chore: Type adjustments

LICENSE

@@ -11,4 +11,4 @@ Redistribution and use in source and binary forms, with or without modification,
 
 3. Neither the name of the copyright holder nor the names of its contributors may be used to endorse or promote products derived from this software without specific prior written permission.
 
-THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
+THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.

docs/source/_static/tables.css

@@ -1,4 +1,4 @@
 /* Force wide pandas tables to scroll */
 .output.text_html {
     overflow: scroll;
-}
+}

docs/source/notebooks/README.md

@@ -6,6 +6,6 @@ This directory contains notebooks of examples for how to use `scmdata`.
 
 We use [Jupytext](https://github.com/mwouts/jupytext) to encode the notebooks as standard .py files. This makes
 it easier to version control notebooks as you get a clear, meaningful diffs. Jupytext also enables these notebooks
-to be edited via Jupyter Lab or Jupyter Notebook. 
+to be edited via Jupyter Lab or Jupyter Notebook.
 
-As part of the CI, these notebooks are run and checked for any errors.
+As part of the CI, these notebooks are run and checked for any errors.

src/scmdata/groupby.py

@@ -3,7 +3,7 @@
 """
 import warnings
 from collections.abc import Iterable
-from typing import TYPE_CHECKING, Callable, Iterator, Optional, Sequence, Union
+from typing import TYPE_CHECKING, Callable, Generic, Iterator, Optional, Sequence, Union
 
 import numpy as np
 import pandas as pd
@@ -12,13 +12,12 @@
 from xarray.core.common import ImplementsArrayReduce
 
 from scmdata._typing import MetadataValue
+from scmdata.run import GenericRun
 
 if TYPE_CHECKING:
     from pandas.core.groupby.generic import DataFrameGroupBy
     from typing_extensions import Concatenate, ParamSpec
 
-    from scmdata.run import GenericRun
-
     P = ParamSpec("P")
 
 
@@ -36,7 +35,7 @@ def _maybe_wrap_array(original, new_array):
         return new_array
 
 
-class RunGroupBy(ImplementsArrayReduce, "Generic[GenericRun]"):
+class RunGroupBy(ImplementsArrayReduce, Generic[GenericRun]):
     """
     GroupBy object specialized to grouping ScmRun objects
     """
@@ -89,7 +88,7 @@ def _try_fill_value(v: MetadataValue) -> MetadataValue:
                 )
             yield res
 
-    def __iter__(self) -> "Iterator[GenericRun]":
+    def __iter__(self) -> Iterator[GenericRun]:
         """
         Iterate over the groups
         """

src/scmdata/pyam_compat.py

@@ -6,7 +6,7 @@
 from dateutil import parser
 
 try:
-    from pyam import IamDataFrame
+    from pyam import IamDataFrame  # type: ignore
 
     # mypy can't work out try-except block forces IamDataFrame to be here
     class LongDatetimeIamDataFrame(IamDataFrame):  # type: ignore

src/scmdata/run.py

@@ -55,7 +55,6 @@
     pattern_match,
     years_match,
 )
-from .groupby import RunGroupBy
 from .netcdf import inject_nc_methods
 from .offsets import generate_range, to_offset
 from .ops import inject_ops_methods
@@ -74,6 +73,8 @@
     from numpy.typing import NDArray
     from typing_extensions import Concatenate, ParamSpec
 
+    from scmdata.groupby import RunGroupBy
+
     P = ParamSpec("P")
 
 
@@ -690,11 +691,11 @@ def _indent(s):
 
     def _binary_op(
         self,
-        other: Self,
+        other: Self | pint.Quantity | float | int,
         f: Callable[[pd.DataFrame, pd.DataFrame], pd.DataFrame],
         reflexive: bool = False,
         **kwargs: Any,
-    ) -> pd.DataFrame:
+    ) -> Self:
         if isinstance(other, ScmRun):
             return NotImplemented
 
@@ -713,18 +714,18 @@ def _binary_op(
                     f"operations with {other_ndim}d data are not supported"
                 )
 
-        def _perform_op(df):
+        def _perform_op(run: Self) -> Self:
             if isinstance(other, pint.Quantity):
                 try:
-                    data = df.values * ur(df.get_unique_meta("unit", True))
+                    data = run.values * ur(run.get_unique_meta("unit", True))
                     use_pint = True
                 except KeyError:  # pragma: no cover # emergency valve
                     raise KeyError(  # noqa: TRY200
                         "No `unit` column in your metadata, cannot perform operations "
                         "with pint quantities"
                     )
             else:
-                data = df.values
+                data = run.values
                 use_pint = False
 
             res = []
@@ -736,11 +737,11 @@ def _perform_op(df):
             res_stacked = np.vstack(res)
 
             if use_pint:
-                df._df.values[:] = res_stacked.magnitude.T
-                df["unit"] = str(res_stacked.units)
+                run._df.values[:] = res_stacked.magnitude.T
+                run["unit"] = str(res_stacked.units)
             else:
-                df._df.values[:] = res_stacked.T
-            return df
+                run._df.values[:] = res_stacked.T
+            return run
 
         return self.copy().groupby("unit").apply(_perform_op)
 
@@ -1299,7 +1300,7 @@ def _day_match(self, values):
 
         return day_match(days, values)
 
-    def head(self, *args: Any, **kwargs: Any) -> pd.DataFrame[float]:
+    def head(self, *args: Any, **kwargs: Any) -> pd.DataFrame:
         """
         Return head of :func:`self.timeseries()`.
 
@@ -1318,7 +1319,7 @@ def head(self, *args: Any, **kwargs: Any) -> pd.DataFrame[float]:
         """
         return self.timeseries().head(*args, **kwargs)  # type: ignore
 
-    def tail(self, *args: Any, **kwargs: Any) -> pd.DataFrame[float]:
+    def tail(self, *args: Any, **kwargs: Any) -> pd.DataFrame:
         """
         Return tail of :func:`self.timeseries()`.
 
@@ -1941,6 +1942,8 @@ def groupby(self, *group: str | Iterable[str]) -> RunGroupBy[Self]:
         :class:`RunGroupBy`
             See the documentation for :class:`RunGroupBy` for more information
         """
+        from .groupby import RunGroupBy
+
         group = self._check_groupby_input(group)
 
         return RunGroupBy(self, group)
@@ -2028,6 +2031,8 @@ def groupby_all_except(self, *not_group: str) -> RunGroupBy[Self]:
         :class:`RunGroupBy`
             See the documentation for :class:`RunGroupBy` for more information
         """
+        from .groupby import RunGroupBy
+
         group = self.get_meta_columns_except(not_group)
 
         return RunGroupBy(self, group)