ModelSmith-AI / backend /experiments /benchmark_runner.py
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import time
class BenchmarkRunner:
def run(self, orchestrator, datasets):
results = []
for name, (df, target) in datasets.items():
start = time.time()
try:
output = orchestrator.run(df, target, train=True)
end = time.time()
results.append({
"dataset": name,
"strategy": output.get("strategy"),
"metrics": output.get("metrics"),
"time": round(end - start, 2),
"error": None
})
except Exception as e:
end = time.time()
results.append({
"dataset": name,
"strategy": None,
"metrics": None,
"time": round(end - start, 2),
"error": str(e)
})
return results