Hi folks! As no one seems to answer my question in
stackoverflow(http://stackoverflow.com/questions/2303767/sqlalchemy-
checking-unicode-strings-validity-for-a-given-type-of-db-column), I'm
trying my luck here.
Am developing an extract-transform-load script with sqlalchemy.
Scenario is as follows:
* take 30+ mln text file (csv, tab-delimited or any other...).
* parse it and generate file, suitable for 'Load data infile'
mySQL import command (as described
http://dev.mysql.com/doc/refman/5.0/en/load-data.html
)
* From within script, disable MyISAM indexes, import file 'Load
data infile', recreate indexes.
The thing is that while parsing a text file, i'd like to check whether
the given string will be suitable for a given column's data
type(according to it's definition in mysql table), as it'd shame if
the 30 millionth row would contain a 50 symbol string while the mysql
column have been described as VARCHAR(49)...
I imagine the type checking could be implemented as follows:
types = [col.type for col in q.columns]
text = ['a','b','asdasd','','45.5','čąęąčę','2005-09-13 12:12:12']
if len(types)==len(text):
for i in range(len(types)):
assert(types[i].some_cool_type_checking_method(text[i]))
where some_cool_type_checking_method would be a simple method of the
sqlalchemy.dialects.mysql.base.(INTEGER|VARCHAR|etc) class, which
takes the string as an argument and returns True if the string "will
be accepted, according to the Column metadata retrieved from DB via
reflection and False, if the given string is for some reason
misformated(too many characters for a VARCHAR, mismatching charsets,
Float where the integer is expected, etc) for a given Db column.
some_cool_type_checking_method is something i would originaly expect,
but as from the public methods avialable for
sqlalchemy.dialects.mysql.base.(INTEGER|VARCHAR|etc) classes, i don't
seem to find a similar one. Of course it's naive to hope that
developers think the same way I do:) - so the question is how is this
type of type-checking implemented following SQLAlchemy best practices?
Thanks in advance for any ideas!
--
You received this message because you are subscribed to the Google Groups
"sqlalchemy" group.
To post to this group, send email to sqlalch...@googlegroups.com.
To unsubscribe from this group, send email to
sqlalchemy+unsubscr...@googlegroups.com.
For more options, visit this group at
http://groups.google.com/group/sqlalchemy?hl=en.
