- 1 year ago
get timing as accurate as possible in python
To get timing as accurate as possible in Python, you can use the timeit
module or the perf_counter()
function from the time
module. Here's how you can utilize these approaches:
- Using the
timeit
module: Thetimeit
module is specifically designed for measuring the execution time of small code snippets. It provides a convenient interface to measure the time taken by a piece of code across multiple iterations. Here's an example:
pythonimport timeit
# Measure the execution time of a code snippet
execution_time = timeit.timeit(stmt='''your_code_here''', number=1000000)
print(f"Execution time: {execution_time} seconds")
Replace 'your_code_here'
with the actual code you want to measure. The stmt
parameter accepts a string containing the code snippet to be timed, and the number
parameter specifies the number of times the code should be executed. The result will be the total time taken for the specified number of executions.
- Using
perf_counter()
: Theperf_counter()
function from thetime
module provides a high-resolution timer that is suitable for measuring small time intervals. Here's an example:
pythonimport time
# Start the timer
start_time = time.perf_counter()
# Your code here
# Stop the timer
end_time = time.perf_counter()
# Calculate the execution time
execution_time = end_time - start_time
print(f"Execution time: {execution_time} seconds")
Place your code between the start_time
and end_time
statements. The perf_counter()
function returns the time in fractional seconds, allowing for accurate timing of small intervals.
By using either the timeit
module or the perf_counter()
function, you can achieve more accurate timing measurements in Python. Keep in mind that factors such as system load, external dependencies, and the nature of the code being executed can still introduce some variability in the timing results.