
"""simple docstring"""




import os
import sys
import warnings
from dataclasses import dataclass, field
from io import BytesIO
from typing import TYPE_CHECKING, Any, ClassVar, Dict, List, Optional, Union

import numpy as np
import pyarrow as pa

from .. import config
from ..download.streaming_download_manager import xopen
from ..table import array_cast
from ..utils.file_utils import is_local_path
from ..utils.py_utils import first_non_null_value, no_op_if_value_is_null, string_to_dict


if TYPE_CHECKING:
    import PIL.Image

    from .features import FeatureType


a		:       Optional[List[str]]     						=       None
a		:       Any     						=       '<' if sys.byteorder == 'little' else '>'
# Origin: https://github.com/python-pillow/Pillow/blob/698951e19e19972aeed56df686868f1329981c12/src/PIL/Image.py#L3126 minus "|i1" which values are not preserved correctly when saving and loading an image
a		:       List[str]     						=       [
    np.dtype('|b1'),
    np.dtype('|u1'),
    np.dtype('<u2'),
    np.dtype('>u2'),
    np.dtype('<i2'),
    np.dtype('>i2'),
    np.dtype('<u4'),
    np.dtype('>u4'),
    np.dtype('<i4'),
    np.dtype('>i4'),
    np.dtype('<f4'),
    np.dtype('>f4'),
    np.dtype('<f8'),
    np.dtype('>f8'),
]







@dataclass
class     lowercase:
     __snake_case:	bool						=     True
     __snake_case:	Optional[str]						=     None
     # Automatically constructed
     __snake_case:	ClassVar[str]						=     "PIL.Image.Image"
     __snake_case:	ClassVar[Any]						=     pa.struct({'bytes': pa.binary(), 'path': pa.string()}       )
     __snake_case:	str						=     field(default='Image'    ,						init=_lowercase    ,						repr=_lowercase       )



     def __call__(							self   )		->     Dict:







         """simple docstring"""



         return self.pa_type



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     dict:







         """simple docstring"""



         if config.PIL_AVAILABLE:
             import PIL.Image
         else:
             raise ImportError('To support encoding images, please install \'Pillow\'.'   )

         if isinstance(__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE   ):
             a__		=			np.array(__SCREAMING_SNAKE_CASE   )

         if isinstance(__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE   ):
             return {"path": value, "bytes": None}
         elif isinstance(__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE   ):
             return {"path": None, "bytes": value}
         elif isinstance(__SCREAMING_SNAKE_CASE     ,				np.ndarray   ):
             # convert the image array to PNG/TIFF bytes
             return encode_np_array(__SCREAMING_SNAKE_CASE   )
         elif isinstance(__SCREAMING_SNAKE_CASE     ,				PIL.Image.Image   ):
             # convert the PIL image to bytes (default format is PNG/TIFF)
             return encode_pil_image(__SCREAMING_SNAKE_CASE   )
         elif value.get('path'   ) is not None and os.path.isfile(value['path']   ):
             # we set "bytes": None to not duplicate the data if they're already available locally
             return {"bytes": None, "path": value.get('path'   )}
         elif value.get('bytes'   ) is not None or value.get('path'   ) is not None:
             # store the image bytes, and path is used to infer the image format using the file extension
             return {"bytes": value.get('bytes'   ), "path": value.get('path'   )}
         else:
             raise ValueError(
                 f'An image sample should have one of \'path\' or \'bytes\' but they are missing or None in {value}.'   )



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE=None   )		->     "PIL.Image.Image":







         """simple docstring"""



         if not self.decode:
             raise RuntimeError('Decoding is disabled for this feature. Please use Image(decode=True) instead.'   )

         if config.PIL_AVAILABLE:
             import PIL.Image
         else:
             raise ImportError('To support decoding images, please install \'Pillow\'.'   )

         if token_per_repo_id is None:
             a__		=			{}

         a__	,     a__		=			value['path'], value['bytes']
         if bytes_ is None:
             if path is None:
                 raise ValueError(f'An image should have one of \'path\' or \'bytes\' but both are None in {value}.'   )
             else:
                 if is_local_path(__SCREAMING_SNAKE_CASE   ):
                     a__		=			PIL.Image.open(__SCREAMING_SNAKE_CASE   )
                 else:
                     a__		=			path.split('::'   )[-1]
                     try:
                         a__		=			string_to_dict(__SCREAMING_SNAKE_CASE     ,				config.HUB_DATASETS_URL   )['repo_id']
                         a__		=			token_per_repo_id.get(__SCREAMING_SNAKE_CASE   )
                     except ValueError:
                         a__		=			None
                     with xopen(__SCREAMING_SNAKE_CASE     ,				'rb'     ,				use_auth_token=__SCREAMING_SNAKE_CASE   ) as f:
                         a__		=			BytesIO(f.read()   )
                     a__		=			PIL.Image.open(bytes_   )
         else:
             a__		=			PIL.Image.open(BytesIO(bytes_   )   )
         image.load()  # to avoid "Too many open files" errors
         return image



     def 			lowercase__  (							self   )		->     Union["FeatureType", Dict[str, "FeatureType"]]:







         """simple docstring"""



         from .features import Value

         return (
             self
             if self.decode
             else {
                 "bytes": Value('binary'   ),
                 "path": Value('string'   ),
             }
         )



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     pa.StructArray:







         """simple docstring"""



         if pa.types.is_string(storage.type   ):
             a__		=			pa.array([None] * len(__SCREAMING_SNAKE_CASE   )     ,				type=pa.binary()   )
             a__		=			pa.StructArray.from_arrays([bytes_array, storage]     ,				['bytes', 'path']     ,				mask=storage.is_null()   )
         elif pa.types.is_binary(storage.type   ):
             a__		=			pa.array([None] * len(__SCREAMING_SNAKE_CASE   )     ,				type=pa.string()   )
             a__		=			pa.StructArray.from_arrays([storage, path_array]     ,				['bytes', 'path']     ,				mask=storage.is_null()   )
         elif pa.types.is_struct(storage.type   ):
             if storage.type.get_field_index('bytes'   ) >= 0:
                 a__		=			storage.field('bytes'   )
             else:
                 a__		=			pa.array([None] * len(__SCREAMING_SNAKE_CASE   )     ,				type=pa.binary()   )
             if storage.type.get_field_index('path'   ) >= 0:
                 a__		=			storage.field('path'   )
             else:
                 a__		=			pa.array([None] * len(__SCREAMING_SNAKE_CASE   )     ,				type=pa.string()   )
             a__		=			pa.StructArray.from_arrays([bytes_array, path_array]     ,				['bytes', 'path']     ,				mask=storage.is_null()   )
         elif pa.types.is_list(storage.type   ):
             a__		=			pa.array(
                 [encode_np_array(np.array(__SCREAMING_SNAKE_CASE   )   )['bytes'] if arr is not None else None for arr in storage.to_pylist()]     ,				type=pa.binary()     ,				)
             a__		=			pa.array([None] * len(__SCREAMING_SNAKE_CASE   )     ,				type=pa.string()   )
             a__		=			pa.StructArray.from_arrays(
                 [bytes_array, path_array]     ,				['bytes', 'path']     ,				mask=bytes_array.is_null()   )
         return array_cast(__SCREAMING_SNAKE_CASE     ,				self.pa_type   )




     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     pa.StructArray:







         """simple docstring"""



         @no_op_if_value_is_null
         def path_to_bytes(__SCREAMING_SNAKE_CASE   ):
             with xopen(__SCREAMING_SNAKE_CASE     ,				'rb'   ) as f:
                 a__		=			f.read()
             return bytes_

         a__		=			pa.array(
             [
                 (path_to_bytes(x['path']   ) if x['bytes'] is None else x['bytes']) if x is not None else None
                 for x in storage.to_pylist()
             ]     ,				type=pa.binary()     ,				)
         a__		=			pa.array(
             [os.path.basename(__SCREAMING_SNAKE_CASE   ) if path is not None else None for path in storage.field('path'   ).to_pylist()]     ,				type=pa.string()     ,				)
         a__		=			pa.StructArray.from_arrays([bytes_array, path_array]     ,				['bytes', 'path']     ,				mask=bytes_array.is_null()   )
         return array_cast(__SCREAMING_SNAKE_CASE     ,				self.pa_type   )




def     __magic_name__		(					)     ->						List[str]:
    if config.PIL_AVAILABLE:
        import PIL.Image
    else:
        raise ImportError('To support encoding images, please install \'Pillow\'.'     )

    global _IMAGE_COMPRESSION_FORMATS
    if _IMAGE_COMPRESSION_FORMATS is None:
        PIL.Image.init()
        a__		=			list(set(PIL.Image.OPEN.keys()     ) & set(PIL.Image.SAVE.keys()     )     )
    return _IMAGE_COMPRESSION_FORMATS



def     __magic_name__		(					UpperCamelCase     :		"PIL.Image.Image"     )     ->						bytes:
    a__		=			BytesIO()
    if image.format in list_image_compression_formats():
        a__		=			image.format
    else:
        a__		=			'PNG' if image.mode in ['1', 'L', 'LA', 'RGB', 'RGBA'] else 'TIFF'
    image.save(UpperCamelCase							,		format=UpperCamelCase     )
    return buffer.getvalue()



def     __magic_name__		(					UpperCamelCase     :		"PIL.Image.Image"     )     ->						dict:
    if hasattr(UpperCamelCase							,		'filename'     ) and image.filename != "":
        return {"path": image.filename, "bytes": None}
    else:
        return {"path": None, "bytes": image_to_bytes(UpperCamelCase     )}



def     __magic_name__		(					UpperCamelCase     :		np.ndarray     )     ->						dict:
    if config.PIL_AVAILABLE:
        import PIL.Image
    else:
        raise ImportError('To support encoding images, please install \'Pillow\'.'     )

    a__		=			array.dtype
    a__		=			dtype.byteorder if dtype.byteorder != '=' else _NATIVE_BYTEORDER
    a__		=			dtype.kind
    a__		=			dtype.itemsize

    a__		=			None

    # Multi-channel array case (only np.dtype("|u1") is allowed)
    if array.shape[2:]:
        a__		=			np.dtype('|u1'     )
        if dtype_kind not in ["u", "i"]:
            raise TypeError(
                f'Unsupported array dtype {dtype} for image encoding. Only {dest_dtype} is supported for multi-channel arrays.'     )
        if dtype is not dest_dtype:
            warnings.warn(f'Downcasting array dtype {dtype} to {dest_dtype} to be compatible with \'Pillow\''     )
    # Exact match
    elif dtype in _VALID_IMAGE_ARRAY_DTPYES:
        a__		=			dtype
    else:  # Downcast the type within the kind (np.can_cast(from_type, to_type, casting="same_kind") doesn't behave as expected, so do it manually)
        while dtype_itemsize >= 1:
            a__		=			dtype_byteorder + dtype_kind + str(UpperCamelCase     )
            a__		=			np.dtype(UpperCamelCase     )
            if dest_dtype in _VALID_IMAGE_ARRAY_DTPYES:
                warnings.warn(f'Downcasting array dtype {dtype} to {dest_dtype} to be compatible with \'Pillow\''     )
                break
            else:
                dtype_itemsize //= 2

    if dest_dtype is None:
        raise TypeError(
            f'Cannot convert dtype {dtype} to a valid image dtype. Valid image dtypes: {_VALID_IMAGE_ARRAY_DTPYES}'     )
    a__		=			PIL.Image.fromarray(array.astype(UpperCamelCase     )     )
    return {"path": None, "bytes": image_to_bytes(UpperCamelCase     )}



def     __magic_name__		(					UpperCamelCase     :		Union[List[str], List[dict], List[np.ndarray], List["PIL.Image.Image"]]     )     ->						List[dict]:
    if config.PIL_AVAILABLE:
        import PIL.Image
    else:
        raise ImportError('To support encoding images, please install \'Pillow\'.'     )

    if objs:
        a__	,     a__		=			first_non_null_value(UpperCamelCase     )
        if isinstance(UpperCamelCase							,		UpperCamelCase     ):
            return [{"path": obj, "bytes": None} if obj is not None else None for obj in objs]
        if isinstance(UpperCamelCase							,		np.ndarray     ):
            a__		=			no_op_if_value_is_null(UpperCamelCase     )
            return [obj_to_image_dict_func(UpperCamelCase     ) for obj in objs]
        elif isinstance(UpperCamelCase							,		PIL.Image.Image     ):
            a__		=			no_op_if_value_is_null(UpperCamelCase     )
            return [obj_to_image_dict_func(UpperCamelCase     ) for obj in objs]
        else:
            return objs
    else:
        return objs




"""simple docstring"""




from collections import deque







class     lowercase:



     def __init__(							self     ,				__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE   )		->     None:







         """simple docstring"""



         a__		=			process_name  # process name
         a__		=			arrival_time  # arrival time of the process
         # completion time of finished process or last interrupted time
         a__		=			arrival_time
         a__		=			burst_time  # remaining burst time
         a__		=			0  # total time of the process wait in ready queue
         a__		=			0  # time from arrival time to completion time







class     lowercase:



     def __init__(							self     ,				__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE     ,				)		->     None:







         """simple docstring"""



         a__		=			number_of_queues
         # time slice of queues that round robin algorithm applied
         a__		=			time_slices
         # unfinished process is in this ready_queue
         a__		=			queue
         # current time
         a__		=			current_time
         # finished process is in this sequence queue
         a__		=			deque()



     def 			lowercase__  (							self   )		->     list[str]:







         """simple docstring"""



         a__		=			[]
         for i in range(len(self.finish_queue   )   ):
             sequence.append(self.finish_queue[i].process_name   )
         return sequence



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     list[int]:







         """simple docstring"""



         a__		=			[]
         for i in range(len(__SCREAMING_SNAKE_CASE   )   ):
             waiting_times.append(queue[i].waiting_time   )
         return waiting_times



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     list[int]:







         """simple docstring"""



         a__		=			[]
         for i in range(len(__SCREAMING_SNAKE_CASE   )   ):
             turnaround_times.append(queue[i].turnaround_time   )
         return turnaround_times



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     list[int]:







         """simple docstring"""



         a__		=			[]
         for i in range(len(__SCREAMING_SNAKE_CASE   )   ):
             completion_times.append(queue[i].stop_time   )
         return completion_times



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     list[int]:







         """simple docstring"""



         return [q.burst_time for q in queue]



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     int:







         """simple docstring"""



         process.waiting_time += self.current_time - process.stop_time
         return process.waiting_time



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE   )		->     deque[Process]:







         """simple docstring"""



         a__		=			deque()  # sequence deque of finished process
         while len(__SCREAMING_SNAKE_CASE   ) != 0:
             a__		=			ready_queue.popleft()  # current process

             # if process's arrival time is later than current time, update current time
             if self.current_time < cp.arrival_time:
                 self.current_time += cp.arrival_time

             # update waiting time of current process
             self.update_waiting_time(__SCREAMING_SNAKE_CASE   )
             # update current time
             self.current_time += cp.burst_time
             # finish the process and set the process's burst-time 0
             a__		=			0
             # set the process's turnaround time because it is finished
             a__		=			self.current_time - cp.arrival_time
             # set the completion time
             a__		=			self.current_time
             # add the process to queue that has finished queue
             finished.append(__SCREAMING_SNAKE_CASE   )

         self.finish_queue.extend(__SCREAMING_SNAKE_CASE   )  # add finished process to finish queue
         # FCFS will finish all remaining processes
         return finished



     def 			lowercase__  (							self     ,				__SCREAMING_SNAKE_CASE     ,				__SCREAMING_SNAKE_CASE   )		->     tuple[deque[Process], deque[Process]]:







         """simple docstring"""



         a__		=			deque()  # sequence deque of terminated process
         # just for 1 cycle and unfinished processes will go back to queue
         for _ in range(len(__SCREAMING_SNAKE_CASE   )   ):
             a__		=			ready_queue.popleft()  # current process

             # if process's arrival time is later than current time, update current time
             if self.current_time < cp.arrival_time:
                 self.current_time += cp.arrival_time

             # update waiting time of unfinished processes
             self.update_waiting_time(__SCREAMING_SNAKE_CASE   )
             # if the burst time of process is bigger than time-slice
             if cp.burst_time > time_slice:
                 # use CPU for only time-slice
                 self.current_time += time_slice
                 # update remaining burst time
                 cp.burst_time -= time_slice
                 # update end point time
                 a__		=			self.current_time
                 # locate the process behind the queue because it is not finished
                 ready_queue.append(__SCREAMING_SNAKE_CASE   )
             else:
                 # use CPU for remaining burst time
                 self.current_time += cp.burst_time
                 # set burst time 0 because the process is finished
                 a__		=			0
                 # set the finish time
                 a__		=			self.current_time
                 # update the process' turnaround time because it is finished
                 a__		=			self.current_time - cp.arrival_time
                 # add the process to queue that has finished queue
                 finished.append(__SCREAMING_SNAKE_CASE   )

         self.finish_queue.extend(__SCREAMING_SNAKE_CASE   )  # add finished process to finish queue
         # return finished processes queue and remaining processes queue
         return finished, ready_queue




     def 			lowercase__  (							self   )		->     deque[Process]:







         """simple docstring"""



         for i in range(self.number_of_queues - 1   ):
             a__	,     a__		=			self.round_robin(
                 self.ready_queue     ,				self.time_slices[i]   )
         #  the last queue has first_come_first_served algorithm
         self.first_come_first_served(self.ready_queue   )

         return self.finish_queue


if __name__ == "__main__":
    import doctest

    a		:       List[str]     						=       Process('P1', 0, 53)
    a		:       Optional[int]     						=       Process('P2', 0, 17)
    a		:       Union[str, Any]     						=       Process('P3', 0, 68)
    a		:       Optional[int]     						=       Process('P4', 0, 24)
    a		:       Optional[int]     						=       3
    a		:       Optional[Any]     						=       [17, 25]
    a		:       Union[str, Any]     						=       deque([Pa, Pa, Pa, Pa])

    if len(time_slices) != number_of_queues - 1:
        raise SystemExit(0)

    doctest.testmod(extraglobs={'queue': deque([Pa, Pa, Pa, Pa])})

    a		:       Union[str, Any]     						=       Process('P1', 0, 53)
    a		:       Optional[int]     						=       Process('P2', 0, 17)
    a		:       Optional[Any]     						=       Process('P3', 0, 68)
    a		:       str     						=       Process('P4', 0, 24)
    a		:       Optional[Any]     						=       3
    a		:       Tuple     						=       [17, 25]
    a		:       int     						=       deque([Pa, Pa, Pa, Pa])
    a		:       Tuple     						=       MLFQ(number_of_queues, time_slices, queue, 0)
    a		:       Optional[int]     						=       mlfq.multi_level_feedback_queue()

    # print total waiting times of processes(P1, P2, P3, P4)
    print(
        F'''waiting time:\
        \t\t\t{MLFQ.calculate_waiting_time(mlfq, [Pa, Pa, Pa, Pa])}'''
    )
    # print completion times of processes(P1, P2, P3, P4)
    print(
        F'''completion time:\
        \t\t{MLFQ.calculate_completion_time(mlfq, [Pa, Pa, Pa, Pa])}'''
    )
    # print total turnaround times of processes(P1, P2, P3, P4)
    print(
        F'''turnaround time:\
        \t\t{MLFQ.calculate_turnaround_time(mlfq, [Pa, Pa, Pa, Pa])}'''
    )
    # print sequence of finished processes
    print(
        F'''sequence of finished processes:\
        {mlfq.calculate_sequence_of_finish_queue()}'''
    )


