code: def test_read_csv(self):
      with self.csv_file(self.csv_text) as fn:
  
          def check(
              header="infer", names=None, usecols=None, index_col=None
          ):
              expected = pd.read_csv(
                  fn,
                  header=header,
                  names=names,
                  usecols=usecols,
                  index_col=index_col,
              )
              actual = ps.read_csv(
                  fn,
                  header=header,
                  names=names,
                  usecols=usecols,
                  index_col=index_col,
              )
              self.assert_eq(expected, actual, almost=True)
  
          check()
          check(header=0)
          check(header=None)
          check(names=["n", "a"])
          check(names=[("x", "n"), ("y", "a")])
          check(names=[10, 20])
          check(header=0, names=["n", "a"])
          check(usecols=[1])
          check(usecols=[1, 0])
          check(usecols=["amount"])
          check(usecols=["amount", "name"])
          check(usecols=[])
          check(usecols=[1, 1])
          check(usecols=["amount", "amount"])
          check(header=None, usecols=[1])
          check(names=["n", "a"], usecols=["a"])
          check(header=None, names=["n", "a"], usecols=["a"])
          check(index_col=["amount"])
          check(header=None, index_col=[1])
          check(names=["n", "a"], index_col=["a"])
          check(names=["n", "a"], index_col="a")
  
          # check with pyspark patch.
          expected = pd.read_csv(fn)
          actual = ps.read_csv(fn)
          self.assert_eq(expected, actual, almost=True)
  
          self.assertRaisesRegex(
              ValueError,
              "non-unique",
              lambda: ps.read_csv(fn, names=["n", "n"]),
          )
          self.assertRaisesRegex(
              ValueError,
              "does not match the number.*3",
              lambda: ps.read_csv(fn, names=["n", "a", "b"]),
          )
          self.assertRaisesRegex(
              ValueError,
              "does not match the number.*3",
              lambda: ps.read_csv(fn, header=0, names=["n", "a", "b"]),
          )
          self.assertRaisesRegex(
              ValueError,
              "Usecols do not match.*3",
              lambda: ps.read_csv(fn, usecols=[1, 3]),
          )
          self.assertRaisesRegex(
              ValueError,
              "Usecols do not match.*col",
              lambda: ps.read_csv(fn, usecols=["amount", "col"]),
          )
          self.assertRaisesRegex(
              ValueError,
              "Unknown header argument 1",
              lambda: ps.read_csv(fn, header="1"),
          )
          expected_error_message = (
              "'usecols' must either be list-like of all strings, "
              "all unicode, all integers or a callable."
          )
          self.assertRaisesRegex(
              ValueError,
              expected_error_message,
              lambda: ps.read_csv(fn, usecols=[1, "amount"]),
          )
  
          # check with index_col
          expected = pd.read_csv(fn).set_index("name")
          actual = ps.read_csv(fn, index_col="name")
          self.assert_eq(expected, actual, almost=True)
  
imports: import os
  from contextlib import contextmanager
  import pandas
  import numpy
  from pyspark import pandas
  from pyspark.testing.pandasutils import PandasOnSparkTestCase, TestUtils
label_desc: Use image node_id 8 for calling the CsvTestsMixin obj's underlying member method code with example usage: obj.test_read_csv() without return types