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1.2 Intermezzo: Errors and Exceptions

An important convention throughout the Python interpreter is the following: when a function fails, it should set an exception condition and return an error value (usually a `NULL` pointer). Exceptions are stored in a static global variable inside the interpreter; if this variable is `NULL` no exception has occurred. A second global variable stores the ``associated value'' of the exception (the second argument to `raise`). A third variable contains the stack traceback in case the error originated in Python code. These three variables are the C equivalents of the Python variables `sys.exc_type`, `sys.exc_value` and `sys.exc_traceback` (see the section on module `sys` in the Python Library Reference). It is important to know about them to understand how errors are passed around.

The Python API defines a number of functions to set various types of exceptions.

The most common one is `PyErr_SetString()`. Its arguments are an exception object and a C string. The exception object is usually a predefined object like `PyExc_ZeroDivisionError`. The C string indicates the cause of the error and is converted to a Python string object and stored as the ``associated value'' of the exception.

Another useful function is `PyErr_SetFromErrno()`, which only takes an exception argument and constructs the associated value by inspection of the (Unix) global variable `errno`. The most general function is `PyErr_SetObject()`, which takes two object arguments, the exception and its associated value. You don't need to `Py_INCREF()` the objects passed to any of these functions.

You can test non-destructively whether an exception has been set with `PyErr_Occurred()`. This returns the current exception object, or `NULL` if no exception has occurred. You normally don't need to call `PyErr_Occurred()` to see whether an error occurred in a function call, since you should be able to tell from the return value.

When a function f that calls another function g detects that the latter fails, f should itself return an error value (e.g. `NULL` or `-1`). It should not call one of the `PyErr_*()` functions -- one has already been called by g. f's caller is then supposed to also return an error indication to its caller, again without calling `PyErr_*()`, and so on -- the most detailed cause of the error was already reported by the function that first detected it. Once the error reaches the Python interpreter's main loop, this aborts the currently executing Python code and tries to find an exception handler specified by the Python programmer.

(There are situations where a module can actually give a more detailed error message by calling another `PyErr_*()` function, and in such cases it is fine to do so. As a general rule, however, this is not necessary, and can cause information about the cause of the error to be lost: most operations can fail for a variety of reasons.)

To ignore an exception set by a function call that failed, the exception condition must be cleared explicitly by calling `PyErr_Clear()`. The only time C code should call `PyErr_Clear()` is if it doesn't want to pass the error on to the interpreter but wants to handle it completely by itself (e.g. by trying something else or pretending nothing happened).

Note that a failing `malloc()` call must be turned into an exception -- the direct caller of `malloc()` (or `realloc()`) must call `PyErr_NoMemory()` and return a failure indicator itself. All the object-creating functions (`PyInt_FromLong()` etc.) already do this, so only if you call `malloc()` directly this note is of importance.

Also note that, with the important exception of `PyArg_ParseTuple()` and friends, functions that return an integer status usually return a positive value or zero for success and `-1` for failure, like Unix system calls.

Finally, be careful to clean up garbage (by making `Py_XDECREF()` or `Py_DECREF()` calls for objects you have already created) when you return an error indicator!

The choice of which exception to raise is entirely yours. There are predeclared C objects corresponding to all built-in Python exceptions, e.g. `PyExc_ZeroDivisionError`, which you can use directly. Of course, you should choose exceptions wisely -- don't use `PyExc_TypeError` to mean that a file couldn't be opened (that should probably be `PyExc_IOError`). If something's wrong with the argument list, the `PyArg_ParseTuple()` function usually raises `PyExc_TypeError`. If you have an argument whose value must be in a particular range or must satisfy other conditions, `PyExc_ValueError` is appropriate.

You can also define a new exception that is unique to your module. For this, you usually declare a static object variable at the beginning of your file, e.g.

      static PyObject *SpamError;

and initialize it in your module's initialization function (`initspam()`) with an exception object, e.g. (leaving out the error checking for now):

      void
      initspam()
      {
          PyObject *m, *d;

          m = Py_InitModule("spam", SpamMethods);
          d = PyModule_GetDict(m);
          SpamError = PyErr_NewException("spam.error", NULL, NULL);
          PyDict_SetItemString(d, "error", SpamError);
      }

Note that the Python name for the exception object is `spam.error`. The `PyErr_NewException()` function may create either a string or class, depending on whether the "`-X`" flag was passed to the interpreter. If "`-X`" was used, `SpamError` will be a string object, otherwise it will be a class object with the base class being `Exception`, described in the Python Library Reference under ``Built-in Exceptions.''