How to get time of whole program execution in Python

To get the time of whole program execution in Python, you can use the time module from the Python standard library. You can measure the start time before your program starts and the end time after your program finishes, then calculate the elapsed time by subtracting the start time from the end time.

Here's an example:

import time

# Measure the start time
start_time = time.time()

# Your program's code goes here
for i in range(1000000):
    pass

# Measure the end time
end_time = time.time()

# Calculate the elapsed time
elapsed_time = end_time - start_time

# Print the elapsed time
print("The program execution took:", elapsed_time, "seconds")

In this example, we first import the time module. We use the time.time() function to get the current time in seconds since the epoch (January 1, 1970, 00:00:00 UTC) before and after the program's code. Then, we calculate the elapsed time by subtracting the start time from the end time, and we print the elapsed time in seconds.

Please note that the time.time() function returns a float representing the time in seconds with microsecond precision. The actual precision of the elapsed time depends on your system's clock resolution.

Get total program execution time using time module in Python:

import time

start_time = time.time()

# Your program logic goes here

end_time = time.time()
execution_time = end_time - start_time

print(f"Total program execution time: {execution_time} seconds")

Using timeit module for measuring program execution time in Python:

import timeit

def main():
    # Your program logic goes here

execution_time = timeit.timeit(main, number=1)

print(f"Total program execution time: {execution_time} seconds")

Python datetime for tracking program start and end time:

from datetime import datetime

start_time = datetime.now()

# Your program logic goes here

end_time = datetime.now()
execution_time = end_time - start_time

print(f"Total program execution time: {execution_time}")

Calculate program execution time with time.perf_counter() in Python:

import time

start_time = time.perf_counter()

# Your program logic goes here

end_time = time.perf_counter()
execution_time = end_time - start_time

print(f"Total program execution time: {execution_time} seconds")

Measure program execution time with contextlib in Python:

from contextlib import contextmanager
import time

@contextmanager
def timer():
    start_time = time.time()
    yield
    end_time = time.time()
    execution_time = end_time - start_time
    print(f"Total program execution time: {execution_time} seconds")

with timer():
    # Your program logic goes here

Using timeit.Timer() for profiling program execution in Python:

import timeit

timer = timeit.Timer(stmt="""
    # Your program logic goes here
""")

execution_time = timer.timeit(number=1)
print(f"Total program execution time: {execution_time} seconds")

Python decorators for measuring program execution time:

import time

def timing_decorator(func):
    def wrapper(*args, **kwargs):
        start_time = time.time()
        result = func(*args, **kwargs)
        end_time = time.time()
        execution_time = end_time - start_time
        print(f"{func.__name__} execution time: {execution_time} seconds")
        return result
    return wrapper

@timing_decorator
def main():
    # Your program logic goes here

main()

Get total program execution time with atexit module in Python:

import atexit
import time

start_time = time.time()

@atexit.register
def on_exit():
    end_time = time.time()
    execution_time = end_time - start_time
    print(f"Total program execution time: {execution_time} seconds")

# Your program logic goes here

Using context managers for measuring program time in Python:

import time

class Timer:
    def __enter__(self):
        self.start_time = time.time()
        return self

    def __exit__(self, exc_type, exc_value, traceback):
        end_time = time.time()
        execution_time = end_time - self.start_time
        print(f"Total program execution time: {execution_time} seconds")

with Timer():
    # Your program logic goes here

Calculate program execution time using contextlib and with statement in Python:

from contextlib import contextmanager
import time

@contextmanager
def timer():
    start_time = time.time()
    yield
    end_time = time.time()
    execution_time = end_time - start_time
    print(f"Total program execution time: {execution_time} seconds")

with timer():
    # Your program logic goes here

Python profile module for detailed program execution time analysis:

import cProfile

def main():
    # Your program logic goes here

cProfile.run("main()", sort="cumulative")

Measuring program execution time with logging module in Python:

import logging
import time

logging.basicConfig(level=logging.INFO)
logger = logging.getLogger(__name__)

start_time = time.time()

# Your program logic goes here

end_time = time.time()
execution_time = end_time - start_time
logger.info(f"Total program execution time: {execution_time} seconds")

Tracking program execution time using sys module in Python:

import sys
import time

start_time = time.time()

# Your program logic goes here

end_time = time.time()
execution_time = end_time - start_time
print(f"Total program execution time: {execution_time} seconds")

sys.exit()

Python timeit.default_timer() for cross-platform program time measurement:

import timeit

start_time = timeit.default_timer()

# Your program logic goes here

end_time = timeit.default_timer()
execution_time = end_time - start_time

print(f"Total program execution time: {execution_time} seconds")

Using cProfile for program execution time profiling in Python:

import cProfile

def main():
    # Your program logic goes here

cProfile.run("main()", sort="cumulative")

Measuring program time with resource module in Python:

import resource
import time

start_time = time.time()

# Your program logic goes here

end_time = time.time()
execution_time = end_time - start_time

print(f"Total program execution time: {execution_time} seconds")

Calculate program execution time with asyncio in Python:

import asyncio

async def main():
    # Your asynchronous program logic goes here

start_time = time.time()
asyncio.run(main())
end_time = time.time()
execution_time = end_time - start_time

print(f"Total program execution time: {execution_time} seconds")

Python decorators and signals for measuring program execution time:

import signal
import time

def timeout_handler(signum, frame):
    raise TimeoutError("Program execution time exceeded the limit")

def timed_execution(seconds):
    def decorator(func):
        def wrapper(*args, **kwargs):
            signal.signal(signal.SIGALRM, timeout_handler)
            signal.alarm(seconds)
            start_time = time.time()
            try:
                result = func(*args, **kwargs)
            finally:
                signal.alarm(0)
                end_time = time.time()
                execution_time = end_time - start_time
                print(f"{func.__name__} execution time: {execution_time} seconds")
            return result
        return wrapper
    return decorator

@timed_execution(5)
def main():
    # Your program logic goes here

main()

Using tracemalloc for program execution time and memory profiling in Python:

import tracemalloc
import time

tracemalloc.start()

start_time = time.time()

# Your program logic goes here

end_time = time.time()
execution_time = end_time - start_time

print(f"Total program execution time: {execution_time} seconds")

current, peak = tracemalloc.get_traced_memory()
print(f"Peak memory usage: {peak / 10**6} MB")
tracemalloc.stop()