From 2f172d8f1525defe9bba4d49e967fdfc69151731 Mon Sep 17 00:00:00 2001 From: Pablo Galindo Date: Mon, 1 Jun 2020 00:41:14 +0100 Subject: [PATCH] bpo-17005: Move topological sort functionality to its own module (GH-20558) The topological sort functionality that was introduced initially in the functools module has been moved to a new graphlib module to better accommodate the new tools and keep the original scope of the functools module. --- Doc/library/datatypes.rst | 1 + Doc/library/functools.rst | 196 +------------ Doc/library/graphlib.rst | 209 ++++++++++++++ Doc/whatsnew/3.9.rst | 15 +- Lib/functools.py | 245 ---------------- Lib/graphlib.py | 245 ++++++++++++++++ Lib/test/test_functools.py | 271 +----------------- Lib/test/test_graphlib.py | 244 ++++++++++++++++ .../2020-05-31-23-32-36.bpo-17005.JlRUGB.rst | 4 + PCbuild/lib.pyproj | 1 + 10 files changed, 714 insertions(+), 717 deletions(-) create mode 100644 Doc/library/graphlib.rst create mode 100644 Lib/graphlib.py create mode 100644 Lib/test/test_graphlib.py create mode 100644 Misc/NEWS.d/next/Library/2020-05-31-23-32-36.bpo-17005.JlRUGB.rst diff --git a/Doc/library/datatypes.rst b/Doc/library/datatypes.rst index 675bbb6fafd..ff51b2779e5 100644 --- a/Doc/library/datatypes.rst +++ b/Doc/library/datatypes.rst @@ -33,3 +33,4 @@ The following modules are documented in this chapter: pprint.rst reprlib.rst enum.rst + graphlib.rst diff --git a/Doc/library/functools.rst b/Doc/library/functools.rst index a44eb85b27d..14aa184e2cd 100644 --- a/Doc/library/functools.rst +++ b/Doc/library/functools.rst @@ -543,184 +543,6 @@ The :mod:`functools` module defines the following functions: .. versionadded:: 3.8 -.. class:: TopologicalSorter(graph=None) - - Provides functionality to topologically sort a graph of hashable nodes. - - A topological order is a linear ordering of the vertices in a graph such that - for every directed edge u -> v from vertex u to vertex v, vertex u comes - before vertex v in the ordering. For instance, the vertices of the graph may - represent tasks to be performed, and the edges may represent constraints that - one task must be performed before another; in this example, a topological - ordering is just a valid sequence for the tasks. A complete topological - ordering is possible if and only if the graph has no directed cycles, that - is, if it is a directed acyclic graph. - - If the optional *graph* argument is provided it must be a dictionary - representing a directed acyclic graph where the keys are nodes and the values - are iterables of all predecessors of that node in the graph (the nodes that - have edges that point to the value in the key). Additional nodes can be added - to the graph using the :meth:`~TopologicalSorter.add` method. - - In the general case, the steps required to perform the sorting of a given - graph are as follows: - - * Create an instance of the :class:`TopologicalSorter` with an optional - initial graph. - * Add additional nodes to the graph. - * Call :meth:`~TopologicalSorter.prepare` on the graph. - * While :meth:`~TopologicalSorter.is_active` is ``True``, iterate over - the nodes returned by :meth:`~TopologicalSorter.get_ready` and - process them. Call :meth:`~TopologicalSorter.done` on each node as it - finishes processing. - - In case just an immediate sorting of the nodes in the graph is required and - no parallelism is involved, the convenience method - :meth:`TopologicalSorter.static_order` can be used directly: - - .. doctest:: - - >>> graph = {"D": {"B", "C"}, "C": {"A"}, "B": {"A"}} - >>> ts = TopologicalSorter(graph) - >>> tuple(ts.static_order()) - ('A', 'C', 'B', 'D') - - The class is designed to easily support parallel processing of the nodes as - they become ready. For instance:: - - topological_sorter = TopologicalSorter() - - # Add nodes to 'topological_sorter'... - - topological_sorter.prepare() - while topological_sorter.is_active(): - for node in topological_sorter.get_ready(): - # Worker threads or processes take nodes to work on off the - # 'task_queue' queue. - task_queue.put(node) - - # When the work for a node is done, workers put the node in - # 'finalized_tasks_queue' so we can get more nodes to work on. - # The definition of 'is_active()' guarantees that, at this point, at - # least one node has been placed on 'task_queue' that hasn't yet - # been passed to 'done()', so this blocking 'get()' must (eventually) - # succeed. After calling 'done()', we loop back to call 'get_ready()' - # again, so put newly freed nodes on 'task_queue' as soon as - # logically possible. - node = finalized_tasks_queue.get() - topological_sorter.done(node) - - .. method:: add(node, *predecessors) - - Add a new node and its predecessors to the graph. Both the *node* and all - elements in *predecessors* must be hashable. - - If called multiple times with the same node argument, the set of - dependencies will be the union of all dependencies passed in. - - It is possible to add a node with no dependencies (*predecessors* is not - provided) or to provide a dependency twice. If a node that has not been - provided before is included among *predecessors* it will be automatically - added to the graph with no predecessors of its own. - - Raises :exc:`ValueError` if called after :meth:`~TopologicalSorter.prepare`. - - .. method:: prepare() - - Mark the graph as finished and check for cycles in the graph. If any cycle - is detected, :exc:`CycleError` will be raised, but - :meth:`~TopologicalSorter.get_ready` can still be used to obtain as many - nodes as possible until cycles block more progress. After a call to this - function, the graph cannot be modified, and therefore no more nodes can be - added using :meth:`~TopologicalSorter.add`. - - .. method:: is_active() - - Returns ``True`` if more progress can be made and ``False`` otherwise. - Progress can be made if cycles do not block the resolution and either - there are still nodes ready that haven't yet been returned by - :meth:`TopologicalSorter.get_ready` or the number of nodes marked - :meth:`TopologicalSorter.done` is less than the number that have been - returned by :meth:`TopologicalSorter.get_ready`. - - The :meth:`~TopologicalSorter.__bool__` method of this class defers to - this function, so instead of:: - - if ts.is_active(): - ... - - if possible to simply do:: - - if ts: - ... - - Raises :exc:`ValueError` if called without calling - :meth:`~TopologicalSorter.prepare` previously. - - .. method:: done(*nodes) - - Marks a set of nodes returned by :meth:`TopologicalSorter.get_ready` as - processed, unblocking any successor of each node in *nodes* for being - returned in the future by a call to :meth:`TopologicalSorter.get_ready`. - - Raises :exc:`ValueError` if any node in *nodes* has already been marked as - processed by a previous call to this method or if a node was not added to - the graph by using :meth:`TopologicalSorter.add`, if called without - calling :meth:`~TopologicalSorter.prepare` or if node has not yet been - returned by :meth:`~TopologicalSorter.get_ready`. - - .. method:: get_ready() - - Returns a ``tuple`` with all the nodes that are ready. Initially it - returns all nodes with no predecessors, and once those are marked as - processed by calling :meth:`TopologicalSorter.done`, further calls will - return all new nodes that have all their predecessors already processed. - Once no more progress can be made, empty tuples are returned. - - Raises :exc:`ValueError` if called without calling - :meth:`~TopologicalSorter.prepare` previously. - - .. method:: static_order() - - Returns an iterable of nodes in a topological order. Using this method - does not require to call :meth:`TopologicalSorter.prepare` or - :meth:`TopologicalSorter.done`. This method is equivalent to:: - - def static_order(self): - self.prepare() - while self.is_active(): - node_group = self.get_ready() - yield from node_group - self.done(*node_group) - - The particular order that is returned may depend on the specific order in - which the items were inserted in the graph. For example: - - .. doctest:: - - >>> ts = TopologicalSorter() - >>> ts.add(3, 2, 1) - >>> ts.add(1, 0) - >>> print([*ts.static_order()]) - [2, 0, 1, 3] - - >>> ts2 = TopologicalSorter() - >>> ts2.add(1, 0) - >>> ts2.add(3, 2, 1) - >>> print([*ts2.static_order()]) - [0, 2, 1, 3] - - This is due to the fact that "0" and "2" are in the same level in the - graph (they would have been returned in the same call to - :meth:`~TopologicalSorter.get_ready`) and the order between them is - determined by the order of insertion. - - - If any cycle is detected, :exc:`CycleError` will be raised. - - .. versionadded:: 3.9 - - .. function:: update_wrapper(wrapper, wrapped, assigned=WRAPPER_ASSIGNMENTS, updated=WRAPPER_UPDATES) Update a *wrapper* function to look like the *wrapped* function. The optional @@ -829,20 +651,4 @@ callable, weak referencable, and can have attributes. There are some important differences. For instance, the :attr:`~definition.__name__` and :attr:`__doc__` attributes are not created automatically. Also, :class:`partial` objects defined in classes behave like static methods and do not transform into bound methods -during instance attribute look-up. - - -Exceptions ----------- -The :mod:`functools` module defines the following exception classes: - -.. exception:: CycleError - - Subclass of :exc:`ValueError` raised by :meth:`TopologicalSorter.prepare` if cycles exist - in the working graph. If multiple cycles exist, only one undefined choice among them will - be reported and included in the exception. - - The detected cycle can be accessed via the second element in the :attr:`~CycleError.args` - attribute of the exception instance and consists in a list of nodes, such that each node is, - in the graph, an immediate predecessor of the next node in the list. In the reported list, - the first and the last node will be the same, to make it clear that it is cyclic. +during instance attribute look-up. \ No newline at end of file diff --git a/Doc/library/graphlib.rst b/Doc/library/graphlib.rst new file mode 100644 index 00000000000..820615e7230 --- /dev/null +++ b/Doc/library/graphlib.rst @@ -0,0 +1,209 @@ +:mod:`graphlib` --- Functionality to operate with graph-like structures +========================================================================= + +.. module:: graphlib + :synopsis: Functionality to operate with graph-like structures + + +**Source code:** :source:`Lib/graphlib.py` + +.. testsetup:: default + + import graphlib + from graphlib import * + +-------------- + + +.. class:: TopologicalSorter(graph=None) + + Provides functionality to topologically sort a graph of hashable nodes. + + A topological order is a linear ordering of the vertices in a graph such that + for every directed edge u -> v from vertex u to vertex v, vertex u comes + before vertex v in the ordering. For instance, the vertices of the graph may + represent tasks to be performed, and the edges may represent constraints that + one task must be performed before another; in this example, a topological + ordering is just a valid sequence for the tasks. A complete topological + ordering is possible if and only if the graph has no directed cycles, that + is, if it is a directed acyclic graph. + + If the optional *graph* argument is provided it must be a dictionary + representing a directed acyclic graph where the keys are nodes and the values + are iterables of all predecessors of that node in the graph (the nodes that + have edges that point to the value in the key). Additional nodes can be added + to the graph using the :meth:`~TopologicalSorter.add` method. + + In the general case, the steps required to perform the sorting of a given + graph are as follows: + + * Create an instance of the :class:`TopologicalSorter` with an optional + initial graph. + * Add additional nodes to the graph. + * Call :meth:`~TopologicalSorter.prepare` on the graph. + * While :meth:`~TopologicalSorter.is_active` is ``True``, iterate over + the nodes returned by :meth:`~TopologicalSorter.get_ready` and + process them. Call :meth:`~TopologicalSorter.done` on each node as it + finishes processing. + + In case just an immediate sorting of the nodes in the graph is required and + no parallelism is involved, the convenience method + :meth:`TopologicalSorter.static_order` can be used directly: + + .. doctest:: + + >>> graph = {"D": {"B", "C"}, "C": {"A"}, "B": {"A"}} + >>> ts = TopologicalSorter(graph) + >>> tuple(ts.static_order()) + ('A', 'C', 'B', 'D') + + The class is designed to easily support parallel processing of the nodes as + they become ready. For instance:: + + topological_sorter = TopologicalSorter() + + # Add nodes to 'topological_sorter'... + + topological_sorter.prepare() + while topological_sorter.is_active(): + for node in topological_sorter.get_ready(): + # Worker threads or processes take nodes to work on off the + # 'task_queue' queue. + task_queue.put(node) + + # When the work for a node is done, workers put the node in + # 'finalized_tasks_queue' so we can get more nodes to work on. + # The definition of 'is_active()' guarantees that, at this point, at + # least one node has been placed on 'task_queue' that hasn't yet + # been passed to 'done()', so this blocking 'get()' must (eventually) + # succeed. After calling 'done()', we loop back to call 'get_ready()' + # again, so put newly freed nodes on 'task_queue' as soon as + # logically possible. + node = finalized_tasks_queue.get() + topological_sorter.done(node) + + .. method:: add(node, *predecessors) + + Add a new node and its predecessors to the graph. Both the *node* and all + elements in *predecessors* must be hashable. + + If called multiple times with the same node argument, the set of + dependencies will be the union of all dependencies passed in. + + It is possible to add a node with no dependencies (*predecessors* is not + provided) or to provide a dependency twice. If a node that has not been + provided before is included among *predecessors* it will be automatically + added to the graph with no predecessors of its own. + + Raises :exc:`ValueError` if called after :meth:`~TopologicalSorter.prepare`. + + .. method:: prepare() + + Mark the graph as finished and check for cycles in the graph. If any cycle + is detected, :exc:`CycleError` will be raised, but + :meth:`~TopologicalSorter.get_ready` can still be used to obtain as many + nodes as possible until cycles block more progress. After a call to this + function, the graph cannot be modified, and therefore no more nodes can be + added using :meth:`~TopologicalSorter.add`. + + .. method:: is_active() + + Returns ``True`` if more progress can be made and ``False`` otherwise. + Progress can be made if cycles do not block the resolution and either + there are still nodes ready that haven't yet been returned by + :meth:`TopologicalSorter.get_ready` or the number of nodes marked + :meth:`TopologicalSorter.done` is less than the number that have been + returned by :meth:`TopologicalSorter.get_ready`. + + The :meth:`~TopologicalSorter.__bool__` method of this class defers to + this function, so instead of:: + + if ts.is_active(): + ... + + if possible to simply do:: + + if ts: + ... + + Raises :exc:`ValueError` if called without calling + :meth:`~TopologicalSorter.prepare` previously. + + .. method:: done(*nodes) + + Marks a set of nodes returned by :meth:`TopologicalSorter.get_ready` as + processed, unblocking any successor of each node in *nodes* for being + returned in the future by a call to :meth:`TopologicalSorter.get_ready`. + + Raises :exc:`ValueError` if any node in *nodes* has already been marked as + processed by a previous call to this method or if a node was not added to + the graph by using :meth:`TopologicalSorter.add`, if called without + calling :meth:`~TopologicalSorter.prepare` or if node has not yet been + returned by :meth:`~TopologicalSorter.get_ready`. + + .. method:: get_ready() + + Returns a ``tuple`` with all the nodes that are ready. Initially it + returns all nodes with no predecessors, and once those are marked as + processed by calling :meth:`TopologicalSorter.done`, further calls will + return all new nodes that have all their predecessors already processed. + Once no more progress can be made, empty tuples are returned. + + Raises :exc:`ValueError` if called without calling + :meth:`~TopologicalSorter.prepare` previously. + + .. method:: static_order() + + Returns an iterable of nodes in a topological order. Using this method + does not require to call :meth:`TopologicalSorter.prepare` or + :meth:`TopologicalSorter.done`. This method is equivalent to:: + + def static_order(self): + self.prepare() + while self.is_active(): + node_group = self.get_ready() + yield from node_group + self.done(*node_group) + + The particular order that is returned may depend on the specific order in + which the items were inserted in the graph. For example: + + .. doctest:: + + >>> ts = TopologicalSorter() + >>> ts.add(3, 2, 1) + >>> ts.add(1, 0) + >>> print([*ts.static_order()]) + [2, 0, 1, 3] + + >>> ts2 = TopologicalSorter() + >>> ts2.add(1, 0) + >>> ts2.add(3, 2, 1) + >>> print([*ts2.static_order()]) + [0, 2, 1, 3] + + This is due to the fact that "0" and "2" are in the same level in the + graph (they would have been returned in the same call to + :meth:`~TopologicalSorter.get_ready`) and the order between them is + determined by the order of insertion. + + + If any cycle is detected, :exc:`CycleError` will be raised. + + .. versionadded:: 3.9 + + +Exceptions +---------- +The :mod:`graphlib` module defines the following exception classes: + +.. exception:: CycleError + + Subclass of :exc:`ValueError` raised by :meth:`TopologicalSorter.prepare` if cycles exist + in the working graph. If multiple cycles exist, only one undefined choice among them will + be reported and included in the exception. + + The detected cycle can be accessed via the second element in the :attr:`~CycleError.args` + attribute of the exception instance and consists in a list of nodes, such that each node is, + in the graph, an immediate predecessor of the next node in the list. In the reported list, + the first and the last node will be the same, to make it clear that it is cyclic. \ No newline at end of file diff --git a/Doc/whatsnew/3.9.rst b/Doc/whatsnew/3.9.rst index 3d5cec6026a..a468130af10 100644 --- a/Doc/whatsnew/3.9.rst +++ b/Doc/whatsnew/3.9.rst @@ -245,6 +245,14 @@ PyPI and maintained by the CPython core team. PEP written and implemented by Paul Ganssle +graphlib +--------- + +Add the :mod:`graphlib` that contains the :class:`graphlib.TopologicalSorter` class +to offer functionality to perform topological sorting of graphs. (Contributed by Pablo +Galindo, Tim Peters and Larry Hastings in :issue:`17005`.) + + Improved Modules ================ @@ -352,13 +360,6 @@ ftplib if the given timeout for their constructor is zero to prevent the creation of a non-blocking socket. (Contributed by Dong-hee Na in :issue:`39259`.) -functools ---------- - -Add the :class:`functools.TopologicalSorter` class to offer functionality to perform -topological sorting of graphs. (Contributed by Pablo Galindo, Tim Peters and Larry -Hastings in :issue:`17005`.) - gc -- diff --git a/Lib/functools.py b/Lib/functools.py index 87c7d874389..5cab497d264 100644 --- a/Lib/functools.py +++ b/Lib/functools.py @@ -11,7 +11,6 @@ __all__ = ['update_wrapper', 'wraps', 'WRAPPER_ASSIGNMENTS', 'WRAPPER_UPDATES', 'total_ordering', 'cache', 'cmp_to_key', 'lru_cache', 'reduce', - 'TopologicalSorter', 'CycleError', 'partial', 'partialmethod', 'singledispatch', 'singledispatchmethod', 'cached_property'] @@ -199,250 +198,6 @@ def total_ordering(cls): setattr(cls, opname, opfunc) return cls -################################################################################ -### topological sort -################################################################################ - -_NODE_OUT = -1 -_NODE_DONE = -2 - - -class _NodeInfo: - __slots__ = 'node', 'npredecessors', 'successors' - - def __init__(self, node): - # The node this class is augmenting. - self.node = node - - # Number of predecessors, generally >= 0. When this value falls to 0, - # and is returned by get_ready(), this is set to _NODE_OUT and when the - # node is marked done by a call to done(), set to _NODE_DONE. - self.npredecessors = 0 - - # List of successor nodes. The list can contain duplicated elements as - # long as they're all reflected in the successor's npredecessors attribute). - self.successors = [] - - -class CycleError(ValueError): - """Subclass of ValueError raised by TopologicalSorterif cycles exist in the graph - - If multiple cycles exist, only one undefined choice among them will be reported - and included in the exception. The detected cycle can be accessed via the second - element in the *args* attribute of the exception instance and consists in a list - of nodes, such that each node is, in the graph, an immediate predecessor of the - next node in the list. In the reported list, the first and the last node will be - the same, to make it clear that it is cyclic. - """ - pass - - -class TopologicalSorter: - """Provides functionality to topologically sort a graph of hashable nodes""" - - def __init__(self, graph=None): - self._node2info = {} - self._ready_nodes = None - self._npassedout = 0 - self._nfinished = 0 - - if graph is not None: - for node, predecessors in graph.items(): - self.add(node, *predecessors) - - def _get_nodeinfo(self, node): - if (result := self._node2info.get(node)) is None: - self._node2info[node] = result = _NodeInfo(node) - return result - - def add(self, node, *predecessors): - """Add a new node and its predecessors to the graph. - - Both the *node* and all elements in *predecessors* must be hashable. - - If called multiple times with the same node argument, the set of dependencies - will be the union of all dependencies passed in. - - It is possible to add a node with no dependencies (*predecessors* is not provided) - as well as provide a dependency twice. If a node that has not been provided before - is included among *predecessors* it will be automatically added to the graph with - no predecessors of its own. - - Raises ValueError if called after "prepare". - """ - if self._ready_nodes is not None: - raise ValueError("Nodes cannot be added after a call to prepare()") - - # Create the node -> predecessor edges - nodeinfo = self._get_nodeinfo(node) - nodeinfo.npredecessors += len(predecessors) - - # Create the predecessor -> node edges - for pred in predecessors: - pred_info = self._get_nodeinfo(pred) - pred_info.successors.append(node) - - def prepare(self): - """Mark the graph as finished and check for cycles in the graph. - - If any cycle is detected, "CycleError" will be raised, but "get_ready" can - still be used to obtain as many nodes as possible until cycles block more - progress. After a call to this function, the graph cannot be modified and - therefore no more nodes can be added using "add". - """ - if self._ready_nodes is not None: - raise ValueError("cannot prepare() more than once") - - self._ready_nodes = [i.node for i in self._node2info.values() - if i.npredecessors == 0] - # ready_nodes is set before we look for cycles on purpose: - # if the user wants to catch the CycleError, that's fine, - # they can continue using the instance to grab as many - # nodes as possible before cycles block more progress - cycle = self._find_cycle() - if cycle: - raise CycleError(f"nodes are in a cycle", cycle) - - def get_ready(self): - """Return a tuple of all the nodes that are ready. - - Initially it returns all nodes with no predecessors; once those are marked - as processed by calling "done", further calls will return all new nodes that - have all their predecessors already processed. Once no more progress can be made, - empty tuples are returned. - - Raises ValueError if called without calling "prepare" previously. - """ - if self._ready_nodes is None: - raise ValueError("prepare() must be called first") - - # Get the nodes that are ready and mark them - result = tuple(self._ready_nodes) - n2i = self._node2info - for node in result: - n2i[node].npredecessors = _NODE_OUT - - # Clean the list of nodes that are ready and update - # the counter of nodes that we have returned. - self._ready_nodes.clear() - self._npassedout += len(result) - - return result - - def is_active(self): - """Return True if more progress can be made and ``False`` otherwise. - - Progress can be made if cycles do not block the resolution and either there - are still nodes ready that haven't yet been returned by "get_ready" or the - number of nodes marked "done" is less than the number that have been returned - by "get_ready". - - Raises ValueError if called without calling "prepare" previously. - """ - if self._ready_nodes is None: - raise ValueError("prepare() must be called first") - return self._nfinished < self._npassedout or bool(self._ready_nodes) - - def __bool__(self): - return self.is_active() - - def done(self, *nodes): - """Marks a set of nodes returned by "get_ready" as processed. - - This method unblocks any successor of each node in *nodes* for being returned - in the future by a a call to "get_ready" - - Raises :exec:`ValueError` if any node in *nodes* has already been marked as - processed by a previous call to this method, if a node was not added to the - graph by using "add" or if called without calling "prepare" previously or if - node has not yet been returned by "get_ready". - """ - - if self._ready_nodes is None: - raise ValueError("prepare() must be called first") - - n2i = self._node2info - - for node in nodes: - - # Check if we know about this node (it was added previously using add() - if (nodeinfo := n2i.get(node)) is None: - raise ValueError(f"node {node!r} was not added using add()") - - # If the node has not being returned (marked as ready) previously, inform the user. - stat = nodeinfo.npredecessors - if stat != _NODE_OUT: - if stat >= 0: - raise ValueError(f"node {node!r} was not passed out (still not ready)") - elif stat == _NODE_DONE: - raise ValueError(f"node {node!r} was already marked done") - else: - assert False, f"node {node!r}: unknown status {stat}" - - # Mark the node as processed - nodeinfo.npredecessors = _NODE_DONE - - # Go to all the successors and reduce the number of predecessors, collecting all the ones - # that are ready to be returned in the next get_ready() call. - for successor in nodeinfo.successors: - successor_info = n2i[successor] - successor_info.npredecessors -= 1 - if successor_info.npredecessors == 0: - self._ready_nodes.append(successor) - self._nfinished += 1 - - def _find_cycle(self): - n2i = self._node2info - stack = [] - itstack = [] - seen = set() - node2stacki = {} - - for node in n2i: - if node in seen: - continue - - while True: - if node in seen: - # If we have seen already the node and is in the - # current stack we have found a cycle. - if node in node2stacki: - return stack[node2stacki[node]:] + [node] - # else go on to get next successor - else: - seen.add(node) - itstack.append(iter(n2i[node].successors).__next__) - node2stacki[node] = len(stack) - stack.append(node) - - # Backtrack to the topmost stack entry with - # at least another successor. - while stack: - try: - node = itstack[-1]() - break - except StopIteration: - del node2stacki[stack.pop()] - itstack.pop() - else: - break - return None - - def static_order(self): - """Returns an iterable of nodes in a topological order. - - The particular order that is returned may depend on the specific - order in which the items were inserted in the graph. - - Using this method does not require to call "prepare" or "done". If any - cycle is detected, :exc:`CycleError` will be raised. - """ - self.prepare() - while self.is_active(): - node_group = self.get_ready() - yield from node_group - self.done(*node_group) - ################################################################################ ### cmp_to_key() function converter diff --git a/Lib/graphlib.py b/Lib/graphlib.py new file mode 100644 index 00000000000..948f62f1dc3 --- /dev/null +++ b/Lib/graphlib.py @@ -0,0 +1,245 @@ +__all__ = ["TopologicalSorter", "CycleError"] + +_NODE_OUT = -1 +_NODE_DONE = -2 + + +class _NodeInfo: + __slots__ = "node", "npredecessors", "successors" + + def __init__(self, node): + # The node this class is augmenting. + self.node = node + + # Number of predecessors, generally >= 0. When this value falls to 0, + # and is returned by get_ready(), this is set to _NODE_OUT and when the + # node is marked done by a call to done(), set to _NODE_DONE. + self.npredecessors = 0 + + # List of successor nodes. The list can contain duplicated elements as + # long as they're all reflected in the successor's npredecessors attribute). + self.successors = [] + + +class CycleError(ValueError): + """Subclass of ValueError raised by TopologicalSorterif cycles exist in the graph + + If multiple cycles exist, only one undefined choice among them will be reported + and included in the exception. The detected cycle can be accessed via the second + element in the *args* attribute of the exception instance and consists in a list + of nodes, such that each node is, in the graph, an immediate predecessor of the + next node in the list. In the reported list, the first and the last node will be + the same, to make it clear that it is cyclic. + """ + + pass + + +class TopologicalSorter: + """Provides functionality to topologically sort a graph of hashable nodes""" + + def __init__(self, graph=None): + self._node2info = {} + self._ready_nodes = None + self._npassedout = 0 + self._nfinished = 0 + + if graph is not None: + for node, predecessors in graph.items(): + self.add(node, *predecessors) + + def _get_nodeinfo(self, node): + if (result := self._node2info.get(node)) is None: + self._node2info[node] = result = _NodeInfo(node) + return result + + def add(self, node, *predecessors): + """Add a new node and its predecessors to the graph. + + Both the *node* and all elements in *predecessors* must be hashable. + + If called multiple times with the same node argument, the set of dependencies + will be the union of all dependencies passed in. + + It is possible to add a node with no dependencies (*predecessors* is not provided) + as well as provide a dependency twice. If a node that has not been provided before + is included among *predecessors* it will be automatically added to the graph with + no predecessors of its own. + + Raises ValueError if called after "prepare". + """ + if self._ready_nodes is not None: + raise ValueError("Nodes cannot be added after a call to prepare()") + + # Create the node -> predecessor edges + nodeinfo = self._get_nodeinfo(node) + nodeinfo.npredecessors += len(predecessors) + + # Create the predecessor -> node edges + for pred in predecessors: + pred_info = self._get_nodeinfo(pred) + pred_info.successors.append(node) + + def prepare(self): + """Mark the graph as finished and check for cycles in the graph. + + If any cycle is detected, "CycleError" will be raised, but "get_ready" can + still be used to obtain as many nodes as possible until cycles block more + progress. After a call to this function, the graph cannot be modified and + therefore no more nodes can be added using "add". + """ + if self._ready_nodes is not None: + raise ValueError("cannot prepare() more than once") + + self._ready_nodes = [ + i.node for i in self._node2info.values() if i.npredecessors == 0 + ] + # ready_nodes is set before we look for cycles on purpose: + # if the user wants to catch the CycleError, that's fine, + # they can continue using the instance to grab as many + # nodes as possible before cycles block more progress + cycle = self._find_cycle() + if cycle: + raise CycleError(f"nodes are in a cycle", cycle) + + def get_ready(self): + """Return a tuple of all the nodes that are ready. + + Initially it returns all nodes with no predecessors; once those are marked + as processed by calling "done", further calls will return all new nodes that + have all their predecessors already processed. Once no more progress can be made, + empty tuples are returned. + + Raises ValueError if called without calling "prepare" previously. + """ + if self._ready_nodes is None: + raise ValueError("prepare() must be called first") + + # Get the nodes that are ready and mark them + result = tuple(self._ready_nodes) + n2i = self._node2info + for node in result: + n2i[node].npredecessors = _NODE_OUT + + # Clean the list of nodes that are ready and update + # the counter of nodes that we have returned. + self._ready_nodes.clear() + self._npassedout += len(result) + + return result + + def is_active(self): + """Return True if more progress can be made and ``False`` otherwise. + + Progress can be made if cycles do not block the resolution and either there + are still nodes ready that haven't yet been returned by "get_ready" or the + number of nodes marked "done" is less than the number that have been returned + by "get_ready". + + Raises ValueError if called without calling "prepare" previously. + """ + if self._ready_nodes is None: + raise ValueError("prepare() must be called first") + return self._nfinished < self._npassedout or bool(self._ready_nodes) + + def __bool__(self): + return self.is_active() + + def done(self, *nodes): + """Marks a set of nodes returned by "get_ready" as processed. + + This method unblocks any successor of each node in *nodes* for being returned + in the future by a a call to "get_ready" + + Raises :exec:`ValueError` if any node in *nodes* has already been marked as + processed by a previous call to this method, if a node was not added to the + graph by using "add" or if called without calling "prepare" previously or if + node has not yet been returned by "get_ready". + """ + + if self._ready_nodes is None: + raise ValueError("prepare() must be called first") + + n2i = self._node2info + + for node in nodes: + + # Check if we know about this node (it was added previously using add() + if (nodeinfo := n2i.get(node)) is None: + raise ValueError(f"node {node!r} was not added using add()") + + # If the node has not being returned (marked as ready) previously, inform the user. + stat = nodeinfo.npredecessors + if stat != _NODE_OUT: + if stat >= 0: + raise ValueError( + f"node {node!r} was not passed out (still not ready)" + ) + elif stat == _NODE_DONE: + raise ValueError(f"node {node!r} was already marked done") + else: + assert False, f"node {node!r}: unknown status {stat}" + + # Mark the node as processed + nodeinfo.npredecessors = _NODE_DONE + + # Go to all the successors and reduce the number of predecessors, collecting all the ones + # that are ready to be returned in the next get_ready() call. + for successor in nodeinfo.successors: + successor_info = n2i[successor] + successor_info.npredecessors -= 1 + if successor_info.npredecessors == 0: + self._ready_nodes.append(successor) + self._nfinished += 1 + + def _find_cycle(self): + n2i = self._node2info + stack = [] + itstack = [] + seen = set() + node2stacki = {} + + for node in n2i: + if node in seen: + continue + + while True: + if node in seen: + # If we have seen already the node and is in the + # current stack we have found a cycle. + if node in node2stacki: + return stack[node2stacki[node] :] + [node] + # else go on to get next successor + else: + seen.add(node) + itstack.append(iter(n2i[node].successors).__next__) + node2stacki[node] = len(stack) + stack.append(node) + + # Backtrack to the topmost stack entry with + # at least another successor. + while stack: + try: + node = itstack[-1]() + break + except StopIteration: + del node2stacki[stack.pop()] + itstack.pop() + else: + break + return None + + def static_order(self): + """Returns an iterable of nodes in a topological order. + + The particular order that is returned may depend on the specific + order in which the items were inserted in the graph. + + Using this method does not require to call "prepare" or "done". If any + cycle is detected, :exc:`CycleError` will be raised. + """ + self.prepare() + while self.is_active(): + node_group = self.get_ready() + yield from node_group + self.done(*node_group) diff --git a/Lib/test/test_functools.py b/Lib/test/test_functools.py index 72b7765853b..e726188982b 100644 --- a/Lib/test/test_functools.py +++ b/Lib/test/test_functools.py @@ -3,7 +3,7 @@ import builtins import collections import collections.abc import copy -from itertools import permutations, chain +from itertools import permutations import pickle from random import choice import sys @@ -1164,275 +1164,6 @@ class Orderable_LT: return self.value == other.value -class TestTopologicalSort(unittest.TestCase): - - def _test_graph(self, graph, expected): - - def static_order_with_groups(ts): - ts.prepare() - while ts.is_active(): - nodes = ts.get_ready() - for node in nodes: - ts.done(node) - yield nodes - - ts = functools.TopologicalSorter(graph) - self.assertEqual(list(static_order_with_groups(ts)), list(expected)) - - ts = functools.TopologicalSorter(graph) - self.assertEqual(list(ts.static_order()), list(chain(*expected))) - - def _assert_cycle(self, graph, cycle): - ts = functools.TopologicalSorter() - for node, dependson in graph.items(): - ts.add(node, *dependson) - try: - ts.prepare() - except functools.CycleError as e: - msg, seq = e.args - self.assertIn(' '.join(map(str, cycle)), - ' '.join(map(str, seq * 2))) - else: - raise - - def test_simple_cases(self): - self._test_graph( - {2: {11}, - 9: {11, 8}, - 10: {11, 3}, - 11: {7, 5}, - 8: {7, 3}}, - [(3, 5, 7), (11, 8), (2, 10, 9)] - ) - - self._test_graph({1: {}}, [(1,)]) - - self._test_graph({x: {x+1} for x in range(10)}, - [(x,) for x in range(10, -1, -1)]) - - self._test_graph({2: {3}, 3: {4}, 4: {5}, 5: {1}, - 11: {12}, 12: {13}, 13: {14}, 14: {15}}, - [(1, 15), (5, 14), (4, 13), (3, 12), (2, 11)]) - - self._test_graph({ - 0: [1, 2], - 1: [3], - 2: [5, 6], - 3: [4], - 4: [9], - 5: [3], - 6: [7], - 7: [8], - 8: [4], - 9: [] - }, - [(9,), (4,), (3, 8), (1, 5, 7), (6,), (2,), (0,)] - ) - - self._test_graph({ - 0: [1, 2], - 1: [], - 2: [3], - 3: [] - }, - [(1, 3), (2,), (0,)] - ) - - self._test_graph({ - 0: [1, 2], - 1: [], - 2: [3], - 3: [], - 4: [5], - 5: [6], - 6: [] - }, - [(1, 3, 6), (2, 5), (0, 4)] - ) - - def test_no_dependencies(self): - self._test_graph( - {1: {2}, - 3: {4}, - 5: {6}}, - [(2, 4, 6), (1, 3, 5)] - ) - - self._test_graph( - {1: set(), - 3: set(), - 5: set()}, - [(1, 3, 5)] - ) - - def test_the_node_multiple_times(self): - # Test same node multiple times in dependencies - self._test_graph({1: {2}, 3: {4}, 0: [2, 4, 4, 4, 4, 4]}, - [(2, 4), (1, 3, 0)]) - - # Test adding the same dependency multiple times - ts = functools.TopologicalSorter() - ts.add(1, 2) - ts.add(1, 2) - ts.add(1, 2) - self.assertEqual([*ts.static_order()], [2, 1]) - - def test_graph_with_iterables(self): - dependson = (2*x + 1 for x in range(5)) - ts = functools.TopologicalSorter({0: dependson}) - self.assertEqual(list(ts.static_order()), [1, 3, 5, 7, 9, 0]) - - def test_add_dependencies_for_same_node_incrementally(self): - # Test same node multiple times - ts = functools.TopologicalSorter() - ts.add(1, 2) - ts.add(1, 3) - ts.add(1, 4) - ts.add(1, 5) - - ts2 = functools.TopologicalSorter({1: {2, 3, 4, 5}}) - self.assertEqual([*ts.static_order()], [*ts2.static_order()]) - - def test_empty(self): - self._test_graph({}, []) - - def test_cycle(self): - # Self cycle - self._assert_cycle({1: {1}}, [1, 1]) - # Simple cycle - self._assert_cycle({1: {2}, 2: {1}}, [1, 2, 1]) - # Indirect cycle - self._assert_cycle({1: {2}, 2: {3}, 3: {1}}, [1, 3, 2, 1]) - # not all elements involved in a cycle - self._assert_cycle({1: {2}, 2: {3}, 3: {1}, 5: {4}, 4: {6}}, [1, 3, 2, 1]) - # Multiple cycles - self._assert_cycle({1: {2}, 2: {1}, 3: {4}, 4: {5}, 6: {7}, 7: {6}}, - [1, 2, 1]) - # Cycle in the middle of the graph - self._assert_cycle({1: {2}, 2: {3}, 3: {2, 4}, 4: {5}}, [3, 2]) - - def test_calls_before_prepare(self): - ts = functools.TopologicalSorter() - - with self.assertRaisesRegex(ValueError, r"prepare\(\) must be called first"): - ts.get_ready() - with self.assertRaisesRegex(ValueError, r"prepare\(\) must be called first"): - ts.done(3) - with self.assertRaisesRegex(ValueError, r"prepare\(\) must be called first"): - ts.is_active() - - def test_prepare_multiple_times(self): - ts = functools.TopologicalSorter() - ts.prepare() - with self.assertRaisesRegex(ValueError, r"cannot prepare\(\) more than once"): - ts.prepare() - - def test_invalid_nodes_in_done(self): - ts = functools.TopologicalSorter() - ts.add(1, 2, 3, 4) - ts.add(2, 3, 4) - ts.prepare() - ts.get_ready() - - with self.assertRaisesRegex(ValueError, "node 2 was not passed out"): - ts.done(2) - with self.assertRaisesRegex(ValueError, r"node 24 was not added using add\(\)"): - ts.done(24) - - def test_done(self): - ts = functools.TopologicalSorter() - ts.add(1, 2, 3, 4) - ts.add(2, 3) - ts.prepare() - - self.assertEqual(ts.get_ready(), (3, 4)) - # If we don't mark anything as done, get_ready() returns nothing - self.assertEqual(ts.get_ready(), ()) - ts.done(3) - # Now 2 becomes available as 3 is done - self.assertEqual(ts.get_ready(), (2,)) - self.assertEqual(ts.get_ready(), ()) - ts.done(4) - ts.done(2) - # Only 1 is missing - self.assertEqual(ts.get_ready(), (1,)) - self.assertEqual(ts.get_ready(), ()) - ts.done(1) - self.assertEqual(ts.get_ready(), ()) - self.assertFalse(ts.is_active()) - - def test_is_active(self): - ts = functools.TopologicalSorter() - ts.add(1, 2) - ts.prepare() - - self.assertTrue(ts.is_active()) - self.assertEqual(ts.get_ready(), (2,)) - self.assertTrue(ts.is_active()) - ts.done(2) - self.assertTrue(ts.is_active()) - self.assertEqual(ts.get_ready(), (1,)) - self.assertTrue(ts.is_active()) - ts.done(1) - self.assertFalse(ts.is_active()) - - def test_not_hashable_nodes(self): - ts = functools.TopologicalSorter() - self.assertRaises(TypeError, ts.add, dict(), 1) - self.assertRaises(TypeError, ts.add, 1, dict()) - self.assertRaises(TypeError, ts.add, dict(), dict()) - - def test_order_of_insertion_does_not_matter_between_groups(self): - def get_groups(ts): - ts.prepare() - while ts.is_active(): - nodes = ts.get_ready() - ts.done(*nodes) - yield set(nodes) - - ts = functools.TopologicalSorter() - ts.add(3, 2, 1) - ts.add(1, 0) - ts.add(4, 5) - ts.add(6, 7) - ts.add(4, 7) - - ts2 = functools.TopologicalSorter() - ts2.add(1, 0) - ts2.add(3, 2, 1) - ts2.add(4, 7) - ts2.add(6, 7) - ts2.add(4, 5) - - self.assertEqual(list(get_groups(ts)), list(get_groups(ts2))) - - def test_static_order_does_not_change_with_the_hash_seed(self): - def check_order_with_hash_seed(seed): - code = """if 1: - import functools - ts = functools.TopologicalSorter() - ts.add('blech', 'bluch', 'hola') - ts.add('abcd', 'blech', 'bluch', 'a', 'b') - ts.add('a', 'a string', 'something', 'b') - ts.add('bluch', 'hola', 'abcde', 'a', 'b') - print(list(ts.static_order())) - """ - env = os.environ.copy() - # signal to assert_python not to do a copy - # of os.environ on its own - env['__cleanenv'] = True - env['PYTHONHASHSEED'] = str(seed) - out = assert_python_ok('-c', code, **env) - return out - - run1 = check_order_with_hash_seed(1234) - run2 = check_order_with_hash_seed(31415) - - self.assertNotEqual(run1, "") - self.assertNotEqual(run2, "") - self.assertEqual(run1, run2) - - class TestCache: # This tests that the pass-through is working as designed. # The underlying functionality is tested in TestLRU. diff --git a/Lib/test/test_graphlib.py b/Lib/test/test_graphlib.py new file mode 100644 index 00000000000..00432537f22 --- /dev/null +++ b/Lib/test/test_graphlib.py @@ -0,0 +1,244 @@ +from itertools import chain +import graphlib +import os +import unittest + +from test.support.script_helper import assert_python_ok + +class TestTopologicalSort(unittest.TestCase): + def _test_graph(self, graph, expected): + def static_order_with_groups(ts): + ts.prepare() + while ts.is_active(): + nodes = ts.get_ready() + for node in nodes: + ts.done(node) + yield nodes + + ts = graphlib.TopologicalSorter(graph) + self.assertEqual(list(static_order_with_groups(ts)), list(expected)) + + ts = graphlib.TopologicalSorter(graph) + self.assertEqual(list(ts.static_order()), list(chain(*expected))) + + def _assert_cycle(self, graph, cycle): + ts = graphlib.TopologicalSorter() + for node, dependson in graph.items(): + ts.add(node, *dependson) + try: + ts.prepare() + except graphlib.CycleError as e: + msg, seq = e.args + self.assertIn(" ".join(map(str, cycle)), " ".join(map(str, seq * 2))) + else: + raise + + def test_simple_cases(self): + self._test_graph( + {2: {11}, 9: {11, 8}, 10: {11, 3}, 11: {7, 5}, 8: {7, 3}}, + [(3, 5, 7), (11, 8), (2, 10, 9)], + ) + + self._test_graph({1: {}}, [(1,)]) + + self._test_graph( + {x: {x + 1} for x in range(10)}, [(x,) for x in range(10, -1, -1)] + ) + + self._test_graph( + {2: {3}, 3: {4}, 4: {5}, 5: {1}, 11: {12}, 12: {13}, 13: {14}, 14: {15}}, + [(1, 15), (5, 14), (4, 13), (3, 12), (2, 11)], + ) + + self._test_graph( + { + 0: [1, 2], + 1: [3], + 2: [5, 6], + 3: [4], + 4: [9], + 5: [3], + 6: [7], + 7: [8], + 8: [4], + 9: [], + }, + [(9,), (4,), (3, 8), (1, 5, 7), (6,), (2,), (0,)], + ) + + self._test_graph({0: [1, 2], 1: [], 2: [3], 3: []}, [(1, 3), (2,), (0,)]) + + self._test_graph( + {0: [1, 2], 1: [], 2: [3], 3: [], 4: [5], 5: [6], 6: []}, + [(1, 3, 6), (2, 5), (0, 4)], + ) + + def test_no_dependencies(self): + self._test_graph({1: {2}, 3: {4}, 5: {6}}, [(2, 4, 6), (1, 3, 5)]) + + self._test_graph({1: set(), 3: set(), 5: set()}, [(1, 3, 5)]) + + def test_the_node_multiple_times(self): + # Test same node multiple times in dependencies + self._test_graph({1: {2}, 3: {4}, 0: [2, 4, 4, 4, 4, 4]}, [(2, 4), (1, 3, 0)]) + + # Test adding the same dependency multiple times + ts = graphlib.TopologicalSorter() + ts.add(1, 2) + ts.add(1, 2) + ts.add(1, 2) + self.assertEqual([*ts.static_order()], [2, 1]) + + def test_graph_with_iterables(self): + dependson = (2 * x + 1 for x in range(5)) + ts = graphlib.TopologicalSorter({0: dependson}) + self.assertEqual(list(ts.static_order()), [1, 3, 5, 7, 9, 0]) + + def test_add_dependencies_for_same_node_incrementally(self): + # Test same node multiple times + ts = graphlib.TopologicalSorter() + ts.add(1, 2) + ts.add(1, 3) + ts.add(1, 4) + ts.add(1, 5) + + ts2 = graphlib.TopologicalSorter({1: {2, 3, 4, 5}}) + self.assertEqual([*ts.static_order()], [*ts2.static_order()]) + + def test_empty(self): + self._test_graph({}, []) + + def test_cycle(self): + # Self cycle + self._assert_cycle({1: {1}}, [1, 1]) + # Simple cycle + self._assert_cycle({1: {2}, 2: {1}}, [1, 2, 1]) + # Indirect cycle + self._assert_cycle({1: {2}, 2: {3}, 3: {1}}, [1, 3, 2, 1]) + # not all elements involved in a cycle + self._assert_cycle({1: {2}, 2: {3}, 3: {1}, 5: {4}, 4: {6}}, [1, 3, 2, 1]) + # Multiple cycles + self._assert_cycle({1: {2}, 2: {1}, 3: {4}, 4: {5}, 6: {7}, 7: {6}}, [1, 2, 1]) + # Cycle in the middle of the graph + self._assert_cycle({1: {2}, 2: {3}, 3: {2, 4}, 4: {5}}, [3, 2]) + + def test_calls_before_prepare(self): + ts = graphlib.TopologicalSorter() + + with self.assertRaisesRegex(ValueError, r"prepare\(\) must be called first"): + ts.get_ready() + with self.assertRaisesRegex(ValueError, r"prepare\(\) must be called first"): + ts.done(3) + with self.assertRaisesRegex(ValueError, r"prepare\(\) must be called first"): + ts.is_active() + + def test_prepare_multiple_times(self): + ts = graphlib.TopologicalSorter() + ts.prepare() + with self.assertRaisesRegex(ValueError, r"cannot prepare\(\) more than once"): + ts.prepare() + + def test_invalid_nodes_in_done(self): + ts = graphlib.TopologicalSorter() + ts.add(1, 2, 3, 4) + ts.add(2, 3, 4) + ts.prepare() + ts.get_ready() + + with self.assertRaisesRegex(ValueError, "node 2 was not passed out"): + ts.done(2) + with self.assertRaisesRegex(ValueError, r"node 24 was not added using add\(\)"): + ts.done(24) + + def test_done(self): + ts = graphlib.TopologicalSorter() + ts.add(1, 2, 3, 4) + ts.add(2, 3) + ts.prepare() + + self.assertEqual(ts.get_ready(), (3, 4)) + # If we don't mark anything as done, get_ready() returns nothing + self.assertEqual(ts.get_ready(), ()) + ts.done(3) + # Now 2 becomes available as 3 is done + self.assertEqual(ts.get_ready(), (2,)) + self.assertEqual(ts.get_ready(), ()) + ts.done(4) + ts.done(2) + # Only 1 is missing + self.assertEqual(ts.get_ready(), (1,)) + self.assertEqual(ts.get_ready(), ()) + ts.done(1) + self.assertEqual(ts.get_ready(), ()) + self.assertFalse(ts.is_active()) + + def test_is_active(self): + ts = graphlib.TopologicalSorter() + ts.add(1, 2) + ts.prepare() + + self.assertTrue(ts.is_active()) + self.assertEqual(ts.get_ready(), (2,)) + self.assertTrue(ts.is_active()) + ts.done(2) + self.assertTrue(ts.is_active()) + self.assertEqual(ts.get_ready(), (1,)) + self.assertTrue(ts.is_active()) + ts.done(1) + self.assertFalse(ts.is_active()) + + def test_not_hashable_nodes(self): + ts = graphlib.TopologicalSorter() + self.assertRaises(TypeError, ts.add, dict(), 1) + self.assertRaises(TypeError, ts.add, 1, dict()) + self.assertRaises(TypeError, ts.add, dict(), dict()) + + def test_order_of_insertion_does_not_matter_between_groups(self): + def get_groups(ts): + ts.prepare() + while ts.is_active(): + nodes = ts.get_ready() + ts.done(*nodes) + yield set(nodes) + + ts = graphlib.TopologicalSorter() + ts.add(3, 2, 1) + ts.add(1, 0) + ts.add(4, 5) + ts.add(6, 7) + ts.add(4, 7) + + ts2 = graphlib.TopologicalSorter() + ts2.add(1, 0) + ts2.add(3, 2, 1) + ts2.add(4, 7) + ts2.add(6, 7) + ts2.add(4, 5) + + self.assertEqual(list(get_groups(ts)), list(get_groups(ts2))) + + def test_static_order_does_not_change_with_the_hash_seed(self): + def check_order_with_hash_seed(seed): + code = """if 1: + import graphlib + ts = graphlib.TopologicalSorter() + ts.add('blech', 'bluch', 'hola') + ts.add('abcd', 'blech', 'bluch', 'a', 'b') + ts.add('a', 'a string', 'something', 'b') + ts.add('bluch', 'hola', 'abcde', 'a', 'b') + print(list(ts.static_order())) + """ + env = os.environ.copy() + # signal to assert_python not to do a copy + # of os.environ on its own + env["__cleanenv"] = True + env["PYTHONHASHSEED"] = str(seed) + out = assert_python_ok("-c", code, **env) + return out + + run1 = check_order_with_hash_seed(1234) + run2 = check_order_with_hash_seed(31415) + + self.assertNotEqual(run1, "") + self.assertNotEqual(run2, "") + self.assertEqual(run1, run2) diff --git a/Misc/NEWS.d/next/Library/2020-05-31-23-32-36.bpo-17005.JlRUGB.rst b/Misc/NEWS.d/next/Library/2020-05-31-23-32-36.bpo-17005.JlRUGB.rst new file mode 100644 index 00000000000..0fd01fb6230 --- /dev/null +++ b/Misc/NEWS.d/next/Library/2020-05-31-23-32-36.bpo-17005.JlRUGB.rst @@ -0,0 +1,4 @@ +The topological sort functionality that was introduced initially in the +:mod:`functools` module has been moved to a new :mod:`graphlib` module to +better accommodate the new tools and keep the original scope of the +:mod:`functools` module. Patch by Pablo Galindo diff --git a/PCbuild/lib.pyproj b/PCbuild/lib.pyproj index 7ce88e5690b..f0c51edb9d1 100644 --- a/PCbuild/lib.pyproj +++ b/PCbuild/lib.pyproj @@ -419,6 +419,7 @@ +