Make package installable/testable on clean docker image

Makefile

@@ -0,0 +1,3 @@
+install-test:
+	docker build -t miplearnjl-test -f test/docker/Dockerfile .
+	docker run --rm -it miplearnjl-test

Project.toml

@@ -4,7 +4,6 @@ authors = ["Alinson S Xavier <git@axavier.org>"]
 version = "0.3.0"
 
 [deps]
-CPLEX = "a076750e-1247-5638-91d2-ce28b192dca0"
 Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d"
 DataStructures = "864edb3b-99cc-5e75-8d2d-829cb0a9cfe8"
 HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"

deps/build.jl

@@ -5,7 +5,7 @@ function install_miplearn()
     Conda.update()
     pip = joinpath(dirname(pyimport("sys").executable), "pip")
     isfile(pip) || error("$pip: invalid path")
-    run(`$pip install miplearn==0.3.0.dev0`)
+    run(`$pip install miplearn==0.3.0.dev1`)
 end
 
 install_miplearn()

src/Cuts/Cuts.jl

@@ -8,7 +8,7 @@ import ..to_str_array
 
 include("tableau/structs.jl")
 
-include("blackbox/cplex.jl")
+# include("blackbox/cplex.jl")
 include("tableau/collect.jl")
 include("tableau/gmi.jl")
 include("tableau/moi.jl")

test/Project.toml

@@ -4,7 +4,6 @@ authors = ["Alinson S. Xavier <git@axavier.org>"]
 version = "0.1.0"
 
 [deps]
-CPLEX = "a076750e-1247-5638-91d2-ce28b192dca0"
 Clp = "e2554f3b-3117-50c0-817c-e040a3ddf72d"
 Glob = "c27321d9-0574-5035-807b-f59d2c89b15c"
 HDF5 = "f67ccb44-e63f-5c2f-98bd-6dc0ccc4ba2f"

test/docker/Dockerfile

@@ -0,0 +1,3 @@
+FROM julia:1.9-buster
+ADD . /app
+CMD julia --project=/app/test /app/test/docker/run.jl

test/docker/run.jl

@@ -0,0 +1,6 @@
+using Pkg
+Pkg.develop(path="/app")
+Pkg.build("MIPLearn")
+
+using MIPLearnT
+runtests()

test/src/BB/test_bb.jl

@@ -3,7 +3,7 @@
 #  Released under the modified BSD license. See COPYING.md for more details.
 
 using Clp
-using CPLEX
+# using CPLEX
 using HiGHS
 using JuMP
 using Test
@@ -130,5 +130,5 @@ end
 function test_bb()
     @time bb_run("Clp", optimizer_with_attributes(Clp.Optimizer))
     @time bb_run("HiGHS", optimizer_with_attributes(HiGHS.Optimizer))
-    @time bb_run("CPLEX", optimizer_with_attributes(CPLEX.Optimizer, "CPXPARAM_Threads" => 1))
+    # @time bb_run("CPLEX", optimizer_with_attributes(CPLEX.Optimizer, "CPXPARAM_Threads" => 1))
 end

test/src/MIPLearnT.jl

@@ -27,7 +27,7 @@ function runtests()
         @testset "BB" begin
             test_bb()
         end
-        test_cuts_blackbox_cplex()
+        # test_cuts_blackbox_cplex()
         test_io()
         test_problems_setcover()
         test_solvers_jump()

test/src/test_usage.jl

@@ -6,10 +6,10 @@ function test_usage()
     LogisticRegression = pyimport("sklearn.linear_model").LogisticRegression
 
     @debug "Generating data files..."
-    dirname = tempdir()
+    dirname = mktempdir()
     data = [fixture_setcover_data()]
     data_filenames = write_pkl_gz(data, dirname)
-    h5_filenames = ["$(f).h5" for f in data_filenames]
+    h5_filenames = [replace(f, ".pkl.gz" => ".h5") for f in data_filenames]
 
     @debug "Setting up LearningSolver..."
     solver = LearningSolver(