Download data

# Full simulation output (default file)
df = client.simulation.get_sim_data(sim_id)
print(df.shape)
print(df.head())

# Mid-price resampled to 1-minute bars
mid_df = client.simulation.get_sim_data(sim_id, "mid_price_by_min.parquet")

cached = client.simulation.list_cached(symbol="700.HK")
sim_ids = [s["example_sim_id"] for s in cached["simulations"]]

zip_bytes = client.simulation.get_bulk_data(
    sim_ids=sim_ids,
    include_sim_data=True,
    include_mid_price=True
)

with open("simulation_data.zip", "wb") as f:
    f.write(zip_bytes)

# Or load directly without saving
import zipfile, io, polars as pl

with zipfile.ZipFile(io.BytesIO(zip_bytes)) as zf:
    for name in zf.namelist():
        if name.endswith(".parquet"):
            df = pl.read_parquet(io.BytesIO(zf.read(name)))
            print(f"{name}: {df.shape}")

mid_df = client.simulation.get_sim_data(sim_id, "mid_price_by_min.parquet")

import matplotlib.pyplot as plt
plt.plot(mid_df["time"], mid_df["mid_price"])
plt.title("Simulated Price Path")
plt.show()

files = client.simulation.list_sim_files(sim_id)
if files["has_exec_schedule"]:
    exec_df = client.simulation.get_sim_data(sim_id, "exec_schedule.parquet")