
# flake8: noqa
# Lint as: python3

from typing import Dict, List, Optional, Type

from .. import config
from ..utils import logging
from .formatting import (
    ArrowFormatter,
    CustomFormatter,
    Formatter,
    PandasFormatter,
    PythonFormatter,
    TensorFormatter,
    format_table,
    query_table,
)
from .np_formatter import NumpyFormatter


_A						      =				logging.get_logger(__name__)

_A						      =				{}
_A						      =				{}
_A						      =				{}



def 		lowercase_    (     A__				,	A__				,	A__ = None				,	)							->							Any:
    """simple docstring"""

    snake_case				  =      aliases if aliases is not None else []
    if format_type in _FORMAT_TYPES:
        logger.warning(
            F'Overwriting format type \'{format_type}\' ({_FORMAT_TYPES[format_type].__name__} -> {formatter_cls.__name__})'	)
    snake_case				  =      formatter_cls
    for alias in set(aliases + [format_type]	):
        if alias in _FORMAT_TYPES_ALIASES:
            logger.warning(
                F'Overwriting format type alias \'{alias}\' ({_FORMAT_TYPES_ALIASES[alias]} -> {format_type})'	)
        snake_case				  =      format_type



def 		lowercase_    (     A__				,	A__				,	A__ = None	)							->							List[Any]:
    """simple docstring"""

    snake_case				  =      aliases if aliases is not None else []
    for alias in set(aliases + [format_type]	):
        snake_case				  =      unavailable_error


# Here we define all the available formatting functions that can be used by `Dataset.set_format`
_register_formatter(PythonFormatter, None, aliases=["python"])
_register_formatter(ArrowFormatter, "arrow", aliases=["pa", "pyarrow"])
_register_formatter(NumpyFormatter, "numpy", aliases=["np"])
_register_formatter(PandasFormatter, "pandas", aliases=["pd"])
_register_formatter(CustomFormatter, "custom")

if config.TORCH_AVAILABLE:
   from .torch_formatter import TorchFormatter

   _register_formatter(TorchFormatter, "torch", aliases=["pt", "pytorch"])
else:
   _A						      =				ValueError("PyTorch needs to be installed to be able to return PyTorch tensors.")
   _register_unavailable_formatter(_torch_error, "torch", aliases=["pt", "pytorch"])

if config.TF_AVAILABLE:
   from .tf_formatter import TFFormatter

   _register_formatter(TFFormatter, "tensorflow", aliases=["tf"])
else:
   _A						      =				ValueError("Tensorflow needs to be installed to be able to return Tensorflow tensors.")
   _register_unavailable_formatter(_tf_error, "tensorflow", aliases=["tf"])

if config.JAX_AVAILABLE:
   from .jax_formatter import JaxFormatter

   _register_formatter(JaxFormatter, "jax", aliases=[])
else:
   _A						      =				ValueError("JAX needs to be installed to be able to return JAX arrays.")
   _register_unavailable_formatter(_jax_error, "jax", aliases=[])



def 		lowercase_    (     A__	)							->							Optional[str]:
    """simple docstring"""

    if format_type in _FORMAT_TYPES_ALIASES:
        return _FORMAT_TYPES_ALIASES[format_type]
    else:
        return format_type





def 		lowercase_    (     A__				,	**A__	)							->							Formatter:
    """simple docstring"""

    snake_case				  =      get_format_type_from_alias(A__	)
    if format_type in _FORMAT_TYPES:
        return _FORMAT_TYPES[format_type](**A__	)
    if format_type in _FORMAT_TYPES_ALIASES_UNAVAILABLE:
        raise _FORMAT_TYPES_ALIASES_UNAVAILABLE[format_type]
    else:
        raise ValueError(
            F'Return type should be None or selected in {list(type for type in _FORMAT_TYPES.keys() if type != None	)}, but got \'{format_type}\''	)



def 		lowercase_    (     A__				,	A__	)							->							List[Any]:
    """simple docstring"""

    snake_case				  =      [0 for i in range(r + 1	)]
    # nc0 = 1
    snake_case				  =      1
    for i in range(1				,	n + 1	):
        # to compute current row from previous row.
        snake_case				  =      min(A__				,	A__	)
        while j > 0:
            c[j] += c[j - 1]
            j -= 1
    return c[r]





print(binomial_coefficient(n=10, r=5))

