Consider an $m \times n$ contingency table and test of independence.
Suppose the expected counts are such that chi-squared test is not recommended (close to zero in some cells), as it becomes pretty inaccurate.
Instead, we can run exact Fisher test.
Question 1: What are the options to compute a power of exact Fisher test? Is there a way without running expensive simulations?
Question 2 (pretty hypothetical): How bad would it be to compute a power of a chi-squared test as a proxy for power of exact Fisher test? Computationally, it's really fast, involves effect size (closed form expression of the table entries), sample size, dofs, and alpha (p-value threshold). But is it a reasonable approximation of the true power?