Do files get closed during an exception exit?

Question

Do open files (and other resources) get automatically closed when the script exits due to an exception?

I\'m wondering if I need to be closing my resources during my

Answer 1

I, as well as other persons in this thread, are left with the question, "Well what is finally true?"

Now, supposing that files are left open in a premature program termination -- and there are a lot of such cases besides exceptions due to file handling -- the only safe way to avoid this, is to read the whole (or part of the) file into a buffer and close it. Then handle the contents in the buffer as needed. This is esp. the case for global search, changes, etc. that have to be done on the file. After changes are done, one can then write the whole buffer to the same or other file at once, avoiding the risk to leave the the newly created file open -- by doing a lot readings and writings -- which is the worst case of all!

Answer 2

A fairly straightforward question.

Two answers.

One saying, “Yes.”

The other saying, “No!”

Both with significant upvotes.

Who to believe? Let me attempt to clarify.

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Both answers have some truth to them, and it depends on what you mean by a file being closed.

First, consider what is meant by closing a file from the operating system’s perspective.

When a process exits, the operating system clears up all the resources that only that process had open. Otherwise badly-behaved programs that crash but didn’t free up their resources could consume all the system resources.

If Python was the only process that had that file open, then the file will be closed. Similarly the operating system will clear up memory allocated by the process, any networking ports that were still open, and most other things. There are a few exceptional functions like shmat that create objects that persist beyond the process, but for the most part the operating system takes care of everything.

Now, what about closing files from Python’s perspective? If any program written in any programming language exits, most resources will get cleaned up—but how does Python handle cleanup inside standard Python programs?

The standard CPython implementation of Python—as opposed to other Python implementations like Jython—uses reference counting to do most of its garbage collection. An object has a reference count field. Every time something in Python gets a reference to some other object, the reference count field in the referred-to object is incremented. When a reference is lost, e.g, because a variable is no longer in scope, the reference count is decremented. When the reference count hits zero, no Python code can reach the object anymore, so the object gets deallocated. And when it gets deallocated, Python calls the __del__() destructor.

Python’s __del__() method for files flushes the buffers and closes the file from the operating system’s point of view. Because of reference counting, in CPython, if you open a file in a function and don’t return the file object, then the reference count on the file goes down to zero when the function exits, and the file is automatically flushed and closed. When the program ends, CPython dereferences all objects, and all objects have their destructors called, even if the program ends due to an unhanded exception. (This does technically fail for the pathological case where you have a cycle of objects with destructors, at least in Python versions before 3.4.)

But that’s just the CPython implementation. Python the language is defined in the Python language reference, which is what all Python implementations are required to follow in order to call themselves Python-compatible.

The language reference explains resource management in its data model section:

Some objects contain references to “external” resources such as open files or windows. It is understood that these resources are freed when the object is garbage-collected, but since garbage collection is not guaranteed to happen, such objects also provide an explicit way to release the external resource, usually a close() method. Programs are strongly recommended to explicitly close such objects. The ‘try...finally‘ statement and the ‘with‘ statement provide convenient ways to do this.

That is, CPython will usually immediately close the object, but that may change in a future release, and other Python implementations aren’t even required to close the object at all.

So, for portability and because explicit is better than implicit, it’s highly recommended to call close() on everything that can be close()d, and to do that in a finally block if there is code between the object creation and close() that might raise an exception. Or to use the with syntactic sugar that accomplishes the same thing. If you do that, then buffers on files will be flushed, even if an exception is raised.

However, even with the with statement, the same underlying mechanisms are at work. If the program crashes in a way that doesn’t give Python’s __del__() method a chance to run, you can still end up with a corrupt file on disk:

#!/usr/bin/env python3.3

import ctypes

# Cast the memory adress 0x0001 to the C function int f()
prototype = ctypes.CFUNCTYPE(int)
f = prototype(1)

with open('foo.txt', 'w'):
    x.write('hi')
    # Segfault
    print(f())

This program produces a zero-length file. It’s an abnormal case, but it shows that even with the with statement resources won’t always necessarily be cleaned up the way you expect. Python tells the operating system to open a file for writing, which creates it on disk; Python writes hi into the C library’s stdio buffers; and then it crashes before the with statement ends, and because of the apparent memory corruption, it’s not safe for the operating system to try to read the remains of the buffer and flush them to disk. So the program fails to clean up properly even though there’s a with statement. Whoops. Despite this, close() and with almost always work, and your program is always better off having them than not having them.

So the answer is neither yes nor no. The with statement and close() are technically not necessary for most ordinary CPython programs. But not using them results in non-portable code that will look wrong. And while they are extremely helpful, it is still possible for them to fail in pathological cases.

Answer 3

No, they don't.

Use with statement if you want your files to be closed even if an exception occurs.

From the docs:

The with statement is used to wrap the execution of a block with methods defined by a context manager. This allows common try...except...finally usage patterns to be encapsulated for convenient reuse.

From docs:

 The with statement allows objects like files to be used in a way that ensures they are always cleaned up promptly and correctly.

with open("myfile.txt") as f:
    for line in f:
        print line,

After the statement is executed, the file f is always closed, even if a problem was encountered while processing the lines. Other objects which provide predefined clean-up actions will indicate this in their documentation.

Answer 4

Yes they do.

This is a CLIB (at least in cpython) and operating system thing. When the script exits, CLIB will flush and close all file objects. Even if it doesn't (e.g., python itself crashes) the operating system closes its resources just like any other process. It doesn't matter if it was an exception or a normal exit or even if its python or any other program.

Here's a script that writes a file and raises an exception before the file contents have been flushed to disk. Works fine:

~/tmp/so$ cat xyz.txt
cat: xyz.txt: No such file or directory
~/tmp/so$ cat exits.py
f = open("xyz.txt", "w")
f.write("hello")
print("file is", open("xyz.txt").read())
assert False

~/tmp/so$ python exits.py
('file is', '')
Traceback (most recent call last):
  File "exits.py", line 4, in <module>
    assert False
AssertionError
~/tmp/so$ cat xyz.txt
hello