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__module__� __qualname__�__doc__� r r �8/usr/lib/python3.9/site-packages/resolvelib/resolvers.pyr s r c s$ e Zd Z� fdd�Zdd� Z� ZS )�RequirementsConflictedc s t t| ��|� || _d S �N)�superr �__init__� criterion)�selfr �� __class__r r r s z RequirementsConflicted.__init__c C s d� d�dd� | j�� D ���S )NzRequirements conflict: {}�, c s s | ]}t |�V qd S r ��repr��.0�rr r r � <genexpr> � z1RequirementsConflicted.__str__.<locals>.<genexpr>)�format�joinr �iter_requirement�r r r r �__str__ s �z RequirementsConflicted.__str__�r
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dd� Z dS )� CriterionaQ Representation of possible resolution results of a package.
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to exclude from consideration.
* `candidates` is a collection containing all possible candidates deducted
from the union of contributing requirements and known incompatibilities.
It should never be empty, except when the criterion is an attribute of a
raised `RequirementsConflicted` (in which case it is always empty).
.. note::
This class is intended to be externally immutable. **Do not** mutate
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candidates� information�incompatibilities)r r* r+ r, r r r r @ s zCriterion.__init__c C s d� dd� | jD ��}d�|�S )Nr c s s | ]\}}d � ||�V qdS )z({!r}, via={!r})N)r )r Zreqr r r r r F s �z%Criterion.__repr__.<locals>.<genexpr>z
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� |� }|r dS q dS ) a� Perform backtracking.
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[ state Z ]
[ state Y ]
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2. We want to reset state Y to unpinned, and pin another candidate.
3. State X holds what state Y was before the pin, but does not
have the incompatibility information gathered in state Y.
Each iteration of the loop will:
1. Discard Z.
2. Discard Y but remember its incompatibility information gathered
previously, and the failure we're dealing with right now.
3. Push a new state Y' based on X, and apply the incompatibility
information from Y to Y'.
4a. If this causes Y' to conflict, we need to backtrack again. Make Y'
the new Z and go back to step 2.
4b. If the incompatibilities apply cleanly, end backtracking.
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�r� c @ s e Zd ZdZeZddd�ZdS )�Resolverz3The thing that performs the actual resolution work.�d c C s$ t | j| j�}|j||d�}t|�S )a 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.
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