399 lines
16 KiB
Python
399 lines
16 KiB
Python
import warnings
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from collections import deque
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from functools import total_ordering
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from django.db.migrations.state import ProjectState
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from django.utils.datastructures import OrderedSet
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from .exceptions import CircularDependencyError, NodeNotFoundError
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RECURSION_DEPTH_WARNING = (
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"Maximum recursion depth exceeded while generating migration graph, "
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"falling back to iterative approach. If you're experiencing performance issues, "
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"consider squashing migrations as described at "
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"https://docs.djangoproject.com/en/dev/topics/migrations/#squashing-migrations."
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)
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@total_ordering
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class Node:
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"""
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A single node in the migration graph. Contains direct links to adjacent
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nodes in either direction.
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"""
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def __init__(self, key):
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self.key = key
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self.children = set()
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self.parents = set()
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def __eq__(self, other):
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return self.key == other
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def __lt__(self, other):
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return self.key < other
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def __hash__(self):
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return hash(self.key)
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def __getitem__(self, item):
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return self.key[item]
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def __str__(self):
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return str(self.key)
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def __repr__(self):
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return '<Node: (%r, %r)>' % self.key
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def add_child(self, child):
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self.children.add(child)
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def add_parent(self, parent):
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self.parents.add(parent)
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# Use manual caching, @cached_property effectively doubles the
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# recursion depth for each recursion.
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def ancestors(self):
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# Use self.key instead of self to speed up the frequent hashing
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# when constructing an OrderedSet.
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if '_ancestors' not in self.__dict__:
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ancestors = deque([self.key])
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for parent in sorted(self.parents):
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ancestors.extendleft(reversed(parent.ancestors()))
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self.__dict__['_ancestors'] = list(OrderedSet(ancestors))
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return self.__dict__['_ancestors']
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# Use manual caching, @cached_property effectively doubles the
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# recursion depth for each recursion.
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def descendants(self):
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# Use self.key instead of self to speed up the frequent hashing
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# when constructing an OrderedSet.
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if '_descendants' not in self.__dict__:
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descendants = deque([self.key])
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for child in sorted(self.children):
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descendants.extendleft(reversed(child.descendants()))
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self.__dict__['_descendants'] = list(OrderedSet(descendants))
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return self.__dict__['_descendants']
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class DummyNode(Node):
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def __init__(self, key, origin, error_message):
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super().__init__(key)
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self.origin = origin
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self.error_message = error_message
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def __repr__(self):
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return '<DummyNode: (%r, %r)>' % self.key
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def promote(self):
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"""
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Transition dummy to a normal node and clean off excess attribs.
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Creating a Node object from scratch would be too much of a
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hassle as many dependendies would need to be remapped.
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"""
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del self.origin
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del self.error_message
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self.__class__ = Node
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def raise_error(self):
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raise NodeNotFoundError(self.error_message, self.key, origin=self.origin)
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class MigrationGraph:
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"""
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Represents the digraph of all migrations in a project.
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Each migration is a node, and each dependency is an edge. There are
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no implicit dependencies between numbered migrations - the numbering is
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merely a convention to aid file listing. Every new numbered migration
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has a declared dependency to the previous number, meaning that VCS
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branch merges can be detected and resolved.
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Migrations files can be marked as replacing another set of migrations -
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this is to support the "squash" feature. The graph handler isn't responsible
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for these; instead, the code to load them in here should examine the
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migration files and if the replaced migrations are all either unapplied
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or not present, it should ignore the replaced ones, load in just the
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replacing migration, and repoint any dependencies that pointed to the
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replaced migrations to point to the replacing one.
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A node should be a tuple: (app_path, migration_name). The tree special-cases
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things within an app - namely, root nodes and leaf nodes ignore dependencies
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to other apps.
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"""
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def __init__(self):
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self.node_map = {}
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self.nodes = {}
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self.cached = False
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def add_node(self, key, migration):
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# If the key already exists, then it must be a dummy node.
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dummy_node = self.node_map.get(key)
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if dummy_node:
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# Promote DummyNode to Node.
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dummy_node.promote()
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else:
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node = Node(key)
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self.node_map[key] = node
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self.nodes[key] = migration
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self.clear_cache()
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def add_dummy_node(self, key, origin, error_message):
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node = DummyNode(key, origin, error_message)
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self.node_map[key] = node
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self.nodes[key] = None
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def add_dependency(self, migration, child, parent, skip_validation=False):
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"""
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This may create dummy nodes if they don't yet exist.
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If `skip_validation` is set, validate_consistency should be called afterwards.
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"""
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if child not in self.nodes:
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error_message = (
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"Migration %s dependencies reference nonexistent"
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" child node %r" % (migration, child)
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)
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self.add_dummy_node(child, migration, error_message)
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if parent not in self.nodes:
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error_message = (
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"Migration %s dependencies reference nonexistent"
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" parent node %r" % (migration, parent)
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)
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self.add_dummy_node(parent, migration, error_message)
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self.node_map[child].add_parent(self.node_map[parent])
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self.node_map[parent].add_child(self.node_map[child])
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if not skip_validation:
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self.validate_consistency()
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self.clear_cache()
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def remove_replaced_nodes(self, replacement, replaced):
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"""
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Removes each of the `replaced` nodes (when they exist). Any
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dependencies that were referencing them are changed to reference the
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`replacement` node instead.
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"""
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# Cast list of replaced keys to set to speed up lookup later.
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replaced = set(replaced)
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try:
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replacement_node = self.node_map[replacement]
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except KeyError as err:
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raise NodeNotFoundError(
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"Unable to find replacement node %r. It was either never added"
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" to the migration graph, or has been removed." % (replacement, ),
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replacement
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) from err
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for replaced_key in replaced:
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self.nodes.pop(replaced_key, None)
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replaced_node = self.node_map.pop(replaced_key, None)
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if replaced_node:
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for child in replaced_node.children:
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child.parents.remove(replaced_node)
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# We don't want to create dependencies between the replaced
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# node and the replacement node as this would lead to
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# self-referencing on the replacement node at a later iteration.
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if child.key not in replaced:
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replacement_node.add_child(child)
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child.add_parent(replacement_node)
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for parent in replaced_node.parents:
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parent.children.remove(replaced_node)
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# Again, to avoid self-referencing.
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if parent.key not in replaced:
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replacement_node.add_parent(parent)
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parent.add_child(replacement_node)
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self.clear_cache()
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def remove_replacement_node(self, replacement, replaced):
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"""
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The inverse operation to `remove_replaced_nodes`. Almost. Removes the
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replacement node `replacement` and remaps its child nodes to
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`replaced` - the list of nodes it would have replaced. Its parent
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nodes are not remapped as they are expected to be correct already.
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"""
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self.nodes.pop(replacement, None)
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try:
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replacement_node = self.node_map.pop(replacement)
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except KeyError as err:
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raise NodeNotFoundError(
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"Unable to remove replacement node %r. It was either never added"
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" to the migration graph, or has been removed already." % (replacement, ),
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replacement
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) from err
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replaced_nodes = set()
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replaced_nodes_parents = set()
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for key in replaced:
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replaced_node = self.node_map.get(key)
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if replaced_node:
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replaced_nodes.add(replaced_node)
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replaced_nodes_parents |= replaced_node.parents
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# We're only interested in the latest replaced node, so filter out
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# replaced nodes that are parents of other replaced nodes.
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replaced_nodes -= replaced_nodes_parents
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for child in replacement_node.children:
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child.parents.remove(replacement_node)
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for replaced_node in replaced_nodes:
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replaced_node.add_child(child)
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child.add_parent(replaced_node)
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for parent in replacement_node.parents:
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parent.children.remove(replacement_node)
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# NOTE: There is no need to remap parent dependencies as we can
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# assume the replaced nodes already have the correct ancestry.
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self.clear_cache()
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def validate_consistency(self):
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"""
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Ensure there are no dummy nodes remaining in the graph.
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"""
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[n.raise_error() for n in self.node_map.values() if isinstance(n, DummyNode)]
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def clear_cache(self):
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if self.cached:
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for node in self.nodes:
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self.node_map[node].__dict__.pop('_ancestors', None)
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self.node_map[node].__dict__.pop('_descendants', None)
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self.cached = False
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def forwards_plan(self, target):
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"""
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Given a node, returns a list of which previous nodes (dependencies)
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must be applied, ending with the node itself.
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This is the list you would follow if applying the migrations to
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a database.
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"""
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if target not in self.nodes:
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raise NodeNotFoundError("Node %r not a valid node" % (target, ), target)
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# Use parent.key instead of parent to speed up the frequent hashing in ensure_not_cyclic
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self.ensure_not_cyclic(target, lambda x: (parent.key for parent in self.node_map[x].parents))
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self.cached = True
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node = self.node_map[target]
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try:
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return node.ancestors()
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except RuntimeError:
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# fallback to iterative dfs
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warnings.warn(RECURSION_DEPTH_WARNING, RuntimeWarning)
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return self.iterative_dfs(node)
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def backwards_plan(self, target):
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"""
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Given a node, returns a list of which dependent nodes (dependencies)
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must be unapplied, ending with the node itself.
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This is the list you would follow if removing the migrations from
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a database.
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"""
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if target not in self.nodes:
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raise NodeNotFoundError("Node %r not a valid node" % (target, ), target)
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# Use child.key instead of child to speed up the frequent hashing in ensure_not_cyclic
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self.ensure_not_cyclic(target, lambda x: (child.key for child in self.node_map[x].children))
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self.cached = True
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node = self.node_map[target]
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try:
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return node.descendants()
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except RuntimeError:
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# fallback to iterative dfs
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warnings.warn(RECURSION_DEPTH_WARNING, RuntimeWarning)
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return self.iterative_dfs(node, forwards=False)
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def iterative_dfs(self, start, forwards=True):
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"""
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Iterative depth first search, for finding dependencies.
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"""
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visited = deque()
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visited.append(start)
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if forwards:
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stack = deque(sorted(start.parents))
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else:
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stack = deque(sorted(start.children))
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while stack:
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node = stack.popleft()
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visited.appendleft(node)
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if forwards:
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children = sorted(node.parents, reverse=True)
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else:
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children = sorted(node.children, reverse=True)
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# reverse sorting is needed because prepending using deque.extendleft
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# also effectively reverses values
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stack.extendleft(children)
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return list(OrderedSet(visited))
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def root_nodes(self, app=None):
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"""
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Returns all root nodes - that is, nodes with no dependencies inside
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their app. These are the starting point for an app.
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"""
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roots = set()
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for node in self.nodes:
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if not any(key[0] == node[0] for key in self.node_map[node].parents) and (not app or app == node[0]):
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roots.add(node)
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return sorted(roots)
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def leaf_nodes(self, app=None):
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"""
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Returns all leaf nodes - that is, nodes with no dependents in their app.
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These are the "most current" version of an app's schema.
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Having more than one per app is technically an error, but one that
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gets handled further up, in the interactive command - it's usually the
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result of a VCS merge and needs some user input.
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"""
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leaves = set()
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for node in self.nodes:
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if not any(key[0] == node[0] for key in self.node_map[node].children) and (not app or app == node[0]):
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leaves.add(node)
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return sorted(leaves)
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def ensure_not_cyclic(self, start, get_children):
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# Algo from GvR:
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# http://neopythonic.blogspot.co.uk/2009/01/detecting-cycles-in-directed-graph.html
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todo = set(self.nodes)
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while todo:
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node = todo.pop()
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stack = [node]
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while stack:
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top = stack[-1]
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for node in get_children(top):
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if node in stack:
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cycle = stack[stack.index(node):]
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raise CircularDependencyError(", ".join("%s.%s" % n for n in cycle))
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if node in todo:
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stack.append(node)
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todo.remove(node)
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break
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else:
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node = stack.pop()
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def __str__(self):
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return 'Graph: %s nodes, %s edges' % self._nodes_and_edges()
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def __repr__(self):
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nodes, edges = self._nodes_and_edges()
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return '<%s: nodes=%s, edges=%s>' % (self.__class__.__name__, nodes, edges)
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def _nodes_and_edges(self):
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return len(self.nodes), sum(len(node.parents) for node in self.node_map.values())
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def make_state(self, nodes=None, at_end=True, real_apps=None):
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"""
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Given a migration node or nodes, returns a complete ProjectState for it.
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If at_end is False, returns the state before the migration has run.
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If nodes is not provided, returns the overall most current project state.
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"""
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if nodes is None:
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nodes = list(self.leaf_nodes())
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if len(nodes) == 0:
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return ProjectState()
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if not isinstance(nodes[0], tuple):
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nodes = [nodes]
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plan = []
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for node in nodes:
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for migration in self.forwards_plan(node):
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if migration not in plan:
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if not at_end and migration in nodes:
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continue
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plan.append(migration)
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project_state = ProjectState(real_apps=real_apps)
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for node in plan:
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project_state = self.nodes[node].mutate_state(project_state, preserve=False)
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return project_state
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def __contains__(self, node):
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return node in self.nodes
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