This repository has been archived by the owner on Oct 25, 2024. It is now read-only.
Week10 - Measuring performance and using numpy #193
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to subscribe to this conversation on GitHub.
Already have an account?
Sign in.
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
Original code
$ python -m timeit -n 100 -r 5 -s "from calc_pi import calculate_pi_timeit" "calculate_pi_timeit(10_000)()"
100 loops, best of 5: 14.3 msec per loop
Updated code (using numpy)
$ python -m timeit -n 100 -r 5 -s "from calc_pi_np import calculate_pi_timeit" "calculate_pi_timeit(10_000)()"
100 loops, best of 5: 883 usec per loop
Numpy version is much faster but for whatever reason line 63 gives me an error in the numpy version so I had to comment it out
Measuring performance and using numpy #185