feat(v2.2.1): release: prepare ExcelAlchemy 2.2.1

CHANGELOG.md

@@ -4,7 +4,47 @@ All notable changes to this project will be documented in this file.
 
 The format is inspired by Keep a Changelog and versioned according to PEP 440.
 
-## [2.2.0] - Unreleased
+## [2.2.1] - Unreleased
+
+This release continues the stable 2.x line with deeper metadata layering,
+stronger internal immutability, and tighter type boundaries around the
+Pydantic adapter layer.
+
+### Added
+
+- Added regression tests that verify split metadata layers behave like
+  immutable value objects
+- Added regression tests that verify facade-level mutation replaces internal
+  metadata layers rather than mutating them in place
+
+### Changed
+
+- Made `DeclaredFieldMeta`, `RuntimeFieldBinding`,
+  `WorkbookPresentationMeta`, and `ImportConstraints` frozen internal
+  structures
+- Updated `FieldMetaInfo` mutation paths to replace internal layer objects via
+  structural updates instead of mutating them in place
+- Normalized workbook presentation internals so character sets and options are
+  stored in immutable forms
+- Tightened key type boundaries in the Pydantic adapter around annotations,
+  codecs, and normalized input payloads
+
+### Compatibility Notes
+
+- No public import or export workflow API was removed in this release
+- `FieldMeta(...)` and `ExcelMeta(...)` remain the stable public metadata entry
+  points
+- The metadata layering changes are internal and preserve the public 2.x
+  surface
+
+### Release Summary
+
+- metadata internals are now more immutable and easier to reason about
+- facade-level metadata updates preserve 2.x ergonomics while reducing hidden
+  shared state
+- the Pydantic adapter layer now has clearer type boundaries
+
+## [2.2.0] - 2026-04-03
 
 This release continues the stable 2.x line with runtime consolidation,
 clearer configuration ergonomics, and a stronger protocol-first storage story.

docs/releases/2.2.0.md

@@ -5,7 +5,7 @@ line.
 
 ## Purpose
 
-- publish the next stable 2.x refinement release of ExcelAlchemy
+- publish the stable `2.2.0` refinement release of ExcelAlchemy
 - present `2.2.0` as a runtime-consolidation and developer-ergonomics release
 - keep the public 2.x workflow stable while making the internal import runtime
   more explicit

docs/releases/2.2.1.md

@@ -0,0 +1,112 @@
+# 2.2.1 Release Checklist
+
+This checklist is intended for the `2.2.1` release on top of the stable 2.x
+line.
+
+## Purpose
+
+- publish the next stable 2.x refinement release of ExcelAlchemy
+- present `2.2.1` as a metadata-consolidation and typing-tightening release
+- keep the public 2.x workflow stable while making internal metadata structures
+  more immutable
+- continue reducing hidden shared state and internal type ambiguity
+
+## Release Positioning
+
+`2.2.1` should be presented as an architectural refinement release:
+
+- the public import and export workflow API stays stable
+- metadata internals become more immutable and easier to reason about
+- facade-level metadata mutation remains ergonomic while internal layering gets
+  safer
+- the Pydantic adapter layer continues moving toward clearer type boundaries
+
+## Before Tagging
+
+1. Confirm the intended version in `src/excelalchemy/__init__.py`.
+2. Review the `2.2.1` section in `CHANGELOG.md`.
+3. Confirm `README.md`, `README-pypi.md`, and `MIGRATIONS.md` still describe
+   the recommended public paths correctly.
+4. Confirm `README_cn.md` remains aligned with the current release position.
+5. Confirm the compatibility notes for:
+   - `FieldMeta(...)` and `ExcelMeta(...)` as stable public metadata entry points
+   - internal metadata layering remaining an implementation detail
+   - `storage=...` as the recommended backend path
+
+## Local Verification
+
+Run these commands from the repository root:
+
+```bash
+uv sync --extra development
+uv run ruff check .
+uv run pyright
+uv run pytest tests
+rm -rf dist
+uv build
+uvx twine check dist/*
+```
+
+Optional smoke tests:
+
+```bash
+uv venv .pkg-smoke-base --python 3.14
+uv pip install --python .pkg-smoke-base/bin/python dist/*.whl
+.pkg-smoke-base/bin/python -c "import excelalchemy; print(excelalchemy.__version__)"
+```
+
+## GitHub Release Steps
+
+1. Push the release commit to the default branch.
+2. In GitHub Releases, draft a new release.
+3. Create a new tag: `v2.2.1`.
+4. Use the `2.2.1` section from `CHANGELOG.md` as the release notes base.
+5. Publish the release and monitor the `Upload Python Package` workflow.
+
+## Release Focus
+
+When reviewing the final release notes, make sure they communicate these three
+themes clearly:
+
+- metadata internals are now more immutable and less prone to hidden shared state
+- facade-level metadata updates preserve 2.x ergonomics while internal layers
+  are replaced structurally
+- the Pydantic adapter layer now has clearer type boundaries
+
+## Recommended Release Messaging
+
+Prefer wording that emphasizes refinement and stability:
+
+- "continues the stable 2.x line"
+- "keeps the public import/export workflow API stable"
+- "makes metadata internals more immutable"
+- "tightens internal type boundaries without forcing public API changes"
+
+## PyPI Verification
+
+After the workflow completes:
+
+1. Confirm the new release appears on PyPI.
+2. Confirm the long description renders correctly.
+3. Confirm screenshots and absolute links still work on the PyPI project page.
+4. Test base install:
+
+```bash
+pip install -U ExcelAlchemy
+```
+
+5. Test optional Minio install:
+
+```bash
+pip install -U "ExcelAlchemy[minio]"
+```
+
+6. Run one template-generation example.
+7. Run one import flow and one export flow.
+
+## Done When
+
+- the tag `v2.2.1` is published
+- the GitHub Release notes clearly communicate the three release themes
+- PyPI renders the project description correctly
+- CI, typing, tests, and package publishing all pass for the tagged release

src/excelalchemy/helper/pydantic.py

@@ -1,7 +1,7 @@
 from collections.abc import Generator, Iterable, Mapping
 from dataclasses import dataclass
 from types import UnionType
-from typing import Any, Union, cast, get_args, get_origin
+from typing import Union, cast, get_args, get_origin
 
 from pydantic import BaseModel, ValidationError
 from pydantic.fields import FieldInfo
@@ -23,23 +23,23 @@ class PydanticFieldAdapter:
     raw_field: FieldInfo
 
     @property
-    def annotation(self) -> Any:
+    def annotation(self) -> object:
         return self.raw_field.annotation
 
     @property
-    def excel_codec(self) -> type[Any]:
+    def excel_codec(self) -> type[ExcelFieldCodec]:
         annotation = self.annotation
         origin = get_origin(annotation)
         if origin in (UnionType, Union):
             args = [arg for arg in get_args(annotation) if arg is not type(None)]
             if len(args) != 1:
                 raise ProgrammaticError(msg(MessageKey.UNSUPPORTED_FIELD_TYPE_DECLARATION, annotation=annotation))
-            return cast(type[Any], args[0])
+            return cast(type[ExcelFieldCodec], args[0])
 
-        return cast(type[Any], annotation)
+        return cast(type[ExcelFieldCodec], annotation)
 
     @property
-    def value_type(self) -> type[Any]:
+    def value_type(self) -> type[ExcelFieldCodec]:
         """Backward-compatible alias for excel_codec."""
         return self.excel_codec
 
@@ -67,14 +67,14 @@ def runtime_metadata(self) -> FieldMetaInfo:
         declared = self.declared_metadata
         return declared.bind_runtime(
             required=self.required,
-            excel_codec=cast(type[ExcelFieldCodec], self.excel_codec),
+            excel_codec=self.excel_codec,
             parent_label=declared.label,
             parent_key=Key(self.name),
             key=Key(self.name),
             offset=0,
         )
 
-    def validate_value(self, raw_value: Any) -> Any:
+    def validate_value(self, raw_value: object) -> object:
         if raw_value is None:
             if self.allows_none and not self.required:
                 return None
@@ -116,12 +116,12 @@ def get_model_field_names(model: type[BaseModel]) -> list[str]:
 
 
 def instantiate_pydantic_model[ModelT: BaseModel](
-    data: Mapping[str, Any],
+    data: Mapping[str, object],
     model: type[ModelT],
 ) -> ModelT | list[ExcelCellError | ExcelRowError]:
     """Instantiate a Pydantic model and return mapped Excel errors when validation fails."""
     model_adapter = PydanticModelAdapter(model)
-    normalized_data: dict[str, Any] = {}
+    normalized_data: dict[str, object] = {}
     errors: list[ExcelCellError | ExcelRowError] = []
     failed_fields: set[str] = set()
 
@@ -158,18 +158,14 @@ def _extract_pydantic_model(model: PydanticModelAdapter) -> Generator[FieldMetaI
                 inherited = sub_field_info.inherited_from(declared_metadata)
                 yield inherited.bind_runtime(
                     required=field_adapter.required,
-                    excel_codec=cast(type[ExcelFieldCodec], excel_codec),
+                    excel_codec=excel_codec,
                     parent_label=declared_metadata.label,
                     parent_key=Key(field_adapter.name),
                     key=key,
                     offset=offset,
                 )
-
-        elif issubclass(excel_codec, ExcelFieldCodec):
-            yield field_adapter.runtime_metadata()
-
         else:
-            raise ProgrammaticError(msg(MessageKey.VALUE_TYPE_DECLARATION_UNSUPPORTED, value_type=excel_codec))
+            yield field_adapter.runtime_metadata()
 
 
 def _handle_error(
@@ -188,7 +184,7 @@ def _handle_error(
 
 
 def _model_validate[ModelT: BaseModel](
-    data: dict[str, Any],
+    data: dict[str, object],
     model: type[ModelT],
     model_adapter: PydanticModelAdapter,
     failed_fields: set[str],