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b47df51478
* Add new JSON IPC implementation to be shared between the product and the tests. Add pytest-based test support, and wire it up to setup.py and Travis. Dial pylint down to complain about important things only. Various minor fixes exposed by pylint. Add basic .vscode/settings.json for linter settings (and anything else that's workspace-specific). Fixes #831.
81 lines
2.7 KiB
Python
81 lines
2.7 KiB
Python
# Copyright (c) Microsoft Corporation. All rights reserved.
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# Licensed under the MIT License. See LICENSE in the project root
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# for license information.
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from collections import defaultdict
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class Any(object):
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"""Represents a wildcard in a pattern as used by json_matches(),
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and matches any single object in the same place in input data.
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"""
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def __repr__(self):
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return '<*>'
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@staticmethod
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def dict_with(items):
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return Any.DictWith(items)
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class DictWith(defaultdict):
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"""A dict subclass that returns ANY for any non-existent key.
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This can be used in conjunction with json_matches to match some keys
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in a dict while ignoring others. For example:
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d1 = {'a': 1, 'b': 2, 'c': 3}
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d2 = {'a': 1, 'b': 2}
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json_matches(d1, d2) # False
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json_matches(d1, ANY.dict_with(d2)) # True
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"""
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def __init__(self, other=None):
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super(Any.DictWith, self).__init__(lambda: ANY, other or {})
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def __repr__(self):
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return dict.__repr__(self)[:-2] + ', ...}'
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ANY = Any()
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def json_matches(data, pattern):
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"""Match data against pattern, returning True if it matches, and False otherwise.
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The data argument must be an object obtained via json.load, or equivalent.
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In other words, it must be a recursive data structure consisting only of
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dicts, lists, strings, numbers, Booleans, and None.
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The pattern argument is like data, but can also use the special value ANY.
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For strings, numbers, Booleans and None, the data matches the pattern if they're
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equal as defined by ==, or if the pattern is ANY.
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For lists, the data matches the pattern if they're both of the same length,
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and if every element json_matches() the element in the other list with the same
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index.
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For dicts, the data matches the pattern if, for every K in data.keys() + pattern.keys(),
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data.has_key(K) and json_matches(data[K], pattern[K]). ANY.dict_with() can be used to
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perform partial matches.
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See test_jsonre.py for examples.
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"""
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if isinstance(pattern, Any):
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return True
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elif isinstance(data, list):
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return len(data) == len(pattern) and all((json_matches(x, y) for x, y in zip(data, pattern)))
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elif isinstance(data, dict):
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keys = set(tuple(data.keys()) + tuple(pattern.keys()))
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def pairs_match(key):
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try:
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dval = data[key]
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pval = pattern[key]
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except KeyError:
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return False
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return json_matches(dval, pval)
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return all((pairs_match(key) for key in keys))
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else:
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return data == pattern
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