If I have a class that wraps a resource, e.g., an sqlite database connection or a file, is there a way I can use the with statement to close the resource when my object goes out of scope or is gcollected?
To clarify what I mean, I want to avoid this:
class x:
def __init__(self):
# open resource
def close(self): # or __del__, even worst
# close resource
but make it in such a way that the resource is always freed as in
with open('foo') as f:
# use resource
You need to provide __enter__ and __exit__ methods. See PEP 343.
This PEP adds a new statement "with" to the Python language to make it
possible to factor out standard uses of try/finally statements.
In this PEP, context managers provide __enter__() and __exit__()
methods that are invoked on entry to and exit from the body of the
with statement.
Use contextlib.closing:
with contextlib.closing(thing) as thing:
do_stuff_with(thing)
# Thing is closed now.
You can always put any cleanup code you need into a class's __del__ method:
class x:
def __init__(self):
self.thing = get_thing()
def __del__(self):
self.thing.close()
But you shouldn't.
This is a bad idea, for a few reasons. If you're using CPython, having custom __del__ methods means the GC can't break reference cycles. If you're using most other Python implementations, __del__ methods aren't called at predictable times.
This is why you usually put cleanup in explicit close methods. That's the best you can do within the class itself. It's always up to the user of your class to make sure the close method gets called, not the class itself.
So, there's no way you can use a with statement, or anything equivalent, inside your class. But you can make it easier for users of your class to use a with statement, by making your class into a context manager, as described in roippi's answer, or just by suggesting they use contextlib.closing in your documentation.
Related
I am new to Python. I come from C++.
In some code reviews, I've had several peers wanting me to move things from init and del to a start and stop method. Most of them time, this goes against the RAII that was beaten into my head with decades of C++.
https://en.wikipedia.org/wiki/Resource_acquisition_is_initialization
Is RAII not a thing in Python?
Shouldn't it be?
After all, we can throw exceptions and we'd want to release resources when we do, no?
If it isn't. Can someone give some insight as to why things are done differently? Is there a language feature that I don't understand?
if I have:
class Poop:
def __init__:
# Get some Windows Resource
def __del__:
#Release some Windows Resource
def foo():
poop = Poop()
raise Exception("Poop happens")
The Windows Resource is released, right?
RAII works in C++ because destruction is deterministic.
In garbage collected languages like Python, your object could theoretically never be destroyed, even if you call del on it.
Anyway, the idiomatic way to handle resources in Python is not with RAII, nor with start/stop, but with context managers.
The simplest example is with a file object:
with open('this_file.txt') as f:
# ... do stuff with f ...
# ... back to code that doesn't touch f ...
The with statement is, more or less, a try-finally block that creates a resource and ensures that the resource is cleaned up when the block ends; something like this:
try:
f = open('this_file.txt')
# ... do stuff with f ...
finally:
f.close()
# ... back to code that doesn't touch f ...
I don't know Java, but I believe that the JVM also uses garbage collection, and similarly try-finally is an idiom for resource management in Java.
Anyway, the with statement takes a context manager, which is an instance of a class defining the __enter__ and __exit__ methods (see the docs).
For completeness, there may be cases where you want a context manager, but don't want to define a whole class just for that. In that case, contextlib may help.
A worked example; say you have a resource:
class Resource:
def method(self):
pass
get_resource = Resource
release_resource = lambda x: None
A RAII-like class might look something like this:
class RAIILike:
def __init__(self):
self.resource = get_resource()
def __del__(self):
release_resource(self.resource)
def do_complex_thing(self):
# do something complex with resource
pass
raii_thingy = RAIILike()
And you would use the resource like this:
raii_thingy.resource.method()
On the other hand, a context managed resource could look like this...
class ContextManagedResource:
def __enter__(self):
self._resource = get_resource()
return self._resource
def __exit__(self, exc_type, exc_value, traceback):
if exc_type is not None:
# handle exception here
pass
else:
pass
release_resource(self._resource)
return True
...and be used like this:
with ContextManagedResource() as res:
res.method()
Once the with block ends, the resource will be automatically released, regardless of whether the object that obtained it has been garbage collected.
Your own reference to wikipedia says:
Perl, Python (in the CPython implementation), and PHP manage
object lifetime by reference counting, which makes it possible to use
RAII. Objects that are no longer referenced are immediately destroyed
or finalized and released, so a destructor or finalizer can release
the resource at that time. However, it is not always idiomatic in such
languages, and is specifically discouraged in Python (in favor of
context managers and finalizers from the weakref package).
You can do RAII in python, or get pretty close. However, unlike C++ where you do the work in the constuctor and destructor, in python you need to use the dunder functions of enter and exit. This post has a excellent write up of how to write the functions and how they will behave in the presence of exceptions: https://preshing.com/20110920/the-python-with-statement-by-example/
I have an application with a ProcessPoolExecutor, to which I deliver an object instance that has a destructor implemented using the __del__ method.
The problem is, that the __del__ method deletes files from the disk, that are common to all the threads (processes). When a process in the pool finishes its job, it calls the __del__ method of the object it got and thus ruins the resources of the other threads (processes).
I tried to prepare a "safe" object, without a destructor, which I would use when submitting jobs to the pool:
my_safe_object = copy.deepcopy(my_object)
delattr(my_safe_object, '__del__')
But the delattr call fails with the following error:
AttributeError: __del__
Any idea how to get rid of the __del__ method of an existing object at runtime?
UPDATE - My solution:
Eventually I solved it using quite an elegant workaround:
class C:
def __init__(self):
self.orig_id = id(self)
# ... CODE ...
def __del__(self):
if id(self) != self.orig_id:
return
# .... CODE ....
So the field orig_id is only computed for the original object, where the constructor is really executed. The other object "clones" are created using a deep-copy, so their orig_id value will contain the id of the original object. Thus, when the clones are destroyed and call __del__, they will compare their own id with the original object id and will return, as the IDs will not match. Thus, only the original object will pass into executing __del__.
The best thing yo do there, if you have access to the object's class code, is not to rely on __del__ at all. The fact of __del__ having a permanent side-effect could be a problem by itself, but in an environment using multiprocessing it is definitively a no-go!
Here is why: first __del__ is a method that lies on the instance's class, as most "magic" methods (and that is why you can't delete it from an instance). Second: __del__ is called when references to an object reach zero. However, if you don't have any reference to an object on the "master" process, that does not mean all the child processes are over with it. This is likely the source of your problem: reference counting for objects are independent in each process. And third: you don't have that much control on when __del__ is called, even in a single process application. It is not hard to have a dangling reference to an object in a dictionary, or cache somewhere - so tying important application behavior to __del__ is normally discouraged. And all of this is only for recent Python versions (~ > 3.5), as prior to that, __del__ would be even more unreliable, and Python would not ensure it was called at all.
So, as the other answers put it, you could try snooze __del__ directly on the class, but that would have to be done on the object's class in all the sub-processes as well.
Therefore the way I recommend you to do this is to have a method to be explicitly called that will perform the file-erasing and other side-effects when disposing of an object. You simply rename your __del__ method and call it just on the main process.
If you want to ensure this "destructor" to be called,Python does offer some automatic control with the context protocol: you will then use your objects within a with statement block - and destroy it with inside an __exit__ method. This method is called automatically at the end of the with block. Of course, you will have to devise a way for the with block just to be left when work in the subprocess on the instance have finished. That is why in this case, I think an ordinary, explicit, clean-up method that would be called on your main process when consuming the "result" of whatever you executed off-process would be easier.
TL;DR
Change your source object's class clean-up code from __del__ to an ordinary method, like cleanup
On submitting your instances to off-process executing, call the clean-up in your main-process, by using the concurrent.futures.as_completed call.
In case you can't change the source code for the object's class, inherit it,
override __del__ with a no-op method, and force the object's __class__ atribute to the inherited class before submitting it to other processes:
class SafeObject(BombObject):
def __del__(self):
pass
def execute(obj):
# this function is executed in other process
...
def execute_all(obj_list):
executor = concurrent.futures.ProcessPoolExecutor(max_workers=XX)
with executor:
futures = {}
for obj in obj_list:
obj.__class__ = SafeObject
futures[executor.submit(execute, obj)] = obj
for future in concurrent.futures.as_completed(futures):
value = future.result() # add try/except aroudn this as needed.
BombClass.__del__(obj) # Or just restore the "__class__" if the isntances will be needed elsewhere
del futures # Needed to clean-up the extra references to the objects created in the futures dict.
(please note that the "with" statement above is from the recommended usage for ProcessPoolExecutor, from the docs, not for the custom __exit__ method I suggested you using earlier in the answer. Having a with block equivalent that will allow you to take full advantage of the ProcessPoolExecutor will require some ingenuity into it)
In general, methods belong to the class. While generally you can shadow a method on an instance, special "dunder" methods are optimized to check the class first regardless. So consider:
In [1]: class Foo:
...: def __int__(self):
...: return 42
...:
In [2]: foo = Foo()
In [3]: int(foo)
Out[3]: 42
In [4]: foo.__int__ = lambda self: 43
In [5]: int(foo)
Out[5]: 42
You can read more about this behavior in the docs
For custom classes, implicit invocations of special methods are only guaranteed to work correctly if defined on an object’s type, not in the object’s instance dictionary.
I think the cleanest solution if you are using multiprocessing is to simply derive from the class and override __del__. I fear that monkey-patching the class will not play nice with multiprocessing, unless you monkey patch the class in all the processes. Not sure how the pickleing will work out here.
I often see code that uses self to manage a context. For example
with self:
self.x = 4
self.y = 6
What's going on here? What does using self as a context allow?
Code that uses with self: suggests that whatever class you're using provides __enter__ and __exit__ methods. These methods create context. They can be convenient for setup / teardown in testing, etc.
What's going on here? What does using self as a context allow?
As long as the class has implemented the necessary "hooks" that a context manager should, Python allows it to be used like a normal context manager. Here is an excerpt from the docs which helps clear things up here:
Python’s with statement supports the concept of a runtime context defined by a context manager. This is implemented using a pair of methods that allow user-defined classes to define a runtime context that is entered before the statement body is executed and exited when the statement ends:
contextmanager.__enter__()
Enter the runtime context and return either this object or another object related to the runtime context. The value returned by this method is bound to the identifier in the as clause of with statements using this context manager.
[...]
contextmanager.__exit__(exc_type, exc_val, exc_tb)
Exit the runtime context and return a Boolean flag indicating if any exception that occurred should be suppressed. If an exception occurred while executing the body of the with statement, the arguments contain the exception type, value and traceback information. Otherwise, all three arguments are None.
[...]
As stated above, when you implement the necessary __enter__ and __exit__ magic methods for your class, Python allows you to treat it as a context manager.
If self is a context manager (i.e. has __enter__ and __exit__ methods) this will simply invoke that functionality, the same as it would if the instance were used in a with block outside the class.
There's nothing special happening here. self behaves the same way in a with block that anything else would. It calls __enter__ when you enter the scope and __exit__ when you leave the scope through any means. I can't imagine what using self here would accomplish, but if you can come up with some examples of where you've seen that, we might be able to provide a better answer.
I have a class that needs to run a TensorFlow session for each instance of the class, as long as that instance exists.
TensorFlow sessions use context managers, but I don't want to force anyone who uses my class to put my class into a context manager.
Is there any way to auto-close the session once the instance is no longer in use without using a context manager?
Can I just put in an __exit__ method and not an __enter__ method and start the session without the context manager and just close the session in the exit?
Is there any way to auto-close the session once the instance is no longer in use without using a context manager?
Not really, how would an object figure out when it’s no longer being used? If there was a safe way to do this, there wouldn’t be a need for context managers in the first place.
So you have to use context managers and the with statement to get this kind of feedback. But just because you have to use context managers, that does not mean that you actually need to have some separate “thing” you open. You can return anything in the __enter__ method, including the current object.
So the simplest context manager implementation that closes itself when the context is closed looks like this:
class MyClass:
def __enter__ (self):
return self
def __exit__ (self, *exc):
self.close()
def close (self):
# actually close the object
In fact, this pattern is so common, that there is a built-in recipe for this context manager: contextlib.closing. Using that, you do not actually need to modify your class at all, you can just wrap it in a closing() call and have it call close when the context is exited:
with closing(my_object):
my_object.do_something()
# my_object.close() is automatically called
You must define an __enter__ method, but you can just define it as:
def __enter__(self):
return self
and have the session defined in the init. Then, define __exit__ like so:
def __exit__(self, *exc):
self.close()
Then, define a close method that closes whatever resources were opened in __init__. (In my case, it's a TensorFlow session.)
This way, if the user decides to use the context manager, it will close it for them, and if they don't, they'll have to close it on their own.
Can someone explain why the following code behaves the way it does:
import types
class Dummy():
def __init__(self, name):
self.name = name
def __del__(self):
print "delete",self.name
d1 = Dummy("d1")
del d1
d1 = None
print "after d1"
d2 = Dummy("d2")
def func(self):
print "func called"
d2.func = types.MethodType(func, d2)
d2.func()
del d2
d2 = None
print "after d2"
d3 = Dummy("d3")
def func(self):
print "func called"
d3.func = types.MethodType(func, d3)
d3.func()
d3.func = None
del d3
d3 = None
print "after d3"
The output (note that the destructor for d2 is never called) is this (python 2.7)
delete d1
after d1
func called
after d2
func called
delete d3
after d3
Is there a way to "fix" the code so the destructor is called without deleting the method added? I mean, the best place to put the d2.func = None would be in the destructor!
Thanks
[edit] Based on the first few answers, I'd like to clarify that I'm not asking about the merits (or lack thereof) of using __del__. I tried to create the shortest function that would demonstrate what I consider to be non-intuitive behavior. I'm assuming a circular reference has been created, but I'm not sure why. If possible, I'd like to know how to avoid the circular reference....
You cannot assume that __del__ will ever be called - it is not a place to hope that resources are automagically deallocated. If you want to make sure that a (non-memory) resource is released, you should make a release() or similar method and then call that explicitly (or use it in a context manager as pointed out by Thanatos in comments below).
At the very least you should read the __del__ documentation very closely, and then you should probably not try to use __del__. (Also refer to the gc.garbage documentation for other bad things about __del__)
I'm providing my own answer because, while I appreciate the advice to avoid __del__, my question was how to get it to work properly for the code sample provided.
Short version: The following code uses weakref to avoid the circular reference. I thought I'd tried this before posting the question, but I guess I must have done something wrong.
import types, weakref
class Dummy():
def __init__(self, name):
self.name = name
def __del__(self):
print "delete",self.name
d2 = Dummy("d2")
def func(self):
print "func called"
d2.func = types.MethodType(func, weakref.ref(d2)) #This works
#d2.func = func.__get__(weakref.ref(d2), Dummy) #This works too
d2.func()
del d2
d2 = None
print "after d2"
Longer version:
When I posted the question, I did search for similar questions. I know you can use with instead, and that the prevailing sentiment is that __del__ is BAD.
Using with makes sense, but only in certain situations. Opening a file, reading it, and closing it is a good example where with is a perfectly good solution. You've gone a specific block of code where the object is needed, and you want to clean up the object and the end of the block.
A database connection seems to be used often as an example that doesn't work well using with, since you usually need to leave the section of code that creates the connection and have the connection closed in a more event-driven (rather than sequential) timeframe.
If with is not the right solution, I see two alternatives:
You make sure __del__ works (see this blog for a better
description of weakref usage)
You use the atexit module to run a callback when your program closes. See this topic for example.
While I tried to provide simplified code, my real problem is more event-driven, so with is not an appropriate solution (with is fine for the simplified code). I also wanted to avoid atexit, as my program can be long-running, and I want to be able to perform the cleanup as soon as possible.
So, in this specific case, I find it to be the best solution to use weakref and prevent circular references that would prevent __del__ from working.
This may be an exception to the rule, but there are use-cases where using weakref and __del__ is the right implementation, IMHO.
Instead of del, you can use the with operator.
http://effbot.org/zone/python-with-statement.htm
just like with filetype objects, you could something like
with Dummy('d1') as d:
#stuff
#d's __exit__ method is guaranteed to have been called
del doesn't call __del__
del in the way you are using removes a local variable. __del__ is called when the object is destroyed. Python as a language makes no guarantees as to when it will destroy an object.
CPython as the most common implementation of Python, uses reference counting. As a result del will often work as you expect. However it will not work in the case that you have a reference cycle.
d3 -> d3.func -> d3
Python doesn't detect this and so won't clean it up right away. And its not just reference cycles. If an exception is throw you probably want to still call your destructor. However, Python will typically hold onto to the local variables as part of its traceback.
The solution is not to depend on the __del__ method. Rather, use a context manager.
class Dummy:
def __enter__(self):
return self
def __exit__(self, type, value, traceback):
print "Destroying", self
with Dummy() as dummy:
# Do whatever you want with dummy in here
# __exit__ will be called before you get here
This is guaranteed to work, and you can even check the parameters to see whether you are handling an exception and do something different in that case.
A full example of a context manager.
class Dummy(object):
def __init__(self, name):
self.name = name
def __enter__(self):
return self
def __exit__(self, exct_type, exce_value, traceback):
print 'cleanup:', d
def __repr__(self):
return 'Dummy(%r)' % (self.name,)
with Dummy("foo") as d:
print 'using:', d
print 'later:', d
It seems to me the real heart of the matter is here:
adding the functions is dynamic (at runtime) and not known in advance
I sense that what you are really after is a flexible way to bind different functionality to an object representing program state, also known as polymorphism. Python does that quite well, not by attaching/detaching methods, but by instantiating different classes. I suggest you look again at your class organization. Perhaps you need to separate a core, persistent data object from transient state objects. Use the has-a paradigm rather than is-a: each time state changes, you either wrap the core data in a state object, or you assign the new state object to an attribute of the core.
If you're sure you can't use that kind of pythonic OOP, you could still work around your problem another way by defining all your functions in the class to begin with and subsequently binding them to additional instance attributes (unless you're compiling these functions on the fly from user input):
class LongRunning(object):
def bark_loudly(self):
print("WOOF WOOF")
def bark_softly(self):
print("woof woof")
while True:
d = LongRunning()
d.bark = d.bark_loudly
d.bark()
d.bark = d.bark_softly
d.bark()
An alternative solution to using weakref is to dynamically bind the function to the instance only when it is called by overriding __getattr__ or __getattribute__ on the class to return func.__get__(self, type(self)) instead of just func for functions bound to the instance. This is how functions defined on the class behave. Unfortunately (for some use cases) python doesn't perform the same logic for functions attached to the instance itself, but you can modify it to do this. I've had similar problems with descriptors bound to instances. Performance here probably isn't as good as using weakref, but it is an option that will work transparently for any dynamically assigned function with the use of only python builtins.
If you find yourself doing this often, you might want a custom metaclass that does dynamic binding of instance-level functions.
Another alternative is to add the function directly to the class, which will then properly perform the binding when it's called. For a lot of use cases, this would have some headaches involved: namely, properly namespacing the functions so they don't collide. The instance id could be used for this, though, since the id in cPython isn't guaranteed unique over the life of the program, you'd need to ponder this a bit to make sure it works for your use case... in particular, you probably need to make sure you delete the class function when an object goes out of scope, and thus its id/memory address is available again. __del__ is perfect for this :). Alternatively, you could clear out all methods namespaced to the instance on object creation (in __init__ or __new__).
Another alternative (rather than messing with python magic methods) is to explicitly add a method for calling your dynamically bound functions. This has the downside that your users can't call your function using normal python syntax:
class MyClass(object):
def dynamic_func(self, func_name):
return getattr(self, func_name).__get__(self, type(self))
def call_dynamic_func(self, func_name, *args, **kwargs):
return getattr(self, func_name).__get__(self, type(self))(*args, **kwargs)
"""
Alternate without using descriptor functionality:
def call_dynamic_func(self, func_name, *args, **kwargs):
return getattr(self, func_name)(self, *args, **kwargs)
"""
Just to make this post complete, I'll show your weakref option as well:
import weakref
inst = MyClass()
def func(self):
print 'My func'
# You could also use the types modules, but the descriptor method is cleaner IMO
inst.func = func.__get__(weakref.ref(inst), type(inst))
use eval()
In [1]: int('25.0')
---------------------------------------------------------------------------
ValueError Traceback (most recent call last)
<ipython-input-1-67d52e3d0c17> in <module>
----> 1 int('25.0')
ValueError: invalid literal for int() with base 10: '25.0'
In [2]: int(float('25.0'))
Out[2]: 25
In [3]: eval('25.0')
Out[3]: 25.0