Actually the ibm_db_sa support several methods to connect to iSeries;
natively through ibm_db, pyodbc, or jdbc (with jython).
On Jun 8, 2014 8:53 AM, "Cory Lutton" <cory.lut...@gmail.com> wrote:
> Thanks for such a quick reply. Great to hear that I am starting out on
> the right path with building a dialect, I have some work to do so I just
> wanted to make sure I wasn't missing something before I spend the time.
> Hopefully I can get things working enough where I can post it somewhere.
>
> I have looked at that IBM DB package, unfortunately the iSeries is a
> "remote" connection using ibm_db meaning I would have to get the Enterprise
> DB2 connect or get a special quote for unlimited.... makes me laugh a bit
> what the listed price is.
>
> On Saturday, June 7, 2014 5:48:02 PM UTC-7, Michael Bayer wrote:
>>
>>
>> On Jun 7, 2014, at 8:27 PM, Cory Lutton <cory....@gmail.com> wrote:
>>
>> I have been looking at using sqlalchemy in an internal company cherrypy
>> application I am working on. It will need to interface with my companies
>> iSeries server in order to use ERP data. I have been using pyodbc so far
>> and everything works great. I am thinking of adding access to another
>> database that is postgres. Rather than write that stuff again, I was
>> thinking about trying to use sqlalchemy. If I use that I would want to use
>> it for both....one for the iSeries (DB2) and one for postgres......
>>
>> So, I started writing a "dialect" for iseries+pyodbc and want to make
>> sure I am headed down the right path. It seems to be working so far....
>> import sqlalchemy as sa
>> import sqlalchemy_iseries
>> from urllib.parse import quote
>>
>> engine = sa.create_engine(
>> "iseries+pyodbc:///?odbc_connect={connect}".format(
>> connect=quote(connect)), pool_size=1)
>> con = engine.connect()
>>
>> # Only using like a pyodbc cursor, executing specifically created
>> statements.
>> rows = con.execute("SELECT * FROM alpha.r50all.lbmx")
>>
>> # Access via name like a dictionary rather than row.LBID
>> for row in rows:
>> print(row['LBID'])
>>
>> con.close()
>>
>> Being new to sqlalchemy I am hoping to get some advice on whether what I
>> am doing below is basically going in the right direction or point me in the
>> right direction if I am headed the wrong way (or reinventing something)
>> .....
>>
>> Here is what I have so far...
>>
>> *__init__.py:*
>> from sqlalchemy.dialects import registry
>> from . import pyodbc
>>
>> dialect = pyodbc.dialect
>>
>> registry.register("iseries.pyodbc", "sqlalchemy_iseries", "dialect")
>>
>> *base.py:*
>> from sqlalchemy.engine import default
>>
>> class ISeriesDialect(default.DefaultDialect):
>> name = 'iseries'
>> max_identifier_length = 128
>> schema_name = "qgpl"
>>
>>
>> *pyodbc.py:*
>> from .base import ISeriesDialect
>> from sqlalchemy.connectors.pyodbc import PyODBCConnector
>>
>> class ISeriesDialect_pyodbc(PyODBCConnector, ISeriesDialect):
>> pyodbc_driver_name = 'iSeries Access ODBC Driver'
>>
>> def _check_unicode_returns(self, connection):
>> return False
>>
>> dialect = ISeriesDialect_pyodbc
>>
>>
>>
>> looks great. if you want examples of the full format, take a look at
>> some of the existing external dialects at http://docs.sqlalchemy.org/
>> en/rel_0_9/dialects/index.html#external-dialects.
>>
>> Are you sure that the IBM DB SA dialect doesn’t cover this backend
>> already? They have support for pyodbc + DB2, but I’m not really sure how
>> “iSeries” differs. https://code.google.com/p/ibm-db/
>>
>>
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