomizer Docs###Usage Example:from datomizer import Datomizer, DatoMapper, DatoTrainer, DatoGenerator

datomizer = Datomizer(username=username, password=password)

mapper = DatoMapper(datomizer)
mapper.discover(df=df, title="Some Title")

trainer = DatoTrainer(mapper)
trainer.train()

generator = DatoGenerator(trainer)
generator.generate()
dato_df = pd.read_csv(generator.get_generated_data_csv())###Async Usage Examplefrom datomizer import Datomizer, DatoMapper, DatoTrainer, DatoGenerator

datomizer = Datomizer(username=username, password=password)

mapper = DatoMapper(datomizer)
mapper.discover(df=df, title="Some Title", wait=False)
...do something...
mapper.wait()

trainer = DatoTrainer(mapper)
trainer.train(wait=False)
...do something...
trainer.wait()


generator = DatoGenerator(trainer)
generator.generate(wait=False)
...do something...
generator.wait()
dato_df = pd.read_csv(generator.get_generated_data_csv())