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Added new_array_type() function
Allows the creation of a generic array typecaster from Python.
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NEWS
2
NEWS
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@ -1,6 +1,8 @@
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What's new in psycopg 2.4.3
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---------------------------
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- Added 'new_array_type()' function for easy creation of array
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typecasters.
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- Fixed segfault in case of transaction started with connection lost
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(and possibly other events).
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- Rollback connections in transaction or in error before putting them
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@ -216,6 +216,9 @@ read:
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>>> print type(point), point.x, point.y
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<class 'Point'> 10.2 20.3
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A typecaster created by `!new_type()` can be also used with
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`~psycopg2.extensions.new_array_type()` to create a typecaster converting a
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PostgreSQL array into a Python list.
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.. index::
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@ -290,7 +290,7 @@ details.
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.. function:: new_type(oids, name, adapter)
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Create a new type caster to convert from a PostgreSQL type to a Python
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object. The created object must be registered using
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object. The object created must be registered using
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`register_type()` to be used.
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:param oids: tuple of OIDs of the PostgreSQL type to convert.
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@ -309,6 +309,23 @@ details.
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See :ref:`type-casting-from-sql-to-python` for an usage example.
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.. function:: new_array_type(oids, name, base_caster)
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Create a new type caster to convert from a PostgreSQL array type to a list
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of Python object. The object created must be registered using
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`register_type()` to be used.
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:param oids: tuple of OIDs of the PostgreSQL type to convert. It should
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probably be the oid of the array type (e.g. the ``typarray`` field in
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the ``pg_type`` table.
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:param name: the name of the new type adapter.
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:param base_caster: a Psycopg typecaster, e.g. created using the
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`new_type()` function. The caster should be able to parse a single
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item of the desired type.
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.. versionadded:: 2.4.3
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.. function:: register_type(obj [, scope])
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Register a type caster created using `new_type()`.
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@ -57,7 +57,7 @@ except ImportError:
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pass
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from psycopg2._psycopg import adapt, adapters, encodings, connection, cursor, lobject, Xid
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from psycopg2._psycopg import string_types, binary_types, new_type, register_type
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from psycopg2._psycopg import string_types, binary_types, new_type, new_array_type, register_type
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from psycopg2._psycopg import ISQLQuote, Notify
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from psycopg2._psycopg import QueryCanceledError, TransactionRollbackError
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@ -257,7 +257,7 @@ psyco_connect(PyObject *self, PyObject *args, PyObject *keywds)
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" * `conn_or_curs`: A connection, cursor or None"
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#define typecast_from_python_doc \
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"new_type(oids, name, adapter) -> new type object\n\n" \
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"new_type(oids, name, castobj) -> new type object\n\n" \
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"Create a new binding object. The object can be used with the\n" \
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"`register_type()` function to bind PostgreSQL objects to python objects.\n\n" \
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":Parameters:\n" \
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@ -268,6 +268,15 @@ psyco_connect(PyObject *self, PyObject *args, PyObject *keywds)
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" the string representation returned by PostgreSQL (`!None` if ``NULL``)\n" \
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" and ``cur`` is the cursor from which data are read."
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#define typecast_array_from_python_doc \
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"new_array_type(oids, name, baseobj) -> new type object\n\n" \
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"Create a new binding object to parse an array.\n\n" \
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"The object can be used with `register_type()`.\n\n" \
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":Parameters:\n" \
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" * `oids`: Tuple of ``oid`` of the PostgreSQL types to convert.\n" \
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" * `name`: Name for the new type\n" \
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" * `baseobj`: Adapter to perform type conversion of a single array item."
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static void
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_psyco_register_type_set(PyObject **dict, PyObject *type)
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{
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@ -758,6 +767,8 @@ static PyMethodDef psycopgMethods[] = {
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METH_VARARGS, psyco_register_type_doc},
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{"new_type", (PyCFunction)typecast_from_python,
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METH_VARARGS|METH_KEYWORDS, typecast_from_python_doc},
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{"new_array_type", (PyCFunction)typecast_array_from_python,
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METH_VARARGS|METH_KEYWORDS, typecast_array_from_python_doc},
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{"AsIs", (PyCFunction)psyco_AsIs,
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METH_VARARGS, psyco_AsIs_doc},
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@ -603,6 +603,29 @@ typecast_from_python(PyObject *self, PyObject *args, PyObject *keywds)
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return typecast_new(name, v, cast, base);
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}
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PyObject *
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typecast_array_from_python(PyObject *self, PyObject *args, PyObject *keywds)
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{
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PyObject *values, *name = NULL, *base = NULL;
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typecastObject *obj = NULL;
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static char *kwlist[] = {"values", "name", "baseobj", NULL};
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if (!PyArg_ParseTupleAndKeywords(args, keywds, "O!O!O!", kwlist,
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&PyTuple_Type, &values,
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&Text_Type, &name,
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&typecastType, &base)) {
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return NULL;
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}
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if ((obj = (typecastObject *)typecast_new(name, values, NULL, base))) {
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obj->ccast = typecast_GENERIC_ARRAY_cast;
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obj->pcast = NULL;
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}
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return (PyObject *)obj;
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}
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PyObject *
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typecast_from_c(typecastObject_initlist *type, PyObject *dict)
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{
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@ -77,9 +77,11 @@ HIDDEN int typecast_add(PyObject *obj, PyObject *dict, int binary);
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/* the C callable typecastObject creator function */
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HIDDEN PyObject *typecast_from_c(typecastObject_initlist *type, PyObject *d);
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/* the python callable typecast creator function */
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/* the python callable typecast creator functions */
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HIDDEN PyObject *typecast_from_python(
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PyObject *self, PyObject *args, PyObject *keywds);
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HIDDEN PyObject *typecast_array_from_python(
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PyObject *self, PyObject *args, PyObject *keywds);
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/* the function used to dispatch typecasting calls */
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HIDDEN PyObject *typecast_cast(
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@ -285,6 +285,19 @@ class TypesBasicTests(unittest.TestCase):
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l1 = self.execute("select -%s;", (-1L,))
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self.assertEqual(1, l1)
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def testGenericArray(self):
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def caster(s, cur):
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if s is None: return "nada"
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return int(s) * 2
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base = psycopg2.extensions.new_type((23,), "INT4", caster)
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array = psycopg2.extensions.new_array_type((1007,), "INT4ARRAY", base)
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psycopg2.extensions.register_type(array, self.conn)
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a = self.execute("select '{1,2,3}'::int4[]")
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self.assertEqual(a, [2,4,6])
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a = self.execute("select '{1,2,NULL}'::int4[]")
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self.assertEqual(a, [2,4,'nada'])
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class AdaptSubclassTest(unittest.TestCase):
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def test_adapt_subtype(self):
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