Function import_single_folder

scripts_python/profiling_statistics.py:263–314

(conn: sqlite3.Connection, folder: Path)

def import_single_folder(conn: sqlite3.Connection, folder: Path) -> bool:
    cursor = conn.cursor()
    folder_name = folder.name
    metadata_file = folder / "metatdata.json"

    if not metadata_file.exists():
        return False

    try:
        with open(metadata_file, "r") as f:
            metadata = json.load(f)
    except json.JSONDecodeError:
        return False

    timestamp = parse_folder_timestamp(folder_name)
    cprofile_exists = check_file_exists(folder, "cProfile.prof")
    flamegraph_exists = check_file_exists(folder, "flamegraph.svg")
    args_exists = check_file_exists(folder, "args")

    try:
        cursor.execute(
            """
            INSERT INTO profiling_runs 
            (folder_name, timestamp, execution_time_seconds, n_concurrent_trials, 
             disable_diffs, agent_name, cprofile_exists, flamegraph_exists, args_exists)
            VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?)
        """,
            (
                folder_name,
                timestamp,
                metadata.get("execution_time_seconds"),
                metadata.get("n_concurrent_trials"),
                metadata.get("disable_diffs"),
                metadata.get("agent_name"),
                cprofile_exists,
                flamegraph_exists,
                args_exists,
            ),
        )

        run_id = cursor.lastrowid

        if cprofile_exists:
            prof_path = folder / "cProfile.prof"
            import_cprofile_data(cursor, run_id, prof_path)

        conn.commit()
        return True

    except sqlite3.Error:
        conn.rollback()
        return False


def create_histogram(data: np.ndarray, title: str, xlabel: str, output_path: Path):