Across the PyCharm 2026.2 release line, we shipped 263 fixes and improvements. Many improve Python code insight directly, with more precise type inference, fewer false positives, smarter completion and imports, and more reliable refactoring. Here are some of the smaller changes you’re likely to notice in everyday Python development.
SQLAlchemy 2.0 support
SQLAlchemy has been a long-standing source of false positives – enough that several duplicate tickets have accumulated over the years. This release resolves a batch of them for the 2.0 style.
String forward-references inside Mapped[...] resolve correctly:
posts: Mapped[list["Post"]] = relationship(back_populates="author") # "Post" now resolves to the model class
PyCharm also correctly infers the mapped type returned by Session.get(), instead of treating the result as the model class itself:
report = session.get(Report, report_id) reveal_type(report) # was: type[Report] | None now: Report | None
Modern hybrid_property setters written as @name.inplace.setter are recognized, so assigning to the property no longer produces a warning. Model class attributes defined via mixins are picked up again, too, clearing the old unexpected argument reports on model constructors.
(PY-78816, PY-65142, PY-59732, PY-51906, PY-28762)
Code insight and type inference
Control-flow narrowing and “unreachable code”
Several false This code is unreachable reports and instances of lost narrowing across loops have been fixed. The common issue: flow analysis either gave up or over-eagerly narrowed to Never in branches it should have kept alive.
isinstance on a numeric union no longer kills the else branch:
def foo(y: int | float) -> None: if isinstance(y, float): pass else: print(y) # was flagged unreachable, y inferred as Never
Narrowing also survives a while loop, so re-narrowing an optional attribute inside the loop body no longer reports a bogus has no attribute error.
(PY-83206, PY-83354, PY-88265)
Strings inside type annotations
A string used as metadata inside Annotated[...] – a Pydantic discriminator field name, for instance – is no longer parsed as a forward reference and flagged as unresolved.
Iterable unpacking and star expressions
PyCharm’s analysis of tuple and star unpacking could lose type information and fall back to Any. Unpacking a starred value into a tuple lost its element types, *-expansion collapsed to Any, and several genuine errors went unreported. Starred expressions preserve their element types:
def a() -> tuple[int, int]: return 2, 3 def b() -> tuple[int, int, int]: return (1, *a()) # no more bogus "Expected tuple[int, int, int]"
(PY-12592, PY-27205, PY-43585, PY-90219)
Augmented assignment
A cluster of false positives came from augmented assignments being misanalyzed. A simple /= on an int produced the wrong type:
foo = 5 foo /= 2 reveal_type(foo) # was: int now: float | int
(PY-80622)
Self and constructor return types
Self binds correctly through classmethod parameters typed as type[Self]:
class A: @classmethod def bar(cls, y: type[Self]) -> Self: ... x = A.bar(A) # was a spurious "Expected type[A], got type[A]" reveal_type(x) # was: Any now: A
Construction also respects __new__, __init__, and metaclass __call__. When __new__ returns something other than an instance, that’s the constructed type – even when an __init__ is present. The same fix covers explicitly parameterized calls like MyClass[int]() and __new__ assigned as a class attribute.
(PY-89296, PY-77611, PY-88644, PY-89571)
Enum members: Literal types for .value and .name
Reading an enum member’s .value or .name yields a precise Literal instead of a widened str or int, so assignments to Literal[...] target type-check. This matches mypy’s inference:
from enum import Enum from typing import Literal class E(Enum): a = "a" b: Literal["a"] = E.a.value # was: Expected 'Literal["a"]', got 'str' n: Literal["a"] = E.a.name # .name is a Literal too
Parameter types inferred from decorators
When a decorator constrains the callable it accepts, the decorated function’s parameters are inferred from that constraint instead of falling back to Any:
from typing import Callable def d(fn: Callable[[int], str]): ... @d def f(a): reveal_type(a) # was: Any now: int
(PY-79204)
Also fixed
- Keyword arguments in a class header are validated against the base class’s
__init_subclass__signature, and offered in completion (PY-79173). - An ellipsis in a
Callableused as a PEP 695 type-parameter bound no longer reports a bogus Invalid type expression (PY-83570). - Type-checker findings are split into granular suppression codes rather than a single
PyTypeCheckerid, and# noinspectiondirectives accept a simplified name form.PyTypeCheckerstill works as a blanket ignore (PY-90265).
Completion and auto-import
Smarter auto-import
Auto-import is now noticeably less noisy. Previously, if a module was already imported, PyCharm would offer to add a second, redundant import instead of qualifying through the one you already had. The quick-fix – and the completion popup – prefer to reuse the existing import.
Given pkg/src.py containing MyClass, and a file that already imports the module, Alt+Enter produces this:
from pkg import src # no longer flagged as unused src.MyClass
instead of adding from pkg.src import MyClass. The same reuse logic applies to plain import pkg.src, and to the auto-import completion on a second Ctrl+Space.
Nested classes can be auto-imported too, which is something PyCharm didn’t previously support:
# mod.py class Outer: class Inner: pass # main.py – Alt+Enter on Inner now offers "Import Outer from mod" from mod import Outer value = Outer.Inner()
(PY-87970, PY-87971, PY-87972, PY-88009, PY-88016)
Completion for unittest.mock.patch() targets
Patching by string target previously offered no code assistance, so dotted paths had to be entered manually. The string argument to mock.patch(...) gets code completion for modules, classes, and their attributes, and it no longer suggests the invalid as keyword mid-path:
from unittest import mock
# sample.py defines: class Foo: my_attr = 42
with mock.patch("sample.Foo.my_attr", 14):
...
# completion now offers `sample`, `Foo`, and `my_attr`
(PY-89189, PY-89191, PY-89192)
Typed signatures when overriding built-in methods
Completing an override of a dunder or built-in method fills in the full annotated signature – and auto-imports the types it needs – instead of bare parameters:
from types import TracebackType class A: def __exit__(self, exc_type: type[BaseException] | None, exc_val: BaseException | None, exc_tb: TracebackType | None): ... # was: def __exit__(self, exc_type, exc_val, exc_tb):
(PY-79218)
Editor and inspections
Type inlay hints
Inferred type arguments are shown inline at the call site, so you can see what a generic resolved to without hovering over it:
class A[T]: def __init__(self, t: T): ... A[int](1) # [int] shown as an inlay hint
Type names rendered inside inlay hints – return types and solved arguments alike – are also clickable, so you can jump straight to a type’s definition from the hint.
f-string format-spec validation
PyCharm already validated the str.format() mini-language. Those checks apply to f-strings too, and PyCharm flags formatting a type that doesn’t implement __format__:
data = 1
f"{data:.2f}" # ok
f"{data:.2q}" # now flagged: unsupported format spec
class A: ...
f"{A():d}" # now flagged: A doesn't support the 'd' format
Refactoring
The Rename refactoring also updates references to a module when the module itself is renamed. Previously, the renaming left importing sites pointing at the old name:
# rename provider/provider_module.py → some_module.py from ..provider import provider_module # this reference is updated too
(PY-53274)
The Refactor | Field action is now Attribute, and the documentation says “instance attributes” to match Python terminology (PY-85828).
Conclusion
Taken together, these changes make PyCharm’s understanding of Python more precise and predictable: fewer false positives, better type inference, smarter completion, and less time spent working around cases where the IDE gets valid code wrong.
Many of these improvements started with real-world examples reported by users. If PyCharm still misunderstands a typing pattern, framework API, or other valid Python code in your project, let us know in YouTrack – a small reproducer can help us turn that friction into the next fix.
Try PyCharm 2026.2 and let us know which improvements make the biggest difference for your workflow.
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