"""simple docstring"""



import copy
import os
import tempfile
from unittest import TestCase
from unittest.mock import patch

import numpy as np
import pyarrow as pa
import pyarrow.parquet as pq
import pytest

from datasets.arrow_writer import ArrowWriter, OptimizedTypedSequence, ParquetWriter, TypedSequence
from datasets.features import ArrayaD, ClassLabel, Features, Image, Value
from datasets.features.features import ArrayaDExtensionType, cast_to_python_objects
from datasets.keyhash import DuplicatedKeysError, InvalidKeyError

from .utils import require_pil






class 				snake_case__     (   snake_case_   ):


 def 		a__ (				self		):
        __a     				=  pa.array(TypedSequence([1, 2, 3]		)		)
        self.assertEqual(arr.type  ,						pa.intaa()		)


 def 		a__ (				self		):
        with self.assertRaises(lowerCamelCase		):
               __a     				=  pa.array(TypedSequence([1, 2, 3]		)  ,						type=pa.intaa()		)


 def 		a__ (				self		):
        with self.assertRaises(lowerCamelCase		):
               __a     				=  pa.array(TypedSequence([1, 2, 3]  ,						try_type=Value("bool"		)  ,						type=Value("int64"		)		)		)


 def 		a__ (				self		):
        __a     				=  pa.array(TypedSequence([1, 2, 3]  ,						type=Value("int32"		)		)		)
        self.assertEqual(arr.type  ,						pa.intaa()		)


 def 		a__ (				self		):
        with self.assertRaises((TypeError, pa.lib.ArrowInvalid)		):
               __a     				=  pa.array(TypedSequence(["foo", "bar"]  ,						type=Value("int64"		)		)		)


 def 		a__ (				self		):
        __a     				=  pa.array(TypedSequence([1, 2, 3]  ,						try_type=Value("int32"		)		)		)
        self.assertEqual(arr.type  ,						pa.intaa()		)


 def 		a__ (				self		):
        __a     				=  pa.array(TypedSequence(["foo", "bar"]  ,						try_type=Value("int64"		)		)		)
        self.assertEqual(arr.type  ,						pa.string()		)


 def 		a__ (				self		):
        __a     				=  pa.array(TypedSequence([[[1, 2, 3]]]  ,						type=ArrayaD((1, 3)  ,						"int64"		)		)		)
        self.assertEqual(arr.type  ,						ArrayaDExtensionType((1, 3)  ,						"int64"		)		)


 def 		a__ (				self		):
        with self.assertRaises((TypeError, pa.lib.ArrowInvalid)		):
               __a     				=  pa.array(TypedSequence(["foo", "bar"]  ,						type=ArrayaD((1, 3)  ,						"int64"		)		)		)


 def 		a__ (				self		):
        __a     				=  pa.array(TypedSequence([[[1, 2, 3]]]  ,						try_type=ArrayaD((1, 3)  ,						"int64"		)		)		)
        self.assertEqual(arr.type  ,						ArrayaDExtensionType((1, 3)  ,						"int64"		)		)


 def 		a__ (				self		):
        __a     				=  pa.array(TypedSequence(["foo", "bar"]  ,						try_type=ArrayaD((1, 3)  ,						"int64"		)		)		)
        self.assertEqual(arr.type  ,						pa.string()		)






 @require_pil
 def 		a__ (				self		):
        import PIL.Image

        __a     				=  PIL.Image.fromarray(np.arange(10  ,						dtype=np.uinta		).reshape(2  ,						5		)		)
        with patch(
            "datasets.arrow_writer.cast_to_python_objects"  ,						side_effect=lowerCamelCase		) as mock_cast_to_python_objects:
               __a     				=  pa.array(TypedSequence([{"path": None, "bytes": b"image_bytes"}, pil_image]  ,						type=Image()		)		)
               __a				, __a     				=  mock_cast_to_python_objects.call_args_list[-1]
               self.assertIn("optimize_list_casting"  ,						lowerCamelCase		)
               self.assertFalse(kwargs["optimize_list_casting"]		)



def 					_lowerCamelCase(					a ,  a							):
       __a     				=  pa.BufferReader(a							) if isinstance(a ,  pa.Buffer							) else pa.memory_map(a							)
       __a     				=  pa.ipc.open_stream(a							)
       __a     				=  f.read_all()
       assert len(pa_table.to_batches()							) == expected_num_chunks
       assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}
       del pa_table



@pytest.mark.parametrize("writer_batch_size" ,  [None, 1, 1_0]							)
@pytest.mark.parametrize(
    "fields" ,  [None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]							)
def 					_lowerCamelCase(					a ,  a							):
       __a     				=  pa.BufferOutputStream()
       __a     				=  pa.schema(a							) if fields else None
       with ArrowWriter(stream=a ,  schema=a ,  writer_batch_size=a							) as writer:
              writer.write({"col_1": "foo", "col_2": 1}							)
              writer.write({"col_1": "bar", "col_2": 2}							)
              __a				, __a     				=  writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       if not fields:
              __a     				=  {"col_1": pa.string(), "col_2": pa.intaa()}
       assert writer._schema == pa.schema(a ,  metadata=writer._schema.metadata							)
       _check_output(output.getvalue() ,  expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)



def 					_lowerCamelCase(					):
       __a     				=  pa.BufferOutputStream()
       __a     				=  Features({"labels": ClassLabel(names=["neg", "pos"]							)}							)
       with ArrowWriter(stream=a ,  features=a							) as writer:
              writer.write({"labels": 0}							)
              writer.write({"labels": 1}							)
              __a				, __a     				=  writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       assert writer._schema == features.arrow_schema
       assert writer._schema.metadata == features.arrow_schema.metadata
       __a     				=  pa.BufferReader(output.getvalue()							)
       __a     				=  pa.ipc.open_stream(a							)
       __a     				=  f.read_all()
       __a     				=  pa_table.schema
       assert pa_table.num_rows == 2
       assert schema == features.arrow_schema
       assert schema.metadata == features.arrow_schema.metadata
       assert features == Features.from_arrow_schema(a							)



@pytest.mark.parametrize("writer_batch_size" ,  [None, 1, 1_0]							)
def 					_lowerCamelCase(					a							):
       __a     				=  pa.BufferOutputStream()
       with ArrowWriter(
           stream=a ,  writer_batch_size=a ,  hash_salt="split_name" ,  check_duplicates=a ,  ) as writer:
              with pytest.raises(a							):
                     writer.write({"col_1": "foo", "col_2": 1} ,  key=[1, 2]							)
                     __a				, __a     				=  writer.finalize()



@pytest.mark.parametrize("writer_batch_size" ,  [None, 2, 1_0]							)
def 					_lowerCamelCase(					a							):
       __a     				=  pa.BufferOutputStream()
       with ArrowWriter(
           stream=a ,  writer_batch_size=a ,  hash_salt="split_name" ,  check_duplicates=a ,  ) as writer:
              with pytest.raises(a							):
                     writer.write({"col_1": "foo", "col_2": 1} ,  key=1_0							)
                     writer.write({"col_1": "bar", "col_2": 2} ,  key=1_0							)
                     __a				, __a     				=  writer.finalize()



@pytest.mark.parametrize("writer_batch_size" ,  [None, 2, 1_0]							)
def 					_lowerCamelCase(					a							):
       __a     				=  pa.BufferOutputStream()
       with ArrowWriter(
           stream=a ,  writer_batch_size=a ,  hash_salt="split_name" ,  check_duplicates=a ,  ) as writer:
              writer.write({"col_1": "foo", "col_2": 1} ,  key=1							)
              writer.write({"col_1": "bar", "col_2": 2} ,  key=2							)
              __a				, __a     				=  writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       _check_output(output.getvalue() ,  expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)



@pytest.mark.parametrize("writer_batch_size" ,  [None, 1, 1_0]							)
@pytest.mark.parametrize(
    "fields" ,  [None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]							)
def 					_lowerCamelCase(					a ,  a							):
       __a     				=  pa.BufferOutputStream()
       __a     				=  pa.schema(a							) if fields else None
       with ArrowWriter(stream=a ,  schema=a ,  writer_batch_size=a							) as writer:
              writer.write_batch({"col_1": ["foo", "bar"], "col_2": [1, 2]}							)
              writer.write_batch({"col_1": [], "col_2": []}							)
              __a				, __a     				=  writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       if not fields:
              __a     				=  {"col_1": pa.string(), "col_2": pa.intaa()}
       assert writer._schema == pa.schema(a ,  metadata=writer._schema.metadata							)
       _check_output(output.getvalue() ,  expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)



@pytest.mark.parametrize("writer_batch_size" ,  [None, 1, 1_0]							)
@pytest.mark.parametrize(
    "fields" ,  [None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]							)
def 					_lowerCamelCase(					a ,  a							):
       __a     				=  pa.BufferOutputStream()
       __a     				=  pa.schema(a							) if fields else None
       with ArrowWriter(stream=a ,  schema=a ,  writer_batch_size=a							) as writer:
              writer.write_table(pa.Table.from_pydict({"col_1": ["foo", "bar"], "col_2": [1, 2]}							)							)
              __a				, __a     				=  writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       if not fields:
              __a     				=  {"col_1": pa.string(), "col_2": pa.intaa()}
       assert writer._schema == pa.schema(a ,  metadata=writer._schema.metadata							)
       _check_output(output.getvalue() ,  expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)



@pytest.mark.parametrize("writer_batch_size" ,  [None, 1, 1_0]							)
@pytest.mark.parametrize(
    "fields" ,  [None, {"col_1": pa.string(), "col_2": pa.intaa()}, {"col_1": pa.string(), "col_2": pa.intaa()}]							)
def 					_lowerCamelCase(					a ,  a							):
       __a     				=  pa.BufferOutputStream()
       __a     				=  pa.schema(a							) if fields else None
       with ArrowWriter(stream=a ,  schema=a ,  writer_batch_size=a							) as writer:
              writer.write_row(pa.Table.from_pydict({"col_1": ["foo"], "col_2": [1]}							)							)
              writer.write_row(pa.Table.from_pydict({"col_1": ["bar"], "col_2": [2]}							)							)
              __a				, __a     				=  writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       if not fields:
              __a     				=  {"col_1": pa.string(), "col_2": pa.intaa()}
       assert writer._schema == pa.schema(a ,  metadata=writer._schema.metadata							)
       _check_output(output.getvalue() ,  expected_num_chunks=num_examples if writer_batch_size == 1 else 1							)



def 					_lowerCamelCase(					):
       with tempfile.TemporaryDirectory() as tmp_dir:
              __a     				=  {"col_1": pa.string(), "col_2": pa.intaa()}
              __a     				=  os.path.join(a ,  "test.arrow"							)
              with ArrowWriter(path=a ,  schema=pa.schema(a							)							) as writer:
                     writer.write_batch({"col_1": ["foo", "bar"], "col_2": [1, 2]}							)
                     __a				, __a     				=  writer.finalize()
              assert num_examples == 2
              assert num_bytes > 0
              assert writer._schema == pa.schema(a ,  metadata=writer._schema.metadata							)
              _check_output(a ,  1							)



def 					_lowerCamelCase(					a							):
       if pa.types.is_list(a							):
              return get_base_dtype(arr_type.value_type							)
       else:
              return arr_type



def 					_lowerCamelCase(					a ,  a							):
       if isinstance(lst[0] ,  a							):
              change_first_primitive_element_in_list(lst[0] ,  a							)
       else:
              __a     				=  value



@pytest.mark.parametrize("optimized_int_type, expected_dtype" ,  [(None, pa.intaa()), (Value("int32"							), pa.intaa())]							)
@pytest.mark.parametrize("sequence" ,  [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]							)
def 					_lowerCamelCase(					a ,  a ,  a							):
       __a     				=  pa.array(TypedSequence(a ,  optimized_int_type=a							)							)
       assert get_base_dtype(arr.type							) == expected_dtype



@pytest.mark.parametrize(
    "col, expected_dtype" ,  [
        ("attention_mask", pa.inta()),
        ("special_tokens_mask", pa.inta()),
        ("token_type_ids", pa.inta()),
        ("input_ids", pa.intaa()),
        ("other", pa.intaa()),
    ] ,  )
@pytest.mark.parametrize("sequence" ,  [[1, 2, 3], [[1, 2, 3]], [[[1, 2, 3]]]]							)
def 					_lowerCamelCase(					a ,  a ,  a							):
       # in range
       __a     				=  pa.array(OptimizedTypedSequence(a ,  col=a							)							)
       assert get_base_dtype(arr.type							) == expected_dtype

       # not in range
       if col != "other":
              # avoids errors due to in-place modifications
              __a     				=  copy.deepcopy(a							)
              __a     				=  np.iinfo(expected_dtype.to_pandas_dtype()							).max + 1
              change_first_primitive_element_in_list(a ,  a							)
              __a     				=  pa.array(OptimizedTypedSequence(a ,  col=a							)							)
              assert get_base_dtype(arr.type							) == pa.intaa()



@pytest.mark.parametrize("raise_exception" ,  [False, True]							)
def 					_lowerCamelCase(					a ,  a							):
       __a     				=  str(tmp_path / "dataset-train.arrow"							)
       try:
              with ArrowWriter(path=a							) as writer:
                     if raise_exception:
                            raise pa.lib.ArrowInvalid()
                     else:
                            writer.stream.close()
       except pa.lib.ArrowInvalid:
              pass
       finally:
              assert writer.stream.closed



def 					_lowerCamelCase(					a							):
       __a     				=  "mock://dataset-train.arrow"
       with ArrowWriter(path=a ,  storage_options=mockfs.storage_options							) as writer:
              assert isinstance(writer._fs ,  type(a							)							)
              assert writer._fs.storage_options == mockfs.storage_options
              writer.write({"col_1": "foo", "col_2": 1}							)
              writer.write({"col_1": "bar", "col_2": 2}							)
              __a				, __a     				=  writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       assert mockfs.exists(a							)



def 					_lowerCamelCase(					):
       __a     				=  pa.BufferOutputStream()
       with ParquetWriter(stream=a							) as writer:
              writer.write({"col_1": "foo", "col_2": 1}							)
              writer.write({"col_1": "bar", "col_2": 2}							)
              __a				, __a     				=  writer.finalize()
       assert num_examples == 2
       assert num_bytes > 0
       __a     				=  pa.BufferReader(output.getvalue()							)
       __a     				=  pq.read_table(a							)
       assert pa_table.to_pydict() == {"col_1": ["foo", "bar"], "col_2": [1, 2]}



@require_pil
@pytest.mark.parametrize("embed_local_files" ,  [False, True]							)
def 					_lowerCamelCase(					a ,  a							):
       import PIL.Image

       __a     				=  str(tmp_path / "test_image_rgb.jpg"							)
       PIL.Image.fromarray(np.zeros((5, 5) ,  dtype=np.uinta							)							).save(a ,  format="png"							)
       __a     				=  pa.BufferOutputStream()
       with ParquetWriter(
           stream=a ,  features=Features({"image": Image()}							) ,  embed_local_files=a							) as writer:
              writer.write({"image": image_path}							)
              writer.finalize()
       __a     				=  pa.BufferReader(output.getvalue()							)
       __a     				=  pq.read_table(a							)
       __a     				=  pa_table.to_pydict()
       if embed_local_files:
              assert isinstance(out["image"][0]["path"] ,  a							)
              with open(a ,  "rb"							) as f:
                     assert out["image"][0]["bytes"] == f.read()
       else:
              assert out["image"][0]["path"] == image_path
              assert out["image"][0]["bytes"] is None




def 					_lowerCamelCase(					):
       __a     				=  pa.schema([pa.field("col_1" ,  pa.string() ,  nullable=a							)]							)
       __a     				=  pa.BufferOutputStream()
       with ArrowWriter(stream=a							) as writer:
              writer._build_writer(inferred_schema=a							)
              assert writer._schema == pa.schema([pa.field("col_1" ,  pa.string()							)]							)

"""simple docstring"""



import math



def 					_lowerCamelCase(					a							):
       __a     				=  []
       __a     				=  2
       __a     				=  int(math.sqrt(a							)							)  # Size of every segment
       __a     				=  [True] * (end + 1)
       __a     				=  []

       while start <= end:
              if temp[start] is True:
                     in_prime.append(a							)
                     for i in range(start * start ,  end + 1 ,  a							):
                            __a     				=  False
              start += 1
       prime += in_prime

       __a     				=  end + 1
       __a     				=  min(2 * end ,  a							)

       while low <= n:
              __a     				=  [True] * (high - low + 1)
              for each in in_prime:
                     __a     				=  math.floor(low / each							) * each
                     if t < low:
                            t += each

                     for j in range(a ,  high + 1 ,  a							):
                            __a     				=  False

              for j in range(len(a							)							):
                     if temp[j] is True:
                            prime.append(j + low							)

              __a     				=  high + 1
              __a     				=  min(high + end ,  a							)

       return prime




print(sieve(10**6))
