How can I modify the test script above to avoid the error message when the script is run as shown (under Unix/bash
)?
You will need to prevent the script from writing anything to standard output. That means removing any print
statements and any use of sys.stdout.write
, as well as any code that calls those.
The reason this is happening is that you're piping a nonzero amount of output from your Python script to something which never reads from standard input. This is not unique to the :
command; you can get the same result by piping to any command which doesn't read standard input, such as
python testscript.py | cd .
Or for a simpler example, consider a script printer.py
containing nothing more than
print 'abcde'
Then
python printer.py | python printer.py
will produce the same error.
When you pipe the output of one program into another, the output produced by the writing program gets backed up in a buffer, and waits for the reading program to request that data from the buffer. As long as the buffer is nonempty, any attempt to close the writing file object is supposed to fail with an error. This is the root cause of the messages you're seeing.
The specific code that triggers the error is in the C language implementation of Python, which explains why you can't catch it with a try
/except
block: it runs after the contents of your script has finished processing. Basically, while Python is shutting itself down, it attempts to close stdout
, but that fails because there is still buffered output waiting to be read. So Python tries to report this error as it would normally, but sys.excepthook
has already been removed as part of the finalization procedure, so that fails. Python then tries to print a message to sys.stderr
, but that has already been deallocated so again, it fails. The reason you see the messages on the screen is that the Python code does contain a contingency fprintf
to write out some output to the file pointer directly, even if Python's output object doesn't exist.
Technical details
For those interested in the details of this procedure, let's take a look at the Python interpreter's shutdown sequence, which is implemented in the Py_Finalize
function of pythonrun.c
.
- After invoking exit hooks and shutting down threads, the finalization code calls
PyImport_Cleanup
to finalize and deallocate all imported modules. The next-to-last task performed by this function is removing the sys
module, which mainly consists of calling _PyModule_Clear
to clear all the entries in the module's dictionary - including, in particular, the standard stream objects (the Python objects) such as stdout
and stderr
.
- When a value is removed from a dictionary or replaced by a new value, its reference count is decremented using the
Py_DECREF
macro. Objects whose reference count reaches zero become eligible for deallocation. Since the sys
module holds the last remaining references to the standard stream objects, when those references are unset by _PyModule_Clear
, they are then ready to be deallocated.1
Deallocation of a Python file object is accomplished by the file_dealloc
function in fileobject.c
. This first invokes the Python file object's close
method using the aptly-named close_the_file
function:
ret = close_the_file(f);
For a standard file object, close_the_file(f)
delegates to the C fclose
function, which sets an error condition if there is still data to be written to the file pointer. file_dealloc
then checks for that error condition and prints the first message you see:
if (!ret) {
PySys_WriteStderr("close failed in file object destructor:
");
PyErr_Print();
}
else {
Py_DECREF(ret);
}
After printing that message, Python then attempts to display the exception using PyErr_Print
. That delegates to PyErr_PrintEx
, and as part of its functionality, PyErr_PrintEx
attempts to access the Python exception printer from sys.excepthook
.
hook = PySys_GetObject("excepthook");
This would be fine if done in the normal course of a Python program, but in this situation, sys.excepthook
has already been cleared.2 Python checks for this error condition and prints the second message as a notification.
if (hook && hook != Py_None) {
...
} else {
PySys_WriteStderr("sys.excepthook is missing
");
PyErr_Display(exception, v, tb);
}
After notifying us about the missing excepthook
, Python then falls back to printing the exception info using PyErr_Display
, which is the default method for displaying a stack trace. The very first thing this function does is try to access sys.stderr
.
PyObject *f = PySys_GetObject("stderr");
In this case, that doesn't work because sys.stderr
has already been cleared and is inaccessible.3 So the code invokes fprintf
directly to send the third message to the C standard error stream.
if (f == NULL || f == Py_None)
fprintf(stderr, "lost sys.stderr
");
Interestingly, the behavior is a little different in Python 3.4+ because the finalization procedure now explicitly flushes the standard output and error streams before builtin modules are cleared. This way, if you have data waiting to be written, you get an error that explicitly signals that condition, rather than an "accidental" failure in the normal finalization procedure. Also, if you run
python printer.py | python printer.py
using Python 3.4 (after putting parentheses on the print
statement of course), you don't get any error at all. I suppose the second invocation of Python may be consuming standard input for some reason, but that's a whole separate issue.
1Actually, that's a lie. Python's import mechanism caches a copy of each imported module's dictionary, which is not released until _PyImport_Fini
runs, later in the implementation of Py_Finalize
, and that's when the last references to the standard stream objects disappear. Once the reference count reaches zero, Py_DECREF
deallocates the objects immediately. But all that matters for the main answer is that the references are removed from the sys
module's dictionary and then deallocated sometime later.
2Again, this is because the sys
module's dictionary is cleared completely before anything is really deallocated, thanks to the attribute caching mechanism. You can run Python with the -vv
option to see all the module's attributes being unset before you get the error message about closing the file pointer.
3This particular piece of behavior is the only part that doesn't make sense unless you know about the attribute caching mechanism mentioned in previous footnotes.