def _process_sheet(self, tabular_data):
import db
repo = db.Repository('sqlite:///%s' % dbpath)
years = range(2002, 2011)
td = tabular_data
cells = td.data
title = cells[0][0]
table = db.PesaTable(title=title)
footnotes = []
for lastrow in reversed(cells):
if len(lastrow) > 2: # into the data
break
foot = lastrow[0].strip()
if foot:
footnotes.append(foot)
table.footnotes = simplejson.dumps(footnotes)
entries = {}
for row in cells[6:]:
if row[1]: # not a subheading or footnote
series_name = row[0]
for (year, cell) in zip(years, row[1:10]):
db.Expenditure(
title=series_name,
date=unicode(year),
amount=swiss.floatify(cell),
pesatable=table,
)
db.Session.flush()
def _process_sheet(self, tabular_data):
import db
repo = db.Repository('sqlite:///%s' % dbpath)
years = range(2002, 2011)
td = tabular_data
cells = td.data
title = cells[0][0]
table = db.PesaTable(title=title)
footnotes = []
for lastrow in reversed(cells):
if len(lastrow) > 2: # into the data
break
foot = lastrow[0].strip()
if foot:
footnotes.append(foot)
table.footnotes = simplejson.dumps(footnotes)
entries = {}
for row in cells[6:]:
if row[1]: # not a subheading or footnote
series_name = row[0]
for (year, cell) in zip(years, row[1:10]):
db.Expenditure(
title=series_name,
date=unicode(year),
amount=swiss.floatify(cell),
pesatable=table,
)
db.Session.flush()
def load(self):
'''
Looks like LA is very limited and is always associated with a given
"department" -- so this is really a classifier for the account
Simplest normalization:
* years
* dept FK
Expenditure
* subfunc
* year
* caporcur
* region: usuals ones ... (ID or Non-ID not needed ...)
* programme FK
# does the same programme ever occur within two differnet departments?
Programme
* department
Department?
What questions do i want to ask:
* Basically we want to browse in by facets
* Region, func, subfunc, ...
'''
import db
fp = cache.retrieve(url)
reader = csv.reader(open(fp))
# theoretically we'd have distributions to dept from CG as well ...
# acc = 'CG' acc = 'LA'
# dept -> account
# Tag accounts:
# subfunc
# Tags relate to other tags ...
repo = db.Repository(dburi)
# skip headings
reader.next()
_clean = lambda _str: unicode(_str.strip())
for count, row in enumerate(reader):
deptcode = _clean(row[0])
dept = _clean(row[1])
# have some blank rows at end
if not dept:
continue
function = _clean(row[2])
subfunction = _clean(row[3])
pog = _clean(row[4])
poga = _clean(row[5]) # take verbose one
# pog = row['Programme Object Group']
caporcur = _clean(row[7])
region = _clean(row[9])
exps = row[10:]
area = db.Area(title=poga,
deptcode=deptcode,
department=dept,
function=function,
subfunction=subfunction,
pog=pog,
cap_or_cur=caporcur,
region=region)
for ii, exp in enumerate(exps):
amount = swiss.floatify(exp)
if amount: # do not bother with null or zero amounts
area.expenditures.append(
db.Expenditure(amount=amount, year=2003 + ii))
if count % 5000 == 0:
print 'Completed: %s' % count
db.Session.commit()
db.Session.remove()
db.Session.commit()
def load(self):
"""
Looks like LA is very limited and is always associated with a given
"department" -- so this is really a classifier for the account
Simplest normalization:
* years
* dept FK
Expenditure
* subfunc
* year
* caporcur
* region: usuals ones ... (ID or Non-ID not needed ...)
* programme FK
# does the same programme ever occur within two differnet departments?
Programme
* department
Department?
What questions do i want to ask:
* Basically we want to browse in by facets
* Region, func, subfunc, ...
"""
import db
fp = cache.retrieve(url)
reader = csv.reader(open(fp))
# theoretically we'd have distributions to dept from CG as well ...
# acc = 'CG' acc = 'LA'
# dept -> account
# Tag accounts:
# subfunc
# Tags relate to other tags ...
repo = db.Repository(dburi)
# skip headings
reader.next()
_clean = lambda _str: unicode(_str.strip())
for count, row in enumerate(reader):
dept = _clean(row[1])
# have some blank rows at end
if not dept:
continue
subfunction = _clean(row[3])
pog = _clean(row[5]) # take verbose one
# pog = row['Programme Object Group']
caporcur = _clean(row[7])
region = _clean(row[9])
exps = row[10:]
area = db.Area(title=pog, department=dept, cap_or_cur=caporcur, region=region)
for ii, exp in enumerate(exps):
amount = swiss.floatify(exp)
if amount: # do not bother with null or zero amounts
area.expenditures.append(db.Expenditure(amount=amount, year=2003 + ii))
if count % 5000 == 0:
print "Completed: %s" % count
db.Session.commit()
db.Session.remove()
db.Session.commit()
