*With version 1.3:*
Base = declarative_base()
class User(Base):
__tablename__ = "user"
id = Column(Integer, primary_key=True)
name = Column(String)
Base.metadata.create_all(engine)
print(pd.__version__) # 1.3.2
print(sa.__version__) # 1.3.24
session = Session(engine)
My memory is failing me. I seem to recall that there was a succinct way to
get a 1.4/2.0 ORM query to return individual columns instead of ORM
objects. That is, to tell this
print(session.execute(select(User)).fetchall())
# [(<__main__.User object at 0x0090175EC700>,)]
to return the
On Tue, Aug 31, 2021, at 3:10 PM, Terrence-Monroe: Brannon wrote:
>
> Creating a pandas dataframe that contained descriptive column names formerly
> was as easy as:
>
> result_set = session.query(cls.column_1)
> df = pandas.Dataframe(result_set)
> print df.column_1
>
> but while this works
One option would be to replace
result_set = session.query(cls.column_1)
with
result_set = session.execute(select(cls.column_1)).mappings().all()
On Tuesday, August 31, 2021 at 1:10:17 PM UTC-6 thequie...@gmail.com wrote:
>
> Creating a pandas dataframe that contained descriptive column names
Creating a pandas dataframe that contained descriptive column names
formerly was as easy as:
result_set = session.query(cls.column_1)
df = pandas.Dataframe(result_set)
print df.column_1
but while this works in 1.3.20, in later versions of SA such as 1.4.19,
there is not enough column info
You want a combination of the "between" function/method:
https://docs.sqlalchemy.org/en/14/core/sqlelement.html#sqlalchemy.sql.expression.between
...and the "or_" function:
https://docs.sqlalchemy.org/en/14/core/sqlelement.html#sqlalchemy.sql.expression.or_
Something like this:
ranges = [(18,
this is true, the parameters can't be known to be passed along to a secondary
query. the approach here would require that you make careful use of custom
user options and events in order to make it work. the general event hook you
would use is documented at
issue https://github.com/sqlalchemy/sqlalchemy/issues/6963 is added to deal
with possibly multiple failure modes in this case.
On Tue, Aug 31, 2021, at 10:24 AM, Mike Bayer wrote:
> Hi -
>
> Your test case is omitting a critical detail which we would assume is you are
> using the
Hi -
Your test case is omitting a critical detail which we would assume is you are
using the "implicit_returning=False" flag on your create_engine().dont use
this flag as it serves no useful purpose and that will fix your issue here, we
will be deprecating and removing this flag.
will try
Hello All!! , I have a list of age ranges i.e 18-25, 40-55 and more how can
I make make a query using *SQLAlchemy* that will check if a Column is in
ranges [18,25] OR [40-55] OR [60-70]
Regards,Christos
--
SQLAlchemy -
The Python SQL Toolkit and Object Relational Mapper
Sorry, once again :)
class X(Base):
id: int = Column('x_id', Integer, primary_key=True, autoincrement=True)
a_id: int = Column('a_id', Integer, ForeignKey('a.a_id'))
a = relationship(A)
s = select(A).where(A.id == 1)
s = s.options(joinedload(A.b_filtered_rel))
or
s =
Hello Mike,
Thank you very much for your response.
I ended up with that, but i wanna ask you about this solution.
class A(Base):
id: int = Column('a_id', Integer, primary_key=True, autoincrement=True)
#descr
class B(Base):
id: int = Column('b_id', Integer, primary_key=True,
Hi group,
I am tring to migrate from version *1.3.24* to *1.4.23* of SqlAlchemy,
using *PostgreSQL 10*.
I found that the following code example works with 1.3, but triggers a
traceback with 1.4.
import sqlalchemy
session = ...
metadata = sqlalchemy.MetaData()
s_items =
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