Implement simple filters

ixmp4/db/filters.py

@@ -1,7 +1,7 @@
 from types import UnionType
 from typing import Any, ClassVar, Optional, Union, get_args, get_origin
 
-from pydantic import BaseModel, ConfigDict, Field, ValidationError
+from pydantic import BaseModel, ConfigDict, Field, ValidationError, model_validator
 from pydantic.fields import FieldInfo
 
 from ixmp4 import db
@@ -255,6 +255,11 @@ class BaseFilter(BaseModel, metaclass=FilterMeta):
     )
     sqla_model: ClassVar[type | None] = None
 
+    @model_validator(mode="before")
+    @classmethod
+    def expand_simple_filters(cls, v):
+        return expand_simple_filter(v)
+
     def __init__(self, **data: Any) -> None:
         try:
             super().__init__(**data)
@@ -299,3 +304,17 @@ def apply(self, exc: db.sql.Select, model, session) -> db.sql.Select:
                     column = getattr(model, sqla_column, None)
                 exc = filter_func(exc, column, value, session=session)
         return exc.distinct()
+
+
+def expand_simple_filter(value):
+    if isinstance(value, str):
+        if "*" in value:
+            return dict(name__like=value)
+        else:
+            return dict(name=value)
+    elif isinstance(value, list):
+        if any(["*" in v for v in value]):
+            raise NotImplementedError("Filter by list with wildcard is not implemented")
+        return dict(name__in=value)
+
+    return value

tests/core/test_iamc.py

@@ -76,17 +76,28 @@ def test_unit_as_string_dimensionless_raises(test_mp, test_data_annual, request)
 
 
 @all_platforms
-def test_run_tabulate_with_filter_raw(test_mp, test_data_annual, request):
+@pytest.mark.parametrize(
+    "filters",
+    (
+        dict(variable={"name": "Primary Energy"}),
+        dict(variable={"name": "Primary Energy"}, unit={"name": "EJ/yr"}),
+        dict(variable={"name__like": "* Energy"}, unit={"name": "EJ/yr"}),
+        dict(variable={"name__in": ["Primary Energy", "Some Other Variable"]}),
+        dict(variable="Primary Energy"),
+        dict(variable="Primary Energy", unit="EJ/yr"),
+        dict(variable="* Energy", unit="EJ/yr"),
+        dict(variable=["Primary Energy", "Some Other Variable"]),
+    ),
+)
+def test_run_tabulate_with_filter_raw(test_mp, test_data_annual, request, filters):
     test_mp = request.getfixturevalue(test_mp)
     # Filter run directly
     add_regions(test_mp, test_data_annual["region"].unique())
     add_units(test_mp, test_data_annual["unit"].unique())
 
     run = test_mp.runs.create("Model", "Scenario")
     run.iamc.add(test_data_annual, type=DataPoint.Type.ANNUAL)
-    obs = run.iamc.tabulate(
-        raw=True, variable={"name": "Primary Energy"}, unit={"name": "EJ/yr"}
-    ).drop(["id", "type"], axis=1)
+    obs = run.iamc.tabulate(raw=True, **filters).drop(["id", "type"], axis=1)
     exp = test_data_annual[test_data_annual.variable == "Primary Energy"]
     assert_unordered_equality(obs, exp, check_like=True)
 

tests/data/test_iamc_datapoint.py

@@ -71,7 +71,6 @@ def test_filtering(test_mp, filter, exp_filter, request):
 @pytest.mark.parametrize(
     "filter",
     [
-        {"unit": "test"},
         {"dne": {"dne": "test"}},
         {"region": {"dne": "test"}},
         {"region": {"name__in": False}},