TYP: MergeHow + JoinHow

pandas/_typing.py

@@ -343,6 +343,12 @@ def closed(self) -> bool:
 # dropna
 AnyAll = Literal["any", "all"]
 
+# merge
+MergeHow = Literal["left", "right", "inner", "outer", "cross"]
+
+# join
+JoinHow = Literal["left", "right", "inner", "outer"]
+
 MatplotlibColor = Union[str, Sequence[float]]
 TimeGrouperOrigin = Union[
     "Timestamp", Literal["epoch", "start", "start_day", "end", "end_day"]

pandas/core/frame.py

@@ -70,7 +70,9 @@
     IgnoreRaise,
     IndexKeyFunc,
     IndexLabel,
+    JoinHow,
     Level,
+    MergeHow,
     NaPosition,
     PythonFuncType,
     QuantileInterpolation,
@@ -9524,7 +9526,7 @@ def join(
         self,
         other: DataFrame | Series | list[DataFrame | Series],
         on: IndexLabel | None = None,
-        how: str = "left",
+        how: JoinHow = "left",
         lsuffix: str = "",
         rsuffix: str = "",
         sort: bool = False,
@@ -9697,7 +9699,7 @@ def _join_compat(
         self,
         other: DataFrame | Series | Iterable[DataFrame | Series],
         on: IndexLabel | None = None,
-        how: str = "left",
+        how: MergeHow = "left",
         lsuffix: str = "",
         rsuffix: str = "",
         sort: bool = False,
@@ -9783,7 +9785,7 @@ def _join_compat(
     def merge(
         self,
         right: DataFrame | Series,
-        how: str = "inner",
+        how: MergeHow = "inner",
         on: IndexLabel | None = None,
         left_on: IndexLabel | None = None,
         right_on: IndexLabel | None = None,

pandas/core/indexes/base.py

@@ -53,6 +53,7 @@
     F,
     IgnoreRaise,
     IndexLabel,
+    JoinHow,
     Level,
     Shape,
     npt,
@@ -218,7 +219,7 @@ def join(
         self,
         other: Index,
         *,
-        how: str_t = "left",
+        how: JoinHow = "left",
         level=None,
         return_indexers: bool = False,
         sort: bool = False,
@@ -4325,7 +4326,7 @@ def join(
         self,
         other: Index,
         *,
-        how: str_t = ...,
+        how: JoinHow = ...,
         level: Level = ...,
         return_indexers: Literal[True],
         sort: bool = ...,
@@ -4337,7 +4338,7 @@ def join(
         self,
         other: Index,
         *,
-        how: str_t = ...,
+        how: JoinHow = ...,
         level: Level = ...,
         return_indexers: Literal[False] = ...,
         sort: bool = ...,
@@ -4349,7 +4350,7 @@ def join(
         self,
         other: Index,
         *,
-        how: str_t = ...,
+        how: JoinHow = ...,
         level: Level = ...,
         return_indexers: bool = ...,
         sort: bool = ...,
@@ -4362,7 +4363,7 @@ def join(
         self,
         other: Index,
         *,
-        how: str_t = "left",
+        how: JoinHow = "left",
         level: Level = None,
         return_indexers: bool = False,
         sort: bool = False,
@@ -4437,7 +4438,8 @@ def join(
                 return join_index, None, rindexer
 
         if self._join_precedence < other._join_precedence:
-            how = {"right": "left", "left": "right"}.get(how, how)
+            flip: dict[JoinHow, JoinHow] = {"right": "left", "left": "right"}
+            how = flip.get(how, how)
             join_index, lidx, ridx = other.join(
                 self, how=how, level=level, return_indexers=True
             )
@@ -4483,7 +4485,7 @@ def join(
 
     @final
     def _join_via_get_indexer(
-        self, other: Index, how: str_t, sort: bool
+        self, other: Index, how: JoinHow, sort: bool
     ) -> tuple[Index, npt.NDArray[np.intp] | None, npt.NDArray[np.intp] | None]:
         # Fallback if we do not have any fastpaths available based on
         #  uniqueness/monotonicity
@@ -4517,7 +4519,7 @@ def _join_via_get_indexer(
         return join_index, lindexer, rindexer
 
     @final
-    def _join_multi(self, other: Index, how: str_t):
+    def _join_multi(self, other: Index, how: JoinHow):
         from pandas.core.indexes.multi import MultiIndex
         from pandas.core.reshape.merge import restore_dropped_levels_multijoin
 
@@ -4589,7 +4591,8 @@ def _join_multi(self, other: Index, how: str_t):
             self, other = other, self
             flip_order = True
             # flip if join method is right or left
-            how = {"right": "left", "left": "right"}.get(how, how)
+            flip: dict[JoinHow, JoinHow] = {"right": "left", "left": "right"}
+            how = flip.get(how, how)
 
         level = other.names.index(jl)
         result = self._join_level(other, level, how=how)
@@ -4600,7 +4603,7 @@ def _join_multi(self, other: Index, how: str_t):
 
     @final
     def _join_non_unique(
-        self, other: Index, how: str_t = "left"
+        self, other: Index, how: JoinHow = "left"
     ) -> tuple[Index, npt.NDArray[np.intp], npt.NDArray[np.intp]]:
         from pandas.core.reshape.merge import get_join_indexers
 
@@ -4632,7 +4635,7 @@ def _join_non_unique(
 
     @final
     def _join_level(
-        self, other: Index, level, how: str_t = "left", keep_order: bool = True
+        self, other: Index, level, how: JoinHow = "left", keep_order: bool = True
     ) -> tuple[MultiIndex, npt.NDArray[np.intp] | None, npt.NDArray[np.intp] | None]:
         """
         The join method *only* affects the level of the resulting
@@ -4683,7 +4686,8 @@ def _get_leaf_sorter(labels: list[np.ndarray]) -> npt.NDArray[np.intp]:
         flip_order = not isinstance(self, MultiIndex)
         if flip_order:
             left, right = right, left
-            how = {"right": "left", "left": "right"}.get(how, how)
+            flip: dict[JoinHow, JoinHow] = {"right": "left", "left": "right"}
+            how = flip.get(how, how)
 
         assert isinstance(left, MultiIndex)
 
@@ -4780,7 +4784,7 @@ def _get_leaf_sorter(labels: list[np.ndarray]) -> npt.NDArray[np.intp]:
 
     @final
     def _join_monotonic(
-        self, other: Index, how: str_t = "left"
+        self, other: Index, how: JoinHow = "left"
     ) -> tuple[Index, npt.NDArray[np.intp] | None, npt.NDArray[np.intp] | None]:
         # We only get here with matching dtypes and both monotonic increasing
         assert other.dtype == self.dtype

pandas/core/reshape/merge.py

@@ -30,6 +30,9 @@
     AxisInt,
     DtypeObj,
     IndexLabel,
+    JoinHow,
+    Literal,
+    MergeHow,
     Shape,
     Suffixes,
     npt,
@@ -98,7 +101,7 @@
 def merge(
     left: DataFrame | Series,
     right: DataFrame | Series,
-    how: str = "inner",
+    how: MergeHow = "inner",
     on: IndexLabel | None = None,
     left_on: IndexLabel | None = None,
     right_on: IndexLabel | None = None,
@@ -197,7 +200,7 @@ def merge_ordered(
     right_by=None,
     fill_method: str | None = None,
     suffixes: Suffixes = ("_x", "_y"),
-    how: str = "outer",
+    how: JoinHow = "outer",
 ) -> DataFrame:
     """
     Perform a merge for ordered data with optional filling/interpolation.
@@ -612,7 +615,7 @@ class _MergeOperation:
     """
 
     _merge_type = "merge"
-    how: str
+    how: MergeHow | Literal["asof"]
     on: IndexLabel | None
     # left_on/right_on may be None when passed, but in validate_specification
     #  get replaced with non-None.
@@ -635,7 +638,7 @@ def __init__(
         self,
         left: DataFrame | Series,
         right: DataFrame | Series,
-        how: str = "inner",
+        how: MergeHow | Literal["asof"] = "inner",
         on: IndexLabel | None = None,
         left_on: IndexLabel | None = None,
         right_on: IndexLabel | None = None,
@@ -1010,7 +1013,8 @@ def _get_join_indexers(self) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]
     def _get_join_info(
         self,
     ) -> tuple[Index, npt.NDArray[np.intp] | None, npt.NDArray[np.intp] | None]:
-
+        # make mypy happy
+        assert self.how != "cross"
         left_ax = self.left.axes[self.axis]
         right_ax = self.right.axes[self.axis]
 
@@ -1072,7 +1076,7 @@ def _create_join_index(
         index: Index,
         other_index: Index,
         indexer: npt.NDArray[np.intp],
-        how: str = "left",
+        how: JoinHow = "left",
     ) -> Index:
         """
         Create a join index by rearranging one index to match another
@@ -1406,7 +1410,7 @@ def _maybe_coerce_merge_keys(self) -> None:
 
     def _create_cross_configuration(
         self, left: DataFrame, right: DataFrame
-    ) -> tuple[DataFrame, DataFrame, str, str]:
+    ) -> tuple[DataFrame, DataFrame, JoinHow, str]:
         """
         Creates the configuration to dispatch the cross operation to inner join,
         e.g. adding a join column and resetting parameters. Join column is added
@@ -1424,7 +1428,7 @@ def _create_cross_configuration(
             to join over.
         """
         cross_col = f"_cross_{uuid.uuid4()}"
-        how = "inner"
+        how: JoinHow = "inner"
         return (
             left.assign(**{cross_col: 1}),
             right.assign(**{cross_col: 1}),
@@ -1584,7 +1588,11 @@ def _validate(self, validate: str) -> None:
 
 
 def get_join_indexers(
-    left_keys, right_keys, sort: bool = False, how: str = "inner", **kwargs
+    left_keys,
+    right_keys,
+    sort: bool = False,
+    how: MergeHow | Literal["asof"] = "inner",
+    **kwargs,
 ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp]]:
     """
 
@@ -1757,7 +1765,7 @@ def __init__(
         axis: AxisInt = 1,
         suffixes: Suffixes = ("_x", "_y"),
         fill_method: str | None = None,
-        how: str = "outer",
+        how: JoinHow | Literal["asof"] = "outer",
     ) -> None:
 
         self.fill_method = fill_method
@@ -1847,7 +1855,7 @@ def __init__(
         suffixes: Suffixes = ("_x", "_y"),
         copy: bool = True,
         fill_method: str | None = None,
-        how: str = "asof",
+        how: Literal["asof"] = "asof",
         tolerance=None,
         allow_exact_matches: bool = True,
         direction: str = "backward",
@@ -2256,7 +2264,10 @@ def _left_join_on_index(
 
 
 def _factorize_keys(
-    lk: ArrayLike, rk: ArrayLike, sort: bool = True, how: str = "inner"
+    lk: ArrayLike,
+    rk: ArrayLike,
+    sort: bool = True,
+    how: MergeHow | Literal["asof"] = "inner",
 ) -> tuple[npt.NDArray[np.intp], npt.NDArray[np.intp], int]:
     """
     Encode left and right keys as enumerated types.