python_api: type annotate some parts of pytest.approx()

src/_pytest/python_api.py

@@ -33,7 +33,7 @@ if TYPE_CHECKING:
 BASE_TYPE = (type, STRING_TYPES)
 
 
-def _non_numeric_type_error(value, at):
+def _non_numeric_type_error(value, at: Optional[str]) -> TypeError:
     at_str = " at {}".format(at) if at else ""
     return TypeError(
         "cannot make approximate comparisons to non-numeric values: {!r} {}".format(
@@ -55,7 +55,7 @@ class ApproxBase:
     __array_ufunc__ = None
     __array_priority__ = 100
 
-    def __init__(self, expected, rel=None, abs=None, nan_ok=False):
+    def __init__(self, expected, rel=None, abs=None, nan_ok: bool = False) -> None:
         __tracebackhide__ = True
         self.expected = expected
         self.abs = abs
@@ -63,10 +63,10 @@ class ApproxBase:
         self.nan_ok = nan_ok
         self._check_type()
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         raise NotImplementedError
 
-    def __eq__(self, actual):
+    def __eq__(self, actual) -> bool:
         return all(
             a == self._approx_scalar(x) for a, x in self._yield_comparisons(actual)
         )
@@ -74,10 +74,10 @@ class ApproxBase:
     # Ignore type because of https://github.com/python/mypy/issues/4266.
     __hash__ = None  # type: ignore
 
-    def __ne__(self, actual):
+    def __ne__(self, actual) -> bool:
         return not (actual == self)
 
-    def _approx_scalar(self, x):
+    def _approx_scalar(self, x) -> "ApproxScalar":
         return ApproxScalar(x, rel=self.rel, abs=self.abs, nan_ok=self.nan_ok)
 
     def _yield_comparisons(self, actual):
@@ -87,7 +87,7 @@ class ApproxBase:
         """
         raise NotImplementedError
 
-    def _check_type(self):
+    def _check_type(self) -> None:
         """
         Raise a TypeError if the expected value is not a valid type.
         """
@@ -111,11 +111,11 @@ class ApproxNumpy(ApproxBase):
     Perform approximate comparisons where the expected value is numpy array.
     """
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         list_scalars = _recursive_list_map(self._approx_scalar, self.expected.tolist())
         return "approx({!r})".format(list_scalars)
 
-    def __eq__(self, actual):
+    def __eq__(self, actual) -> bool:
         import numpy as np
 
         # self.expected is supposed to always be an array here
@@ -154,12 +154,12 @@ class ApproxMapping(ApproxBase):
     numeric values (the keys can be anything).
     """
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         return "approx({!r})".format(
             {k: self._approx_scalar(v) for k, v in self.expected.items()}
         )
 
-    def __eq__(self, actual):
+    def __eq__(self, actual) -> bool:
         if set(actual.keys()) != set(self.expected.keys()):
             return False
 
@@ -169,7 +169,7 @@ class ApproxMapping(ApproxBase):
         for k in self.expected.keys():
             yield actual[k], self.expected[k]
 
-    def _check_type(self):
+    def _check_type(self) -> None:
         __tracebackhide__ = True
         for key, value in self.expected.items():
             if isinstance(value, type(self.expected)):
@@ -185,7 +185,7 @@ class ApproxSequencelike(ApproxBase):
     numbers.
     """
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         seq_type = type(self.expected)
         if seq_type not in (tuple, list, set):
             seq_type = list
@@ -193,7 +193,7 @@ class ApproxSequencelike(ApproxBase):
             seq_type(self._approx_scalar(x) for x in self.expected)
         )
 
-    def __eq__(self, actual):
+    def __eq__(self, actual) -> bool:
         if len(actual) != len(self.expected):
             return False
         return ApproxBase.__eq__(self, actual)
@@ -201,7 +201,7 @@ class ApproxSequencelike(ApproxBase):
     def _yield_comparisons(self, actual):
         return zip(actual, self.expected)
 
-    def _check_type(self):
+    def _check_type(self) -> None:
         __tracebackhide__ = True
         for index, x in enumerate(self.expected):
             if isinstance(x, type(self.expected)):
@@ -223,7 +223,7 @@ class ApproxScalar(ApproxBase):
     DEFAULT_ABSOLUTE_TOLERANCE = 1e-12  # type: Union[float, Decimal]
     DEFAULT_RELATIVE_TOLERANCE = 1e-6  # type: Union[float, Decimal]
 
-    def __repr__(self):
+    def __repr__(self) -> str:
         """
         Return a string communicating both the expected value and the tolerance
         for the comparison being made, e.g. '1.0 ± 1e-6', '(3+4j) ± 5e-6 ∠ ±180°'.
@@ -245,7 +245,7 @@ class ApproxScalar(ApproxBase):
 
         return "{} ± {}".format(self.expected, vetted_tolerance)
 
-    def __eq__(self, actual):
+    def __eq__(self, actual) -> bool:
         """
         Return true if the given value is equal to the expected value within
         the pre-specified tolerance.
@@ -275,7 +275,8 @@ class ApproxScalar(ApproxBase):
             return False
 
         # Return true if the two numbers are within the tolerance.
-        return abs(self.expected - actual) <= self.tolerance
+        result = abs(self.expected - actual) <= self.tolerance  # type: bool
+        return result
 
     # Ignore type because of https://github.com/python/mypy/issues/4266.
     __hash__ = None  # type: ignore
@@ -337,7 +338,7 @@ class ApproxDecimal(ApproxScalar):
     DEFAULT_RELATIVE_TOLERANCE = Decimal("1e-6")
 
 
-def approx(expected, rel=None, abs=None, nan_ok=False):
+def approx(expected, rel=None, abs=None, nan_ok: bool = False) -> ApproxBase:
     """
     Assert that two numbers (or two sets of numbers) are equal to each other
     within some tolerance.
@@ -527,7 +528,7 @@ def approx(expected, rel=None, abs=None, nan_ok=False):
     return cls(expected, rel, abs, nan_ok)
 
 
-def _is_numpy_array(obj):
+def _is_numpy_array(obj: object) -> bool:
     """
     Return true if the given object is a numpy array.  Make a special effort to
     avoid importing numpy unless it's really necessary.