There's the README at
https://github.com/zzzeek/sqlalchemy/blob/master/README.dialects.rst which
also includes some links to an example dialect.

On Jan 9, 2018 12:35 PM, "Russ Wilson" <rpwil...@gmail.com> wrote:

Is there a good doc that covered at at min needs to be extended to create a
dialect?

On Mon, Jan 8, 2018 at 3:15 PM Mike Bayer <mike...@zzzcomputing.com> wrote:

> On Sun, Jan 7, 2018 at 9:07 PM, Russ Wilson <rpwil...@gmail.com> wrote:
> > I noticed if you use the cursor.fetchmany it returns the pyodbc types. Is
> > this an issue with the dialect?  if you use the connection execute you
> are
> > correct it returns a resultrow. Thanks for the help.
> >
> > cursor = connection.cursor()
> >     cursor.execute("SELECT *  FROM mytable")
> >     results_one = cursor.fetchmany(100)
> >     for row in results_one:
> >         print(type(row))
>
> It's not an issue, when you call SQLAlchemy's fetchmany(), it is
> internally retrieving the pyobc row objects and converting them to
> ResultRow objects.
>
> As I mentioned before, we have three dialects that use Pyodbc and two
> are production quality, same API, same row objects, etc.
>
>
>
> >
> >
> > On Sunday, January 7, 2018 at 12:01:29 PM UTC-6, Mike Bayer wrote:
> >>
> >>
> >>
> >> On Jan 7, 2018 11:29 AM, "Russ Wilson" <rpwi...@gmail.com> wrote:
> >>
> >> When I attempt to create a panda dataframe from the results it throws
> this
> >> error "Shape of passed values is (1, 100), indices imply (9, 100)"
> because
> >> it is seeing the results as 1 column vs a list of columns.  Ill take a
> look
> >> at the SQL Server one.   Thanks
> >>
> >>
> >> That has nothing to do with a SQLAlchemy dialect because all SQLAlchemy
> >> result sets come back as a ResultSet object and every row is a
> ResultRow.
> >> The pyodbc internals are not exposed.
> >>
> >>
> >>
> >> pd.DataFrame(data=data, columns=column_names)
> >>
> >>
> >>
> >> On Saturday, January 6, 2018 at 11:57:57 PM UTC-6, Mike Bayer wrote:
> >>>
> >>> pyodbc.Row acts like a tuple so there is no special conversion needed.
> >>>
> >>> SQLAlchemy has three pyodbc dialects, for SQL Server (very stable),
> >>> MySQL (sorta works), and Sybase (probably doesn't work), but you can
> >>> use the first two as examples for the basics.   They base off of the
> >>> PyODBCConnector in connectors/pyodbc.py.
> >>>
> >>>
> >>> On Sun, Jan 7, 2018 at 12:40 AM, Russ Wilson <rpwi...@gmail.com>
> wrote:
> >>> >
> >>> > I was attempting to create a new dialect but hit and issue.  pyodbc
> is
> >>> > returning a list of pyodbc.Row.  Is there a method i should be
> >>> > implementing
> >>> > to convert the list to a list of tuples.
> >>> >
> >>> > Thanks
> >>> >
> >>> > --
> >>> > SQLAlchemy -
> >>> > The Python SQL Toolkit and Object Relational Mapper
> >>> >
> >>> > http://www.sqlalchemy.org/
> >>> >
> >>> > To post example code, please provide an MCVE: Minimal, Complete, and
> >>> > Verifiable Example. See http://stackoverflow.com/help/mcve for a
> full
> >>> > description.
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> >>
> >> --
> >> SQLAlchemy -
> >> The Python SQL Toolkit and Object Relational Mapper
> >>
> >> http://www.sqlalchemy.org/
> >>
> >> To post example code, please provide an MCVE: Minimal, Complete, and
> >> Verifiable Example. See http://stackoverflow.com/help/mcve for a full
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> >>
> > --
> > SQLAlchemy -
> > The Python SQL Toolkit and Object Relational Mapper
> >
> > http://www.sqlalchemy.org/
> >
> > To post example code, please provide an MCVE: Minimal, Complete, and
> > Verifiable Example. See http://stackoverflow.com/help/mcve for a full
> > description.
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> --
> SQLAlchemy -
> The Python SQL Toolkit and Object Relational Mapper
>
> http://www.sqlalchemy.org/
>
> To post example code, please provide an MCVE: Minimal, Complete, and
> Verifiable Example.  See  http://stackoverflow.com/help/mcve for a full
> description.
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-- 
SQLAlchemy -
The Python SQL Toolkit and Object Relational Mapper

http://www.sqlalchemy.org/

To post example code, please provide an MCVE: Minimal, Complete, and
Verifiable Example. See http://stackoverflow.com/help/mcve for a full
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http://www.sqlalchemy.org/

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