original_docstring: 
      Take csv files with SMILES + properties and use them to crea files
      with just the SMILES strings.
      Args:
        csv_folder (str): path to the folder in which we will save oru
          csv files with the SMILES, properties and training splits.
      Returns:
        None
      
docstring: Take csv files with SMILES + properties and use them to crea files
  with just the SMILES strings.
docstring_tokens: Take csv files with SMILES + properties and use them to crea files with just the SMILES strings .
code: def add_just_smiles(csv_folder):
      """
      Take csv files with SMILES + properties and use them to crea files
      with just the SMILES strings.
      Args:
        csv_folder (str): path to the folder in which we will save oru
          csv files with the SMILES, properties and training splits.
      Returns:
        None
      """
  
      for name in ['train', 'val', 'test']:
          path = os.path.join(csv_folder, name + '.csv')
          smiles_list = []
  
          with open(path) as csvfile:
              readCSV = csv.reader(csvfile, delimiter=',')
              for i, row in enumerate(readCSV):
                  if i == 0:
                      continue
                  smiles_list.append(row[0])
  
          # save to "train_smiles.csv", "val_smiles.csv", etc.
          smiles_path = os.path.join(csv_folder, f"{name}_smiles.csv")
          columns = ["smiles"]
          dict_data = [{"smiles": smiles} for smiles in smiles_list]
  
          with open(smiles_path, 'w') as csvfile:
              writer = csv.DictWriter(csvfile, fieldnames=columns)
              writer.writeheader()
              for data in dict_data:
                  writer.writerow(data)
code_tokens: def add_just_smiles ( csv_folder ) : for name in [ 'train' , 'val' , 'test' ] : path = os . path . join ( csv_folder , name + '.csv' ) smiles_list = [ ] with open ( path ) as csvfile : readCSV = csv . reader ( csvfile , delimiter = ',' ) for i , row in enumerate ( readCSV ) : if i == 0 : continue smiles_list . append ( row [ 0 ] ) smiles_path = os . path . join ( csv_folder , f"{name}_smiles.csv" ) columns = [ "smiles" ] dict_data = [ { "smiles" : smiles } for smiles in smiles_list ] with open ( smiles_path , 'w' ) as csvfile : writer = csv . DictWriter ( csvfile , fieldnames = columns ) writer . writeheader ( ) for data in dict_data : writer . writerow ( data )
short_docstring: Take csv files with SMILES + properties and use them to crea files
  with just the SMILES strings.
short_docstring_tokens: Take csv files with SMILES + properties and use them to crea files with just the SMILES strings .
comment: """
      Take csv files with SMILES + properties and use them to crea files
      with just the SMILES strings.
      Args:
        csv_folder (str): path to the folder in which we will save oru
          csv files with the SMILES, properties and training splits.
      Returns:
        None
      """$SEP$# save to "train_smiles.csv", "val_smiles.csv", etc.