Thanks a lot for bearing with me.
explicit execution - uses a Connection, but will autocommit
conn = engine.connect()
conn.execute(insert into table (a, b, c) values (1, 2, 3))
I still want a clarification about the above case. When we use
explicit execution like the
Hi list,
I defined two tables, Users, Orders and Items, where Orders has a
foreign key user_id depending on User.id and Items has a foreign key
order_id on Order.id. I'd like to do eager loading when joining
these three tables by:
session.query(Users).join(Users.orders,
thank you very much michael, this is some kind of mind spinning sqla
expression !!
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Hi everyone, in my script I have to deal with a table whose number of
columns can change at runtime. Since I have no information about the
structure I will have to handle at a given moment, I would need to
change dynamically the mapping during the program. If I try to re-map
the table I obviously
Dear all,
I'm using the web.py framework, the documentation of which recommends to use
SqlAlchemy this way :
http://webpy.org/cookbook/sqlalchemy
Basically a load hook is loaded before the actual request is processed.
However :
1) They recommend to bind scoped_session at every request, which
On Jan 24, 2011, at 5:46 AM, bool wrote:
Thanks a lot for bearing with me.
explicit execution - uses a Connection, but will autocommit
conn = engine.connect()
conn.execute(insert into table (a, b, c) values (1, 2, 3))
I still want a clarification about the above
On Jan 24, 2011, at 6:55 AM, Massi wrote:
Hi everyone, in my script I have to deal with a table whose number of
columns can change at runtime. Since I have no information about the
structure I will have to handle at a given moment, I would need to
change dynamically the mapping during the
On Jan 24, 2011, at 7:17 AM, Franck wrote:
Dear all,
I'm using the web.py framework, the documentation of which recommends to use
SqlAlchemy this way :
http://webpy.org/cookbook/sqlalchemy
Basically a load hook is loaded before the actual request is processed.
However :
1) They
On Jan 24, 2011, at 5:54 AM, Joel Zhou wrote:
Hi list,
I defined two tables, Users, Orders and Items, where Orders has a
foreign key user_id depending on User.id and Items has a foreign key
order_id on Order.id. I'd like to do eager loading when joining
these three tables by:
yeah always send us the error message with these since otherwise we have to
replicate it , as this mapping looks entirely fine. it asks for a primaryjoin,
and additionally the id column, until 0.7.0 is released where this has been
fixed, is in terms of Node not Department so you have to
I am wanting to have SQLAlchemy pull the table schema from the database. I
have just started trying to work through Essential SQLAlchemy and believe that
I am using a syntax that is no longer supported in SQLAlchemy 0.6.6. This what
I have tried:
from sqlalchemy import MetaData,
I decided to try to get some reflection using SqlSoup on a MS SQL Server 2008
database.
This is a copy of my session with the DSN obfuscated.
from sqlalchemy.ext.sqlsoup import SqlSoup
engine1 = SqlSoup(mssql+pyodbc://mydsn)
valid_species = db.valid_species.all()
Traceback (most recent call
On Jan 24, 2011, at 5:45 PM, Mark Sharp wrote:
I am wanting to have SQLAlchemy pull the table schema from the database. I
have just started trying to work through Essential SQLAlchemy and believe
that I am using a syntax that is no longer supported in SQLAlchemy 0.6.6.
This what I have
that's weird since I don't have that issue testing against a 2008 database. I
can't actually reproduce it. You might want to try ensuring you're on a recent
Pyodbc build.
You can also try this:
from sqlalchemy import create_engine
from sqlalchemy.ext.sqlsoup import SqlSoup
db =
Michael,
I had missed calling MetaData, but after making the call, I get the following
traceback.
from sqlalchemy import MetaData, create_engine, Table
meta = MetaData()
engine1 = create_engine(mssql+pyodbc://mydsn)
valid_species_table = Table(
... 'tf_valid_species', meta, autoload =
Michael,
pyodbc.version returns 2.1.8
I tried your code snippet with the same results.
I am going to try creating some tables and see how that goes.
Mark
R. Mark Sharp, Ph.D.
msh...@sfbr.orgmailto:msh...@sfbr.org
On Jan 24, 2011, at 6:33 PM, Michael Bayer wrote:
that's weird since I don't
Here's a script that runs fine for me on Windows as well as OSX using SQL
Server 2008 with pyodbc 2.1.4, I also tried 2.1.8 on OSX without issue (on OSX
you need to pass '' and not u''). Try it on yours, and if you continue to get
the NTEXT error you may have to report this issue to the pyodbc
This is the result that I received.
conn = pyodbc.connect(DSN=frankie-w7-animal-sa;UID=sa;PWD=select $ from
Bill)
cursor = conn.cursor()
cursor.execute(u
... SELECT [COLUMNS_1].[TABLE_SCHEMA],
... [COLUMNS_1].[TABLE_NAME],
... [COLUMNS_1].[COLUMN_NAME],
...
you have a trailing comma at the end of the statement.
its a long string probably easier to paste it into a .py file and run that.
On Jan 24, 2011, at 9:06 PM, Mark Sharp wrote:
This is the result that I received.
conn = pyodbc.connect(DSN=frankie-w7-animal-sa;UID=sa;PWD=select $ from
Michael,
Back to the same error.
import pyodbc
conn = pyodbc.connect('DSN=frankie-w7-animal-sa;UID=sa;PWD=select $ from
Bill')
cursor = conn.cursor()
cursor.execute(u
... SELECT [COLUMNS_1].[TABLE_SCHEMA],
... [COLUMNS_1].[TABLE_NAME],
... [COLUMNS_1].[COLUMN_NAME],
...
great. report it to pyodbc, since I have no idea what configuration you have
which would cause that:
http://groups.google.com/group/pyodbc
On Jan 24, 2011, at 9:31 PM, Mark Sharp wrote:
Michael,
Back to the same error.
import pyodbc
conn =
Hi does anyone know if is possible to declaratively concatenate two
columns together which you can later do query's on.
E.g. if I wanted to compute a new column course_name made up of
CONCAT(course_code,course_name)
Base = declarative_base()
class Course(Base):
__tablename__ = 'Course'
I'm using the declarative style and unable to to get a mapper to initialize.
Here's a simplified version of the class from client_transaction.py:
class ClientTransaction(Base):
__tablename__ = 'client_transactions'
id = Column(Integer, primary_key=True)
client_promotion_id =
Hey Royce,
This sounds like a job for composite columns:
http://www.sqlalchemy.org/docs/orm/mapper_config.html#composite-column-types
One gotcha that I ran into here is that you cannot have both the component
columns and the composite column mapped at the same time, like you do in
your example.
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