New issue
Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.
By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.
Already on GitHub? Sign in to your account
bpo-41002: Optimize HTTPResponse.read with a given amount #20943
Merged
miss-islington
merged 4 commits into
python:master
from
bmerry:optimize-httpclient-read
Jun 25, 2020
Merged
bpo-41002: Optimize HTTPResponse.read with a given amount #20943
miss-islington
merged 4 commits into
python:master
from
bmerry:optimize-httpclient-read
Jun 25, 2020
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
This only applies to the non-chunked case; the chunked case is still going via readinto. Also added unit tests for reads that are larger than the Content-Length header, because coverage showed that code path wasn't being tested and I wanted 100% for the code I was adding.
Most of the code was already in `_readall_chunked`, so I renamed it to `_read_chunked` and gave it an optional `amt` argument. This also allows the code flow for `read` and `readinto` to be more similar.
@methane this might be of interest to you, since you made the previous optimization I suggested on httplib. |
fasih
pushed a commit
to fasih/cpython
that referenced
this pull request
Jun 29, 2020
…0943) I've done the implementation for both non-chunked and chunked reads. I haven't benchmarked chunked reads because I don't currently have a convenient way to generate a high-bandwidth chunked stream, but I don't see any reason that it shouldn't enjoy the same benefits that the non-chunked case does. I've used the benchmark attached to the bpo bug to verify that performance now matches the unsized read case. Automerge-Triggered-By: @methane
arun-mani-j
pushed a commit
to arun-mani-j/cpython
that referenced
this pull request
Jul 21, 2020
…0943) I've done the implementation for both non-chunked and chunked reads. I haven't benchmarked chunked reads because I don't currently have a convenient way to generate a high-bandwidth chunked stream, but I don't see any reason that it shouldn't enjoy the same benefits that the non-chunked case does. I've used the benchmark attached to the bpo bug to verify that performance now matches the unsized read case. Automerge-Triggered-By: @methane
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Labels
performance
Performance or resource usage
🤖 automerge
PR will be merged once it's been approved and all CI passed
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.
I've done the implementation for both non-chunked and chunked reads. I haven't benchmarked chunked reads because I don't currently have a convenient way to generate a high-bandwidth chunked stream, but I don't see any reason that it shouldn't enjoy the same benefits that the non-chunked case does. I've used the benchmark attached to the bpo bug to verify that performance now matches the unsized read case.
https://bugs.python.org/issue41002
Automerge-Triggered-By: @methane