Something like this?
import csv
reader = csv.reader(csvfile)
header = None
paints = {}
colorants = {}
for line in reader:
if not header: header = line
else:
row = dict([header[i],item) for i,item in enumerate(line)])
name = row['Color Name']
colorant = row['Colorant']
if not name in paints:
paints[name]=db.paint.insert(name=name)
if not colorant in colorants:
colorants[colorant]=db.colorant.insert(name=colorant)
db.paint_colorants.insert(paint_id=paints
[name],colorant_id=colorants[colorant])
On Jan 8, 4:10 am, Jason Brower <encomp...@gmail.com> wrote:
> I have data like this in a csv file....
> "Color Name", Base, Colorant, Amount, Colorant, Amount, Colorant,
> Amount, Colorant, Amount, Colorant, Amount
> "10 PORDRR",G,fo1,76,da1,32,ro1,111,yi1,1,,
> It is for a paint database.
> Is it at all possible to import that into this model?
> Normally I would just take a few minutes and do it by hand. But I have
> 14,000+ entries, so that's out of the question. Any ideas? In
> particular, how do you handle the variance in how many kinds of
> colorants are added. Notice in this example that is only 4 colorants,
> and 5+ could be in the page. (Currently from this extraction, only 5
> colorants and their amounts.
>
> db = SQLDB('sqlite://paint.sqlite')
>
> db.define_table('paint',
> Field('name', length=30, requires=IS_NOT_EMPTY(), unique=True),
> Field('base_coat', length=3, requires=IS_NOT_EMPTY()),
> Field('hex_color', length=6))
>
> db.define_table('colorant',
> Field('name', length=3, requires=IS_NOT_EMPTY()))
>
> db.define_table('paint_colorants',
> Field('paint_id', db.paint),
> Field('colorant_id', db.colorant),
> Field('units', 'integer'))
>
> db.paint_colorants.paint_id.requires=IS_IN_DB(db, 'paint.id',
> '%(name)s')
> db.paint_colorants.colorant_id.requires=IS_IN_DB(db, 'paint.id',
> '%(name)s')
>
> Best Regards,
> Jason Brower
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