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fix: unify mypy environments for local checks and CI (#1291)

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The isolated pre-commit mypy hook previously omitted runtime type information that
make mypy used, hiding errors involving dependencies such as Pydantic and Pendulum.
Makefile, pre-commit and CI now run the same full-project typing policy in the
development environment defined by uv.lock.

- Use uv run --locked --exact --extra dev and the same mypy arguments for Makefile
  and the local hook. Check all of src and tests, including on configuration-only
  changes.
- Pin Python 3.13 for local development and the pre-commit CI job, and install the
  locked pre-commit version in CI.
- Disable incremental analysis because existing Pendulum cache state changes mypy 2.3.1
  diagnostics. Document the policy, the performance tradeoff and the existing typing debt.
- Add a regression test that exercises Makefile, the hook and the CI command in a
  temporary project, accepting valid dependency types and detecting deliberate
  Pydantic/Pendulum assignment errors.

Resolve the newly detected mypy diagnostics.

- Enable the numpydantic and Pydantic mypy plugins, retaining strict Pydantic
  constructor typing with init_typed = true. Validate raw/coercible payloads through model_validate.
- Propagate concrete record, provider and time-window types through generic collections,
  factories and lookup methods. Preserve runtime field inspection and generated time-window
  documentation.
- Align Pendulum annotations with actual factory/arithmetic results while retaining Pydantic
  validation adapters at runtime. Correct optional values, array boundaries, REST handlers
  and plotting interfaces.
- Add pinned scipy-stubs and types-psutil, update uv.lock, and supply the plugins' dependencies.
- Add runtime regression coverage for validated path defaults, normalized time-series metadata,
  generic field inspection, invalid timestamps and unsupported provider imports.

Runtime and compatibility details:

- Validate path defaults as Path objects while retaining raw string defaults needed by
  migration serialization with exclude_defaults.
- Normalize feed-in tariff lists and default charge rates to NumPy arrays; reject missing
  timestamps/uninitialized values explicitly. Importing into a provider without import support
  returns HTTP 400.
- Public JSON schemas and OpenAPI structure match main (excluding the generated version).

Signed-off-by: dr-dimitry

Signed-off-by: dr-dimitry
Signed-off-by: Bobby Noelte <b0661n0e17e@gmail.com>
Co-authored-by: dr-dimitri <87113560+dr-dimitri@users.noreply.github.com>
Co-authored-by: Normann <github@koldrack.com>
This commit is contained in:
Bobby Noelte
2026-09-10 23:20:35 +02:00
committed by GitHub
co-authored by dr-dimitri Normann
parent 5b584cbb57
commit 1abdd345c4
114 changed files with 2217 additions and 1322 deletions
Download Patch File Download Diff File Expand all files Collapse all files
tests/test_configabc.py
+51 -51
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@@ -55,11 +55,11 @@ def aware_dt(year, month, day, hour=0, minute=0, second=0, tz="Europe/Berlin"):
def make_window(start_h, duration_h, **kwargs):
"""Build a TimeWindow with a naive start_time at ``start_h:00``."""
return TimeWindow(
return TimeWindow.model_validate(dict(
start_time=f"{start_h:02d}:00:00",
duration=f"{duration_h} hours",
**kwargs,
)
))
# ===========================================================================
@@ -73,10 +73,10 @@ class TestTimeWindowConstruction:
def test_aware_start_time_stripped_to_naive(self):
"""An aware start_time is silently stripped to naive (to_time may add a tz)."""
w = TimeWindow(
w = TimeWindow.model_validate(dict(
start_time=Time(8, 0, 0, tzinfo=pendulum.timezone("Europe/Berlin")),
duration="2 hours",
)
))
assert w.start_time.tzinfo is None
assert w.start_time.hour == 8
@@ -375,7 +375,7 @@ class TestFitAndAvailable:
class TestTimeWindowSequence:
def setup_method(self, method):
self.seq = TimeWindowSequence(
self.seq = TimeWindowSequence[TimeWindow](
windows=[
make_window(8, 2), # 08:00–10:00
make_window(14, 3), # 14:00–17:00
@@ -417,15 +417,15 @@ class TestTimeWindowSequence:
assert result == pendulum.duration(hours=5)
def test_empty_sequence_contains_false(self):
seq = TimeWindowSequence()
seq = TimeWindowSequence[TimeWindow]()
assert not seq.contains(naive_dt(2024, 6, 15, 9, 0, 0))
def test_empty_sequence_earliest_none(self):
seq = TimeWindowSequence()
seq = TimeWindowSequence[TimeWindow]()
assert seq.earliest_start_time(pendulum.duration(hours=1), naive_dt(2024, 6, 15)) is None
def test_empty_sequence_available_none(self):
seq = TimeWindowSequence()
seq = TimeWindowSequence[TimeWindow]()
assert seq.available_duration(naive_dt(2024, 6, 15)) is None
def test_get_applicable_windows(self):
@@ -445,7 +445,7 @@ class TestTimeWindowSequence:
assert fits[0].start_time.hour == 14
def test_sort_windows_by_start_time(self):
seq = TimeWindowSequence(
seq = TimeWindowSequence[TimeWindow](
windows=[make_window(14, 1), make_window(8, 1)]
)
ref = naive_dt(2024, 6, 15)
@@ -454,7 +454,7 @@ class TestTimeWindowSequence:
assert seq.windows[1].start_time.hour == 14
def test_add_and_remove_window(self):
seq = TimeWindowSequence()
seq = TimeWindowSequence[TimeWindow]()
w = make_window(10, 1)
seq.add_window(w)
assert len(seq) == 1
@@ -463,7 +463,7 @@ class TestTimeWindowSequence:
assert len(seq) == 0
def test_remove_from_empty_raises(self):
seq = TimeWindowSequence()
seq = TimeWindowSequence[TimeWindow]()
with pytest.raises(IndexError):
seq.remove_window(0)
@@ -487,20 +487,20 @@ class TestTimeWindowSequence:
class TestValueTimeWindow:
def test_value_stored(self):
w = ValueTimeWindow(start_time="08:00:00", duration="2 hours", value=0.288)
w = ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="2 hours", value=0.288))
assert w.value == pytest.approx(0.288)
def test_value_default_none(self):
w = ValueTimeWindow(start_time="08:00:00", duration="2 hours")
w = ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="2 hours"))
assert w.value is None
def test_inherits_aware_start_time_stripped(self):
"""ValueTimeWindow inherits the strip-to-naive behaviour from TimeWindow."""
w = ValueTimeWindow(
w = ValueTimeWindow.model_validate(dict(
start_time=Time(8, 0, 0, tzinfo=pendulum.timezone("UTC")),
duration="2 hours",
value=0.1,
)
))
assert w.start_time.tzinfo is None
assert w.start_time.hour == 8
@@ -509,8 +509,8 @@ class TestValueTimeWindowSequence:
def setup_method(self, method):
self.seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(start_time="08:00:00", duration="4 hours", value=0.25),
ValueTimeWindow(start_time="18:00:00", duration="4 hours", value=0.35),
ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="4 hours", value=0.25)),
ValueTimeWindow.model_validate(dict(start_time="18:00:00", duration="4 hours", value=0.35)),
]
)
@@ -528,7 +528,7 @@ class TestValueTimeWindowSequence:
def test_get_value_none_value_returns_zero(self):
seq = ValueTimeWindowSequence(
windows=[ValueTimeWindow(start_time="08:00:00", duration="4 hours", value=None)]
windows=[ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="4 hours", value=None))]
)
assert seq.get_value_for_datetime(naive_dt(2024, 6, 15, 9, 0, 0)) == pytest.approx(0.0)
@@ -552,7 +552,7 @@ class TestTimeWindowSequenceToArray:
"""
def setup_method(self, method):
self.seq = TimeWindowSequence(
self.seq = TimeWindowSequence[TimeWindow](
windows=[
make_window(8, 2), # 08:00–10:00
make_window(14, 3), # 14:00–17:00
@@ -697,7 +697,7 @@ class TestTimeWindowSequenceToArray:
# ------------------------------------------------------------------
def test_empty_sequence_all_zeros(self):
seq = TimeWindowSequence()
seq = TimeWindowSequence[TimeWindow]()
start = naive_dt(2024, 6, 15, 0)
end = naive_dt(2024, 6, 15, 4)
arr = seq.to_array(start, end, pendulum.duration(hours=1))
@@ -710,7 +710,7 @@ class TestTimeWindowSequenceToArray:
def test_day_of_week_constraint_respected(self):
# Monday-only window; 2024-06-17 is Monday, 2024-06-18 is Tuesday
seq = TimeWindowSequence(windows=[make_window(8, 2, day_of_week=0)])
seq = TimeWindowSequence[TimeWindow](windows=[make_window(8, 2, day_of_week=0)])
monday_start = naive_dt(2024, 6, 17, 7)
tuesday_start = naive_dt(2024, 6, 18, 7)
end_offset = pendulum.duration(hours=4)
@@ -737,7 +737,7 @@ class TestTimeWindowSequenceToSeries:
"""
def setup_method(self, method):
self.seq = TimeWindowSequence(
self.seq = TimeWindowSequence[TimeWindow](
windows=[
make_window(8, 2),
make_window(14, 3),
@@ -858,7 +858,7 @@ class TestTimeWindowSequenceToSeries:
)
def test_empty_sequence_all_zeros(self):
seq = TimeWindowSequence()
seq = TimeWindowSequence[TimeWindow]()
start = naive_dt(2024, 6, 15, 0)
end = naive_dt(2024, 6, 15, 4)
@@ -885,8 +885,8 @@ class TestValueTimeWindowSequenceToArray:
def setup_method(self, method):
self.seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(start_time="08:00:00", duration="4 hours", value=0.25),
ValueTimeWindow(start_time="18:00:00", duration="4 hours", value=0.35),
ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="4 hours", value=0.25)),
ValueTimeWindow.model_validate(dict(start_time="18:00:00", duration="4 hours", value=0.35)),
]
)
@@ -939,8 +939,8 @@ class TestValueTimeWindowSequenceToArray:
def test_dropna_false_none_value_emits_nan(self):
seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(start_time="08:00:00", duration="2 hours", value=None),
ValueTimeWindow(start_time="12:00:00", duration="2 hours", value=0.5),
ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="2 hours", value=None)),
ValueTimeWindow.model_validate(dict(start_time="12:00:00", duration="2 hours", value=0.5)),
]
)
start = naive_dt(2024, 6, 15, 8)
@@ -956,8 +956,8 @@ class TestValueTimeWindowSequenceToArray:
def test_dropna_true_none_value_step_omitted(self):
seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(start_time="08:00:00", duration="2 hours", value=None),
ValueTimeWindow(start_time="12:00:00", duration="2 hours", value=0.5),
ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="2 hours", value=None)),
ValueTimeWindow.model_validate(dict(start_time="12:00:00", duration="2 hours", value=0.5)),
]
)
start = naive_dt(2024, 6, 15, 8)
@@ -1018,8 +1018,8 @@ class TestValueTimeWindowSequenceToArray:
def test_overlapping_windows_first_wins(self):
seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(start_time="08:00:00", duration="4 hours", value=0.10),
ValueTimeWindow(start_time="09:00:00", duration="4 hours", value=0.99),
ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="4 hours", value=0.10)),
ValueTimeWindow.model_validate(dict(start_time="09:00:00", duration="4 hours", value=0.99)),
]
)
start = naive_dt(2024, 6, 15, 9)
@@ -1040,16 +1040,16 @@ class TestValueTimeWindowSequenceToSeries:
def setup_method(self, method):
self.seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(
ValueTimeWindow.model_validate(dict(
start_time="08:00:00",
duration="4 hours",
value=0.25,
),
ValueTimeWindow(
)),
ValueTimeWindow.model_validate(dict(
start_time="18:00:00",
duration="4 hours",
value=0.35,
),
)),
]
)
@@ -1096,16 +1096,16 @@ class TestValueTimeWindowSequenceToSeries:
def test_dropna_false_none_value_emits_nan(self):
seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(
ValueTimeWindow.model_validate(dict(
start_time="08:00:00",
duration="2 hours",
value=None,
),
ValueTimeWindow(
)),
ValueTimeWindow.model_validate(dict(
start_time="12:00:00",
duration="2 hours",
value=0.5,
),
)),
]
)
@@ -1134,16 +1134,16 @@ class TestValueTimeWindowSequenceToSeries:
def test_dropna_true_none_value_omits_timestamp(self):
seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(
ValueTimeWindow.model_validate(dict(
start_time="08:00:00",
duration="2 hours",
value=None,
),
ValueTimeWindow(
)),
ValueTimeWindow.model_validate(dict(
start_time="12:00:00",
duration="2 hours",
value=0.5,
),
)),
]
)
@@ -1254,16 +1254,16 @@ class TestValueTimeWindowSequenceToSeries:
def test_overlapping_windows_first_wins(self):
seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(
ValueTimeWindow.model_validate(dict(
start_time="08:00:00",
duration="4 hours",
value=0.10,
),
ValueTimeWindow(
)),
ValueTimeWindow.model_validate(dict(
start_time="09:00:00",
duration="4 hours",
value=0.99,
),
)),
]
)
@@ -1452,7 +1452,7 @@ class TestAlignToIntervalTimezoneInvariance:
def test_vtws_naive_floor_utc(self, set_other_timezone):
set_other_timezone("UTC")
seq = ValueTimeWindowSequence(windows=[
ValueTimeWindow(start_time="08:00:00", duration="2 hours", value=0.25)
ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="2 hours", value=0.25))
])
start = naive_dt(2024, 6, 15, 8, 10)
end = naive_dt(2024, 6, 15, 10, 10)
@@ -1465,7 +1465,7 @@ class TestAlignToIntervalTimezoneInvariance:
def test_vtws_naive_floor_non_utc(self, set_other_timezone):
set_other_timezone()
seq = ValueTimeWindowSequence(windows=[
ValueTimeWindow(start_time="08:00:00", duration="2 hours", value=0.25)
ValueTimeWindow.model_validate(dict(start_time="08:00:00", duration="2 hours", value=0.25))
])
start = naive_dt(2024, 6, 15, 8, 10)
end = naive_dt(2024, 6, 15, 10, 10)
@@ -1480,11 +1480,11 @@ class TestAlignToIntervalTimezoneInvariance:
seq = ValueTimeWindowSequence(
windows=[
ValueTimeWindow(
ValueTimeWindow.model_validate(dict(
start_time="08:00:00",
duration="2 hours",
value=0.25,
)
))
]
)