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The wrapper s code begins by setting up the log string with the function s name and arguments We then try calling the function and storing its result If any exception occurs we store it In all cases the finally block is executed, and there we add the return value (or exception) to the log string and write to the log If no exception occurred, the result is returned; otherwise, we reraise the exception to correctly mimic the original function s behavior If Python is running in optimized mode, __debug__ is False; in this case we de ne the logged() function to simply return the function it is given, so apart from the tiny overhead of this indirection when the function is rst created, there is no runtime overhead at all Note that the standard library s trace and cProfile modules can run and analyse programs and modules to produce various tracing and pro ling reports Both use introspection, so unlike the @logged decorator we have used here, neither trace nor cProfile requires any source code changes

However, there are few areas that need further explanation both work Also, will ow among WCF threads Globalization You can set thread culture and access the Globaliza tion section in Impersonation WCF supports impersonation at the service and operation level using behaviors This is in addition to what is implemented by ASPNET If the service enables impersonation through WCF, this overrides settings in ASPNET If the service does not implement impersonation, ASPNET rules will be used Session state This is fully implemented and derived from ASPNET con guration You can save state with the process, server, or SQL persistence mechanism After ASPNET Compatibility mode is enabled, services can take advantage of the features in ASPNET In Listing 75, we leverage two ASPNET features First, we use the SessionState feature of ASMX to store session-level and

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Functions and methods can be de ned with annotations expressions that can be used in a function s signature Here s the general syntax:

Every colon expression part (: expX) is an optional annotation, and so is the arrow return expression part (-> rexp) The last (or only) positional parameter (if present) can be of the form *args, with or without an annotation; similarly, the last (or only) keyword parameter (if present) can be of the form **kwargs, again with or without an annotation If annotations are present they are added to the function s __annotations__ dictionary; if they are not present this dictionary is empty The dictionary s keys are the parameter names, and the values are the corresponding expressions The syntax allows us to annotate all, some, or none of the parameters and to annotate the return value or not Annotations have no special signi cance to Python The only thing that Python does in the face of annotations is to put them in the __annotations__ dictionary; any other action is up to us Here is an example of an annotated function that is in the Util module:

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def is_unicode_punctuation(s : str) -> bool: for c in s: if unicodedatacategory(c)[0] != "P": return False return True

state Instancing can be scoped as , , or These are further de ned in 5, Behaviors In this example, we use , so that if a client uses the same proxy multiple times to invoke the service, session state will be preserved across calls There are many other ways to store session-level data in WCF, but for those familiar with ASMX, this is a convenient mechanism Second, we use the familiar to store application-speci c con guAppSettings section in collection of the ration data In the service code, the object is used to retrieve these values

Every Unicode character belongs to a particular category and each category is identi ed by a two-character identi er All the categories that begin with P are punctuation characters Here we have used Python data types as the annotation expressions But they have no particular meaning for Python, as these calls should make clear:

Utilis_unicode_punctuation("zebr\a") Utilis_unicode_punctuation(s="!@# ") Utilis_unicode_punctuation(("!", "@")) # returns: False # returns: True # returns: True

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The rst call uses a positional argument and the second call a keyword argument, just to show that both kinds work as expected The last call passes a tuple rather than a string, and this is accepted since Python does nothing more than record the annotations in the __annotations__ dictionary If we want to give meaning to annotations, for example, to provide type checking, one approach is to decorate the functions we want the meaning to apply to with a suitable decorator Here is a very basic type-checking decorator:

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