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@pull pull bot commented Mar 31, 2025

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Created by pull[bot] (v2.0.0-alpha.1)

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## What do these changes do?

Add benchmarks for streaming API.

I get asked all the time if someone should use `iter_chunked`,
`iter_any`, or `iter_chunks`. Its nice to be able to point people at
benchmarks, especially ones they can alter with their numbers and run
locally.

Unsurprisingly `memcpy` is where the performance issues are so avoiding
it as much as possible will give better performance. In almost all cases
`iter_chunks` is going to give the best performance if you can trust the
chunk sizes aren't going to be too large.

## Are there changes in behavior for the user?

no

## Is it a substantial burden for the maintainers to support this?
no
@pull pull bot added the ⤵️ pull label Mar 31, 2025
@pull pull bot merged commit 8c4e60b into tj-python:master Mar 31, 2025
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codecov-commenter commented Mar 31, 2025

⚠️ Please install the 'codecov app svg image' to ensure uploads and comments are reliably processed by Codecov.

Codecov Report

All modified and coverable lines are covered by tests ✅

Project coverage is 98.71%. Comparing base (caa5792) to head (8c4e60b).
Report is 1 commits behind head on master.

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Additional details and impacted files
@@            Coverage Diff             @@
##           master     #184      +/-   ##
==========================================
+ Coverage   98.70%   98.71%   +0.01%     
==========================================
  Files         125      125              
  Lines       37378    37462      +84     
  Branches     2064     2076      +12     
==========================================
+ Hits        36893    36980      +87     
+ Misses        338      335       -3     
  Partials      147      147              
Flag Coverage Δ
CI-GHA 98.59% <100.00%> (+0.01%) ⬆️
OS-Linux 98.25% <100.00%> (+0.01%) ⬆️
OS-Windows 96.20% <100.00%> (+<0.01%) ⬆️
OS-macOS 97.36% <100.00%> (+<0.01%) ⬆️
Py-3.10.11 97.27% <100.00%> (-0.01%) ⬇️
Py-3.10.16 97.82% <100.00%> (+0.01%) ⬆️
Py-3.11.11 97.90% <100.00%> (+<0.01%) ⬆️
Py-3.11.9 97.36% <100.00%> (-0.01%) ⬇️
Py-3.12.9 98.36% <100.00%> (+<0.01%) ⬆️
Py-3.13.2 98.34% <100.00%> (+<0.01%) ⬆️
Py-3.9.13 97.14% <95.23%> (-0.01%) ⬇️
Py-3.9.21 97.68% <95.23%> (+<0.01%) ⬆️
Py-pypy7.3.16 79.06% <100.00%> (-7.72%) ⬇️
VM-macos 97.36% <100.00%> (+<0.01%) ⬆️
VM-ubuntu 98.25% <100.00%> (+0.01%) ⬆️
VM-windows 96.20% <100.00%> (+<0.01%) ⬆️

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2 participants