def round(self, cr, uid, currency, amount):
"""Return ``amount`` rounded according to ``currency``'s
rounding rules.
:param browse_record currency: currency for which we are rounding
:param float amount: the amount to round
:return: rounded float
"""
return float_round(amount, precision_rounding=currency.rounding)
def round(self, cr, uid, currency, amount):
"""Return ``amount`` rounded according to ``currency``'s
rounding rules.
:param browse_record currency: currency for which we are rounding
:param float amount: the amount to round
:return: rounded float
"""
return float_round(amount, precision_rounding=currency.rounding)
def _regularize_new_asset_depreciations(self, cr, uid, new_asset_id, context=None):
new_asset = self.pool.get('account.asset.asset').browse(cr, uid, new_asset_id, context)
line_to_update_ids = []
for line in new_asset.depreciation_line_ids:
if line.move_id:
value_field = line.depreciation_type == 'fiscal' and 'accelerated_value' or 'depreciation_value'
gap = line.move_id.amount - sum([getattr(l, value_field) for l in line.move_id.asset_depreciation_line_ids])
rounding = line.asset_id.currency_id.rounding
gap = float_round(gap, precision_digits=len(str(rounding).split('.')[-1]))
if gap > rounding:
# TODO: fix me
_logger.warning('Asset Split [new_asset_id=%s,line_id=%s,depreciation_type=%s] - Gap = %s > %s'
% (new_asset_id, line.id, line.depreciation_type, gap, rounding))
if gap:
line.write({'depreciation_value': line.depreciation_value + gap})
line_to_update_ids.append(line.id)
if line_to_update_ids:
self.pool.get('account.asset.depreciation.line')._store_set_values(cr, uid, line_to_update_ids, ['accelerated_value'], context)
def required_computation():
"""
Compute the average price of each week, store in a csv file,
and print the week that had the greatest relative spanself.
"""
# read with csv reader (handle bom and unicode)
try:
read_data = list(unicode_csv_dictreader('currency_daily_BTC_USD.csv'))
print 'Successfully read {} daily data.'.format(len(read_data))
except (KeyboardInterrupt, SystemExit):
raise
except:
print 'Failed to read data: {}'.format(traceback.format_exc())
read_data = []
# set the initial values
start_date = None
end_date = None
count = 0
sum = 0
max = 0
min = 0
greatest_relative_span = 0
flagged_start_date = None
flagged_end_date = None
from decimal import Decimal
from pandas import DataFrame
report = DataFrame()
for data in read_data:
date_str = str(data['timestamp'])
start_date = date_str
if end_date is None:
end_date = date_str
count += 1
price_today = Decimal(data['close (USD)'])
sum += price_today
if max == 0 or price_today > max:
max = price_today
if min == 0 or price_today < min:
min = price_today
if find_weekday(date_str) == 0:
average = float_round(sum / count, 8)
relative_span = float_round((max - min) / min, 8)
to_be_inserted = {
'start_date': [start_date],
'end_date': [end_date],
'average': [average],
'max': [max],
'min': [min],
'relative_span': [relative_span]
}
report = report.append(DataFrame(to_be_inserted))
if greatest_relative_span == 0 or relative_span > greatest_relative_span:
greatest_relative_span = relative_span
flagged_start_date = start_date
flagged_end_date = end_date
end_date = None
count = 0
sum = 0
max = 0
min = 0
# make sure the last week is taken into consideration
if find_weekday(date_str) != 0:
average = float_round(sum / count, 8)
relative_span = float_round((max - min) / min, 8)
to_be_inserted = {
'start_date': [start_date],
'end_date': [end_date],
'average': [average],
'max': [max],
'min': [min],
'relative_span': [relative_span]
}
report = report.append(DataFrame(to_be_inserted))
if relative_span > greatest_relative_span:
greatest_relative_span = relative_span
flagged_start_date = start_date
flagged_end_date = end_date
os.chdir('/usr/src/app/Reports')
report.to_csv('week_report.csv',
encoding='utf-8',
columns=[
'start_date', 'end_date', 'average', 'max', 'min',
'relative_span'
])
print(
'The greatest relative span happened in the week between {} and {} '
'with the span of {}.'.format(flagged_start_date, flagged_end_date,
greatest_relative_span))