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🤖 [master] Bump the SparseArrays stdlib from b4b0e72 to 99c99b4 (#50634)
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Stdlib: SparseArrays
URL: https://github.com/JuliaSparse/SparseArrays.jl.git
Stdlib branch: main
Julia branch: master
Old commit: b4b0e72
New commit: 99c99b4
Julia version: 1.11.0-DEV
SparseArrays version: 1.10.0 (Does not match)
Bump invoked by: @dkarrasch
Powered by:
[BumpStdlibs.jl](https://github.com/JuliaLang/BumpStdlibs.jl)

Diff:
JuliaSparse/SparseArrays.jl@b4b0e72...99c99b4

```
$ git log --oneline b4b0e72..99c99b4
99c99b4 Specialize 3-arg `dot` for sparse self-adjoint matrices (#398)
cb10c1e use unwrapping mechanism for triangular matrices (#396)
b3872c8 added warning for iterating while mutating a sparse matrix (#415)
f8f0f40 bring coverage of fixed SparseMatrixCSC to 100% (#392)
0eb9c04 fix typos (#414)
```

Co-authored-by: Dilum Aluthge <dilum@aluthge.com>
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DilumAluthgeBot and DilumAluthge authored Jul 22, 2023
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2 changes: 1 addition & 1 deletion stdlib/SparseArrays.version
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SPARSEARRAYS_BRANCH = main
SPARSEARRAYS_SHA1 = b4b0e721ada6e8cf5f6391aff4db307be69b0401
SPARSEARRAYS_SHA1 = 99c99b4521eb19a7973643d1aa4d7b1e4d50a6db
SPARSEARRAYS_GIT_URL := https://github.com/JuliaSparse/SparseArrays.jl.git
SPARSEARRAYS_TAR_URL = https://api.github.com/repos/JuliaSparse/SparseArrays.jl/tarball/$1

9 comments on commit 6691a75

@nanosoldier
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Executing the daily package evaluation, I will reply here when finished:

@nanosoldier runtests(isdaily = true)

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The package evaluation job you requested has completed - possible new issues were detected.
The full report is available.

@vtjnash
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@nanosoldier runbenchmarks(ALL, isdaily = true)

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Your benchmark job has completed - possible performance regressions were detected. A full report can be found here.

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Good for sparse, not for string?

["sparse", "sparse solves", "least squares (default), matrix rhs"]	0.11 (5%) ✅	1.00 (1%)
["sparse", "sparse solves", "least squares (default), vector rhs"]	0.19 (5%) ✅	1.00 (1%)
["sparse", "sparse solves", "least squares (qr), matrix rhs"]	0.11 (5%) ✅	1.00 (1%)
["sparse", "sparse solves", "least squares (qr), vector rhs"]	0.19 (5%) ✅	1.00 (1%)
["string", "join"]	2.02 (40%) ❌	1.00 (1%)

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@nanosoldier runbenchmarks("string" && "join", vs="@0f56da8988366dd60e170932eefca4adb890acff")

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Your benchmark job has completed - no performance regressions were detected. A full report can be found here.

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@nanosoldier runbenchmarks("string", vs="@0f56da8988366dd60e170932eefca4adb890acff")

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Your benchmark job has completed - no performance regressions were detected. A full report can be found here.

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