Added -delimiter flag for csv input. Other fixes

                      help="Name of the dataset.")

  parser.add_argument("--out", required=1,

                      help="Folder to generate processed dataset in.")

  parser.add_argument("--delimiter", default="\t",

                      help="Delimiter in csv file")

  return parser.parse_args(input_args)

def generate_directories(name, out):

  field_types = ["string", "string", "float", "float", "float", "float",

      "float", "float", "float", "float"]

def get_rows(input_file, input_type):

def get_rows(input_file, input_type, delimiter):

  """Returns an iterator over all rows in input_file"""

  # TODO(rbharath): This function loads into memory, which can be painful. The

  # right option here might be to create a class which internally handles data

    return p.iter_rows()

  elif input_type == "csv":

    with open(input_file, "rb") as f:

      reader = csv.reader(f, delimiter=",")

      reader = csv.reader(f, delimiter=delimiter)

      return [row for row in reader]

  elif input_type == "pandas":

    with gzip.open(input_file) as f:

    return data 

def generate_targets(input_file, input_type, fields, field_types, out_pkl,

    out_sdf):

    out_sdf, delimiter):

  """Process input data file."""

  rows, mols, smiles = [], [], SmilesGenerator()

  for row_index, raw_row in enumerate(get_rows(input_file, input_type)):

  for row_index, raw_row in enumerate(get_rows(input_file, input_type, delimiter)):

    print row_index

    print raw_row

    # Skip row labels.

def main():

  args = parse_args()

  if len(args.fields) != len(args.field_types):

    raise ValueError("number of fields does not equal number of field types")

  out_pkl, out_sdf = generate_directories(args.name, args.out)

  generate_targets(args.input_file, args.input_type, args.fields,

      args.field_types, out_pkl, out_sdf)

      args.field_types, out_pkl, out_sdf, args.delimiter)

  generate_fingerprints(args.name, args.out)