Description

how to get time of execution in python ?

### How to Measure the Execution Time of Your Python Script

In the world of programming, knowing the execution time of a script or function can be crucial for optimization and performance analysis. Python, being flexible and dynamic, offers several methods to measure this time. In this blog post, we’ll explore a few common approaches to measure the execution time of a Python script or specific parts of a program.

#### Using `time` Module

One of the most common methods involved in measuring execution time is by utilizing the `time` module, which Python provides out of the box. This method is simple and involves storing the start and end times:

“`python
import time

begin = time.time()

# Your code here…

end = time.time()

# Print the difference (which is the execution time)
print(“Execution Time: “, end – begin)
“`

This strategy is straightforward and provides you with the execution time in seconds, which can be particularly useful when working with longer running processes or larger datasets.

#### Using `timeit` Module

For more precise measurements within a specific piece of code, you might want to use the `timeit` module. This module is specifically designed to provide a more accurate time measurement by running the code multiple times and returning the average time taken:

“`python
import timeit

# Define the statement or code you want to test
stmt = “””
# Your testing code here…

“””

# Use the timeit function from the timeit module
execution_time = timeit.timeit(stmt, number=1000)

# Print the execution time
print(“Execution Time: “, execution_time)
“`

The parameter `number=1000` is an example, where you can define the number of executions.

#### Using Jupyter Notebook’s Magic Command `%%time`

For users working with Jupyter notebooks, you have access to magic commands like `%%time` at the beginning of a code cell that allows you to quickly measure the time of execution:

“`python
%%time

# Your code here…
“`

This magic command automatically prints the execution time, providing an easy way to measure time without manually inserting code to print execution time.

#### Using the `datetime` Module

Sometimes, formatting the output time in a more readable format can make more sense. The `datetime` module can assist you in creating a more human-readable output:

“`python
from datetime import datetime

begin_time = datetime.now()

# Your code here…

end_time = datetime.now()
print(‘Duration: {}’.format(end_time – begin_time))
“`

This example prints out the exact time of execution in a more comprehensive format.

#### Considerations for Measuring Execution Time

– **Consistency**: Execution times can vary depending on the system load, system specs, and other factors. Always consider running the tests multiple times and averaging the results for more accurate performance analysis.
– **Profiling Tools**: For a more in-depth analysis, consider using advanced profiling tools like `cProfile`, which can help identify bottlenecks or functions that are taking too much time.

Measuring execution time is a valuable step in software development, especially during performance testing or when trying to optimize code. Choose the method based on the context in which you are working, and the level of precision and readability you require.

If you need a more human-readable output or have specific requirements for your application, digging deeper into each of the above methods can help you perform more accurate measurements and gain better control over the performance of your Python programs.