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scripts/decodetree: Implement a topological sort
To support named fields, we will need to be able to do a topological sort (so that we ensure that we output the assignment to field A before the assignment to field B if field B refers to field A by name). The good news is that there is a tsort in the python standard library; the bad news is that it was only added in Python 3.9. To bridge the gap between our current minimum supported Python version and 3.9, provide a local implementation that has the same API as the stdlib version for the parts we care about. In future when QEMU's minimum Python version requirement reaches 3.9 we can delete this code and replace it with an 'import' line. The core of this implementation is based on https://code.activestate.com/recipes/578272-topological-sort/ which is MIT-licensed. Signed-off-by: Peter Maydell <peter.maydell@linaro.org> Acked-by: Richard Henderson <richard.henderson@linaro.org> Message-Id: <20230523120447.728365-5-peter.maydell@linaro.org>
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@ -54,6 +54,80 @@
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re_fmt_ident = '@[a-zA-Z0-9_]*'
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re_pat_ident = '[a-zA-Z0-9_]*'
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# Local implementation of a topological sort. We use the same API that
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# the Python graphlib does, so that when QEMU moves forward to a
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# baseline of Python 3.9 or newer this code can all be dropped and
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# replaced with:
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# from graphlib import TopologicalSorter, CycleError
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#
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# https://docs.python.org/3.9/library/graphlib.html#graphlib.TopologicalSorter
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#
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# We only implement the parts of TopologicalSorter we care about:
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# ts = TopologicalSorter(graph=None)
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# create the sorter. graph is a dictionary whose keys are
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# nodes and whose values are lists of the predecessors of that node.
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# (That is, if graph contains "A" -> ["B", "C"] then we must output
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# B and C before A.)
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# ts.static_order()
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# returns a list of all the nodes in sorted order, or raises CycleError
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# CycleError
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# exception raised if there are cycles in the graph. The second
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# element in the args attribute is a list of nodes which form a
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# cycle; the first and last element are the same, eg [a, b, c, a]
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# (Our implementation doesn't give the order correctly.)
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#
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# For our purposes we can assume that the data set is always small
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# (typically 10 nodes or less, actual links in the graph very rare),
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# so we don't need to worry about efficiency of implementation.
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#
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# The core of this implementation is from
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# https://code.activestate.com/recipes/578272-topological-sort/
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# (but updated to Python 3), and is under the MIT license.
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class CycleError(ValueError):
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"""Subclass of ValueError raised if cycles exist in the graph"""
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pass
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class TopologicalSorter:
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"""Topologically sort a graph"""
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def __init__(self, graph=None):
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self.graph = graph
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def static_order(self):
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# We do the sort right here, unlike the stdlib version
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from functools import reduce
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data = {}
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r = []
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if not self.graph:
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return []
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# This code wants the values in the dict to be specifically sets
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for k, v in self.graph.items():
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data[k] = set(v)
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# Find all items that don't depend on anything.
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extra_items_in_deps = (reduce(set.union, data.values())
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- set(data.keys()))
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# Add empty dependencies where needed
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data.update({item:{} for item in extra_items_in_deps})
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while True:
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ordered = set(item for item, dep in data.items() if not dep)
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if not ordered:
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break
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r.extend(ordered)
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data = {item: (dep - ordered)
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for item, dep in data.items()
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if item not in ordered}
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if data:
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# This doesn't give as nice results as the stdlib, which
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# gives you the cycle by listing the nodes in order. Here
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# we only know the nodes in the cycle but not their order.
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raise CycleError(f'nodes are in a cycle', list(data.keys()))
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return r
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# end TopologicalSorter
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def error_with_file(file, lineno, *args):
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"""Print an error message from file:line and args and exit."""
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global output_file
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