Add PrecompileTools.jl

Project.toml

@@ -8,12 +8,14 @@ Clp_jll = "06985876-5285-5a41-9fcb-8948a742cc53"
 LinearAlgebra = "37e2e46d-f89d-539d-b4ee-838fcccc9c8e"
 MathOptInterface = "b8f27783-ece8-5eb3-8dc8-9495eed66fee"
 OpenBLAS32_jll = "656ef2d0-ae68-5445-9ca0-591084a874a2"
+PrecompileTools = "aea7be01-6a6a-4083-8856-8a6e6704d82a"
 
 [compat]
 Clp_jll = "=100.1700.601, =100.1700.700, =100.1700.900, =100.1700.901"
 LinearAlgebra = "1.6"
 MathOptInterface = "1.1"
 OpenBLAS32_jll = "0.3.10"
+PrecompileTools = "1"
 julia = "1.6"
 
 [extras]

src/Clp.jl

@@ -5,7 +5,7 @@
 
 module Clp
 
-import Clp_jll
+import Clp_jll: libClp
 import LinearAlgebra
 import MathOptInterface as MOI
 import OpenBLAS32_jll
@@ -17,9 +17,10 @@ function __init__()
             LinearAlgebra.BLAS.lbt_forward(OpenBLAS32_jll.libopenblas_path)
         end
     end
-    global libClp = Clp_jll.libClp
     version = VersionNumber(
-        "$(Clp_VersionMajor()).$(Clp_VersionMinor()).$(Clp_VersionRelease())",
+        Clp_VersionMajor(),
+        Clp_VersionMinor(),
+        Clp_VersionRelease(),
     )
     if !(v"1.17.2" <= version <= v"1.17.9")
         error(
@@ -34,7 +35,6 @@ end
 
 include("libClp.jl")
 include("MOI_wrapper/MOI_wrapper.jl")
-include("precompile.jl")
 
 # Clp exports all `Clp_xxx` symbols. If you don't want all of these symbols in
 # your environment, then use `import Clp` instead of `using Clp`.
@@ -43,4 +43,33 @@ for sym in filter(s -> startswith("$s", "Clp_"), names(@__MODULE__, all = true))
     @eval export $sym
 end
 
+import PrecompileTools
+
+PrecompileTools.@setup_workload begin
+    PrecompileTools.@compile_workload begin
+        let
+            model = MOI.Utilities.CachingOptimizer(
+                MOI.Utilities.UniversalFallback(MOI.Utilities.Model{Float64}()),
+                MOI.instantiate(Clp.Optimizer; with_bridge_type = Float64),
+            )
+            MOI.set(model, MOI.Silent(), true)
+            x = MOI.add_variables(model, 3)
+            sets =  (MOI.GreaterThan(0.0), MOI.LessThan(2.0), MOI.EqualTo(1.0))
+            for i in 1:3, f in (x[i], 1.0 * x[1] + 2.0 * x[2])
+                MOI.supports_constraint(model, typeof(f), typeof(sets[i]))
+                MOI.add_constraint(model, f, sets[i])
+            end
+            f = 1.0 * x[1] + x[2] + x[3]
+            MOI.set(model, MOI.ObjectiveSense(), MOI.MAX_SENSE)
+            MOI.supports(model, MOI.ObjectiveFunction{typeof(f)}())
+            MOI.set(model, MOI.ObjectiveFunction{typeof(f)}(), f)
+            MOI.optimize!(model)
+            MOI.get(model, MOI.TerminationStatus())
+            MOI.get(model, MOI.PrimalStatus())
+            MOI.get(model, MOI.DualStatus())
+            MOI.get(model, MOI.VariablePrimal(), x)
+        end
+    end
+end
+
 end