🤖 Format .jl files

.breakage/get_jso_users.jl

@@ -1,18 +1,18 @@
-import GitHub, PkgDeps  # both export users()
-
-length(ARGS) >= 1 || error("specify at least one JSO package as argument")
-
-jso_repos, _ = GitHub.repos("JuliaSmoothOptimizers")
-jso_names = [splitext(x.name)[1] for x ∈ jso_repos]
-
-name = splitext(ARGS[1])[1]
-name ∈ jso_names || error("argument should be one of ", jso_names)
-
-dependents = String[]
-try
-  global dependents = filter(x -> x ∈ jso_names, PkgDeps.users(name))
-catch e
-  # package not registered; don't insert into dependents
-end
-
-println(dependents)
+import GitHub, PkgDeps  # both export users()
+
+length(ARGS) >= 1 || error("specify at least one JSO package as argument")
+
+jso_repos, _ = GitHub.repos("JuliaSmoothOptimizers")
+jso_names = [splitext(x.name)[1] for x ∈ jso_repos]
+
+name = splitext(ARGS[1])[1]
+name ∈ jso_names || error("argument should be one of ", jso_names)
+
+dependents = String[]
+try
+  global dependents = filter(x -> x ∈ jso_names, PkgDeps.users(name))
+catch e
+  # package not registered; don't insert into dependents
+end
+
+println(dependents)

benchmark/benchmarks.jl

@@ -1,6 +1,6 @@
 using LinearAlgebra, StatsBase
 using BenchmarkTools
-using Krylov, LinearOperators 
+using Krylov, LinearOperators
 using PartitionedStructures
 using PartitionedVectors
 
@@ -31,12 +31,12 @@ res = similar(pv_x)
 
 Krylov.solve!(solver, lo_epm, -pv_gradient)
 SUITE["Krylov small PartitionedVectors"] = BenchmarkGroup()
-SUITE["Krylov small PartitionedVectors"] = @benchmarkable Krylov.solve!(solver, lo_epm, -pv_gradient)
+SUITE["Krylov small PartitionedVectors"] =
+  @benchmarkable Krylov.solve!(solver, lo_epm, -pv_gradient)
 
 SUITE["small broadcast"] = BenchmarkGroup()
 SUITE["small broadcast"] = @benchmarkable res .= pv_gradient .+ 3 .* pv_gradient
 
-
 N = 1500
 n = 20000
 nie = 15