






'''simple docstring'''







import itertools
from dataclasses import dataclass
from io import StringIO
from typing import Optional

import pyarrow as pa

import datasets
from datasets.features.features import require_storage_cast
from datasets.table import table_cast


__A   :							Dict     	=						datasets.utils.logging.get_logger(__name__)






@dataclass
class        a__     (      datasets.BuilderConfig    ):
     '''simple docstring'''







     _snake_case							   =	None
     _snake_case							   =	"utf-8"
     _snake_case							   =	None
     _snake_case							   =	10 << 20  # 10MB
     _snake_case							   =	False
     _snake_case							   =	"line"







class        a__     (      datasets.ArrowBasedBuilder    ):
     '''simple docstring'''







     _snake_case							   =	TextConfig






     def      _UpperCamelCase (self     :						Dict       )	->							List[Any]:
           return datasets.DatasetInfo(features=self.config.features       )






     def      _UpperCamelCase (self     :						Optional[int]					,					lowercase__     :						Tuple       )	->							Tuple:
           if not self.config.data_files:
                 raise ValueError(f"At least one data file must be specified, but got data_files={self.config.data_files}"       )
           __A		 =   dl_manager.download_and_extract(self.config.data_files       )
           if isinstance(lowercase__					,					(str, list, tuple)       ):
                 __A		 =   data_files
                 if isinstance(lowercase__					,					lowercase__       ):
                       __A		 =   [files]
                 __A		 =   [dl_manager.iter_files(lowercase__       ) for file in files]
                 return [datasets.SplitGenerator(name=datasets.Split.TRAIN					,					gen_kwargs={"files": files}       )]
           __A		 =   []
           for split_name, files in data_files.items():
                 if isinstance(lowercase__					,					lowercase__       ):
                       __A		 =   [files]
                 __A		 =   [dl_manager.iter_files(lowercase__       ) for file in files]
                 splits.append(datasets.SplitGenerator(name=lowercase__					,					gen_kwargs={"files": files}       )       )
           return splits






     def      _UpperCamelCase (self     :						str					,					lowercase__     :						pa.Table       )	->							pa.Table:
           if self.config.features is not None:
                 __A		 =   self.config.features.arrow_schema
                 if all(not require_storage_cast(lowercase__       ) for feature in self.config.features.values()       ):
                       # cheaper cast
                       __A		 =   pa_table.cast(lowercase__       )
                 else:
                       # more expensive cast; allows str <-> int/float or str to Audio for example
                       __A		 =   table_cast(lowercase__					,					lowercase__       )
                 return pa_table
           else:
                 return pa_table.cast(pa.schema({"text": pa.string()}       )       )






     def      _UpperCamelCase (self     :						List[Any]					,					lowercase__     :						Optional[Any]       )	->							Tuple:
           __A		 =   list(self.config.features       ) if self.config.features is not None else ["text"]
           for file_idx, file in enumerate(itertools.chain.from_iterable(lowercase__       )       ):
                 # open in text mode, by default translates universal newlines ("\n", "\r\n" and "\r") into "\n"
                 with open(lowercase__					,					encoding=self.config.encoding					,					errors=self.config.errors       ) as f:
                       if self.config.sample_by == "line":
                             __A		 =   0
                             while True:
                                   __A		 =   f.read(self.config.chunksize       )
                                   if not batch:
                                         break
                                   batch += f.readline()  # finish current line
                                   # StringIO.readlines, by default splits only on "\n" (and keeps line breaks)
                                   __A		 =   StringIO(lowercase__       ).readlines()
                                   if not self.config.keep_linebreaks:
                                         __A		 =   [line.rstrip("\n"       ) for line in batch]
                                   __A		 =   pa.Table.from_arrays([pa.array(lowercase__       )]					,					names=lowercase__       )
                                   # Uncomment for debugging (will print the Arrow table size and elements)
                                   # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                                   # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                                   yield (file_idx, batch_idx), self._cast_table(lowercase__       )
                                   batch_idx += 1
                       elif self.config.sample_by == "paragraph":
                             __A		 =   0
                             __A		 =   ""
                             while True:
                                   __A		 =   f.read(self.config.chunksize       )
                                   if not new_batch:
                                         break
                                   batch += new_batch
                                   batch += f.readline()  # finish current line
                                   __A		 =   batch.split("\n\n"       )
                                   __A		 =   pa.Table.from_arrays(
                                       [pa.array([example for example in batch[:-1] if example]       )]					,					names=lowercase__       )
                                   # Uncomment for debugging (will print the Arrow table size and elements)
                                   # logger.warning(f"pa_table: {pa_table} num rows: {pa_table.num_rows}")
                                   # logger.warning('\n'.join(str(pa_table.slice(i, 1).to_pydict()) for i in range(pa_table.num_rows)))
                                   yield (file_idx, batch_idx), self._cast_table(lowercase__       )
                                   batch_idx += 1
                                   __A		 =   batch[-1]
                             if batch:
                                   __A		 =   pa.Table.from_arrays([pa.array([batch]       )]					,					names=lowercase__       )
                                   yield (file_idx, batch_idx), self._cast_table(lowercase__       )
                       elif self.config.sample_by == "document":
                             __A		 =   f.read()
                             __A		 =   pa.Table.from_arrays([pa.array([text]       )]					,					names=lowercase__       )
                             yield file_idx, self._cast_table(lowercase__       )










'''simple docstring'''







from __future__ import annotations


def     _UpperCamelCase				(  snake_case__				):
      __A		 =   [0] * len(snake_case__				)
      for i in range(1				,      len(snake_case__				)				):
            __A		 =   duration_times[i - 1] + waiting_times[i - 1]
      return waiting_times


def     _UpperCamelCase				(  snake_case__				,      snake_case__				):
      return [
          duration_time + waiting_times[i]
          for i, duration_time in enumerate(snake_case__				)
      ]


def     _UpperCamelCase				(  snake_case__				):
      return sum(snake_case__				) / len(snake_case__				)


def     _UpperCamelCase				(  snake_case__				):
      return sum(snake_case__				) / len(snake_case__				)


if __name__ == "__main__":
       # process id's
       __A   :							List[str]     	=						[1, 2, 3]

       # ensure that we actually have processes
       if len(processes) == 0:
              print('Zero amount of processes')
              raise SystemExit(0)

       # duration time of all processes
       __A   :							List[Any]     	=						[1_9, 8, 9]

       # ensure we can match each id to a duration time
       if len(duration_times) != len(processes):
              print('Unable to match all id\'s with their duration time')
              raise SystemExit(0)

       # get the waiting times and the turnaround times
       __A   :							Dict     	=						calculate_waiting_times(duration_times)
       __A   :							Optional[int]     	=						calculate_turnaround_times(duration_times, waiting_times)

       # get the average times
       __A   :							Dict     	=						calculate_average_waiting_time(waiting_times)
       __A   :							Tuple     	=						calculate_average_turnaround_time(turnaround_times)

       # print all the results
       print('Process ID\tDuration Time\tWaiting Time\tTurnaround Time')
       for i, process in enumerate(processes):
              print(
                  F"""{process}\t\t{duration_times[i]}\t\t{waiting_times[i]}\t\t"""
                  F"""{turnaround_times[i]}"""
              )
       print(F"""Average waiting time = {average_waiting_time}""")
       print(F"""Average turn around time = {average_turnaround_time}""")


