298 lines
10 KiB
Python
298 lines
10 KiB
Python
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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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# Copyright 2012 California Institute of Technology. ALL RIGHTS RESERVED.
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain 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,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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#
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# United States Government Sponsorship acknowledged. This software is subject to
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# U.S. export control laws and regulations and has been classified as 'EAR99 NLR'
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# (No [Export] License Required except when exporting to an embargoed country,
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# end user, or in support of a prohibited end use). By downloading this software,
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# the user agrees to comply with all applicable U.S. export laws and regulations.
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# The user has the responsibility to obtain export licenses, or other export
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# authority as may be required before exporting this software to any 'EAR99'
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# embargoed foreign country or citizen of those countries.
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#
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# Author: Eric Belz
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#~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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## \namespace isceobj.Util.decorators Utility decorators
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"""This module has generic decorators, such as:
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float_setter (makes sure a setter calls it's args __float__)
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type_check (a type checker for methods)
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object_wrapper (for making methods that interface to a C for Fortran library)
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dov (deal with dictionaryOfVariables in a DRY way)
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profiler (a method profile-- TBD).
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etc
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"""
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from functools import wraps
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## force a setter to use a type
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def force(type_):
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def enforcer(setter):
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@wraps(setter)
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def checked_setter(self, value):
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try:
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checked = type_(value)
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except (ValueError, TypeError, AttributeError):
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message = "Expecting a %s, but got: %s, in setter: %s, %s"%(
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str(type_),
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str(value),
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self.__class__.__name__,
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setter.__name__)
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if hasattr(self, "logger"):
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self.logger.warning(message)
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else:
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raise ValueError(message)
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pass
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return setter(self, checked)
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return checked_setter
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return enforcer
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## for floating point
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float_setter = force(float)
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## decorator to wrap a 1-argument **methods** and check if the argument is an instance
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# of "cls"
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def type_check(cls):
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"""decorator=type_check(cls)
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"cls" is a class that the decorated method's sole argument must be an instance of (or
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a TypeError is raised-- a string explaining the problem is included"
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"decorator" is the decorator with which to decorate the method-- the decorator
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protocol is that a decorator with arguments returns a decorator.
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USAGE WARNING: CANNOT DECORATE FUNCTIONS or STATICMETHODS (yet).
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"""
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## The checker knows "cls", and takes the method to make, an return, checked_method
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def checker(method):
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## The interpretor installs this method in method's place--
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## it checks and raises a TypeEror if needed
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def checked_method(*args):
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obj = args[-1]
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if not isinstance(obj, cls):
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raise TypeError(
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method.__name__+
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" excpected: "+
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cls.__name__ +
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", got:" +
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str(obj.__class__)
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)
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return method(*args)
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return checked_method
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return checker
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## If self.method(*args) return self.object.method(*args), then decorate method with:
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## @object_wrapper("object")
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def object_wrapper(objname):
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"""If self.method(*args) return self.object.method(*args), then decorate method with
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@object_wrapper("object") and make sure that the method looks like this:
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@object_wrapprt("object")
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def method(self, x1, ..., xn.):
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return object.method
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where object.method(x1,..., xn) is object.method's signature. See LineAccesorPy.py
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for a concrete example.
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"""
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## functools.wraps prevents the decorator from overiding the method's:
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## __name__, __doc__ attributes.
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def accessor(func):
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"""This is a method decorator. The bare method returns "func", while the
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decorated method ("new_method") calls it, with self.<objname> as the implicit 1st
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argument. """
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@wraps(func)
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def new_method(self, *args):
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return func(getattr(self, objname), *args)
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return new_method
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return accessor
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## This decorator decorates __init__ methods for classes that need their mandatory and
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## optional variables computed -- it may removed when Parameters replace variable tuples.
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def dov(init):
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"""Usage:
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dictionaryOfVariables = {....}
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@dov
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def __init__(self,...):
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Decorates __init__ so that it takes a STATIC dictionary of variables and computes
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dynamic mandatoryVariables and optionalVariables dictionies. Obviously easy to
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rewrite to take a dynamic dictionaryOfVariables.
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Nevertheless, it should be a class decorator that only handles static variables.
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That's TBD.
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"""
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def constructor(self, *args, **kwargs):
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self.descriptionOfVariables = {}
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self.mandatoryVariables = []
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self.optionalVariables = []
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typePos = 2
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for key , val in self.dictionaryOfVariables.items():
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value = val[typePos]
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if value is True or value == 'mandatory':
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self.mandatoryVariables.append(key)
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elif value is False or value == 'optional':
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self.optionalVariables.append(key)
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else:
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raise ValueError(
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'Error. Variable can only be "optional"/False or "mandatory"/True'
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)
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pass
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return init(self, *args, **kwargs)
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return constructor
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## Decorator to add logging to a class's __init__.
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def logged(init):
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"""Usage:
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-------------------------------------------------
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| class CLS(object): |
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| logging_name = 'isce.cls' # or whatever |
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| @logged |
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| def __init__(self, ...) |
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-------------------------------------------------
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This decorator adds a logger names "logging_name"
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to any instance of CLS.
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"""
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import logging
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def constructor(self, *args, **kwargs):
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init(self, *args, **kwargs)
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self.logger = logging.getLogger(self.__class__.logging_name)
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return None
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return constructor
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## The no-pickle list, may be moved to a /library.
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DONT_PICKLE_ME = ('logger', '_inputPorts', '_outputPorts')
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## Decorator to add pickling to a class without using inheritance
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def pickled(cls):
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"""Usage:
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-------------------------------------------------
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| @pickled |
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| class CLS(object): |
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| logging_name = 'isce.cls' # or whatever |
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-------------------------------------------------
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This decorator adds pickling to class CLS.
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By default, it also invokes @logged on the CLS.__init__,
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so you need to
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"""
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## reject objects bases on name
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def __getstate__(self):
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d = dict(self.__dict__)
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## for future use: modify no pickle list.
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skip = (
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() if not hasattr(self.__class__, 'dont_pickle_me') else
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self.__class__.dont_pickle_me
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)
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for key in DONT_PICKLE_ME+skip:
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if key in d:
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del d[key]
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pass
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pass
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return d
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def __setstate__(self,d):
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self.__dict__.update(d)
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import logging
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self.logger = logging.getLogger(self.__class__.logging_name)
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pass
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if not hasattr(cls, '__setstate__'): cls.__setstate__ = __setstate__
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if not hasattr(cls, '__getstate__'): cls.__getstate__ = __getstate__
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return cls
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## A decorator for making a port out of a trivial method named add<port>
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def port(check):
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"""port(check) makes a decorator.
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if "check" is a str [type] it enforces:
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hasattr(port, check) [isintanace(port, check)].
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The decorated method should be as follows, for port "spam"
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@port("eggs")
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def addspam(self):
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pass
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That will setup:
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self.spam from self.inputPorts['spam'] and ensure:
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self.spam.eggs exists.
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Of course, the method canbe notrivial, too.
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"""
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def port_decorator(method):
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port_name = method.__name__[3:].lower()
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attr = port_name
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@wraps(method)
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def port_method(self):
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local_object = self.inputPorts[port_name]
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setattr(self, attr, local_object)
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if check is not None:
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if isinstance(check, str):
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if not hasattr(local_object, check):
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raise AttributeError(check+" failed")
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pass
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else:
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if not isinstance(local_object, check):
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raise TypeError(str(check)+" failed")
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pass
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pass
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return method(self) # *args, **kwargs is TBD.
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return port_method
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return port_decorator
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##Provide a decorator for those methods that need to use the old api.
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##at one point one might just turn it off by simply returning the original function
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def use_api(func):
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from iscesys.ImageApi.DataAccessorPy import DataAccessor
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def use_api_decorator(*args,**kwargs):
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#turn on the use of the old image api
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if DataAccessor._accessorType == 'api':
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leave = True
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else:
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DataAccessor._accessorType = 'api'
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leave = False
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ret = func(*args,**kwargs)
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#turn off. The default will be used, i.e. api for write and gdal for read
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if not leave:
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DataAccessor._accessorType = ''
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return ret
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return use_api_decorator
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