Example from Ch 4 of Bayesian Methods for Hackers.

posterior_upvote_ratio.py

import pymc3 as pm

def posterior_upvote_ratio(upvotes, downvotes, samples = 20000):
  “””
  This function accepts the number of upvotes and downvotes a particular submission recieved,
  and the number of posterior samples to return to the user. Assumes a uniform prior.
  “””
  N = upvotes + downvotes
  with pm.Model() as model:
    upvote_ratio = pm.Uniform(“upvote_ratio”, 0, 1) # (1)
    observations = pm.Binomial( “obs”, N, upvote_ratio, observed=upvotes) # (2)

    trace = pm.sample(samples, step=pm.Metropolis()) # (3)
  
  burned_trace = trace[int(samples/4):] # (4)
  return burned_trace[“upvote_ratio”]