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Kevin Jacobs wrote:<br>
<blockquote type="cite"
cite="midPine.LNX.4.44.0306031330590.4071-100000@penguin.theopalgroup.com">
<pre wrap="">[Updated to include results from pgdb and pyPgSQL]
Due to the recent interest in PostgreSQL DB-API driver comparisons, I
thought I'd jump on the proverbial bandwagon. As some of you already know,
my company has developed very substantial financial applications using
Python, and frequently PostgreSQL.
We've been using the PsycoPg driver for the past two years, because we found
it to be the most solid and least flawed of all the available drivers at the
time. I've updated our driver suite to include a recent versions PoPy,
pgdb, and pyPgSQL, and then run one of our very substantial test suites.
The suite constitutes a mix the following tasks:
1) Many simple OLTP queries.
2) Many simple and complex OLAP queries, some returning as many as a
hundred thousand rows of data.
3) Data-cube construction and manipulation
4) Business report generation
The application server and database run on the same (otherwise quiescent)
test server, the working data set is all in-core (though quite large), and
only serial requests (i.e., only a single active worker thread) are issued.
Results running Python CVS on the same application server with only the
driver setting changed:
Driver / version Wall Time (average of 4 runs, though little variation was
---------------- --------- observed)
PsycoPg 1.0.13 10m41s
PoPy 2.0.8 11m33s [1]
pgdb 3.3 14m40s
pyPgSQL 2.3 >15m51s [2] Did not complete all tests!
Notes:
[1] Unfortunately, other than for this simple test suite, PoPy is basically
unusable for us. This is because it does not return proper PostgreSQL
type codes, only vague type strings ('NUMBER','DATETIME','MISSING'?!).
Thus, it does not provide enough information to distinguish, e.g.,
booleans from numbers, numeric from floating-point values, dates from
datetimes, etc. As previously reported, it does not translate large
integers correctly, and it mangles some date interval types. These
deficiencies may not affect simpler or less-demanding applications, but
to us they qualify as unacceptable information loss.
[2] pyPgSQL required several minor modifications to work properly. First,
the compile failed if LONG_LONG was not defined/detected. Second, it
returns a non-standard cursor.description with an extra element
indicating array status. While a potentially useful thing, it is very
very non-standard. Finally, the cursor descriptions use non-hashable
type codes, which caused problems for our OR-mapper. I modified the
type objects, adding an appropriate __hash__ method, and all was well.</pre>
</blockquote>
Kevin, what system did you compile pyPgSQL on? Setup.py tries to
detect if long long is supported on the system it is compiled on. If
it is detected, then the LONG_LONG definition from pyport.h (via
Python.h) is used. If long long support isn't detected, then it
doesn't compile in pgint8 support. I'm curious as to your configuration.<br>
<br>
In regards to the description, pyPgSQL adds a array indicator as an
eigth item. The symantics of the first seven items have not changed,
they match the DB-API specification. How is this <i>very</i>
non-standard and how would this break code using the descriptor
(descriptor[x][y] where x is the field (column) index and x is 0
through 6 will return what the DB-API 2.0 specification mandates)?<br>
<br>
You're right. PgTypes is not hashable. I never had a reason to have
it hashable before. It will be hashable in the next release (the hash
of a PgTypes will return the hash of the underlying type OID).<br>
<blockquote type="cite"
cite="midPine.LNX.4.44.0306031330590.4071-100000@penguin.theopalgroup.com">
<pre wrap=""> Once it was running, several test vectors failed deterministically with
the following error:
/usr/local/python-cvs/lib/python2.3/site-packages/pyPgSQL/PgSQL.py:
OperationalError: RelationForgetRelation: relation xxxxxxx is still open
</pre>
</blockquote>
I've never run across that error before. Were there perhaps multiple
threads sharing a connection? PostgreSQL's connections are not thread
safe and pyPgSQL does not support threads sharing a connection
(threadsafety == 1).<br>
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