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import io
import json
import zipfile
import pandas as pd
from typing import Tuple
from .sim import World
from .kpi import compute_kpis
def export_run(w: World) -> Tuple[bytes, str]:
"""
Returns (zip_bytes, filename)
Contents:
- events.jsonl
- metrics.csv
- run_summary.json
"""
# events
events_jsonl = w.events.to_jsonl().encode("utf-8")
# metrics (single-row snapshot; you can also store per-tick KPI series later)
kpi = compute_kpis(w)
df = pd.DataFrame([kpi])
metrics_csv = df.to_csv(index=False).encode("utf-8")
# summary
summary = {
"run_id": w.run_id,
"seed": w.seed,
"tick": w.step,
"minutes_per_tick": w.config.minutes_per_tick,
"ledger": {
"spend_usd": w.ledger.spend_usd,
"llm_calls": w.ledger.llm_calls,
"tool_calls": w.ledger.tool_calls,
"tokens_prompt": w.ledger.tokens_prompt,
"tokens_completion": w.ledger.tokens_completion,
},
"kpi": kpi,
"alerts": w.ledger.alerts[-10:],
"tasks_total": len(w.tasks.tasks),
"tasks_done": len(w.tasks.done_tasks()),
"tasks_overdue": len(w.tasks.overdue_tasks(w.step)),
}
summary_json = json.dumps(summary, indent=2).encode("utf-8")
# zip
buf = io.BytesIO()
with zipfile.ZipFile(buf, mode="w", compression=zipfile.ZIP_DEFLATED) as z:
z.writestr("events.jsonl", events_jsonl)
z.writestr("metrics.csv", metrics_csv)
z.writestr("run_summary.json", summary_json)
buf.seek(0)
fname = f"zen_orchestrator_export__{w.run_id}.zip"
return buf.read(), fname
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