Charles Waldman writes:
""" Problem description: Run the following script: import test.test_cpickle for x in xrange(1000000): reload(test.test_cpickle) Watch Python's memory use go up up and away! In the course of debugging this I also saw that cPickle is inconsistent with pickle - if you attempt a pickle.load or pickle.dump on a closed file, you get a ValueError, whereas the corresponding cPickle operations give an IOError. Since cPickle is advertised as being compatible with pickle, I changed these exceptions to match. """
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@ -2152,18 +2152,17 @@ newPicklerobject(PyObject *file, int bin) {
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else
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file=Pdata_New();
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self->file = file;
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UNLESS (self->file = file)
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goto err;
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UNLESS (self->memo = PyDict_New()) {
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Py_XDECREF((PyObject *)self);
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return NULL;
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}
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UNLESS (self->memo = PyDict_New())
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goto err;
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if (PyFile_Check(file)) {
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self->fp = PyFile_AsFile(file);
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if (self->fp == NULL) {
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PyErr_SetString(PyExc_IOError, "output file closed");
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return NULL;
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PyErr_SetString(PyExc_ValueError, "I/O operation on closed file");
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goto err;
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}
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self->write_func = write_file;
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}
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@ -4054,10 +4053,8 @@ newUnpicklerobject(PyObject *f) {
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self->safe_constructors = NULL;
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self->find_class = NULL;
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UNLESS (self->memo = PyDict_New()) {
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Py_XDECREF((PyObject *)self);
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return NULL;
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}
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UNLESS (self->memo = PyDict_New())
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goto err;
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Py_INCREF(f);
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self->file = f;
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@ -4066,8 +4063,8 @@ newUnpicklerobject(PyObject *f) {
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if (PyFile_Check(f)) {
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self->fp = PyFile_AsFile(f);
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if (self->fp == NULL) {
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PyErr_SetString(PyExc_IOError, "input file closed");
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return NULL;
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PyErr_SetString(PyExc_ValueError, "I/O operation on closed file");
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goto err;
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}
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self->read_func = read_file;
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self->readline_func = readline_file;
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