human
Can you provide a the Python program you requested given the following:
I am working on the file "Efficient_sampling_from_a_Binomial_distribution.ipynb".
The first task is:
First function using the inversion method
This first function is a generic implementation of the discrete inverse transform method.
For more details, see the Wikipedia page.

Inverse transformation sampling takes uniform samples of a number $u$ between $0$ and $1$, interpreted as a probability, and then returns the largest number $x$ from the domain of the distribution $\mathbb{P}(X)$ such that $\mathbb{P}(-\infty <X<x)\leq u$.
Can you write Python program for it?
assistant
#Here is the Python program you requested.

# a generic function
from typing import Callable

def inversion_method(compute_proba: Callable[[int], int], xmax: int, xmin: int =0) -> int:
    probas = [ compute_proba(x) for x in range(xmin, xmax + 1) ]
    result = xmin
    current_proba = 0
    one_uniform_sample = uniform_01()
    while current_proba <= one_uniform_sample:
        current_proba += probas[result]
        result += 1
    return result - 1

def first_inversion_binomial(n: int, p: float) -> int:
    def compute_proba(x):
        return proba_binomial(n, p, x)
    xmax = n
    xmin = 0
    return inversion_method(compute_proba, xmax, xmin=xmin)