PyOhio 2026
What do you do when the standard way to solve a problem is just too slow? In any field, comparing pairs of items, whether patients, products, or data points, leads to code that grinds to a halt as the dataset grows. The usual advice? “Just wait longer” or “use a faster language.” But what if you could rewrite the rules?
In this talk, we’ll show how the right algorithm can dramatically speed up a statistical test used in medical research: the win ratio. This method helps doctors and researchers evaluate pairs of patients on complicated criteria, but until now, it’s been painfully slow for large datasets. We’ll break down:
- Why the old way is slow, and why most people accept it
- How re-framing the problem led to a smarter solution
- The results: 20-50x speedups for typical trials, and over 100x for huge ones
No advanced math or statistics background required, just curiosity about how Python can solve real-world problems in unexpected ways.
Takeaways:
- Learn how algorithmic thinking can turn a slow process into a fast one
- See how pure Python can outperform optimized C++ code in some cases
- Get inspired to look for hidden inefficiencies in your own projects
