17c909ec83
Signed-off-by: Dean Troyer <dtroyer@gmail.com>
174 lines
5.9 KiB
Python
174 lines
5.9 KiB
Python
# vim: tabstop=4 shiftwidth=4 softtabstop=4
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# Copyright 2010 United States Government as represented by the
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# Administrator of the National Aeronautics and Space Administration.
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# Copyright 2011 Justin Santa Barbara
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# All Rights Reserved.
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#
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# Licensed under the Apache License, Version 2.0 (the "License"); you may
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# not use this file except in compliance with the License. You may obtain
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# a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS, WITHOUT
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# WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the
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# License for the specific language governing permissions and limitations
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# under the License.
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#
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# Copyright (c) 2013-2014 Wind River Systems, Inc.
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#
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'''
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JSON related utilities.
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This module provides a few things:
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1) A handy function for getting an object down to something that can be
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JSON serialized. See to_primitive().
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2) Wrappers around loads() and dumps(). The dumps() wrapper will
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automatically use to_primitive() for you if needed.
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3) This sets up anyjson to use the loads() and dumps() wrappers if anyjson
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is available.
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'''
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import datetime
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import functools
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import inspect
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import itertools
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import json
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import types
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import xmlrpclib
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import six
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from sm_api.openstack.common import timeutils
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_nasty_type_tests = [inspect.ismodule, inspect.isclass, inspect.ismethod,
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inspect.isfunction, inspect.isgeneratorfunction,
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inspect.isgenerator, inspect.istraceback, inspect.isframe,
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inspect.iscode, inspect.isbuiltin, inspect.isroutine,
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inspect.isabstract]
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_simple_types = (types.NoneType, int, basestring, bool, float, long)
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def to_primitive(value, convert_instances=False, convert_datetime=True,
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level=0, max_depth=3):
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"""Convert a complex object into primitives.
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Handy for JSON serialization. We can optionally handle instances,
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but since this is a recursive function, we could have cyclical
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data structures.
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To handle cyclical data structures we could track the actual objects
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visited in a set, but not all objects are hashable. Instead we just
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track the depth of the object inspections and don't go too deep.
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Therefore, convert_instances=True is lossy ... be aware.
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"""
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# handle obvious types first - order of basic types determined by running
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# full tests on nova project, resulting in the following counts:
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# 572754 <type 'NoneType'>
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# 460353 <type 'int'>
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# 379632 <type 'unicode'>
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# 274610 <type 'str'>
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# 199918 <type 'dict'>
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# 114200 <type 'datetime.datetime'>
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# 51817 <type 'bool'>
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# 26164 <type 'list'>
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# 6491 <type 'float'>
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# 283 <type 'tuple'>
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# 19 <type 'long'>
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if isinstance(value, _simple_types):
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return value
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if isinstance(value, datetime.datetime):
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if convert_datetime:
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return timeutils.strtime(value)
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else:
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return value
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# value of itertools.count doesn't get caught by nasty_type_tests
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# and results in infinite loop when list(value) is called.
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if type(value) == itertools.count:
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return six.text_type(value)
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# FIXME(vish): Workaround for LP bug 852095. Without this workaround,
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# tests that raise an exception in a mocked method that
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# has a @wrap_exception with a notifier will fail. If
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# we up the dependency to 0.5.4 (when it is released) we
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# can remove this workaround.
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if getattr(value, '__module__', None) == 'mox':
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return 'mock'
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if level > max_depth:
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return '?'
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# The try block may not be necessary after the class check above,
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# but just in case ...
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try:
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recursive = functools.partial(to_primitive,
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convert_instances=convert_instances,
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convert_datetime=convert_datetime,
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level=level,
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max_depth=max_depth)
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if isinstance(value, dict):
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return dict((k, recursive(v)) for k, v in value.iteritems())
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elif isinstance(value, (list, tuple)):
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return [recursive(lv) for lv in value]
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# It's not clear why xmlrpclib created their own DateTime type, but
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# for our purposes, make it a datetime type which is explicitly
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# handled
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if isinstance(value, xmlrpclib.DateTime):
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value = datetime.datetime(*tuple(value.timetuple())[:6])
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if convert_datetime and isinstance(value, datetime.datetime):
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return timeutils.strtime(value)
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elif hasattr(value, 'iteritems'):
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return recursive(dict(value.iteritems()), level=level + 1)
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elif hasattr(value, '__iter__'):
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return recursive(list(value))
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elif convert_instances and hasattr(value, '__dict__'):
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# Likely an instance of something. Watch for cycles.
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# Ignore class member vars.
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return recursive(value.__dict__, level=level + 1)
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else:
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if any(test(value) for test in _nasty_type_tests):
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return six.text_type(value)
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return value
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except TypeError:
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# Class objects are tricky since they may define something like
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# __iter__ defined but it isn't callable as list().
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return six.text_type(value)
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def dumps(value, default=to_primitive, **kwargs):
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return json.dumps(value, default=default, **kwargs)
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def loads(s):
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return json.loads(s)
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def load(s):
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return json.load(s)
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try:
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import anyjson
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except ImportError:
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pass
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else:
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anyjson._modules.append((__name__, 'dumps', TypeError,
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'loads', ValueError, 'load'))
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anyjson.force_implementation(__name__)
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