How to use the awswrangler.s3 function in awswrangler

def test_delete_objects(bucket):
    write_fake_objects(bucket, "objs/", 3)
    awswrangler.s3.utils.delete_objects("s3://" + bucket + "/objs/", batch_size=2)

def test_delete_listed_objects(bucket):
    write_fake_objects(bucket, "objs/", 3)
    keys = awswrangler.s3.utils.list_objects("s3://" + bucket + "/objs/", batch_size=2)
    assert len(keys) == 3
    awswrangler.s3.utils.delete_listed_objects(bucket, keys, batch_size=2)
    keys = awswrangler.s3.utils.list_objects("s3://" + bucket + "/objs/", batch_size=2)
    assert len(keys) == 0

def test_s3_write_single(bucket, database, file_format):
    df = pd.read_csv("data_samples/micro.csv")
    awswrangler.s3.write(
        df=df,
        database=database,
        path=f"s3://{bucket}/test/",
        file_format=file_format,
        preserve_index=False,
        mode="overwrite",
        num_procs=1,
    )
    df2 = awswrangler.athena.read(database, "select * from test")
    assert len(df.index) == len(df2.index)

def test_s3_write(bucket, database, file_format):
    df = pd.read_csv("data_samples/micro.csv")
    awswrangler.s3.write(
        df=df,
        database=database,
        path=f"s3://{bucket}/test/",
        file_format=file_format,
        preserve_index=True,
        mode="overwrite",
    )
    df2 = awswrangler.athena.read(database, "select * from test")
    assert len(df.index) == len(df2.index)

def _data_to_s3_object_writer(dataframe,
                                  path,
                                  preserve_index,
                                  compression,
                                  session_primitives,
                                  file_format,
                                  cast_columns=None,
                                  extra_args=None,
                                  isolated_dataframe=False):
        fs = s3.get_fs(session_primitives=session_primitives)
        fs = pa.filesystem._ensure_filesystem(fs)
        s3.mkdir_if_not_exists(fs, path)

        if compression is None:
            compression_end = ""
        elif compression == "snappy":
            compression_end = ".snappy"
        elif compression == "gzip":
            compression_end = ".gz"
        else:
            raise InvalidCompression(compression)

        guid = pa.compat.guid()
        if file_format == "parquet":
            outfile = f"{guid}.parquet{compression_end}"
        elif file_format == "csv":
            outfile = f"{guid}.csv{compression_end}"
        else:

def _data_to_s3_object_writer(dataframe,
                                  path,
                                  preserve_index,
                                  compression,
                                  session_primitives,
                                  file_format,
                                  cast_columns=None,
                                  extra_args=None,
                                  isolated_dataframe=False):
        fs = s3.get_fs(session_primitives=session_primitives)
        fs = pa.filesystem._ensure_filesystem(fs)
        s3.mkdir_if_not_exists(fs, path)

        if compression is None:
            compression_end = ""
        elif compression == "snappy":
            compression_end = ".snappy"
        elif compression == "gzip":
            compression_end = ".gz"
        else:
            raise InvalidCompression(compression)

        guid = pa.compat.guid()
        if file_format == "parquet":
            outfile = f"{guid}.parquet{compression_end}"
        elif file_format == "csv":

:param usecols: Same as pandas.read_csv()
        :param dtype: Same as pandas.read_csv()
        :param sep: Same as pandas.read_csv()
        :param thousands: Same as pandas.read_csv()
        :param decimal: Same as pandas.read_csv()
        :param lineterminator: Same as pandas.read_csv()
        :param quotechar: Same as pandas.read_csv()
        :param quoting: Same as pandas.read_csv()
        :param escapechar: Same as pandas.read_csv()
        :param parse_dates: Same as pandas.read_csv()
        :param infer_datetime_format: Same as pandas.read_csv()
        :param encoding: Same as pandas.read_csv()
        :param converters: Same as pandas.read_csv()
        :return: Pandas Dataframe
        """
        metadata = s3.S3.head_object_with_retry(client=client_s3, bucket=bucket_name, key=key_path)
        logger.debug(f"metadata: {metadata}")
        total_size = metadata["ContentLength"]
        logger.debug(f"total_size: {total_size}")
        if total_size <= 0:
            raise EmptyS3Object(metadata)
        elif total_size <= max_result_size:
            yield Pandas._read_csv_once(client_s3=client_s3,
                                        bucket_name=bucket_name,
                                        key_path=key_path,
                                        header=header,
                                        names=names,
                                        usecols=usecols,
                                        dtype=dtype,
                                        sep=sep,
                                        thousands=thousands,
                                        decimal=decimal,