substra_template/mlflow_live_performances.py

import pandas as pd
import json
from pathlib import Path
from mlflow import log_metric
import time
import os
from glob import glob

TIMEOUT = 60  # Number of seconds to stop the script after the last update of the json file
POLLING_FREQUENCY = 10  # Try to read the updates in the file every 10 seconds

# Wait for the file to be found
start = time.time()
while not len(glob(str(Path("local-worker") / "live_performances" / "*" / "performances.json"))) > 0:
    time.sleep(POLLING_FREQUENCY)
    if time.time() - start >= TIMEOUT:
        raise TimeoutError("The performance file does not exist, maybe no test task has been executed yet.")

path_to_json = Path(glob(str(Path("local-worker") / "live_performances" / "*" / "performances.json"))[0])

logged_rows = []
last_update = time.time()

while (time.time() - last_update) <= TIMEOUT:

    if last_update == os.path.getmtime(str(path_to_json)):
        time.sleep(POLLING_FREQUENCY)
        continue

    last_update = os.path.getmtime(str(path_to_json))

    time.sleep(1)  # Waiting for the json to be fully written
    dict_perf = json.load(path_to_json.open())

    df = pd.DataFrame(dict_perf)

    for _, row in df.iterrows():
        if row["testtask_key"] in logged_rows:
            continue

        logged_rows.append(row["testtask_key"])

        step = int(row["round_idx"]) if row["round_idx"] is not None else int(row["testtask_rank"])

        log_metric(f"{row['metric_name']}_{row['worker']}", row["performance"], step)