From: | Heikki Linnakangas <hlinnaka(at)iki(dot)fi> |
---|---|
To: | Nikita Glukhov <n(dot)gluhov(at)postgrespro(dot)ru>, David Steele <david(at)pgmasters(dot)net>, Haozhou Wang <hawang(at)pivotal(dot)io>, Anthony Bykov <a(dot)bykov(at)postgrespro(dot)ru> |
Cc: | pgsql-hackers(at)postgresql(dot)org, Paul Guo <pguo(at)pivotal(dot)io>, Hubert Zhang <hzhang(at)pivotal(dot)io> |
Subject: | Re: [PATCH] Add missing type conversion functions for PL/Python |
Date: | 2018-07-11 18:03:00 |
Message-ID: | 2b1ed3ca-288f-3d60-2d2a-93332a9b2aa8@iki.fi |
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Lists: | pgsql-hackers |
On 26/03/18 19:07, Nikita Glukhov wrote:
> Attached fixed 3th version of the patch:
Thanks, I'm reviewing this now. Nice speedup!
There is no test coverage for some of the added code. You can get a code
coverage report with:
./configure --enable-coverage ...
make
make -C src/pl/plpython check
make coverage-html
That produces a code coverage report in coverage/index.html. Please look
at the coverage of the new functions, and add tests to
src/pl/plpython/sql/plpython_types.sql so that all the new code is covered.
In some places, where you've already checked the object type e.g. with
PyFloat_Check(), I think you could use the less safe variants, like
PyFloat_AS_DOUBLE() instead of PyFloat_AsDouble(). Since this patch is
all about performance, seems worth doing.
Some of the conversions seem a bit questionable. For example:
> /*
> * Convert a Python object to a PostgreSQL float8 datum directly.
> * If can not convert it directly, fallback to PLyObject_ToScalar
> * to convert it.
> */
> static Datum
> PLyObject_ToFloat8(PLyObToDatum *arg, PyObject *plrv,
> bool *isnull, bool inarray)
> {
> if (plrv == Py_None)
> {
> *isnull = true;
> return (Datum) 0;
> }
>
> if (PyFloat_Check(plrv) || PyInt_Check(plrv) || PyLong_Check(plrv))
> {
> *isnull = false;
> return Float8GetDatum((double)PyFloat_AsDouble(plrv));
> }
>
> return PLyObject_ToScalar(arg, plrv, isnull, inarray);
> }
The conversion from Python int to C double is performed by
PyFloat_AsDouble(). But there's no error checking. And wouldn't
PyLong_AsDouble() be more appropriate in that case, since we already
checked the python type?
- Heikki
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