Timing Code Segments with Pythons timeit Module

Introduction

Measuring the execution time of code segments is essential for performance testing and optimization. Python's timeit module provides a convenient way to measure and compare the running time of different code blocks.

Question

A Python user has a script that performs a database update operation. They want to measure the time it takes for the update statement to execute and write the result to a file. The user has attempted to use the timeit module but has encountered difficulty in implementing it.

Answer

Using timeit for performance timing can be achieved with the following steps:

• Import the timeit module: Begin by importing the timeit module into your Python script.

import timeit

• Create a setup string: The setup string contains any necessary imports or variable declarations that should be available to the code being timed. In this case, it should define the required database connection and query statement.

setup = """
import ibm_db
conn = ibm_db.pconnect("dsn=myDB","usrname","secretPWD")
query_stmt = ibm_db.prepare(conn, update)
"""

• Create a statement string: This string represents the code block that will be timed. In this case, it's the database update operation.

stmt = """
ibm_db.execute(query_stmt)
"""

• Execute the timing: Use the timeit.Timer class to measure the execution time of the code block. The following code will measure the time taken to execute the update statement 100 times.

timer = timeit.Timer(stmt, setup)
avg_time = timer.timeit(number=100)

• Write the result to file: Once the timing is complete, write the average execution time to the specified file.

myfile = open("results_update.txt", "a")
myfile.write("Average execution time: {}\n".format(avg_time))
myfile.close()

By following these steps, the user can effectively measure and write the execution time of the database update statement to a file using Python's timeit module.