Added new_array_type() function

Allows the creation of a generic array typecaster from Python.
This commit is contained in:
Daniele Varrazzo 2011-09-22 15:08:53 +01:00
parent 6c8051907c
commit e3054ac9f3
8 changed files with 75 additions and 4 deletions

2
NEWS
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@ -1,6 +1,8 @@
What's new in psycopg 2.4.3
---------------------------
- Added 'new_array_type()' function for easy creation of array
typecasters.
- Fixed segfault in case of transaction started with connection lost
(and possibly other events).
- Rollback connections in transaction or in error before putting them

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@ -216,6 +216,9 @@ read:
>>> print type(point), point.x, point.y
<class 'Point'> 10.2 20.3
A typecaster created by `!new_type()` can be also used with
`~psycopg2.extensions.new_array_type()` to create a typecaster converting a
PostgreSQL array into a Python list.
.. index::

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@ -290,7 +290,7 @@ details.
.. function:: new_type(oids, name, adapter)
Create a new type caster to convert from a PostgreSQL type to a Python
object. The created object must be registered using
object. The object created must be registered using
`register_type()` to be used.
:param oids: tuple of OIDs of the PostgreSQL type to convert.
@ -309,6 +309,23 @@ details.
See :ref:`type-casting-from-sql-to-python` for an usage example.
.. function:: new_array_type(oids, name, base_caster)
Create a new type caster to convert from a PostgreSQL array type to a list
of Python object. The object created must be registered using
`register_type()` to be used.
:param oids: tuple of OIDs of the PostgreSQL type to convert. It should
probably be the oid of the array type (e.g. the ``typarray`` field in
the ``pg_type`` table.
:param name: the name of the new type adapter.
:param base_caster: a Psycopg typecaster, e.g. created using the
`new_type()` function. The caster should be able to parse a single
item of the desired type.
.. versionadded:: 2.4.3
.. function:: register_type(obj [, scope])
Register a type caster created using `new_type()`.

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@ -57,7 +57,7 @@ except ImportError:
pass
from psycopg2._psycopg import adapt, adapters, encodings, connection, cursor, lobject, Xid
from psycopg2._psycopg import string_types, binary_types, new_type, register_type
from psycopg2._psycopg import string_types, binary_types, new_type, new_array_type, register_type
from psycopg2._psycopg import ISQLQuote, Notify
from psycopg2._psycopg import QueryCanceledError, TransactionRollbackError

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@ -257,7 +257,7 @@ psyco_connect(PyObject *self, PyObject *args, PyObject *keywds)
" * `conn_or_curs`: A connection, cursor or None"
#define typecast_from_python_doc \
"new_type(oids, name, adapter) -> new type object\n\n" \
"new_type(oids, name, castobj) -> new type object\n\n" \
"Create a new binding object. The object can be used with the\n" \
"`register_type()` function to bind PostgreSQL objects to python objects.\n\n" \
":Parameters:\n" \
@ -268,6 +268,15 @@ psyco_connect(PyObject *self, PyObject *args, PyObject *keywds)
" the string representation returned by PostgreSQL (`!None` if ``NULL``)\n" \
" and ``cur`` is the cursor from which data are read."
#define typecast_array_from_python_doc \
"new_array_type(oids, name, baseobj) -> new type object\n\n" \
"Create a new binding object to parse an array.\n\n" \
"The object can be used with `register_type()`.\n\n" \
":Parameters:\n" \
" * `oids`: Tuple of ``oid`` of the PostgreSQL types to convert.\n" \
" * `name`: Name for the new type\n" \
" * `baseobj`: Adapter to perform type conversion of a single array item."
static void
_psyco_register_type_set(PyObject **dict, PyObject *type)
{
@ -758,6 +767,8 @@ static PyMethodDef psycopgMethods[] = {
METH_VARARGS, psyco_register_type_doc},
{"new_type", (PyCFunction)typecast_from_python,
METH_VARARGS|METH_KEYWORDS, typecast_from_python_doc},
{"new_array_type", (PyCFunction)typecast_array_from_python,
METH_VARARGS|METH_KEYWORDS, typecast_array_from_python_doc},
{"AsIs", (PyCFunction)psyco_AsIs,
METH_VARARGS, psyco_AsIs_doc},

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@ -603,6 +603,29 @@ typecast_from_python(PyObject *self, PyObject *args, PyObject *keywds)
return typecast_new(name, v, cast, base);
}
PyObject *
typecast_array_from_python(PyObject *self, PyObject *args, PyObject *keywds)
{
PyObject *values, *name = NULL, *base = NULL;
typecastObject *obj = NULL;
static char *kwlist[] = {"values", "name", "baseobj", NULL};
if (!PyArg_ParseTupleAndKeywords(args, keywds, "O!O!O!", kwlist,
&PyTuple_Type, &values,
&Text_Type, &name,
&typecastType, &base)) {
return NULL;
}
if ((obj = (typecastObject *)typecast_new(name, values, NULL, base))) {
obj->ccast = typecast_GENERIC_ARRAY_cast;
obj->pcast = NULL;
}
return (PyObject *)obj;
}
PyObject *
typecast_from_c(typecastObject_initlist *type, PyObject *dict)
{

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@ -77,9 +77,11 @@ HIDDEN int typecast_add(PyObject *obj, PyObject *dict, int binary);
/* the C callable typecastObject creator function */
HIDDEN PyObject *typecast_from_c(typecastObject_initlist *type, PyObject *d);
/* the python callable typecast creator function */
/* the python callable typecast creator functions */
HIDDEN PyObject *typecast_from_python(
PyObject *self, PyObject *args, PyObject *keywds);
HIDDEN PyObject *typecast_array_from_python(
PyObject *self, PyObject *args, PyObject *keywds);
/* the function used to dispatch typecasting calls */
HIDDEN PyObject *typecast_cast(

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@ -285,6 +285,19 @@ class TypesBasicTests(unittest.TestCase):
l1 = self.execute("select -%s;", (-1L,))
self.assertEqual(1, l1)
def testGenericArray(self):
def caster(s, cur):
if s is None: return "nada"
return int(s) * 2
base = psycopg2.extensions.new_type((23,), "INT4", caster)
array = psycopg2.extensions.new_array_type((1007,), "INT4ARRAY", base)
psycopg2.extensions.register_type(array, self.conn)
a = self.execute("select '{1,2,3}'::int4[]")
self.assertEqual(a, [2,4,6])
a = self.execute("select '{1,2,NULL}'::int4[]")
self.assertEqual(a, [2,4,'nada'])
class AdaptSubclassTest(unittest.TestCase):
def test_adapt_subtype(self):