tests versuch 2
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__all__ = [
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"__version__",
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"AbstractProvider",
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"AbstractResolver",
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"BaseReporter",
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"InconsistentCandidate",
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"Resolver",
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"RequirementsConflicted",
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"ResolutionError",
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"ResolutionImpossible",
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"ResolutionTooDeep",
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]
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__version__ = "1.0.1"
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from .providers import AbstractProvider, AbstractResolver
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from .reporters import BaseReporter
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from .resolvers import (
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InconsistentCandidate,
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RequirementsConflicted,
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ResolutionError,
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ResolutionImpossible,
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ResolutionTooDeep,
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Resolver,
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)
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__all__ = ["Mapping", "Sequence"]
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try:
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from collections.abc import Mapping, Sequence
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except ImportError:
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from collections import Mapping, Sequence
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class AbstractProvider(object):
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"""Delegate class to provide the required interface for the resolver."""
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def identify(self, requirement_or_candidate):
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"""Given a requirement, return an identifier for it.
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This is used to identify a requirement, e.g. whether two requirements
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should have their specifier parts merged.
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"""
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raise NotImplementedError
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def get_preference(
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self,
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identifier,
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resolutions,
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candidates,
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information,
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backtrack_causes,
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):
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"""Produce a sort key for given requirement based on preference.
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The preference is defined as "I think this requirement should be
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resolved first". The lower the return value is, the more preferred
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this group of arguments is.
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:param identifier: An identifier as returned by ``identify()``. This
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identifies the dependency matches which should be returned.
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:param resolutions: Mapping of candidates currently pinned by the
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resolver. Each key is an identifier, and the value is a candidate.
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The candidate may conflict with requirements from ``information``.
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:param candidates: Mapping of each dependency's possible candidates.
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Each value is an iterator of candidates.
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:param information: Mapping of requirement information of each package.
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Each value is an iterator of *requirement information*.
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:param backtrack_causes: Sequence of requirement information that were
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the requirements that caused the resolver to most recently backtrack.
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A *requirement information* instance is a named tuple with two members:
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* ``requirement`` specifies a requirement contributing to the current
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list of candidates.
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* ``parent`` specifies the candidate that provides (depended on) the
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requirement, or ``None`` to indicate a root requirement.
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The preference could depend on various issues, including (not
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necessarily in this order):
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* Is this package pinned in the current resolution result?
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* How relaxed is the requirement? Stricter ones should probably be
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worked on first? (I don't know, actually.)
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* How many possibilities are there to satisfy this requirement? Those
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with few left should likely be worked on first, I guess?
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* Are there any known conflicts for this requirement? We should
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probably work on those with the most known conflicts.
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A sortable value should be returned (this will be used as the ``key``
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parameter of the built-in sorting function). The smaller the value is,
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the more preferred this requirement is (i.e. the sorting function
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is called with ``reverse=False``).
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"""
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raise NotImplementedError
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def find_matches(self, identifier, requirements, incompatibilities):
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"""Find all possible candidates that satisfy the given constraints.
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:param identifier: An identifier as returned by ``identify()``. This
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identifies the dependency matches of which should be returned.
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:param requirements: A mapping of requirements that all returned
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candidates must satisfy. Each key is an identifier, and the value
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an iterator of requirements for that dependency.
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:param incompatibilities: A mapping of known incompatibilities of
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each dependency. Each key is an identifier, and the value an
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iterator of incompatibilities known to the resolver. All
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incompatibilities *must* be excluded from the return value.
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This should try to get candidates based on the requirements' types.
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For VCS, local, and archive requirements, the one-and-only match is
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returned, and for a "named" requirement, the index(es) should be
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consulted to find concrete candidates for this requirement.
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The return value should produce candidates ordered by preference; the
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most preferred candidate should come first. The return type may be one
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of the following:
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* A callable that returns an iterator that yields candidates.
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* An collection of candidates.
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* An iterable of candidates. This will be consumed immediately into a
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list of candidates.
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"""
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raise NotImplementedError
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def is_satisfied_by(self, requirement, candidate):
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"""Whether the given requirement can be satisfied by a candidate.
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The candidate is guaranteed to have been generated from the
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requirement.
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A boolean should be returned to indicate whether ``candidate`` is a
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viable solution to the requirement.
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"""
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raise NotImplementedError
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def get_dependencies(self, candidate):
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"""Get dependencies of a candidate.
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This should return a collection of requirements that `candidate`
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specifies as its dependencies.
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"""
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raise NotImplementedError
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class AbstractResolver(object):
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"""The thing that performs the actual resolution work."""
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base_exception = Exception
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def __init__(self, provider, reporter):
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self.provider = provider
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self.reporter = reporter
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def resolve(self, requirements, **kwargs):
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"""Take a collection of constraints, spit out the resolution result.
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This returns a representation of the final resolution state, with one
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guarenteed attribute ``mapping`` that contains resolved candidates as
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values. The keys are their respective identifiers.
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:param requirements: A collection of constraints.
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:param kwargs: Additional keyword arguments that subclasses may accept.
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:raises: ``self.base_exception`` or its subclass.
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"""
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raise NotImplementedError
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class BaseReporter(object):
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"""Delegate class to provider progress reporting for the resolver."""
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def starting(self):
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"""Called before the resolution actually starts."""
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def starting_round(self, index):
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"""Called before each round of resolution starts.
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The index is zero-based.
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"""
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def ending_round(self, index, state):
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"""Called before each round of resolution ends.
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This is NOT called if the resolution ends at this round. Use `ending`
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if you want to report finalization. The index is zero-based.
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"""
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def ending(self, state):
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"""Called before the resolution ends successfully."""
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def adding_requirement(self, requirement, parent):
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"""Called when adding a new requirement into the resolve criteria.
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:param requirement: The additional requirement to be applied to filter
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the available candidaites.
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:param parent: The candidate that requires ``requirement`` as a
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dependency, or None if ``requirement`` is one of the root
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requirements passed in from ``Resolver.resolve()``.
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"""
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def resolving_conflicts(self, causes):
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"""Called when starting to attempt requirement conflict resolution.
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:param causes: The information on the collision that caused the backtracking.
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"""
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def rejecting_candidate(self, criterion, candidate):
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"""Called when rejecting a candidate during backtracking."""
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def pinning(self, candidate):
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"""Called when adding a candidate to the potential solution."""
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import collections
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import itertools
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import operator
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from .providers import AbstractResolver
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from .structs import DirectedGraph, IteratorMapping, build_iter_view
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RequirementInformation = collections.namedtuple(
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"RequirementInformation", ["requirement", "parent"]
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)
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class ResolverException(Exception):
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"""A base class for all exceptions raised by this module.
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Exceptions derived by this class should all be handled in this module. Any
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bubbling pass the resolver should be treated as a bug.
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"""
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class RequirementsConflicted(ResolverException):
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def __init__(self, criterion):
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super(RequirementsConflicted, self).__init__(criterion)
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self.criterion = criterion
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def __str__(self):
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return "Requirements conflict: {}".format(
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", ".join(repr(r) for r in self.criterion.iter_requirement()),
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)
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class InconsistentCandidate(ResolverException):
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def __init__(self, candidate, criterion):
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super(InconsistentCandidate, self).__init__(candidate, criterion)
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self.candidate = candidate
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self.criterion = criterion
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def __str__(self):
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return "Provided candidate {!r} does not satisfy {}".format(
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self.candidate,
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", ".join(repr(r) for r in self.criterion.iter_requirement()),
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)
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class Criterion(object):
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"""Representation of possible resolution results of a package.
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This holds three attributes:
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* `information` is a collection of `RequirementInformation` pairs.
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Each pair is a requirement contributing to this criterion, and the
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candidate that provides the requirement.
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* `incompatibilities` is a collection of all known not-to-work candidates
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to exclude from consideration.
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* `candidates` is a collection containing all possible candidates deducted
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from the union of contributing requirements and known incompatibilities.
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It should never be empty, except when the criterion is an attribute of a
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raised `RequirementsConflicted` (in which case it is always empty).
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.. note::
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This class is intended to be externally immutable. **Do not** mutate
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any of its attribute containers.
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"""
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def __init__(self, candidates, information, incompatibilities):
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self.candidates = candidates
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self.information = information
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self.incompatibilities = incompatibilities
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def __repr__(self):
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requirements = ", ".join(
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"({!r}, via={!r})".format(req, parent)
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for req, parent in self.information
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)
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return "Criterion({})".format(requirements)
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def iter_requirement(self):
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return (i.requirement for i in self.information)
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def iter_parent(self):
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return (i.parent for i in self.information)
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class ResolutionError(ResolverException):
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pass
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class ResolutionImpossible(ResolutionError):
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def __init__(self, causes):
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super(ResolutionImpossible, self).__init__(causes)
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# causes is a list of RequirementInformation objects
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self.causes = causes
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class ResolutionTooDeep(ResolutionError):
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def __init__(self, round_count):
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super(ResolutionTooDeep, self).__init__(round_count)
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self.round_count = round_count
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# Resolution state in a round.
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State = collections.namedtuple("State", "mapping criteria backtrack_causes")
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class Resolution(object):
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"""Stateful resolution object.
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This is designed as a one-off object that holds information to kick start
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the resolution process, and holds the results afterwards.
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"""
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def __init__(self, provider, reporter):
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self._p = provider
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self._r = reporter
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self._states = []
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@property
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def state(self):
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try:
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return self._states[-1]
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except IndexError:
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raise AttributeError("state")
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def _push_new_state(self):
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"""Push a new state into history.
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This new state will be used to hold resolution results of the next
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coming round.
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"""
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base = self._states[-1]
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state = State(
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mapping=base.mapping.copy(),
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criteria=base.criteria.copy(),
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backtrack_causes=base.backtrack_causes[:],
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)
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self._states.append(state)
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def _add_to_criteria(self, criteria, requirement, parent):
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self._r.adding_requirement(requirement=requirement, parent=parent)
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identifier = self._p.identify(requirement_or_candidate=requirement)
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criterion = criteria.get(identifier)
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if criterion:
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incompatibilities = list(criterion.incompatibilities)
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else:
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incompatibilities = []
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matches = self._p.find_matches(
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identifier=identifier,
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requirements=IteratorMapping(
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criteria,
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operator.methodcaller("iter_requirement"),
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{identifier: [requirement]},
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),
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incompatibilities=IteratorMapping(
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criteria,
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operator.attrgetter("incompatibilities"),
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{identifier: incompatibilities},
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),
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)
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if criterion:
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information = list(criterion.information)
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information.append(RequirementInformation(requirement, parent))
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else:
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information = [RequirementInformation(requirement, parent)]
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criterion = Criterion(
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candidates=build_iter_view(matches),
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information=information,
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incompatibilities=incompatibilities,
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)
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if not criterion.candidates:
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raise RequirementsConflicted(criterion)
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criteria[identifier] = criterion
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def _remove_information_from_criteria(self, criteria, parents):
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"""Remove information from parents of criteria.
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Concretely, removes all values from each criterion's ``information``
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field that have one of ``parents`` as provider of the requirement.
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:param criteria: The criteria to update.
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:param parents: Identifiers for which to remove information from all criteria.
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"""
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if not parents:
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return
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for key, criterion in criteria.items():
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criteria[key] = Criterion(
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criterion.candidates,
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[
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information
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for information in criterion.information
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if (
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information.parent is None
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or self._p.identify(information.parent) not in parents
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)
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],
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criterion.incompatibilities,
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)
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def _get_preference(self, name):
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return self._p.get_preference(
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identifier=name,
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resolutions=self.state.mapping,
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candidates=IteratorMapping(
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self.state.criteria,
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operator.attrgetter("candidates"),
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),
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information=IteratorMapping(
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self.state.criteria,
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operator.attrgetter("information"),
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),
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backtrack_causes=self.state.backtrack_causes,
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)
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def _is_current_pin_satisfying(self, name, criterion):
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try:
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current_pin = self.state.mapping[name]
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except KeyError:
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return False
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return all(
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self._p.is_satisfied_by(requirement=r, candidate=current_pin)
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for r in criterion.iter_requirement()
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)
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def _get_updated_criteria(self, candidate):
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criteria = self.state.criteria.copy()
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for requirement in self._p.get_dependencies(candidate=candidate):
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self._add_to_criteria(criteria, requirement, parent=candidate)
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return criteria
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def _attempt_to_pin_criterion(self, name):
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criterion = self.state.criteria[name]
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|
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causes = []
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for candidate in criterion.candidates:
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try:
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criteria = self._get_updated_criteria(candidate)
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except RequirementsConflicted as e:
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self._r.rejecting_candidate(e.criterion, candidate)
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causes.append(e.criterion)
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continue
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# Check the newly-pinned candidate actually works. This should
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# always pass under normal circumstances, but in the case of a
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# faulty provider, we will raise an error to notify the implementer
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# to fix find_matches() and/or is_satisfied_by().
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satisfied = all(
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self._p.is_satisfied_by(requirement=r, candidate=candidate)
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for r in criterion.iter_requirement()
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)
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if not satisfied:
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raise InconsistentCandidate(candidate, criterion)
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self._r.pinning(candidate=candidate)
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self.state.criteria.update(criteria)
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# Put newly-pinned candidate at the end. This is essential because
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# backtracking looks at this mapping to get the last pin.
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self.state.mapping.pop(name, None)
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self.state.mapping[name] = candidate
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return []
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# All candidates tried, nothing works. This criterion is a dead
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# end, signal for backtracking.
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return causes
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def _backjump(self, causes):
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"""Perform backjumping.
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When we enter here, the stack is like this::
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|
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[ state Z ]
|
||||
[ state Y ]
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[ state X ]
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.... earlier states are irrelevant.
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1. No pins worked for Z, so it does not have a pin.
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2. We want to reset state Y to unpinned, and pin another candidate.
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3. State X holds what state Y was before the pin, but does not
|
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have the incompatibility information gathered in state Y.
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Each iteration of the loop will:
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1. Identify Z. The incompatibility is not always caused by the latest
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state. For example, given three requirements A, B and C, with
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dependencies A1, B1 and C1, where A1 and B1 are incompatible: the
|
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last state might be related to C, so we want to discard the
|
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previous state.
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2. Discard Z.
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3. Discard Y but remember its incompatibility information gathered
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previously, and the failure we're dealing with right now.
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4. Push a new state Y' based on X, and apply the incompatibility
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information from Y to Y'.
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5a. If this causes Y' to conflict, we need to backtrack again. Make Y'
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the new Z and go back to step 2.
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5b. If the incompatibilities apply cleanly, end backtracking.
|
||||
"""
|
||||
incompatible_reqs = itertools.chain(
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(c.parent for c in causes if c.parent is not None),
|
||||
(c.requirement for c in causes),
|
||||
)
|
||||
incompatible_deps = {self._p.identify(r) for r in incompatible_reqs}
|
||||
while len(self._states) >= 3:
|
||||
# Remove the state that triggered backtracking.
|
||||
del self._states[-1]
|
||||
|
||||
# Ensure to backtrack to a state that caused the incompatibility
|
||||
incompatible_state = False
|
||||
while not incompatible_state:
|
||||
# Retrieve the last candidate pin and known incompatibilities.
|
||||
try:
|
||||
broken_state = self._states.pop()
|
||||
name, candidate = broken_state.mapping.popitem()
|
||||
except (IndexError, KeyError):
|
||||
raise ResolutionImpossible(causes)
|
||||
current_dependencies = {
|
||||
self._p.identify(d)
|
||||
for d in self._p.get_dependencies(candidate)
|
||||
}
|
||||
incompatible_state = not current_dependencies.isdisjoint(
|
||||
incompatible_deps
|
||||
)
|
||||
|
||||
incompatibilities_from_broken = [
|
||||
(k, list(v.incompatibilities))
|
||||
for k, v in broken_state.criteria.items()
|
||||
]
|
||||
|
||||
# Also mark the newly known incompatibility.
|
||||
incompatibilities_from_broken.append((name, [candidate]))
|
||||
|
||||
# Create a new state from the last known-to-work one, and apply
|
||||
# the previously gathered incompatibility information.
|
||||
def _patch_criteria():
|
||||
for k, incompatibilities in incompatibilities_from_broken:
|
||||
if not incompatibilities:
|
||||
continue
|
||||
try:
|
||||
criterion = self.state.criteria[k]
|
||||
except KeyError:
|
||||
continue
|
||||
matches = self._p.find_matches(
|
||||
identifier=k,
|
||||
requirements=IteratorMapping(
|
||||
self.state.criteria,
|
||||
operator.methodcaller("iter_requirement"),
|
||||
),
|
||||
incompatibilities=IteratorMapping(
|
||||
self.state.criteria,
|
||||
operator.attrgetter("incompatibilities"),
|
||||
{k: incompatibilities},
|
||||
),
|
||||
)
|
||||
candidates = build_iter_view(matches)
|
||||
if not candidates:
|
||||
return False
|
||||
incompatibilities.extend(criterion.incompatibilities)
|
||||
self.state.criteria[k] = Criterion(
|
||||
candidates=candidates,
|
||||
information=list(criterion.information),
|
||||
incompatibilities=incompatibilities,
|
||||
)
|
||||
return True
|
||||
|
||||
self._push_new_state()
|
||||
success = _patch_criteria()
|
||||
|
||||
# It works! Let's work on this new state.
|
||||
if success:
|
||||
return True
|
||||
|
||||
# State does not work after applying known incompatibilities.
|
||||
# Try the still previous state.
|
||||
|
||||
# No way to backtrack anymore.
|
||||
return False
|
||||
|
||||
def resolve(self, requirements, max_rounds):
|
||||
if self._states:
|
||||
raise RuntimeError("already resolved")
|
||||
|
||||
self._r.starting()
|
||||
|
||||
# Initialize the root state.
|
||||
self._states = [
|
||||
State(
|
||||
mapping=collections.OrderedDict(),
|
||||
criteria={},
|
||||
backtrack_causes=[],
|
||||
)
|
||||
]
|
||||
for r in requirements:
|
||||
try:
|
||||
self._add_to_criteria(self.state.criteria, r, parent=None)
|
||||
except RequirementsConflicted as e:
|
||||
raise ResolutionImpossible(e.criterion.information)
|
||||
|
||||
# The root state is saved as a sentinel so the first ever pin can have
|
||||
# something to backtrack to if it fails. The root state is basically
|
||||
# pinning the virtual "root" package in the graph.
|
||||
self._push_new_state()
|
||||
|
||||
for round_index in range(max_rounds):
|
||||
self._r.starting_round(index=round_index)
|
||||
|
||||
unsatisfied_names = [
|
||||
key
|
||||
for key, criterion in self.state.criteria.items()
|
||||
if not self._is_current_pin_satisfying(key, criterion)
|
||||
]
|
||||
|
||||
# All criteria are accounted for. Nothing more to pin, we are done!
|
||||
if not unsatisfied_names:
|
||||
self._r.ending(state=self.state)
|
||||
return self.state
|
||||
|
||||
# keep track of satisfied names to calculate diff after pinning
|
||||
satisfied_names = set(self.state.criteria.keys()) - set(
|
||||
unsatisfied_names
|
||||
)
|
||||
|
||||
# Choose the most preferred unpinned criterion to try.
|
||||
name = min(unsatisfied_names, key=self._get_preference)
|
||||
failure_causes = self._attempt_to_pin_criterion(name)
|
||||
|
||||
if failure_causes:
|
||||
causes = [i for c in failure_causes for i in c.information]
|
||||
# Backjump if pinning fails. The backjump process puts us in
|
||||
# an unpinned state, so we can work on it in the next round.
|
||||
self._r.resolving_conflicts(causes=causes)
|
||||
success = self._backjump(causes)
|
||||
self.state.backtrack_causes[:] = causes
|
||||
|
||||
# Dead ends everywhere. Give up.
|
||||
if not success:
|
||||
raise ResolutionImpossible(self.state.backtrack_causes)
|
||||
else:
|
||||
# discard as information sources any invalidated names
|
||||
# (unsatisfied names that were previously satisfied)
|
||||
newly_unsatisfied_names = {
|
||||
key
|
||||
for key, criterion in self.state.criteria.items()
|
||||
if key in satisfied_names
|
||||
and not self._is_current_pin_satisfying(key, criterion)
|
||||
}
|
||||
self._remove_information_from_criteria(
|
||||
self.state.criteria, newly_unsatisfied_names
|
||||
)
|
||||
# Pinning was successful. Push a new state to do another pin.
|
||||
self._push_new_state()
|
||||
|
||||
self._r.ending_round(index=round_index, state=self.state)
|
||||
|
||||
raise ResolutionTooDeep(max_rounds)
|
||||
|
||||
|
||||
def _has_route_to_root(criteria, key, all_keys, connected):
|
||||
if key in connected:
|
||||
return True
|
||||
if key not in criteria:
|
||||
return False
|
||||
for p in criteria[key].iter_parent():
|
||||
try:
|
||||
pkey = all_keys[id(p)]
|
||||
except KeyError:
|
||||
continue
|
||||
if pkey in connected:
|
||||
connected.add(key)
|
||||
return True
|
||||
if _has_route_to_root(criteria, pkey, all_keys, connected):
|
||||
connected.add(key)
|
||||
return True
|
||||
return False
|
||||
|
||||
|
||||
Result = collections.namedtuple("Result", "mapping graph criteria")
|
||||
|
||||
|
||||
def _build_result(state):
|
||||
mapping = state.mapping
|
||||
all_keys = {id(v): k for k, v in mapping.items()}
|
||||
all_keys[id(None)] = None
|
||||
|
||||
graph = DirectedGraph()
|
||||
graph.add(None) # Sentinel as root dependencies' parent.
|
||||
|
||||
connected = {None}
|
||||
for key, criterion in state.criteria.items():
|
||||
if not _has_route_to_root(state.criteria, key, all_keys, connected):
|
||||
continue
|
||||
if key not in graph:
|
||||
graph.add(key)
|
||||
for p in criterion.iter_parent():
|
||||
try:
|
||||
pkey = all_keys[id(p)]
|
||||
except KeyError:
|
||||
continue
|
||||
if pkey not in graph:
|
||||
graph.add(pkey)
|
||||
graph.connect(pkey, key)
|
||||
|
||||
return Result(
|
||||
mapping={k: v for k, v in mapping.items() if k in connected},
|
||||
graph=graph,
|
||||
criteria=state.criteria,
|
||||
)
|
||||
|
||||
|
||||
class Resolver(AbstractResolver):
|
||||
"""The thing that performs the actual resolution work."""
|
||||
|
||||
base_exception = ResolverException
|
||||
|
||||
def resolve(self, requirements, max_rounds=100):
|
||||
"""Take a collection of constraints, spit out the resolution result.
|
||||
|
||||
The return value is a representation to the final resolution result. It
|
||||
is a tuple subclass with three public members:
|
||||
|
||||
* `mapping`: A dict of resolved candidates. Each key is an identifier
|
||||
of a requirement (as returned by the provider's `identify` method),
|
||||
and the value is the resolved candidate.
|
||||
* `graph`: A `DirectedGraph` instance representing the dependency tree.
|
||||
The vertices are keys of `mapping`, and each edge represents *why*
|
||||
a particular package is included. A special vertex `None` is
|
||||
included to represent parents of user-supplied requirements.
|
||||
* `criteria`: A dict of "criteria" that hold detailed information on
|
||||
how edges in the graph are derived. Each key is an identifier of a
|
||||
requirement, and the value is a `Criterion` instance.
|
||||
|
||||
The following exceptions may be raised if a resolution cannot be found:
|
||||
|
||||
* `ResolutionImpossible`: A resolution cannot be found for the given
|
||||
combination of requirements. The `causes` attribute of the
|
||||
exception is a list of (requirement, parent), giving the
|
||||
requirements that could not be satisfied.
|
||||
* `ResolutionTooDeep`: The dependency tree is too deeply nested and
|
||||
the resolver gave up. This is usually caused by a circular
|
||||
dependency, but you can try to resolve this by increasing the
|
||||
`max_rounds` argument.
|
||||
"""
|
||||
resolution = Resolution(self.provider, self.reporter)
|
||||
state = resolution.resolve(requirements, max_rounds=max_rounds)
|
||||
return _build_result(state)
|
||||
|
|
@ -0,0 +1,170 @@
|
|||
import itertools
|
||||
|
||||
from .compat import collections_abc
|
||||
|
||||
|
||||
class DirectedGraph(object):
|
||||
"""A graph structure with directed edges."""
|
||||
|
||||
def __init__(self):
|
||||
self._vertices = set()
|
||||
self._forwards = {} # <key> -> Set[<key>]
|
||||
self._backwards = {} # <key> -> Set[<key>]
|
||||
|
||||
def __iter__(self):
|
||||
return iter(self._vertices)
|
||||
|
||||
def __len__(self):
|
||||
return len(self._vertices)
|
||||
|
||||
def __contains__(self, key):
|
||||
return key in self._vertices
|
||||
|
||||
def copy(self):
|
||||
"""Return a shallow copy of this graph."""
|
||||
other = DirectedGraph()
|
||||
other._vertices = set(self._vertices)
|
||||
other._forwards = {k: set(v) for k, v in self._forwards.items()}
|
||||
other._backwards = {k: set(v) for k, v in self._backwards.items()}
|
||||
return other
|
||||
|
||||
def add(self, key):
|
||||
"""Add a new vertex to the graph."""
|
||||
if key in self._vertices:
|
||||
raise ValueError("vertex exists")
|
||||
self._vertices.add(key)
|
||||
self._forwards[key] = set()
|
||||
self._backwards[key] = set()
|
||||
|
||||
def remove(self, key):
|
||||
"""Remove a vertex from the graph, disconnecting all edges from/to it."""
|
||||
self._vertices.remove(key)
|
||||
for f in self._forwards.pop(key):
|
||||
self._backwards[f].remove(key)
|
||||
for t in self._backwards.pop(key):
|
||||
self._forwards[t].remove(key)
|
||||
|
||||
def connected(self, f, t):
|
||||
return f in self._backwards[t] and t in self._forwards[f]
|
||||
|
||||
def connect(self, f, t):
|
||||
"""Connect two existing vertices.
|
||||
|
||||
Nothing happens if the vertices are already connected.
|
||||
"""
|
||||
if t not in self._vertices:
|
||||
raise KeyError(t)
|
||||
self._forwards[f].add(t)
|
||||
self._backwards[t].add(f)
|
||||
|
||||
def iter_edges(self):
|
||||
for f, children in self._forwards.items():
|
||||
for t in children:
|
||||
yield f, t
|
||||
|
||||
def iter_children(self, key):
|
||||
return iter(self._forwards[key])
|
||||
|
||||
def iter_parents(self, key):
|
||||
return iter(self._backwards[key])
|
||||
|
||||
|
||||
class IteratorMapping(collections_abc.Mapping):
|
||||
def __init__(self, mapping, accessor, appends=None):
|
||||
self._mapping = mapping
|
||||
self._accessor = accessor
|
||||
self._appends = appends or {}
|
||||
|
||||
def __repr__(self):
|
||||
return "IteratorMapping({!r}, {!r}, {!r})".format(
|
||||
self._mapping,
|
||||
self._accessor,
|
||||
self._appends,
|
||||
)
|
||||
|
||||
def __bool__(self):
|
||||
return bool(self._mapping or self._appends)
|
||||
|
||||
__nonzero__ = __bool__ # XXX: Python 2.
|
||||
|
||||
def __contains__(self, key):
|
||||
return key in self._mapping or key in self._appends
|
||||
|
||||
def __getitem__(self, k):
|
||||
try:
|
||||
v = self._mapping[k]
|
||||
except KeyError:
|
||||
return iter(self._appends[k])
|
||||
return itertools.chain(self._accessor(v), self._appends.get(k, ()))
|
||||
|
||||
def __iter__(self):
|
||||
more = (k for k in self._appends if k not in self._mapping)
|
||||
return itertools.chain(self._mapping, more)
|
||||
|
||||
def __len__(self):
|
||||
more = sum(1 for k in self._appends if k not in self._mapping)
|
||||
return len(self._mapping) + more
|
||||
|
||||
|
||||
class _FactoryIterableView(object):
|
||||
"""Wrap an iterator factory returned by `find_matches()`.
|
||||
|
||||
Calling `iter()` on this class would invoke the underlying iterator
|
||||
factory, making it a "collection with ordering" that can be iterated
|
||||
through multiple times, but lacks random access methods presented in
|
||||
built-in Python sequence types.
|
||||
"""
|
||||
|
||||
def __init__(self, factory):
|
||||
self._factory = factory
|
||||
self._iterable = None
|
||||
|
||||
def __repr__(self):
|
||||
return "{}({})".format(type(self).__name__, list(self))
|
||||
|
||||
def __bool__(self):
|
||||
try:
|
||||
next(iter(self))
|
||||
except StopIteration:
|
||||
return False
|
||||
return True
|
||||
|
||||
__nonzero__ = __bool__ # XXX: Python 2.
|
||||
|
||||
def __iter__(self):
|
||||
iterable = (
|
||||
self._factory() if self._iterable is None else self._iterable
|
||||
)
|
||||
self._iterable, current = itertools.tee(iterable)
|
||||
return current
|
||||
|
||||
|
||||
class _SequenceIterableView(object):
|
||||
"""Wrap an iterable returned by find_matches().
|
||||
|
||||
This is essentially just a proxy to the underlying sequence that provides
|
||||
the same interface as `_FactoryIterableView`.
|
||||
"""
|
||||
|
||||
def __init__(self, sequence):
|
||||
self._sequence = sequence
|
||||
|
||||
def __repr__(self):
|
||||
return "{}({})".format(type(self).__name__, self._sequence)
|
||||
|
||||
def __bool__(self):
|
||||
return bool(self._sequence)
|
||||
|
||||
__nonzero__ = __bool__ # XXX: Python 2.
|
||||
|
||||
def __iter__(self):
|
||||
return iter(self._sequence)
|
||||
|
||||
|
||||
def build_iter_view(matches):
|
||||
"""Build an iterable view from the value returned by `find_matches()`."""
|
||||
if callable(matches):
|
||||
return _FactoryIterableView(matches)
|
||||
if not isinstance(matches, collections_abc.Sequence):
|
||||
matches = list(matches)
|
||||
return _SequenceIterableView(matches)
|
||||
Loading…
Add table
Add a link
Reference in a new issue