Write ribasim_version to TOML and warn in core if it is different

core/src/config.jl

@@ -111,6 +111,7 @@ end
 @option @addnodetypes struct Toml <: TableOption
     starttime::DateTime
     endtime::DateTime
+    ribasim_version::String
     input_dir::String
     results_dir::String
     database::String = "database.gpkg"

core/src/main.jl

@@ -57,8 +57,11 @@ function main(ARGS::Vector{String})::Cint
             logger =
                 Ribasim.setup_logger(; verbosity = config.logging.verbosity, stream = io)
             with_logger(logger) do
-                ribasim_version = pkgversion(Ribasim)
+                ribasim_version = string(pkgversion(Ribasim))
                 (; starttime, endtime) = config
+                if string(ribasim_version) != config.ribasim_version
+                    @warn "The Ribasim version in the TOML config file does not match the used Ribasim CLI version." config.ribasim_version ribasim_version
+                end
                 @info "Starting a Ribasim simulation." ribasim_version starttime endtime
                 model = Ribasim.run(config)
                 if successful_retcode(model)

core/test/data/config_test.toml

@@ -1,11 +1,8 @@
 starttime = 2019-01-01
 endtime = 2019-12-31
-
-# optional, default is the path of the TOML
 input_dir = "../../generated_testmodels/lhm"
 results_dir = "../../generated_testmodels/lhm"
-
-database = "database.gpkg"
+ribasim_version = "2024.2.0"
 
 [basin]
 time = "basin/time.arrow"

core/test/data/logging_test_loglevel_debug.toml

@@ -2,6 +2,7 @@ starttime = 2019-01-01
 endtime = 2019-12-31
 input_dir = "."
 results_dir = "results"
+ribasim_version = "2024.2.0"
 
 [logging]
 verbosity = "debug"

core/test/data/logging_test_no_loglevel.toml

@@ -2,3 +2,4 @@ starttime = 2019-01-01
 endtime = 2019-12-31
 input_dir = "."
 results_dir = "results"
+ribasim_version = "2024.2.0"

core/test/docs.toml

@@ -7,6 +7,8 @@ endtime = 2021-01-01   # required
 input_dir = "."         # required
 results_dir = "results" # required
 
+ribasim_version = "2024.2.0" # required
+
 # Specific tables can also go into Arrow files rather than the database.
 # For large tables this can benefit from better compressed file sizes.
 # This is optional, tables are retrieved from the database if not specified in the TOML.

core/test/io_test.jl

@@ -8,6 +8,7 @@
         database = "path/to/file",
         input_dir = ".",
         results_dir = "results",
+        ribasim_version = string(Ribasim.pkgversion(Ribasim)),
     )
     config = Ribasim.Config(toml, "model")
     @test Ribasim.input_path(config, "path/to/file") ==
@@ -20,6 +21,7 @@
         database = "path/to/file",
         input_dir = "input",
         results_dir = "results",
+        ribasim_version = string(Ribasim.pkgversion(Ribasim)),
     )
     config = Ribasim.Config(toml, "model")
     @test Ribasim.input_path(config, "path/to/file") ==
@@ -32,6 +34,7 @@
         database = "/path/to/file",
         input_dir = ".",
         results_dir = "results",
+        ribasim_version = string(Ribasim.pkgversion(Ribasim)),
     )
     config = Ribasim.Config(toml)
     @test Ribasim.input_path(config, "/path/to/file") == abspath("/path/to/file")

core/test/main_test.jl

@@ -10,9 +10,18 @@ end
 
 @testitem "toml_path" begin
     using IOCapture: capture
+    import TOML
 
     model_path = normpath(@__DIR__, "../../generated_testmodels/basic/")
     toml_path = normpath(model_path, "ribasim.toml")
+
+    # change the ribasim_version in the toml file to check warning
+    toml_dict = TOML.parsefile(toml_path)
+    toml_dict["ribasim_version"] = "a_different_version"
+    open(toml_path, "w") do io
+        TOML.print(io, toml_dict)
+    end
+
     @test ispath(toml_path)
     (; value, output, error, backtrace) = capture() do
         Ribasim.main([toml_path])
@@ -23,6 +32,7 @@ end
         @show error
         @show backtrace
     end
+    @test occursin("version in the TOML config file does not match", output)
 end
 
 @testitem "too many arguments for main" begin

docs/contribute/release.qmd

@@ -25,13 +25,8 @@ Determine the new version number like `2023.1.0`, filling in the current year, a
 This follows `YYYY.MINOR.MICRO` from [calver](https://calver.org/).
 
 Update the version numbers in the repository to the new version number.
-A single find and replace can update all 5 locations:
-
-- `pixi.toml`
-- `core/Project.toml`
-- `python/ribasim/ribasim/__init__.py`
-- `python/ribasim_api/ribasim_api/__init__.py`
-- `ribasim_qgis/metadata.txt`
+A single find and replace can update all locations.
+The Ribasim version number is not in `pixi.lock`, that file does not need updating.
 
 Now submit a pull request to update the version numbers.
 

python/ribasim/ribasim/model.py

@@ -16,6 +16,7 @@
     model_validator,
 )
 
+import ribasim
 from ribasim.config import (
     Allocation,
     Basin,
@@ -229,6 +230,7 @@ def _write_toml(self, fn: FilePath):
         content = self.model_dump(exclude_unset=True, exclude_none=True, by_alias=True)
         # Filter empty dicts (default Nodes)
         content = dict(filter(lambda x: x[1], content.items()))
+        content["ribasim_version"] = ribasim.__version__
         with open(fn, "wb") as f:
             tomli_w.dump(content, f)
         return fn

python/ribasim/tests/test_io.py

@@ -1,6 +1,7 @@
 import pandas as pd
 import pytest
 import ribasim
+import tomli
 from numpy.testing import assert_array_equal
 from pandas import DataFrame
 from pandas.testing import assert_frame_equal
@@ -36,8 +37,14 @@ def __assert_equal(a: DataFrame, b: DataFrame, is_network=False) -> None:
 
 def test_basic(basic, tmp_path):
     model_orig = basic
-    model_orig.write(tmp_path / "basic/ribasim.toml")
-    model_loaded = ribasim.Model(filepath=tmp_path / "basic/ribasim.toml")
+    toml_path = tmp_path / "basic/ribasim.toml"
+    model_orig.write(toml_path)
+    model_loaded = ribasim.Model(filepath=toml_path)
+
+    with open(toml_path, "rb") as f:
+        toml_dict = tomli.load(f)
+
+    assert toml_dict["ribasim_version"] == ribasim.__version__
 
     index_a = model_orig.network.node.df.index.to_numpy(int)
     index_b = model_loaded.network.node.df.index.to_numpy(int)