Migrate to use PythonCall.jl

.github/workflows/CI.yml

@@ -18,7 +18,7 @@ jobs:
       fail-fast: false
       matrix:
         version:
-          - '1.8'
+          - '1.10'
           - 'nightly'
         os:
           - ubuntu-latest
@@ -33,28 +33,6 @@ jobs:
           version: ${{ matrix.version }}
           arch: ${{ matrix.arch }}
       - uses: julia-actions/cache@v1
-      - name: Fix weird Conda.jl/PyCall.jl build error
-        env:
-          PYTHON: ""
-        shell: julia --color=yes {0}
-        run: |
-          using Pkg
-          try
-            Pkg.instantiate()
-            println("Successfully instantiated the test environment")
-          catch e
-            display(e)
-          end
-          ENV["PYTHON"] = ""
-          Pkg.add("Conda")
-          println("Try building Conda and PyCall")
-          try
-            Pkg.build("Conda")
-            using Conda
-            println("Successfully built Conda")
-          catch e
-            display(e)
-          end
       - uses: julia-actions/julia-buildpkg@v1
         env:
           PYTHON: ""  # for conda packages

.vscode/settings.json

@@ -0,0 +1,2 @@
+{
+}

CondaPkg.toml

@@ -0,0 +1,5 @@
+channels = ["conda-forge"]
+
+[deps]
+andes = ""
+kvxopt = ">1.3.0.0"

Project.toml

@@ -1,18 +1,17 @@
 name = "Andes"
 uuid = "93a26e3f-343a-4ab9-b467-a68c67574964"
-authors = ["Hantao Cui <hcui7@utk.edu>"]
-version = "0.2.0"
+authors = ["Hantao Cui <hcui@ieee.org>"]
+version = "1.0.0"
 
 [deps]
-Conda = "8f4d0f93-b110-5947-807f-2305c1781a2d"
+CondaPkg = "992eb4ea-22a4-4c89-a5bb-47a3300528ab"
 Pkg = "44cfe95a-1eb2-52ea-b672-e2afdf69b78f"
-PyCall = "438e738f-606a-5dbb-bf0a-cddfbfd45ab0"
+PythonCall = "6099a3de-0909-46bc-b1f4-468b9a2dfc0d"
 SparseArrays = "2f01184e-e22b-5df5-ae63-d93ebab69eaf"
 
 [compat]
-PyCall = "1.93"
-Conda = "1.7"
-julia = "1"
+PythonCall = "0.9.15"
+julia = "1.3.1"
 
 [extras]
 Test = "8dfed614-e22c-5e08-85e1-65c5234f0b40"

deps/build.jl

@@ -1,9 +1,9 @@
-using Pkg
-using PyCall
-using Conda
+using PythonCall
+using CondaPkg
 
 try
     pyimport("andes")
+    pyimport("kvxopt")
 catch
     @warn "PyCall is not configured to an existing Python env."
     @warn "Andes.jl will use Conda for PyCall and install andes."

src/Andes.jl

@@ -2,24 +2,21 @@ __precompile__()
 
 module Andes
 
-using Conda
-using PyCall
+using PythonCall
 
-import SparseArrays
+const py = PythonCall.pynew()
 
-const py = PyNULL()
-
-include("kvxopt.jl")
+include("kvxopt_pythoncall.jl")
 
 function __init__()
-    copy!(py, pyimport_conda("andes", "andes", "conda-forge"))
+    PythonCall.pycopy!(py, pyimport("andes"))
 
-    pytype_mapping(pyimport("kvxopt").spmatrix, SparseArrays.SparseMatrixCSC)
+    PythonCall.pyconvert_add_rule("kvxopt.base:spmatrix",
+        AbstractSparseMatrixCSC,
+        spmatrix_to_julia,
+    )
 end
 
+export pyconvert, pytype
 
-# --- export ---
-export convert;
-
-end # module
-
+end

src/kvxopt_pythoncall.jl

@@ -0,0 +1,22 @@
+using CondaPkg
+using SparseArrays: AbstractSparseMatrixCSC, SparseMatrixCSC
+using PythonCall: pyconvert_add_rule
+
+"""
+Convert KVXOPT.spmatrix to SparseMatrixCSC
+"""
+function spmatrix_to_julia(S::Type{T}, x::Py) where {T<:AbstractSparseMatrixCSC}
+    # Ensure x is a KVXOPT spmatrix
+    if Bool(pytype(x) != pyimport("kvxopt").spmatrix)
+        throw(ArgumentError("x must be a KVXOPT spmatrix"))
+    end
+
+    # Extract the size, I, J, and V arrays from the spmatrix and explicitly convert them
+    m, n = pyconvert(Tuple{Int64,Int64}, x.size)
+    I = pyconvert(Vector{Int64}, x.CCS[0]) .+ 1
+    J = pyconvert(Vector{Int64}, x.CCS[1]) .+ 1
+    V = pyconvert(Vector{Float64}, x.CCS[2])
+
+    # Create and return the SparseMatrixCSC
+    return PythonCall.pyconvert_return(SparseMatrixCSC(m, n, I, J, V))
+end

test/runtests.jl

@@ -1,3 +1,3 @@
 using Test
 
-include("test_andes_py.jl")
+include("test_andes_pythoncall.jl")

test/test_andes_pythoncall.jl

@@ -0,0 +1,21 @@
+using Test
+using Andes
+using PythonCall
+using SparseArrays
+
+@testset "Test Andes functionalities" begin
+    @testset "SparseMatrixCSC conversion from Andes system example" begin
+        ss = Andes.py.system.example()
+        converted_matrix = pyconvert(SparseMatrixCSC, ss.dae.gy)
+        @test converted_matrix isa SparseMatrixCSC
+        @test size(converted_matrix) == (34, 34)
+    end
+
+    @testset "Power flow run" begin
+        Andes.py.config_logger(40)
+        kundur = Andes.py.utils.paths.get_case("kundur/kundur_full.xlsx")
+        system = Andes.py.run(kundur, no_output=true)
+
+        @test Bool(system.PFlow.converged == true)
+    end
+end