util: add iterfile to workaround a fileobj.__iter__ issue with EINTR
The fileobj.__iter__ implementation in Python 2.7.12 (hg changeset
45d4cea97b04) is buggy: it cannot handle EINTR correctly.
In Objects/fileobject.c:
size_t Py_UniversalNewlineFread(....) {
....
if (!f->f_univ_newline)
return fread(buf, 1, n, stream);
....
}
According to the "fread" man page:
If an error occurs, or the end of the file is reached, the return value
is a short item count (or zero).
Therefore it's possible for "fread" (and "Py_UniversalNewlineFread") to
return a positive value while errno is set to EINTR and ferror(stream)
changes from zero to non-zero.
There are multiple "Py_UniversalNewlineFread": "file_read", "file_readinto",
"file_readlines", "readahead". While the first 3 have code to handle the
EINTR case, the last one "readahead" doesn't:
static int readahead(PyFileObject *f, Py_ssize_t bufsize) {
....
chunksize = Py_UniversalNewlineFread(
f->f_buf, bufsize, f->f_fp, (PyObject *)f);
....
if (chunksize == 0) {
if (ferror(f->f_fp)) {
PyErr_SetFromErrno(PyExc_IOError);
....
}
}
....
}
It means "readahead" could ignore EINTR, if "Py_UniversalNewlineFread"
returns a non-zero value. And at the next time "readahead" got executed, if
"Py_UniversalNewlineFread" returns 0, "readahead" would raise a Python error
without a incorrect errno - could be 0 - thus "IOError: [Errno 0] Error".
The only user of "readahead" is "readahead_get_line_skip".
The only user of "readahead_get_line_skip" is "file_iternext", aka.
"fileobj.__iter__", which should be avoided.
There are multiple places where the pattern "for x in fp" is used. This
patch adds a "iterfile" method in "util.py" so we can migrate our code from
"for x in fp" to "fox x in util.iterfile(fp)".
filterpyflakes: whitelist listcomp aliasing checking
The test change is because of how filterpyflakes is organized - a line
number changed.
verify: avoid shadowing two variables with a list comprehension
The variable names are clearly worse now, but since we're really just
transposing key and value I'm not too worried about the clarity loss.