

"""simple docstring"""




import os

# Precomputes a list of the 100 first triangular numbers
__UpperCAmelCase =				[int(0.5 * n * (n + 1)) for n in range(1, 101)]
def   lowerCAmelCase						(					):
 '''simple docstring'''





 UpperCAmelCase__					:  List[str]					   =					os.path.dirname(os.path.realpath(__UpperCamelCase      )      )
 UpperCAmelCase__					:  List[Any]					   =					os.path.join(__UpperCamelCase							,    """words.txt"""      )

 UpperCAmelCase__					:  Dict					   =					''
 with open(__UpperCamelCase      ) as f:
  UpperCAmelCase__					:  List[str]					   =					f.readline()

 UpperCAmelCase__					:  Optional[Any]					   =					[word.strip("""\""""      ) for word in words.strip("""\r\n"""      ).split(""","""      )]
 UpperCAmelCase__					:  Dict					   =					[
     word
     for word in [sum(ord(__UpperCamelCase      ) - 64 for x in word      ) for word in words]
     if word in TRIANGULAR_NUMBERS
 ]
 return len(__UpperCamelCase      )


if __name__ == "__main__":
    print(solution())








"""simple docstring"""




from typing import List, Optional, TypeVar

from .arrow_dataset import Dataset, _concatenate_map_style_datasets, _interleave_map_style_datasets
from .dataset_dict import DatasetDict, IterableDatasetDict
from .info import DatasetInfo
from .iterable_dataset import IterableDataset, _concatenate_iterable_datasets, _interleave_iterable_datasets
from .splits import NamedSplit
from .utils import logging
from .utils.py_utils import Literal


__UpperCAmelCase =				logging.get_logger(__name__)


__UpperCAmelCase =				TypeVar('DatasetType', Dataset, IterableDataset)
def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase = None							,    __UpperCamelCase = None							,    __UpperCamelCase = None							,    __UpperCamelCase = None							,    __UpperCamelCase = "first_exhausted"							,    ):
 '''simple docstring'''





 from .arrow_dataset import Dataset
 from .iterable_dataset import IterableDataset

 if not datasets:
  raise ValueError("""Unable to interleave an empty list of datasets."""      )
 for i, dataset in enumerate(__UpperCamelCase      ):
  if not isinstance(__UpperCamelCase							,    (Dataset, IterableDataset)      ):
   if isinstance(__UpperCamelCase							,    (DatasetDict, IterableDatasetDict)      ):
    if not dataset:
     raise ValueError(
         F"Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} "
         """is an empty dataset dictionary."""      )
    raise ValueError(
        F"Dataset at position {i} has at least one split: {list(__UpperCamelCase      )}\n"
        F"Please pick one to interleave with the other datasets, for example: dataset['{next(iter(__UpperCamelCase      )      )}']"      )
   raise ValueError(
       F"Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(__UpperCamelCase      ).__name__}."      )
  if i == 0:
   UpperCAmelCase__   ,      UpperCAmelCase__					:  List[str]					   =					(
       (Dataset, IterableDataset) if isinstance(__UpperCamelCase							,    __UpperCamelCase      ) else (IterableDataset, Dataset)
   )
  elif not isinstance(__UpperCamelCase							,    __UpperCamelCase      ):
   raise ValueError(
       F"Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."      )
 if stopping_strategy not in ["first_exhausted", "all_exhausted"]:
  raise ValueError(F"{stopping_strategy} is not supported. Please enter a valid stopping_strategy."      )
 if dataset_type is Dataset:
  return _interleave_map_style_datasets(
      __UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase							,    info=__UpperCamelCase							,    split=__UpperCamelCase							,    stopping_strategy=__UpperCamelCase      )
 else:
  return _interleave_iterable_datasets(
      __UpperCamelCase							,    __UpperCamelCase							,    __UpperCamelCase							,    info=__UpperCamelCase							,    split=__UpperCamelCase							,    stopping_strategy=__UpperCamelCase      )




def   lowerCAmelCase						(					__UpperCamelCase							,    __UpperCamelCase = None							,    __UpperCamelCase = None							,    __UpperCamelCase = 0							,    ):
 '''simple docstring'''





 if not dsets:
  raise ValueError("""Unable to concatenate an empty list of datasets."""      )
 for i, dataset in enumerate(__UpperCamelCase      ):
  if not isinstance(__UpperCamelCase							,    (Dataset, IterableDataset)      ):
   if isinstance(__UpperCamelCase							,    (DatasetDict, IterableDatasetDict)      ):
    if not dataset:
     raise ValueError(
         F"Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} "
         """is an empty dataset dictionary."""      )
    raise ValueError(
        F"Dataset at position {i} has at least one split: {list(__UpperCamelCase      )}\n"
        F"Please pick one to interleave with the other datasets, for example: dataset['{next(iter(__UpperCamelCase      )      )}']"      )
   raise ValueError(
       F"Expected a list of Dataset objects or a list of IterableDataset objects, but element at position {i} is a {type(__UpperCamelCase      ).__name__}."      )
  if i == 0:
   UpperCAmelCase__   ,      UpperCAmelCase__					:  Optional[int]					   =					(
       (Dataset, IterableDataset) if isinstance(__UpperCamelCase							,    __UpperCamelCase      ) else (IterableDataset, Dataset)
   )
  elif not isinstance(__UpperCamelCase							,    __UpperCamelCase      ):
   raise ValueError(
       F"Unable to interleave a {dataset_type.__name__} (at position 0) with a {other_type.__name__} (at position {i}). Expected a list of Dataset objects or a list of IterableDataset objects."      )
 if dataset_type is Dataset:
  return _concatenate_map_style_datasets(__UpperCamelCase							,    info=__UpperCamelCase							,    split=__UpperCamelCase							,    axis=__UpperCamelCase      )
 else:
  return _concatenate_iterable_datasets(__UpperCamelCase							,    info=__UpperCamelCase							,    split=__UpperCamelCase							,    axis=__UpperCamelCase      )





