Use dict and set literals instead of calls to dict() and set() #5559
Conversation
This file contains hidden or 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
Set literals are available on all supported Python versions. They are
idiomatic and always faster:
$ python3 -m timeit '{}'
10000000 loops, best of 3: 0.0357 usec per loop
$ python3 -m timeit 'dict()'
10000000 loops, best of 3: 0.104 usec per loop
$ python3 -m timeit '{1, 2, 3}'
10000000 loops, best of 3: 0.0754 usec per loop
$ python3 -m timeit 'set([1, 2, 3])'
1000000 loops, best of 3: 0.228 usec per loop
|
How much does it impacts a full request ? |
carltongibson
approved these changes
Nov 6, 2017
Probably not much in practice. However, literals are always supported, always idiomatic, always readable, and always faster. Most of the time, they're always the preferred choice, even without benchmarks. |
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
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Outdated suggestions cannot be applied.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.
Set literals are available on all supported Python versions. They are idiomatic and always faster: