I think I got it.
metadata = MetaData()
insp = reflection.Inspector.from_engine(engine)
for table_name in insp.get_table_names(self.db_schema):
columns = [col['name'] for col in insp.get_columns(table_name, self.
db_schema) if not isinstance(col['type'], IMAGE)]
Table(table_name, metadata, autoload=True, autoload_with=engine,
include_columns=columns)
Base = automap_base(metadata=metadata)
Base.prepare()
It's bit pain that reflection is done twice (first inspector then by
autoload in Table), but it does the job without ripping off SQLAlchemy
code.
Maybe if Table could accept output of insp.reflecttable it would be a way
to ease that.
Zzzeek, what do you think about it? Does it make sense?
On Thursday, December 10, 2015 at 10:57:03 AM UTC+1, mdob wrote:
>
> metadata = MetaData()
> metadata.reflect(engine)
>
> Base = automap_base(metadata=metadata)
> Base.prepare()
>
>
> That did a real nice job but I wanted to skip some columns from being
> mapped (binary types actually at the moment)
> I see metadata.tables['TableName'].columns to be ImmutableColumnCollection
> so there's probably no way to exclude column after reflect
>
> Is there a way to skip some columns from being reflected?
>
> Other option I can think of is
>
> insp = reflection.Inspector.from_engine(engine)
> and do the mapping to declarative manually.
>
> Any thoughts on that?
>
>
>
>
>
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