python,decorator,python-decorators,functools
This should do it: from functools import wraps def count_check(function, count=[0]): """Returns number of times any function with this decorator is called """ @wraps(function) def increase_count(*args, **kwargs): count[0] += 1 return function(*args, **kwargs), count[0] return increase_count You could also get fancy and use a dictionary counting the functions individually as...
You are using a double underscore name, which has undergone private name mangling in the run method. When stepping through the debugger, I get: AttributeError: "'function' object has no attribute '_MyFramework__skip_condition Don't use double underscore names here; if you rename the function attribute to _skip_condition the code works (provided you...
python,function,arguments,decorator
Decorators on methods are applied when the class is being defined, which means that the setup and teardown methods are not bound at that time. This just means you need to pass in the self argument manually. You'll also need to create an outer decorator factory; something that returns the...
python,python-3.x,decorator,python-decorators
Move the check inside of the wrapped_f def __call__(self, f): def wrapped_f(*args, **kwargs): if not permitted: raise Exception("not authenticated to do that") f(*args, **kwargs) return wrapped_f Outside of the wrapped_f, it is checked at the creation of the function. Inside, it becomes part of the body of the new callable,...
c#,polymorphism,decorator,circular-dependency,autofixture
You need to freeze the IComponent first. Then, AutoFixture will re-use the same frozen IComponent instance when creating the LoggingDecorator class. Here are 2 ways of doing this: Using AutoFixture with Auto Mocking: PM> Install-Package AutoFixture.AutoMoq [Fact] public void UsingAutoFixtureAutoMoq() { var fixture = new Fixture() .Customize(new AutoMoqCustomization()); var expected...
python,unit-testing,tdd,decorator,httpretty
You are decorating methods, so your resulting wrapper function needs a self parameter, just like normal functions being used in a class. All that is different is that you used a different name fro that self parameter, test_case. As it happens, the instance is callable, and calling it runs the...
design-patterns,design,decorator,flyweight
Design patterns are not "standards". Design patterns are common Appropriate [vs. Anti-patterns] solutions for common problems. And usually you don't build entire system by using certain design pattern. Rather your subsystems in your code are preferably done by some pattern. Even Asp.net MVC is not really a pattern - it...
python,c++,function,macros,decorator
std::function provides most of the building blocks for my proposed solution. Here is my proposed solution. #include <iostream> #include <functional> //------------------------------- // BEGIN decorator implementation //------------------------------- template <class> struct Decorator; template <class R, class... Args> struct Decorator<R(Args ...)> { Decorator(std::function<R(Args ...)> f) : f_(f) {} R operator()(Args ... args) {...
python,subclass,decorator,metaclass
You decorator is wrong. It should be returning a class instead of a function. def decorator_with_args(*args, **kwargs): def decorator(cls): class Wrapper(cls): def __init__(self, *wargs, **wkwargs): print(wargs, wkwargs) return Wrapper return decorator ...
python,django,decorator,python-decorators
Change: def __call__(self, function, *args): return "<p>{}</p>".format(self.tag, function(*args), self.tag) into: def __call__(self, function): def wrap(*args): return "<{}>{}</{}>".format(self.tag, function(*args), self.tag) return wrap You may want to look into functools for more refined decoration of wrap, but except for supporting help and the like, this should work....
python,exception,logging,decorator,contextmanager
You could put all your processes in a loop: allProcs = [process1, process2, processN] for path in paths: with open(path) as file: text=file.read() for proc in allProcs: try: proc(text) except Exception as e: # handle e record_failure( proc , file.name) continue ...
javascript,prototype,decorator
extend( CaseDecorator, MacbookDecorator ); There is no inheritance taking place to the CaseDecorator from the MacbookDecorator, in fact, the prototype in that way is ignored completely and not beeing inherited by CaseDecorator. You're completely right about this. It looks like a lapse of the author to me, and should...
python,python-3.x,decorator,default-value,metaclass
The wrapper is just a normal function. It does not have "access" to the internals of the wrapped function. You would have to use introspection to get them. See a related question: How to find out the default values of a particular function's argument in another function in Python?...
c#,logging,dependency-injection,decorator,simple-injector
There are multiple ways to do this in Simple Injector. First of all, you can let your decorator's constructor depend on the DecoratorContext class. The DecoratorContext contains contextual information about the decorator. It contains information such as the types of the wrapped decorators and the type of the actual implementation...
python,decorator,mixins,python-decorators
In my opinion, you need mixins when you have a few different classes that should have same functionality. Good examples of using mixins are Django's class-based views. For example, you have a few different classes: FormView, TemplateView, ListView. All of them have one similar piece of functionality: they have to...
python,unit-testing,decorator,python-decorators
I assume you try to reduce the number of retrials to increase test speed. If so, modifying the number of retries variable doesn't seem to be the best approach. Instead, you could unit test the function mymethod without decorator first, and then create a mock function of mymethod. Let's call...
c#,dependency-injection,mono,decorator,autofac
You have this error because the C# compiler doesn't know which overload of the RegisterDecorator method to take. If you force it : builder.RegisterDecorator<ILastActivityUpdator>( new Func<IComponentContext, ILastActivityUpdator, ILastActivityUpdator>( (c, inner) => new AnonymousUserLastActivityUpdator(inner) ), fromKey: "lastActivityUpdator"); You will have a new error : AnonymousUserLastActivityUpdator does not contain a constructor that...
jquery,node.js,error-handling,wrapper,decorator
An example: function sum(a, b) { return a + b; } function logDecorator(fn) { return function() { console.log(arguments); return fn.apply(this, arguments); }; } var sumLog = logDecorator(sum); sumLog(1, 10); // returns 11 and logs { '0': 1, '1': 10 } to the console sumLog(5, 4); // returns 9 and logs...
python,python-2.7,decorator,globals
I find it a little unclear as to what your goal is here. If you need to track per-function state, you can set a flag on the decorated function object itself: def decorator(*a): def real_decorator(function): def wrapper(*args, **kwargs): function.flag = False function(*args, **kwargs) function.flag = True return wrapper return real_decorator...
angularjs,decorator,angular-decorator
Since decorating $http service would be the cleanest way of doing this, you can avoid polluting production code by using something like ng-constants and gulp/grunt to only add decoration code for a 'test' environment. See related Q/A here: angular js - configuration for different enviroments If you are inclined on...
You can use the built-in methods beforeAction (http://www.yiiframework.com/doc/api/1.1/CController#beforeAction-detail) and afterAction (http://www.yiiframework.com/doc/api/1.1/CController#afterAction-detail), inside your ControllerDecorator. This way you would be able to decorate every class tha extends ControllerDecorator. ps: I'm assuming you are using Yii. Right?...
python,python-3.x,wrapper,decorator,wrap
functools.wraps() only copies across attributes. When you then increment the counter on the wrapped function, you are assigning a new integer value to the attribute, and the wrapper will still reference the old value. Instead of having wraps copy across attributes, have it copy across the whole __dict__ attribute of...
You question states: According to this popular answer, the @syntax is just sugar for: function = decorator(function) However, it's more accurate to say that @decorator def function(): pass Is syntactic sugar for: def function(): pass function = decorator(function) Decorators are designed to decorate function, method or class definitions, specifically. The...
If you want to use an existing decorator function on an instance method, note that you can redefine instance methods in __init__, calling the decorator directly rather than using the @ syntax: class MyCls(object): def __init__(self): self.val = 1 self.onefrom1 = dodecorate(self.val)(self.onefrom1) def onefrom1(self, x): return x In use: >>>...
c#,decorator,ioc-container,structuremap
ObjectFactory is obsolete. You can exclude Decorator1<> from being registered as a vanilla ICommandHandler<> with code like this: var container = new Container(config => { config.Scan(scanner => { scanner.AssemblyContainingType(typeof(ICommandHandler<>)); scanner.Exclude(t => t == typeof(Decorator1<>)); scanner.ConnectImplementationsToTypesClosing(typeof(ICommandHandler<>)); }); config.For(typeof(ICommandHandler<>)).DecorateAllWith(typeof(Decorator1<>)); }); UPDATE For multiple modules...
You registered a function in a class. This means that just the function is registered, not a bound method. Functions are not bound to an instance, so no self argument is being passed in. You cannot hope to use the decorator on regular methods in a class definition, because the...
python,python-2.7,logging,decorator,python-decorators
Note that the f(3) in def g(y=f(3)): is executed only once, when the function is defined, not every time when it is called. Thus, the problem seems to be that by the time f(3) is executed in mymodule, the logger is not yet initialized. Initialize first, then import, then it...
You were very close: class Master(SomeOtherClass): __flag = True class Child(Master): pass Two leading underscores without trailing underscores invokes name mangling, so the attribute will be named _Master__flag. Therefore if you check: hasattr(cls, '_{}__flag'.format(cls.__name__)) it will only be True for Master, not Child. ...
You cannot have Decorator know what name it will be assigned to. Assignment occurs after instantiation, so the object will have already been created by the time it is assigned a name. You could however make a decorator that creates decorators dynamically: from functools import wraps def set_return_type(typeobj): def decorator(func):...
ruby,decorator,singleton-methods
extend adds to the list of ancestors, it doesn't replace any existing ancestors - if you examine coffee.singleton_class.ancestors after the second extend you can see that it includes both Milk and Sugar. If you are running 2.2, you can use the new super_method method to examine this: coffee.method(:cost) => #<Method:...
python,python-3.x,decorator,python-decorators
You are assigning to method in the innermost function: message = message.format( name=self.name, cd=method_wrapper.cooldown.remaining, max_cd=method_wrapper.cooldown.limit ) That assignment makes it a local variable, but you cannot make that assignment without first accessing message. You cannot do that with a local. Since you don't want to modify the closed-over argument, you...
java,design-patterns,decorator
The only improvement is to program against interfaces and not implementations. Use the Markable interface instead of SingleMarker in MarkerDecorator and MultipleMarker. It is also a question why MultipleMarker need to extend MarkerDecorator instead of directly implementing the interface. It your case it is not necessary. ...
The problem here is that the self inside Foo.instance1 is a Foo instance, not a Decor instance. You can see this if you print out f.method1 itself: it's a bound method whose instance is f: >>> f.method1 attribute name of instance of class Foo = method1 <bound method Foo.method1 of...
python,class,decorator,with-statement
Each with statement creates a new instance of fcount2 so each instance only has one block_count - I don't have an answer but some additions to your code will illustrate what is happening. class fcount2(object): def __init__(self, inner_func): self.inner_func = inner_func self.count = 0 self.block_count =0 def __call__(self, *args, **kwargs):...
python,caching,decorator,nonetype
Possibly not the most perfect solution, but here's my go: import functools # http://stackoverflow.com/a/28961925/321973 def property_if_None_generator(f, cached=False): @functools.wraps(f) def wrapped(self): value = self.__getattribute__('_' + f.__name__) if value is not None: return value else: return f(self) if cached: wrapped = functools.lru_cache()(wrapped) return property(wrapped) property_if_None = lambda f: property_if_None_generator(f, cached=False) cached_property_if_None =...
python,abstract-class,decorator
Decorators are applied to functions when the class is defined, their return values replace the functions they decorated. By the time the DataWrapper class has been defined, you can no longer alter what decorator is being used. Rather than use decorators, have the decorator delegate to another method on the...
python,function,python-3.x,decorator
Just set the attribute on wrapped_f instead of f. This requires you to set the initial count after defining the function, but that's no big deal: def keep_count(f): @functools.wraps(f) def wrapped_f(*args, **kwargs): f(*args, **kwargs) wrapped_f.count += 1 wrapped_f.count = 0 return wrapped_f Then with your decorated function: >>> test_f() ()...
python,regex,caching,decorator,static-methods
You need to follow this common pattern: you want a function which takes the intended parameters and returns a decorator function. def cachedAttributes(**kwargs): def decorator(func): func.__dict__.update(kwargs) return func return decorator Then: class someclass: @staticmethod @cachedAttributes(doctyperegex = re.compile(r'<!DOCTYPE.*?>\s*', re.S|re.U), htmlregex = re.compile(r'<html.*?>\s*', re.S|re.U), metaregex = re.compile(r'<meta(.*?)>', re.S|re.U)) def method(*args): # compile...
python,python-2.7,decorator,python-decorators
Since it is hard to tell decorator(func) from decorator(callback), make two decorators: from functools import wraps class MyCustomError(Exception): def __init__(self): print('in MyCustomError') # Common implementation def wrap(func,cb=None): @wraps(func) def wrapper(*args, **kwargs): try: return func(*args, **kwargs) except: if cb is not None: cb() raise MyCustomError() return wrapper # No parameters version...
You cannot monkey-patch builtins, so subclassing is the only way (and actually better and cleaner IMHO). I'd go for something like this: class CustomList(list): def __init__(self, parent_instance, *args, **kwargs): super(CustomList, self).__init__(*args, **kwargs) self.parent_instance = parent_instance def append(self, item): self.parent_instance.added = True super(CustomList, self).append(item) class MyClass(object): added = False def __init__(self):...
python,inheritance,wrapper,decorator,super
OK. I solved it. Was a really simple mistake. In add_properties I returned the object of my class, but it needs to return the class itself. So my constructor was executed before my class was completely build. So I just changed it to the following and it works fine: def...
Your create_x function returns an integer: def create_x(): x = input('Give variable x a value: ') return x so create_x()() is never going to work. Part of the problem is that you've used poor parameter names, which is confusing you - you have two xs which refer to two completely...
There are at least two serious errors. The first one is that you check definitions of manifest constants with suffix _H__ but define them without the suffix: #ifndef __TOWER_H__ #define __TOWER__ and #ifndef __TOWERDECORATOR_H__ #define __TOWERDECORATOR__ The second one is that you forgot to place a semicolon after class definition...
python,python-3.x,decorator,python-2.x
The functools.wraps() version in Python 3 can handle function objects with some of the attributes it copies across missing; the one in Python 2 cannot. This is was because issue #3445 was fixed only for Python 3; the methods of dict are defined in C code and have no __module__...
java,design-patterns,override,decorator
Your abstract base type defines four abstract methods: public abstract int getCpu(); public abstract int getRam(); public abstract int getDisco(); public abstract String getCadena(); Your concrete derived type implements one of them: @Override public int getCpu() { return cpd.getCpu()+var; } The error is telling you that you have to implement...
Your decorator needs to provide a wrapper function, which will be called in place of the decorated function. Only when that wrapper is being called is an actual request being routed and can you test the session: from functools import wraps def requirir_login(func): @wraps(func) def wrapper(*args, **kwargs): if session['logged_in']: return...
python,caching,decorator,python-decorators
You should remember that @decorator is just a syntactic sugar for func = decorator(func). So here comes a difference: (1) @decorator def func(): ... is same as func = decorator(func) # Just call of __init__ func(...) # Call of decorator.__call__ but (2) @decorator(some_param) def func(): ... is similiar to...
Think of a decorator as a function that wraps your function. In math you might have a function f(x). If you wrap it with decorator g you have g(f(x)). In python the representation is @function_g def function_f(): pass Here's an example: def entryExit(f): def new_f(): print "Entering", f.__name__ f() print...
decorator,ecmascript-6,aurelia,aurelia-validation
The validation works in all kinds of situations, but using the @ensure decorator can only be used to declare your rules on simple properties (like you found out). Hence... Option a: replace the ensure decorator with the fluent API 'ensure' method, this supports 'nested' or 'complex' binding paths such as:...
javascript,node.js,express,decorator
Example of implementing your middleware: app.use(function(req, res, next) { if (req.path==='somePath' && req.headers.authorization ==='encoded user'){ //costum logic goes here next(); } else { res.sendStatus(403); } }); If you want to pass middleware only in one route you can implement like this: app.get(/*getPath*/, customFunc, function (req, res, next) { // regular...
xml,eclipse,plugins,decorator,readonly
You will have to write a decorator class (specify the class attribute) rather than using the icon attribute. The ILightweightLabelDecorator public void decorate(Object element, IDecoration decoration) method will be passed the IFile as the element so you can do your filtering on that. To deal with the file read only...
Try this var container = new Container(); container.Register<IOp, SimpleOp>(); Container.RegisterDecorator(typeof(IOp), typeof(CompressOp)); var op = container.GetInstance<IOp>(); ...
python,google-app-engine,python-2.7,flask,decorator
The easiest way to do this is to simply invoke the decorator you want to wrap on the wrapper you are returning: def registration_required(): @wraps(f) def decorated_function(*args, **kwargs): if(not is_registered_user(users.get_current_user().user_id())): return redirect(user_reg_url) return f(*args, **kwargs) return login_required(decorated_function) This works because the decorator syntax is just a shorthand: @decorator def some_func():...
In this case, name is going to be the argument passed to your function. In other cases, where we don't know much about the function, we can use *args and **kwargs where you have name in your decorator. A pretty concise explanation actually exists here.
A decorated function or method is usually a different object than the function or method it decorates [*] - so, you can just wrap the original class' method in an explict way. This is rather straightforawrd, and rather boring - but it will work if you need to decorate just...
Not sure if i understand correctly your problem, but the default values for myfunc arguments are known only to myfunc - your decorator has no knowledge of them, so it cannot print them. That's why: myfunc() results in printing: () {} Both *args and **kw are empty for the decorator,...
I see two solutions: 1 - Private inheritance struct A { void stuff() {} }; struct B : private A { using A::stuff; }; int main() { B b; b.stuff(); // OK } You'll need to list all of A's methods, but you don't have to redefine anything. 2 -...
The main benefit you get with the Decorator Pattern is that, for client code, it's transparent. They don't need to know about the decorator, they can just treat it like a plain old concrete implementation of the base interface: ThingDoer thingDoer = new ThingDoerDecorator(new AwesomeThingDoer()); ThingDoer otherThingDoer = new AwesomeThingDoer();...
python,django,permissions,decorator
Apparently 1 of my views using kwargs['slug'] instead of self.kwargs['slug']. Funny that the only thing I've changed is adding that new mixin in my views. Wasted like 4 hours figuring this one out as it has been working fine for 1 month with just using kwargs['slug'].
python,flask,decorator,restful-authentication
Consider using Flask-Login instead to handle authentication and redirect if the user is not logged in. (Or closely examine how it works.) It handles this much more robustly than the function you've written. The function you've written is not a decorator, and has many other issues. First, it needs to...
ruby-on-rails,twitter-bootstrap,decorator,will-paginate,draper
https://github.com/drapergem/draper/issues/429 # app/decorators/application_decorator.rb class ApplicationDecorator < Draper::Decorator def self.collection_decorator_class PaginatingDecorator end end # app/decorators/paginating_decorator.rb class PaginatingDecorator < Draper::CollectionDecorator # support for will_paginate delegate :current_page, :total_entries, :total_pages, :per_page, :offset end # app/decorators/whatever_decorator.rb class WhateverDecorator < ApplicationDecorator end ...
python,decorator,python-decorators
You can easily store a list on the decorator-function object (memoize.decorated): _decorated = [] def memoize(obj): cache = obj.cache = {} # add to the decorated list _decorated.append(obj) @functools.wraps(obj) def memoizer(*args, **kwargs): if args not in cache: cache[args] = obj(*args, **kwargs) return cache[args] return memoizer # make the list accessible...
annotations,typescript,decorator
The return value of this decorator is ignored. This is irrelevant to your situation. The return value of parameter decorators is ignored because they don't need to be able to replace anything (unlike method and class decorators which can replace the descriptor). My problem is that when I try...
self.func() is a valiant attempt, but doesn't work because dot syntax will never care about a local named func. You want to make sure the function receives self, so just pass it in. return func(self, *args, **kwargs) ...
Yes exactly. If you depend on implementations not on abstractions(abstract classes or interfaces), that would be a serious problem for someone/you who wants to add a decorator in between. Please consult the Dependency inversion principle of Solid Principles. That's a general rule at it's core: one should “Depend upon Abstractions....
f becomes index. This: @login_required def index(): return render_template('index.html', title='test home title') Is the same as this: def index(): return render_template('index.html', title='test home title') index = login_required(index) That is, the decorator is called with the decorated function as its argument....
python,decorator,python-decorators
You are trying to 'decorate' the return value of the add() function call, not the add function itself. The proper equivalent would be to use: logger(add)(1, 2) so use the return value of logger() as the function to pass the 1, 2 arguments to. In other words, you need to...
Yes, that's a mistake. If you're not sure, let's test it: def fib(n): if n < 2: return 1 return fib(n-2) + fib(n-1) print(fib(10)) @cache def cfib(n): if n < 2: return 1 return cfib(n-2) + cfib(n-1) print(cfib(10)) The first one prints out 89, the second one aborts: File "rhcache.py",...
Intent of Decorator pattern: Attach additional responsibilities to an object dynamically. Decorators provide a flexible alternative to subclassing for extending functionality. So the clients of the decorator or the undecorated target has a need to see both of them through the same contract. Hence, adding more methods to a...
python,decorator,python-decorators
Your decorator line creates an instance of your class: @ClassIBuilt('1', MessageConverter, timeout=10) That instance is then used to do the actual decorating; you in effect do this: decorator = ClassIBuilt('1', MessageConverter, timeout=10) def testfcn(): # ... testfcn = decorator(testfcn) Because decorator is an instance of your class, the decorator(testfcn) call...
You need to do two things: Have myDecorator return the class object that it is passed: def myDecorator(cls): cls.dec_added_func = myFunction return cls Otherwise, the decorator will return None by default and you will get a TypeError whenever you do MyClass() for trying to call None. Make myFunction accept a...
angularjs,http,module,decorator,interceptor
Pretty sure this can't be solved just by separation using modules since as you've found the $http service is in the 'ng' module which is automatically included. When you inject $http you are getting the same instance that's defined in the 'ng' built-in module. Your best bet is probably to...
python,function,inheritance,override,decorator
You mean something like this: class Base(object): def load(self): print('do logic A') print('do logic B') class Child(Base): def load(self): super().load() print('do logic C') c = Child() c.load() This will print: do logic A do logic B do logic C The only other way I can think of is this one:...
python,garbage-collection,decorator
It is not the decorator that causes this problem. It is the fact that you store a method on the instance they are bound to. The decorator is only the means here, not the actual cause. Methods hold a reference to the instance in __self__, and you then created a...
retry is a decorator that can either be used without arguments or with. If you give it arguments it'll act as a decorator factory and return the actual decorator. Call that returned decorator: a = retry(stop_max_attempt_number=3)(a) as that is the equivalent of using retry() as a decorator: @retry(stop_max_attempt_number=3) def a():...
One approach is to define and use a sentinel object to denote "call the same decorated function now executing. I.e, before the def try_except, add: same = object() and in the body of the wrapper, after the try/except: if on_exception is not None: if on_exception is same: return decorator(func)(*args, **kwargs)...
collections,castle-windsor,decorator
As it turns out, Castle.Windsor cannot do what I'm looking for out of the box. I tried looking into creating a new resolver to handle this scenario, but didn't get very far. In the end, I restructured to use a true factory to decorate the classes. class PrinterModifierFactory : IPrinterModifierFactory...
You can have the decorator add a property to the request object, and then access that value in the context processor. For example, you can use the following decorator: def add_value(function): def wrap(request, *args, **kwargs): request.extra_value = True return function(request, *args, **kwargs) return wrap Then you can access it in...
python,decorator,python-decorators,python-magic
First of all, I suggest you do not do something like that. It's hard to get working code and very hard to make a correct version. Besides I don't really know what you want to do exactly. Should this decorator add a print statement after every assignment and show the...
javascript,json,angularjs,decorator
I have had this problem a number of times, and tried all of the solutions. In general, I will do the following: When it is something I may need to edit and send back, do not decorate, but instead use a separate list and lookup, like your #2 and #3....
c#,inversion-of-control,decorator,autofac
There are several ways to build your container in order to achieve what you need, you can use keyed services or lambdas. Lambdas tend to be a bit less error prone than using strings , so here is a simple container registration that does what you need: ContainerBuilder cbLambdas =...
python,decorator,python-decorators
What is the proper way to allow arguments in this simple wrapper? Thank you You need to pass the argument from my_function to wrapper, i.e.: def wrapper(x): If you want it to be able to handle many more functions generically then you'd have to do something like: def wrapper(*args,...
Use a list of IProcessor objects instead of a bunch of methods. Going this way you are able to add/skip/change call order. In your IProcessor declare Process(PerformanceContext context) method and implement PerformanceContext class to exchange some values like StartTime, NumberOfCalls etc. Good luck!...
You called the decorator here: get_text = p_decorate(get_text) Normally, a decorator replaces a function with another callable (another function, for example), or returns the original function but having registered information about it. But by changing the return value of p_decorate() to "1" rather than the function wrapper, you 'broke' get_text...
python,decorator,py.test,python-decorators
It seems py.test doesn't use the test fixtures when evaluating the expression for skipif. By your example, test_ios is actually successful because it is comparing the function platform found in the module's namespace to the "ios" string, which evaluates to False hence the test is executed and succeeds. If pytest...
python,algorithm,decorator,python-decorators,rate-limiting
You can use a threading.Semaphore to count and block the requests that are exceeding the limit, in combination with threading.Timer to schedule a function that releases the semaphore. from threading import Semaphore, Timer from functools import wraps def ratelimit(limit, every): def limitdecorator(fn): semaphore = Semaphore(limit) @wraps(fn) def wrapper(*args, **kwargs): semaphore.acquire()...
You cannot register bound methods until you have an instance for the method to be bound to. A function decorator alone does not have the context to detect when an instance has been created. You could use a metaclass / decorator combined approach instead: class ObservingMeta(type): def __call__(cls, *args, **kw):...
Use functools.wraps: from functools import wraps def decorate(func): @wraps(func) def wrapper(*args, **kwargs): return func(*args, **kwargs) return wrapper @decorate def test(a=1,b=2): return a+b print test.__name__ ...
If your decorator can only work on methods (because you need access to the instance-specific lock) then just include self in the wrapper signature: from functools import wraps def decobj(func): @wraps(func) def wrapper(self, *args, **kwards): with self.lock: print 'Got the lock' func(self, *args, **kwards) return wrapper I included the @functools.wraps()...
then you use the special keywoard "@func_name" in order to pass the next line of arguments into the function That's not how decorators work. You can pass arguments to a decorator like this @c("of python") def decorate_this_func(): pass But for that to work you need to tweak your decorator...
django,decorator,login-control
I solved in a simple way, I do not know if it's the most efficient, but it worked. views def protected_message(request): return render(request, 'bands/protected_message.html') url url(r'^accounts/login/$', 'protected_message'), menu template <li><a href="{% url 'admin:index' %}">Login</a></li> protected_message.html {% extends "base.html" %} {% block title %} <title>Protected</title> {% endblock title %} {% block...
I think you can just add the following import from flask import request to customlog.py. Here's the test code I used that worked. I just replaced logging.debug with a simple print statement for testing. from functools import wraps from flask import request def webLog(func): @wraps(func) def newFunc(*args, **kwargs): print request.url...
python,properties,decorator,init
For your first question , the answer is simple, x is an attribute of the class (not the object/instance of the class) , it would be evaluated when the class gets defined (not when its object is created). An Example to show this - >>> class CA: ... y =...
I think this does what you want: def validate_input(validation_fn_name): def validation_decorator(func): def validate_input_action(self, *args): error = getattr(self, validation_fn_name)(*args) if error is not None: raise error else: arglist = [self] + list(args) return func(*arglist) return validate_input_action return validation_decorator class Foo(object): def validate_length(self, arg1): if len(arg1) < 3: return ValueError('%r is too...
python,asynchronous,tornado,decorator,coroutine
Order matters because @asynchronous looks at the Future returned by @gen.coroutine, and calls finish for you when the coroutine returns. Since Tornado 3.1, the combination of @asynchronous and @gen.coroutine has been unnecessary and discouraged; in most cases you should use @gen.coroutine alone. However, the example you've shown here is kind...
.net,algorithm,caching,logging,decorator
These look to me to be the classic types of cross cutting concerns that Aspect-Oriented programming is intended to address. Cross cutting concerns span layers and tiers in the code but ideally you want to implement in one place in a non-intrusive manner. Aspect Oriented programming allows behaviour to be...
ruby-on-rails,ruby,design-patterns,module,decorator
I assume page_links would be a virtual attribute. Your code structure is complicated, and you can basically add page_links and page_links= methods to class Plugin with initialization, but if you want to keep this attribute in SomePluggin, you can do it in this way: module Cms class SomePluggin attr_accessor :page_links...
c#,unit-testing,decorator,simple-injector,open-generics
The detail available for the dependency graph has been greatly improved in 2.6. You can achieve the same thing with this code: [Fact] public void RegistersIHandleQuery_UsingOpenGenerics_WithDecorationChain() { var container = this.ContainerFactory(); var instance = container .GetInstance<IHandleQuery<FakeQueryWithoutValidator, string>>(); var registration = ( from currentRegistration in container.GetCurrentRegistrations() where currentRegistration.ServiceType == typeof(IHandleQuery<FakeQueryWithoutValidator, string>)...
If you want to make the "long" function call only once and decorate all three functions with the result, just do exactly that. my_patch = patch('somelongmodulename.somelongmodulefunction') @my_patch def test_a(patched): pass @my_patch def test_b(patched): pass ...