Natsort summary obs csv rows

Natsort is a transitive dependency of resdata, and should be an
explicit dependency of ert when used in Ert code.

Author: SAKavli

pyproject.toml

@@ -79,6 +79,7 @@ dependencies = [
     "xarray",
     "xtgeo >= 3.3.0",
     "resfo-utilities>=0.5.0",
+    "natsort>=8.4.0",
 ]
 
 [project.scripts]

src/ert/gather_summary_observations.py

@@ -16,6 +16,7 @@
 import anyio
 import httpx
 from httpx import AsyncClient
+from natsort import natsorted
 from resfo_utilities import SummaryKeyType
 
 from ert.cli.main import ErtCliError
@@ -203,9 +204,9 @@ def convert_summary_observations(
     with Path(csv_file_name).open(mode="w", encoding="utf-8") as fout:
         fout.write(", ".join([*header_fields, "value", "error", "date"]))
         fout.write("\n")
-        for key, observations in summary_observations.items():
+        for key in natsorted(summary_observations.keys()):
             skd = make_summary_key_data(key)
-            for observation in observations:
+            for observation in summary_observations[key]:
                 for f in header_fields:
                     v = getattr(skd, f)
                     if v is None:

tests/ert/unit_tests/cli/test_gather_summary_observations.py

@@ -1,3 +1,4 @@
+import pathlib
 from textwrap import dedent
 
 import pytest
@@ -72,3 +73,34 @@ def test_that_convert_summary_observations_extracts_localization_information(cap
     };""")
 
     assert expected_print_with_localization in capsys.readouterr().out
+
+
+@pytest.mark.usefixtures("use_tmpdir")
+def test_that_convert_summary_observations_produces_natsorted_csv_rows(capsys):
+    def make_summary_obs(number: int):
+        return {
+            f"WOPR:OP{number}": [
+                {
+                    "name": f"WOPR_OP{number}",
+                    "errors": [0.02],
+                    "values": [0.5],
+                    "x_axis": ["2010-01-27T00:00:00"],
+                },
+            ]
+        }
+
+    summary_obs = (
+        make_summary_obs(30)
+        | make_summary_obs(10)
+        | make_summary_obs(4)
+        | make_summary_obs(2)
+    )
+    convert_summary_observations(
+        summary_observations=summary_obs,
+        breakthrough_observations={},
+        csv_file_name="foo.csv",
+    )
+    with pathlib.Path("foo.csv").open(encoding="utf-8") as f:
+        csv_content = f.readlines()
+    well_names = [row.split(",")[1].strip() for row in csv_content[1:]]
+    assert well_names == ["OP2", "OP4", "OP10", "OP30"]