def _determineCreditCoupon(self, session, order):
# get coupon/credit history of order
# XXX How is the refund amount distributed across the
# various items in an order?
refunds = []
creds = session.query(Refund)\
.filter_by(order_id = order.order_id)\
.options(eagerload("reason_category"),
eagerload("reason_subcategory")).all()
coups = session.query(Coupon)\
.filter_by(orig_order_id = order.order_id)\
.options(eagerload("reason_category"),
eagerload("reason_subcategory")).all()
for refs, kind in((creds, "credit"), (coups, "coupon")):
for ref in refs:
date = str(Date(ref.created))
total = formatDollars(ref.amount, self._determineCurrency(ref))
refunds.append("%s %s issued a %s %s (%s)" %
(date, ref.user.username, total, kind,
ref.comments or
ref.reason_subcategory or
ref.reason_category))
return refunds
def getData(self, session, params):
'''Get the order summary data based on the given parameters.'''
from web.htmlutil import Encryption
encrypt = Encryption().simple_encrypt
cube = DataCube()
data_tables = []
filters = params.filters
facts = params.get('facts', ['orders'] * len(params.dims))
# extras are additional facts that will display in columns to
# the right of the group by columns
extra = params.get('extra_cols', [])
# ratio data <A>_per_<B> computed from A and B, such that
# division of B occurs only after all A's are summed up
extra_facts = [e for e in extra if '_per_' not in e]
for i, dims in enumerate(params.dims):
fact = facts[i]
percent_dims = [d.endswith('_percent') for d in dims[1:]]
percent_cols = []
dims = [d.replace('_percent', '') for d in dims]
# main dimension used to title the table
row_dim = dims[0]
dim_name = ' '.join(s.title() for s in row_dim.split('_'))
data = odict({'title': fact.title(), 'row_name': dim_name,
'cols': [], 'rows': [], 'body': [], 'dims': dims})
if any(percent_dims):
data.title = '%s Percentages' % data.title.rstrip('s')
filter_str = ''
if filters:
filter_str = ';'.join(filters) + ';'
for d in sorted(cube.getData(session, [fact] + extra_facts,
dims, filters[:])):
#print d, '<br/>'
row_val = getattr(d, row_dim)
if row_val not in data.rows:
if not row_val: continue
data.rows.append(row_val)
data.body.append({row_dim: row_val, 'Total': 0,
'detail_params': {}})
row_filter_str = filter_str + "dc.%s == '%s'" % \
(dims[0], row_val)
for g, col_dim in enumerate(dims[1:]):
key = getattr(d, col_dim)
# grouping is to ensure proper column ordering
if len(data.cols) < g + 1:
data.cols.append([])
percent_cols.append([])
if key not in data.cols[g]:
data.cols[g].append(key)
percent_cols[g].append(percent_dims[g])
if key not in data.body[-1]:
data.body[-1][key] = 0
val = getattr(d, fact)
data.body[-1][key] += val
data.body[-1]['Total'] += val
p = row_filter_str + ";dc.%s == '%s'" % (dims[1], key)
data.body[-1]['detail_params'][key] = encrypt(p)
for e in extra:
if e not in data.body[-1]:
data.body[-1][e] = 0
if '_per_' in e:
# just numerator part of ratio data
num = e.split('_per_')[0]
data.body[-1][e] += getattr(d, num)
else:
data.body[-1][e] += getattr(d, e)
data.body[-1]['detail_params']['Total'] = \
encrypt(row_filter_str)
data.cols = [c for g in data.cols for c in g] # flatten cols
percent_cols = [c for g in percent_cols for c in g] # flatten cols
# only show total column if there are more than 1 col to sum
if len(data.cols) > 1:
data.cols.append('Total')
percent_cols.append(percent_cols[-1])
data.cols += extra
percent_cols += [False] * len(extra)
data.total_row = {'detail_params': {}}
# add 0 for missing values, populate total row and detail filters
for col in data.cols:
for row in data.body:
if col not in row:
row[col] = 0
data.total_row[col] = sum(row[col] for row in data.body)
if col not in extra:
p = filter_str + "dc.%s == '%s'" % (dims[1], col)
data.total_row['detail_params'][col] = encrypt(p)
# apply special formatting,
# divide denominator part of ratio data and percents
data.col_names = []
for i, col in enumerate(data.cols):
for row in data.body + [data.total_row]:
if '_per_' in col:
div = col.split('_per_')[1] + 's'
if div == fact:
row[col] /= Decimal(row.get('Total', 1) or 1)
else:
row[col] /= Decimal(row[div] or 1)
elif percent_cols[i]:
if col == 'Total':
div = Decimal(data.total_row['Total'])
else:
div = Decimal(row['Total'])
row[col] *= 100 / (div or 1)
if col.split('_per_')[0] in MONEY_FIELDS:
row[col] = formatDollars(row[col])
elif percent_cols[i] and row[col]:
row[col] = '%0.1f%%' % row[col]
elif isinstance(row[col], (float, Decimal)) and \
row[col] <> int(row[col]):
row[col] = '%0.4f' % row[col]
data.col_names.append(' '.join(s.replace('usd', '$').title()
for s in col.split('_')))
data_tables.append(data)
#for b in data_tables[0].body:
# print [(k, v) for k,v in b.items() if k <> 'detail_params'], '<br/>'
return data_tables
