I have an issue where, I believe due to floating-point representation
issues, reassigning the same value to a floating-point field causes
SQLAlchemy to think the value has been modified, and therefore emits a
gratuitous UPDATE. (This is particularly problematic when using the
versioning mixin,
http://docs.sqlalchemy.org/en/rel_0_8/orm/examples.html?highlight=versioned.)
This doesn't happen all the time, e.g. in the example below the problem
disappears if exp is imported from math rather than from numpy.ma.core. Am
I doing something wrong? If not, is there a way to tell SQLAlchemy that a
particular Float column (or even all Float columns) should not be
considered modified if the new and old values differ by less than some
threshold? Is there a way to provide a custom comparison function used for
this testing? Apologies if I missed something about this in the docs.
from sqlalchemy import Column, Integer, Float, create_engine
from sqlalchemy.ext.declarative import declarative_base
from sqlalchemy.orm import create_session
from numpy.ma.core import exp
sqlite = 'sqlite:///C:\\temp1.db'
engine = create_engine(sqlite, echo=True)
Base = declarative_base(bind=engine)
class A(Base):
__tablename__ = 'a'
id = Column(Integer, primary_key=True)
value = Column(Float)
if __name__ == '__main__':
x = exp(1.0)
print " x = %0.60f" % x
Base.metadata.drop_all()
Base.metadata.create_all()
session = create_session(bind=engine, autocommit=False)
a = A(id=1, value=x)
session.add(a)
session.commit()
print "a.value = %0.60f" % a.value
print "session.is_modified(a) = %s" % session.is_modified(a) # False
a.value = x
print "a.value = %0.60f" % a.value
print "session.is_modified(a) = %s" % session.is_modified(a) # True
session.commit() # UPDATE
session.close()
Thanks,
Seth
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