code: def binom_tost(count, nobs, low, upp):
      """
      Exact TOST test for one proportion using binomial distribution
  
      Parameters
      ----------
      count : {int, array_like}
          the number of successes in nobs trials.
      nobs : int
          the number of trials or observations.
      low, upp : floats
          lower and upper limit of equivalence region
  
      Returns
      -------
      pvalue : float
          p-value of equivalence test
      pval_low, pval_upp : floats
          p-values of lower and upper one-sided tests
  
      """
      # binom_test_stat only returns pval
      tt1 = binom_test(count, nobs, alternative="larger", prop=low)
      tt2 = binom_test(count, nobs, alternative="smaller", prop=upp)
      return (
          np.maximum(tt1, tt2),
          tt1,
          tt2,
      )
  
imports: from statsmodels.compat.python import lzip
  from typing import Callable
  import numpy
  import pandas
  from scipy import optimize, stats
  from statsmodels.stats.base import AllPairsResults, HolderTuple
  from statsmodels.stats.weightstats import _zstat_generic2
  from statsmodels.tools.sm_exceptions import HypothesisTestWarning
  from statsmodels.tools.testing import Holder
  from statsmodels.tools.validation import array_like
label_desc: Use image node_id 10 for calling a global function with example usage: binom_tost(count, nobs, low, upp) and returns: np,  tt1,  tt2