Allow provider to narrow backtrack selection

src/resolvelib/providers.py

@@ -136,3 +136,60 @@ def get_dependencies(self, candidate: CT) -> Iterable[RT]:
         specifies as its dependencies.
         """
         raise NotImplementedError
+
+    def narrow_requirement_selection(
+        self,
+        identifiers: Iterable[KT],
+        resolutions: Mapping[KT, CT],
+        candidates: Mapping[KT, Iterator[CT]],
+        information: Mapping[KT, Iterator[RequirementInformation[RT, CT]]],
+        backtrack_causes: Sequence[RequirementInformation[RT, CT]],
+    ) -> Iterable[KT]:
+        """
+        An optional method to narrow the selection of requirements being
+        considered during resolution.
+
+        The requirement selection is defined as "The possible requirements
+        that will be resolved next." If a requirement is not part of the returned
+        iterable, it will not be considered during the next step of resolution.
+
+        :param identifiers: An iterable of `identifiers` as returned by
+            ``identify()``. These identify all requirements currently being
+            considered.
+        :param resolutions: A mapping of candidates currently pinned by the
+            resolver. Each key is an identifier, and the value is a candidate
+            that may conflict with requirements from ``information``.
+        :param candidates: A mapping of each dependency's possible candidates.
+            Each value is an iterator of candidates.
+        :param information: A mapping of requirement information for each package.
+            Each value is an iterator of *requirement information*.
+        :param backtrack_causes: A sequence of *requirement information* that are
+            the requirements causing the resolver to most recently
+            backtrack.
+
+        A *requirement information* instance is a named tuple with two members:
+
+        * ``requirement`` specifies a requirement contributing to the current
+          list of candidates.
+        * ``parent`` specifies the candidate that provides (is depended on for)
+          the requirement, or ``None`` to indicate a root requirement.
+
+        Must return a non-empty subset of `identifiers`, with the default
+        implementation being to return `identifiers` unchanged.
+
+        Can be used by the provider to optimize the dependency resolution
+        process. `get_preference` will only be called for the identifiers
+        returned. If there is only one identifier returned, then `get_preference`
+        won't be called at all.
+
+        Serving a similar purpose as `get_preference`, this method allows the
+        provider to guide resolvelib through the resolution process. It should
+        be used instead of `get_preference` for logic when the provider needs
+        to consider multiple identifiers simultaneously, or when the provider
+        wants to skip checking all identifiers, e.g., because the checks are
+        prohibitively expensive.
+
+        Returns:
+            Iterable[KT]: A non-empty subset of `identifiers`.
+        """
+        return identifiers

src/resolvelib/resolvers.py

@@ -435,8 +435,34 @@ def resolve(
                 unsatisfied_names
             )
 
-            # Choose the most preferred unpinned criterion to try.
-            name = min(unsatisfied_names, key=self._get_preference)
+            if len(unsatisfied_names) > 1:
+                narrowed_unstatisfied_names = list(
+                    self._p.narrow_requirement_selection(
+                        identifiers=unsatisfied_names,
+                        resolutions=self.state.mapping,
+                        candidates=IteratorMapping(
+                            self.state.criteria,
+                            operator.attrgetter("candidates"),
+                        ),
+                        information=IteratorMapping(
+                            self.state.criteria,
+                            operator.attrgetter("information"),
+                        ),
+                        backtrack_causes=self.state.backtrack_causes,
+                    )
+                )
+            else:
+                narrowed_unstatisfied_names = unsatisfied_names
+
+            # If there is only 1 unsatisfied name skip calling self._get_preference
+            if len(narrowed_unstatisfied_names) > 1:
+                # Choose the most preferred unpinned criterion to try.
+                name = min(
+                    narrowed_unstatisfied_names, key=self._get_preference
+                )
+            else:
+                name = narrowed_unstatisfied_names[0]
+
             failure_criterion = self._attempt_to_pin_criterion(name)
 
             if failure_criterion: