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jsorefgvanrossum
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spelling fixes (#1499)
1 parent 7612a9a commit 57359c1

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.travis.yml

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@@ -5,7 +5,7 @@ python:
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- "3.3"
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- "3.4"
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- "3.5"
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# Pypy build is disaabled because it doubles the travis build time, and it rarely fails
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# Pypy build is disabled because it doubles the travis build time, and it rarely fails
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# unless one one of the other builds fails.
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# - "pypy3"
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docs/source/faq.rst

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@@ -248,7 +248,7 @@ differently:
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inference which is very slow, does not scale well to large programs
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and often produces confusing error messages. Mypy can support
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modularity since it only uses local type inference; static type
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checking depends on having type annotatations for functions
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checking depends on having type annotations for functions
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signatures.
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- Mypy will support introspection, dynamic loading of code and many

docs/source/kinds_of_types.rst

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@@ -156,7 +156,7 @@ values, in callable types. These cover the vast majority of uses of
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callable types, but sometimes this isn't quite enough. Mypy recognizes
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a special form ``Callable[..., T]`` (with a literal ``...``) which can
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be used in less typical cases. It is compatible with arbitrary
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callable objects that return a type compatible with ``T``, independend
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callable objects that return a type compatible with ``T``, independent
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of the number, types or kinds of arguments. Mypy lets you call such
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callable values with arbitrary arguments, without any checking -- in
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this respect they are treated similar to a ``(*args: Any, **kwargs:

lib-typing/2.7/test_typing.py

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@@ -796,7 +796,7 @@ def test_invariance(self):
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typing.MutableSequence[Employee])
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def test_covariance_tuple(self):
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# Check covariace for Tuple (which are really special cases).
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# Check covariance for Tuple (which are really special cases).
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self.assertIsSubclass(Tuple[Manager], Tuple[Employee])
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self.assertNotIsSubclass(Tuple[Employee], Tuple[Manager])
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# And pairwise.

lib-typing/3.2/test_typing.py

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@@ -821,7 +821,7 @@ def test_invariance(self):
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typing.MutableSequence[Employee])
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def test_covariance_tuple(self):
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# Check covariace for Tuple (which are really special cases).
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# Check covariance for Tuple (which are really special cases).
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self.assertIsSubclass(Tuple[Manager], Tuple[Employee])
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self.assertNotIsSubclass(Tuple[Employee], Tuple[Manager])
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# And pairwise.

mypy/build.py

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@@ -839,7 +839,7 @@ def write_cache(id: str, path: str, tree: MypyFile,
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deserialize the cache data and fix up cross-references. Otherwise, we
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do semantic analysis followed by type checking. We also handle (c)
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above; if a module has valid cache data *but* any of its
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dependendencies was processed from source, then the module should be
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dependencies was processed from source, then the module should be
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processed from source.
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A relatively simple optimization (outside SCCs) we might do in the

mypy/checker.py

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@@ -938,7 +938,7 @@ def check_method_or_accessor_override_for_base(self, defn: FuncBase,
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if name in nodes.inplace_operator_methods:
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# Figure out the name of the corresponding operator method.
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method = '__' + name[3:]
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# An inplace overator method such as __iadd__ might not be
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# An inplace operator method such as __iadd__ might not be
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# always introduced safely if a base class defined __add__.
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# TODO can't come up with an example where this is
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# necessary; now it's "just in case"

mypy/checkexpr.py

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@@ -368,7 +368,7 @@ def infer_function_type_arguments_using_context(
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# See also github issues #462 and #360.
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ret_type = NoneTyp()
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args = infer_type_arguments(callable.type_var_ids(), ret_type, erased_ctx)
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# Only substite non-None and non-erased types.
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# Only substitute non-None and non-erased types.
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new_args = [] # type: List[Type]
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for arg in args:
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if isinstance(arg, NoneTyp) or has_erased_component(arg):
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Return a similarity level:
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0: no match
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1: actual is compatible, but only using type promitions (e.g. int vs float)
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1: actual is compatible, but only using type promotions (e.g. int vs float)
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2: actual is compatible without type promotions (e.g. int vs object)
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The distinction is important in cases where multiple overload items match. We want
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give priority to higher similarity matches.
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"""
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# Replace type variables with their upper bounds. Overloading
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# resolution is based on runtime behavior which erases type
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# parameters, so no need to handle type variables occuring within
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# parameters, so no need to handle type variables occurring within
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# a type.
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if isinstance(actual, TypeVarType):
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actual = actual.erase_to_union_or_bound()

mypy/checkmember.py

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@@ -463,7 +463,7 @@ def map_type_from_supertype(typ: Type, sub_info: TypeInfo,
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inst_type = map_instance_to_supertype(inst_type, super_info)
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# Finally expand the type variables in type with those in the previously
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# constructed type. Note that both type and inst_type may have type
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# variables, but in type they are interpreterd in supertype context while
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# variables, but in type they are interpreted in supertype context while
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# in inst_type they are interpreted in subtype context. This works even if
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# the names of type variables in supertype and subtype overlap.
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return expand_type_by_instance(typ, inst_type)

mypy/checkstrformat.py

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@@ -33,7 +33,7 @@ def has_star(self):
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class StringFormatterChecker:
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"""String interplation/formatter type checker.
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"""String interpolation/formatter type checker.
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This class works closely together with checker.ExpressionChecker.
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"""

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