Merge: Release 0.10.0 (#332)

CHANGELOG.md

@@ -4,7 +4,7 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
-## [Unreleased]
+## [0.10.0] - 2024-08-02
 ### Breaking Changes
 - Providing an explicit `batch_size` is now mandatory when asking for recommendations
 - `RecommenderProtocol.recommend` now accepts an optional `Objective` 
@@ -65,7 +65,7 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
   two fixed low and high dimensional prior regimes
 - The previous default kernel factory has been renamed to `EDBOKernelFactory` and now
   fully reflects the original logic
-- The default acquisition function has been changed from "qEI" to "qLogEI" for improved
+- The default acquisition function has been changed from `qEI` to `qLogEI` for improved
   numerical stability
 
 ### Removed
@@ -95,6 +95,19 @@ and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0
 - Passing a dataframe via the `data` argument to the `transform` methods of
   `SearchSpace`, `SubspaceDiscrete` and `SubspaceContinuous` is no longer possible.
   The dataframe must now be passed as positional argument.
+- The new `allow_extra` flag is automatically set to `True` in `transform` methods
+  of search space classes when left unspecified
+
+### Expired Deprecations (from 0.7.*)
+- `Interval.is_finite` property
+- Specifying target configs without type information 
+- Specifying parameters/constraints at the top level of a campaign configs
+- Passing `numerical_measurements_must_be_within_tolerance` to `Campaign`
+- `batch_quantity` argument 
+- Passing `allow_repeated_recommendations` or `allow_recommending_already_measured` 
+  to `MetaRecommender` (or former `Strategy`)
+- `*Strategy` classes and `baybe.strategies` subpackage
+- Specifying `MetaRecommender` (or former `Strategy`) configs without type information 
 
 ## [0.9.1] - 2024-06-04
 ### Changed

baybe/campaign.py

@@ -11,7 +11,6 @@
 from attrs.converters import optional
 from attrs.validators import instance_of
 
-from baybe.exceptions import DeprecationError
 from baybe.objectives.base import Objective, to_objective
 from baybe.parameters.base import Parameter
 from baybe.recommenders.base import RecommenderProtocol
@@ -83,10 +82,6 @@ class Campaign(SerialMixin):
     )
     """The cached recommendations."""
 
-    # Deprecation
-    numerical_measurements_must_be_within_tolerance: bool = field(default=None)
-    """Deprecated! Raises an error when used."""
-
     def __str__(self) -> str:
         start_bold = "\033[1m"
         end_bold = "\033[0m"
@@ -102,28 +97,6 @@ def __str__(self) -> str:
 
         return campaign_str.replace("\n", "\n ").replace("\r", "\r ")
 
-    strategy: RecommenderProtocol = field(default=None)
-    """Deprecated! Raises an error when used."""
-
-    @numerical_measurements_must_be_within_tolerance.validator
-    def _validate_tolerance_flag(self, _, value) -> None:
-        """Raise a DeprecationError if the tolerance flag is used."""
-        if value is not None:
-            raise DeprecationError(
-                f"Passing 'numerical_measurements_must_be_within_tolerance' to "
-                f"the constructor is deprecated. The flag has become a parameter of "
-                f"{self.__class__.__name__}.{Campaign.add_measurements.__name__}."
-            )
-
-    @strategy.validator
-    def _validate_strategy(self, _, value) -> None:
-        """Raise a DeprecationError if the strategy attribute is used."""
-        if value is not None:
-            raise DeprecationError(
-                "Passing 'strategy' to the constructor is deprecated. The attribute "
-                "has been renamed to 'recommender'."
-            )
-
     @property
     def measurements(self) -> pd.DataFrame:
         """The experimental data added to the Campaign."""
@@ -149,13 +122,7 @@ def from_config(cls, config_json: str) -> Campaign:
         Returns:
             The constructed campaign.
         """
-        from baybe.deprecation import compatibilize_config
-
         config = json.loads(config_json)
-
-        # Temporarily enable backward compatibility
-        config = compatibilize_config(config)
-
         return converter.structure(config, Campaign)
 
     @classmethod
@@ -165,13 +132,7 @@ def validate_config(cls, config_json: str) -> None:
         Args:
             config_json: The JSON that should be validated.
         """
-        from baybe.deprecation import compatibilize_config
-
         config = json.loads(config_json)
-
-        # Temporarily enable backward compatibility
-        config = compatibilize_config(config)
-
         _validation_converter.structure(config, Campaign)
 
     def add_measurements(
@@ -255,27 +216,18 @@ def add_measurements(
     def recommend(
         self,
         batch_size: int,
-        batch_quantity: int = None,  # type: ignore[assignment]
     ) -> pd.DataFrame:
         """Provide the recommendations for the next batch of experiments.
 
         Args:
             batch_size: Number of requested recommendations.
-            batch_quantity: Deprecated! Use ``batch_size`` instead.
 
         Returns:
             Dataframe containing the recommendations in experimental representation.
 
         Raises:
             ValueError: If ``batch_size`` is smaller than 1.
         """
-        if batch_quantity is not None:
-            raise DeprecationError(
-                f"Passing the keyword 'batch_quantity' to "
-                f"'{self.__class__.__name__}.{self.recommend.__name__}' is deprecated. "
-                f"Use 'batch_size' instead."
-            )
-
         if batch_size < 1:
             raise ValueError(
                 f"You must at least request one recommendation per batch, but provided "
@@ -325,12 +277,7 @@ def _drop_version(dict_: dict) -> dict:
 
 # Register de-/serialization hooks
 unstructure_hook = cattrs.gen.make_dict_unstructure_fn(
-    Campaign,
-    converter,
-    _cattrs_include_init_false=True,
-    # TODO: Remove once deprecation got expired:
-    numerical_measurements_must_be_within_tolerance=cattrs.override(omit=True),
-    strategy=cattrs.override(omit=True),
+    Campaign, converter, _cattrs_include_init_false=True
 )
 structure_hook = cattrs.gen.make_dict_structure_fn(
     Campaign, converter, _cattrs_include_init_false=True, _cattrs_forbid_extra_keys=True

baybe/recommenders/base.py

@@ -6,9 +6,9 @@
 import pandas as pd
 
 from baybe.objectives.base import Objective
-from baybe.recommenders.deprecation import structure_recommender_protocol
 from baybe.searchspace import SearchSpace
 from baybe.serialization import converter, unstructure_base
+from baybe.serialization.core import get_base_structure_hook
 
 
 @runtime_checkable
@@ -57,4 +57,6 @@ def recommend(
         ),
     ),
 )
-converter.register_structure_hook(RecommenderProtocol, structure_recommender_protocol)
+converter.register_structure_hook(
+    RecommenderProtocol, get_base_structure_hook(RecommenderProtocol)
+)

baybe/recommenders/meta/base.py

@@ -5,50 +5,21 @@
 
 import cattrs
 import pandas as pd
-from attrs import define, field
+from attrs import define
 
-from baybe.exceptions import DeprecationError
 from baybe.objectives.base import Objective
 from baybe.recommenders.base import RecommenderProtocol
-from baybe.recommenders.deprecation import structure_recommender_protocol
 from baybe.recommenders.pure.base import PureRecommender
 from baybe.recommenders.pure.nonpredictive.base import NonPredictiveRecommender
 from baybe.searchspace import SearchSpace
 from baybe.serialization import SerialMixin, converter, unstructure_base
+from baybe.serialization.core import get_base_structure_hook
 
 
 @define
 class MetaRecommender(SerialMixin, RecommenderProtocol, ABC):
     """Abstract base class for all meta recommenders."""
 
-    allow_repeated_recommendations: bool = field(default=None, kw_only=True)
-    """Deprecated! The flag has become an attribute of
-    :class:`baybe.recommenders.pure.base.PureRecommender`."""
-
-    allow_recommending_already_measured: bool = field(default=None, kw_only=True)
-    """Deprecated! The flag has become an attribute of
-    :class:`baybe.recommenders.pure.base.PureRecommender`."""
-
-    @allow_repeated_recommendations.validator
-    def _validate_allow_repeated_recommendations(self, _, value):
-        """Raise a ``DeprecationError`` if the flag is used."""
-        if value is not None:
-            raise DeprecationError(
-                f"Passing 'allow_repeated_recommendations' to "
-                f"'{self.__class__.__name__}' is deprecated. The flag has become an "
-                f"attribute of the '{PureRecommender.__name__}' classes."
-            )
-
-    @allow_recommending_already_measured.validator
-    def _validate_allow_recommending_already_measured(self, _, value):
-        """Raise a ``DeprecationError`` if the flag is used."""
-        if value is not None:
-            raise DeprecationError(
-                f"Passing 'allow_recommending_already_measured' to "
-                f"{self.__class__.__name__} is deprecated. The flag has become an "
-                f"attribute of {PureRecommender.__name__}."
-            )
-
     @abstractmethod
     def select_recommender(
         self,
@@ -117,4 +88,6 @@ def recommend(
         ),
     ),
 )
-converter.register_structure_hook(MetaRecommender, structure_recommender_protocol)
+converter.register_structure_hook(
+    MetaRecommender, get_base_structure_hook(MetaRecommender)
+)