code: def test_csv_read(
      ray_start_regular_shared, fs, data_path, endpoint_url
  ):
      if endpoint_url is None:
          storage_options = {}
      else:
          storage_options = dict(
              client_kwargs=dict(endpoint_url=endpoint_url)
          )
      # Single file.
      df1 = pd.DataFrame({"one": [1, 2, 3], "two": ["a", "b", "c"]})
      path1 = os.path.join(data_path, "test1.csv")
      df1.to_csv(path1, index=False, storage_options=storage_options)
      ds = ray.data.read_csv(path1, filesystem=fs, partitioning=None)
      dsdf = ds.to_pandas()
      assert df1.equals(dsdf)
      # Test metadata ops.
      assert ds.count() == 3
      assert ds.input_files() == [_unwrap_protocol(path1)]
      assert "{one: int64, two: string}" in str(ds), ds
  
      # Two files, parallelism=2.
      df2 = pd.DataFrame({"one": [4, 5, 6], "two": ["e", "f", "g"]})
      path2 = os.path.join(data_path, "test2.csv")
      df2.to_csv(path2, index=False, storage_options=storage_options)
      ds = ray.data.read_csv(
          [path1, path2],
          parallelism=2,
          filesystem=fs,
          partitioning=None,
      )
      dsdf = ds.to_pandas()
      df = pd.concat([df1, df2], ignore_index=True)
      assert df.equals(dsdf)
      # Test metadata ops.
      for block, meta in ds._plan.execute().get_blocks_with_metadata():
          BlockAccessor.for_block(
              ray.get(block)
          ).size_bytes() == meta.size_bytes
  
      # Three files, parallelism=2.
      df3 = pd.DataFrame({"one": [7, 8, 9], "two": ["h", "i", "j"]})
      path3 = os.path.join(data_path, "test3.csv")
      df3.to_csv(path3, index=False, storage_options=storage_options)
      ds = ray.data.read_csv(
          [path1, path2, path3],
          parallelism=2,
          filesystem=fs,
          partitioning=None,
      )
      df = pd.concat([df1, df2, df3], ignore_index=True)
      dsdf = ds.to_pandas()
      assert df.equals(dsdf)
  
      # Directory, two files.
      path = os.path.join(data_path, "test_csv_dir")
      if fs is None:
          os.mkdir(path)
      else:
          fs.create_dir(_unwrap_protocol(path))
      df1 = pd.DataFrame({"one": [1, 2, 3], "two": ["a", "b", "c"]})
      path1 = os.path.join(path, "data0.csv")
      df1.to_csv(path1, index=False, storage_options=storage_options)
      df2 = pd.DataFrame({"one": [4, 5, 6], "two": ["e", "f", "g"]})
      path2 = os.path.join(path, "data1.csv")
      df2.to_csv(path2, index=False, storage_options=storage_options)
      ds = ray.data.read_csv(path, filesystem=fs, partitioning=None)
      df = pd.concat([df1, df2], ignore_index=True)
      dsdf = ds.to_pandas()
      pd.testing.assert_frame_equal(df, dsdf)
      if fs is None:
          shutil.rmtree(path)
      else:
          fs.delete_dir(_unwrap_protocol(path))
  
      # Two directories, three files.
      path1 = os.path.join(data_path, "test_csv_dir1")
      path2 = os.path.join(data_path, "test_csv_dir2")
      if fs is None:
          os.mkdir(path1)
          os.mkdir(path2)
      else:
          fs.create_dir(_unwrap_protocol(path1))
          fs.create_dir(_unwrap_protocol(path2))
      df1 = pd.DataFrame({"one": [1, 2, 3], "two": ["a", "b", "c"]})
      file_path1 = os.path.join(path1, "data0.csv")
      df1.to_csv(
          file_path1, index=False, storage_options=storage_options
      )
      df2 = pd.DataFrame({"one": [4, 5, 6], "two": ["e", "f", "g"]})
      file_path2 = os.path.join(path2, "data1.csv")
      df2.to_csv(
          file_path2, index=False, storage_options=storage_options
      )
      df3 = pd.DataFrame({"one": [7, 8, 9], "two": ["h", "i", "j"]})
      file_path3 = os.path.join(path2, "data2.csv")
      df3.to_csv(
          file_path3, index=False, storage_options=storage_options
      )
      ds = ray.data.read_csv(
          [path1, path2], filesystem=fs, partitioning=None
      )
      df = pd.concat([df1, df2, df3], ignore_index=True)
      dsdf = ds.to_pandas()
      assert df.equals(dsdf)
      if fs is None:
          shutil.rmtree(path1)
          shutil.rmtree(path2)
      else:
          fs.delete_dir(_unwrap_protocol(path1))
          fs.delete_dir(_unwrap_protocol(path2))
  
      # Directory and file, two files.
      dir_path = os.path.join(data_path, "test_csv_dir")
      if fs is None:
          os.mkdir(dir_path)
      else:
          fs.create_dir(_unwrap_protocol(dir_path))
      df1 = pd.DataFrame({"one": [1, 2, 3], "two": ["a", "b", "c"]})
      path1 = os.path.join(dir_path, "data0.csv")
      df1.to_csv(path1, index=False, storage_options=storage_options)
      df2 = pd.DataFrame({"one": [4, 5, 6], "two": ["e", "f", "g"]})
      path2 = os.path.join(data_path, "data1.csv")
      df2.to_csv(path2, index=False, storage_options=storage_options)
      ds = ray.data.read_csv(
          [dir_path, path2], filesystem=fs, partitioning=None
      )
      df = pd.concat([df1, df2], ignore_index=True)
      dsdf = ds.to_pandas()
      assert df.equals(dsdf)
      if fs is None:
          shutil.rmtree(dir_path)
      else:
          fs.delete_dir(_unwrap_protocol(dir_path))
  
      # Directory, two files and non-csv file (test extension-based path filtering).
      path = os.path.join(data_path, "test_csv_dir")
      if fs is None:
          os.mkdir(path)
      else:
          fs.create_dir(_unwrap_protocol(path))
      df1 = pd.DataFrame({"one": [1, 2, 3], "two": ["a", "b", "c"]})
      path1 = os.path.join(path, "data0.csv")
      df1.to_csv(path1, index=False, storage_options=storage_options)
      df2 = pd.DataFrame({"one": [4, 5, 6], "two": ["e", "f", "g"]})
      path2 = os.path.join(path, "data1.csv")
      df2.to_csv(path2, index=False, storage_options=storage_options)
  
      # Add a file with a non-matching file extension. This file should be ignored.
      df_txt = pd.DataFrame({"foobar": [1, 2, 3]})
      df_txt.to_json(
          os.path.join(path, "foo.txt"),
          storage_options=storage_options,
      )
  
      ds = ray.data.read_csv(
          path,
          filesystem=fs,
          file_extensions=["csv"],
          partitioning=None,
      )
      assert ds.num_blocks() == 2
      df = pd.concat([df1, df2], ignore_index=True)
      dsdf = ds.to_pandas()
      assert df.equals(dsdf)
      if fs is None:
          shutil.rmtree(path)
      else:
          fs.delete_dir(_unwrap_protocol(path))
  
imports: import itertools
  import os
  import shutil
  from functools import partial
  import pandas
  import pyarrow
  import pyarrow.parquet
  import pytest
  from packaging.version import Version
  from pytest_lazyfixture import lazy_fixture
  import ray
  from ray.data.block import BlockAccessor
  from ray.data.datasource import BaseFileMetadataProvider, FastFileMetadataProvider, PartitionStyle, PathPartitionFilter
  from ray.data.datasource.file_based_datasource import FILE_SIZE_FETCH_PARALLELIZATION_THRESHOLD
  from ray.data.datasource.path_util import _unwrap_protocol
  from ray.data.tests.conftest import *
  from ray.data.tests.mock_http_server import *
  from ray.data.tests.test_partitioning import PathPartitionEncoder
  from ray.data.tests.util import Counter
  from ray.tests.conftest import *
label_desc: Use image node_id 3 for calling a global function with example usage: test_csv_read(ray_start_regular_shared, fs, data_path, endpoint_url) without return types