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Unified Diff: third_party/WebKit/Source/bindings/scripts/overload_set_algorithm.py

Issue 2712913002: [WebAgentsAPI]: Split overload set functions into their own module. (Closed)
Patch Set: Feedback addressed. Created 3 years, 10 months ago
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Index: third_party/WebKit/Source/bindings/scripts/overload_set_algorithm.py
diff --git a/third_party/WebKit/Source/bindings/scripts/overload_set_algorithm.py b/third_party/WebKit/Source/bindings/scripts/overload_set_algorithm.py
new file mode 100644
index 0000000000000000000000000000000000000000..cda46c2b37013a0850a66e76d3fd191019227050
--- /dev/null
+++ b/third_party/WebKit/Source/bindings/scripts/overload_set_algorithm.py
@@ -0,0 +1,128 @@
+# Copyright 2017 The Chromium Authors. All rights reserved.
+# coding=utf-8
+# Use of this source code is governed by a BSD-style license that can be
+# found in the LICENSE file.
+
+from collections import Counter
+import itertools
+from operator import itemgetter
+
+
+def sort_and_groupby(list_to_sort, key=None):
+ """Returns a generator of (key, list), sorting and grouping list by key."""
+ list_to_sort.sort(key=key)
+ return ((k, list(g)) for k, g in itertools.groupby(list_to_sort, key))
+
+
+def effective_overload_set(F): # pylint: disable=invalid-name
+ """Returns the effective overload set of an overloaded function.
+
+ An effective overload set is the set of overloaded functions + signatures
+ (type list of arguments, with optional and variadic arguments included or
+ not), and is used in the overload resolution algorithm.
+
+ For example, given input [f1(optional long x), f2(DOMString s)], the output
+ is informally [f1(), f1(long), f2(DOMString)], and formally
+ [(f1, [], []), (f1, [long], [optional]), (f2, [DOMString], [required])].
+
+ Currently the optionality list is a list of |is_optional| booleans (True
+ means optional, False means required); to support variadics this needs to
+ be tri-valued as required, optional, or variadic.
+
+ Formally:
+ An effective overload set represents the allowable invocations for a
+ particular operation, constructor (specified with [Constructor] or
+ [NamedConstructor]), legacy caller or callback function.
+
+ An additional argument N (argument count) is needed when overloading
+ variadics, but we don't use that currently.
+
+ Spec: http://heycam.github.io/webidl/#dfn-effective-overload-set
+
+ Formally the input and output lists are sets, but methods are stored
+ internally as dicts, which can't be stored in a set because they are not
+ hashable, so we use lists instead.
+
+ Arguments:
+ F: list of overloads for a given callable name.
+
+ Returns:
+ S: list of tuples of the form (callable, type list, optionality list).
+ """
+ # Code closely follows the algorithm in the spec, for clarity and
+ # correctness, and hence is not very Pythonic.
+
+ # 1. Initialize S to ∅.
+ # (We use a list because we can't use a set, as noted above.)
+ S = [] # pylint: disable=invalid-name
+
+ # 2. Let F be a set with elements as follows, according to the kind of
+ # effective overload set:
+ # (Passed as argument, nothing to do.)
+
+ # 3. & 4. (maxarg, m) are only needed for variadics, not used.
+
+ # 5. For each operation, extended attribute or callback function X in F:
+ for X in F: # X is the "callable". pylint: disable=invalid-name
+ arguments = X['arguments'] # pylint: disable=invalid-name
+ # 1. Let n be the number of arguments X is declared to take.
+ n = len(arguments) # pylint: disable=invalid-name
+ # 2. Let t0..n−1 be a list of types, where ti is the type of X’s
+ # argument at index i.
+ # (“type list”)
+ t = tuple(argument['idl_type_object'] # pylint: disable=invalid-name
+ for argument in arguments)
+ # 3. Let o0..n−1 be a list of optionality values, where oi is “variadic”
+ # if X’s argument at index i is a final, variadic argument, “optional”
+ # if the argument is optional, and “required” otherwise.
+ # (“optionality list”)
+ # (We’re just using a boolean for optional/variadic vs. required.)
+ o = tuple(argument['is_optional'] # pylint: disable=invalid-name
+ or argument['is_variadic'] for argument in arguments)
+ # 4. Add to S the tuple <X, t0..n−1, o0..n−1>.
+ S.append((X, t, o))
+ # 5. If X is declared to be variadic, then:
+ # (Not used, so not implemented.)
+ # 6. Initialize i to n−1.
+ i = n - 1
+ # 7. While i ≥ 0:
+ # Spec bug (fencepost error); should be “While i > 0:”
+ # https://www.w3.org/Bugs/Public/show_bug.cgi?id=25590
+ while i > 0:
+ # 1. If argument i of X is not optional, then break this loop.
+ if not o[i]:
+ break
+ # 2. Otherwise, add to S the tuple <X, t0..i−1, o0..i−1>.
+ S.append((X, t[:i], o[:i]))
+ # 3. Set i to i−1.
+ i = i - 1
+ # 8. If n > 0 and all arguments of X are optional, then add to S the
+ # tuple <X, (), ()> (where “()” represents the empty list).
+ if n > 0 and all(oi for oi in o):
+ S.append((X, [], []))
+ # 6. The effective overload set is S.
+ return S
+
+
+def effective_overload_set_by_length(overloads):
+ def type_list_length(entry):
+ # Entries in the effective overload set are 3-tuples:
+ # (callable, type list, optionality list)
+ return len(entry[1])
+
+ effective_overloads = effective_overload_set(overloads)
+ return list(sort_and_groupby(effective_overloads, type_list_length))
+
+
+def method_overloads_by_name(methods):
+ """Returns generator of overloaded methods by name: [name, [method]]"""
+ # Filter to only methods that are actually overloaded
+ method_counts = Counter(method['name'] for method in methods)
+ overloaded_method_names = set(name
+ for name, count in method_counts.iteritems()
+ if count > 1)
+ overloaded_methods = [method for method in methods
+ if method['name'] in overloaded_method_names]
+
+ # Group by name (generally will be defined together, but not necessarily)
+ return sort_and_groupby(overloaded_methods, itemgetter('name'))
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