decorator to store runtime performance of a function in a CSV file.

runtime_performance.py

import datetime
import pandas as pd
import pytz
import time

# To switch logging on/off add config logic here to determine this variable:
LOG_PERFORMANCE = True

TIMEZONE = "US/Eastern"
DATE_FORMAT = "%Y_%m_%d %H;%M;%S",


class LogRuntime:

    def __init__(self, module: str, cls: str = None, desc: str = None):
        """Decorator to log function performance."""
        self.module = module
        self.cls = cls
        self.desc = desc

    def __call__(self, func):
          utc_now = pytz.utc.localize(datetime.datetime.utcnow())
          now_as_string = utc_now.astimezone(pytz.timezone(TIMEZONE)).strftime(DATE_FORMAT)

        def timed(*a, **kw):
            # Time the function and store the results:
            t1 = time.time()
            f = func(*a, **kw)

            # Log the runtime:
            runtime = time.time() - t1
            fp = os.path.join("path", "to", "master.csv")
            log = pd.read_csv(fp, encoding="utf-8")
            new_row = {"Timestamp": now_as_string(date_format="%Y-%m-%d %H:%M:%S,%f"),
                       "Module": self.module, "Class": self.cls, "Function": func.__name__,
                       "Description": self.desc, "Runtime": runtime}
            log = log.append(new_row, sort=False, ignore_index=True)
            log.to_csv(fp, encoding="utf-8", index=False)

            # Return the function results:
            return f
        return timed