Will it scale to a 50,000-SKU catalogue?

Yes, with the right architecture. A single Prophet fit takes 1-3 seconds on CPU; serial training of 50k SKUs takes 14-42 hours. Parallelize: use concurrent.futures.ProcessPoolExecutor with N workers = CPU cores. On a 16-core machine you train 50k SKUs in 1-3 hours. Three scale tricks: (1) Skip SKUs with < 12 weeks of history or fewer than 30 non-zero days, fall back to category forecast. (2) Use Prophet’s uncertainty_samples=0 when you don’t need confidence intervals (3x faster fit). (3) Cluster slow-mover SKUs and forecast at the cluster level. With these tricks, 50k SKUs is a comfortable nightly job on a single beefy box; you don’t need a Spark cluster.