Promote mixed numeric timeseries arithmetic to float

.github/workflows/build-and-deploy-docs.yml

@@ -19,15 +19,10 @@ concurrency:
   cancel-in-progress: true
 permissions:
   contents: read
-  pages: write
-  id-token: write
 jobs:
   docs:
     name: Build docs
     runs-on: ubuntu-latest
-    environment:
-      name: github-pages
-      url: ${{ steps.deployment.outputs.page_url }}
     steps:
       - uses: actions/checkout@v4
       - name: Setup
@@ -41,10 +36,23 @@ jobs:
         uses: actions/upload-pages-artifact@v3
         with:
           path: docs/_build/html
+
+  deploy:
+    name: Deploy docs
+    if: startsWith(github.ref, 'refs/tags/v') && github.event_name == 'push'
+    needs: docs
+    runs-on: ubuntu-latest
+    permissions:
+      pages: write
+      id-token: write
+    environment:
+      name: github-pages
+      url: ${{ steps.deployment.outputs.page_url }}
+    steps:
       - name: Deploy to GitHub Pages
-        if: startsWith(github.ref, 'refs/tags/v') && github.event_name == 'push'
         id: deployment
         uses: actions/deploy-pages@v4
+
   doctest:
     name: Run doctests
     runs-on: ubuntu-latest

.github/workflows/ci-lint-typecheck.yml

@@ -35,13 +35,15 @@ jobs:
       - uses: actions/checkout@v6
 
       - name: Ruff check
-        uses: astral-sh/ruff-action@v3
+        uses: astral-sh/ruff-action@v4.1.0
         with:
+          version-file: uv.lock
           args: "check"
 
       - name: Ruff format (check)
-        uses: astral-sh/ruff-action@v3
+        uses: astral-sh/ruff-action@v4.1.0
         with:
+          version-file: uv.lock
           args: "format --check"
 
   typecheck:

src/backtest_lib/market/polars_impl/_timeseries.py

@@ -164,12 +164,20 @@ def to_series(
     # the scalar types are properly kept track of.
     def _rhs(
         self, other: VectorOps[Scalar] | ScalarU
-    ) -> tuple[pl.Series | T, type[ScalarU]]:
+    ) -> tuple[pl.Series | ScalarU, type[ScalarU]]:
         if isinstance(other, (int, float)):
-            return self._scalar_type(other), self._scalar_type
+            scalar_type = (
+                float if self._scalar_type is float or isinstance(other, float) else int
+            )
+            return other, scalar_type
         if isinstance(other, PolarsTimeseries):
             if other._axis is self._axis or other._axis.labels == self._axis.labels:
-                return other._vec, other._scalar_type
+                scalar_type = (
+                    float
+                    if self._scalar_type is float or other._scalar_type is float
+                    else int
+                )
+                return other._vec, scalar_type
             raise ValueError("Axis mismatch: operations require identical PeriodAxis.")
         raise TypeError("Only scalars or same-axis PolarsTimeseries are supported.")
 

tests/unit/market/polars_impl/test_polars_timeseries.py

@@ -113,6 +113,15 @@ def test_arithmetic_with_timeseries(small_timeseries, timeseries_type) -> None:
     assert combined.to_series().to_list() == [11.0, 22.0, 33.0]
 
 
+def test_arithmetic_promotes_mixed_numeric_types(timeseries_type) -> None:
+    periods = [np.datetime64("2024-01-01"), np.datetime64("2024-01-02")]
+    ints = timeseries_type.from_vectors([1, 2], periods)
+    floats = timeseries_type.from_vectors([0.5, 1.5], periods)
+
+    assert (ints + 0.5).to_series().to_list() == [1.5, 2.5]
+    assert (floats + ints).to_series().to_list() == [1.5, 3.5]
+
+
 def test_axis_mismatch_raises(timeseries_type) -> None:
     left = timeseries_type.from_vectors(
         values=[1.0, 2.0],