def calculate_net_worths(entries, options_map):
holdings_list, price_map = holdings.get_assets_holdings(
entries, options_map)
net_worths = []
for currency in options_map['operating_currency']:
# Convert holdings to a unified currency.
#
# Note: It's entirely possible that the price map does not have all
# the necessary rate conversions here. The resulting holdings will
# simply have no cost when that is the case. We must handle this
# gracefully below.
currency_holdings_list = holdings.convert_to_currency(
price_map, currency, holdings_list)
if not currency_holdings_list:
continue
aggregated_holdings_list = holdings.aggregate_holdings_by(
currency_holdings_list, lambda holding: holding.cost_currency)
aggregated_holdings_list = [
holding for holding in aggregated_holdings_list
if holding.currency and holding.cost_currency
]
# If after conversion there are no valid holdings, skip the currency
# altogether.
if not aggregated_holdings_list:
continue
net_worths.append((currency, aggregated_holdings_list[0].market_value))
return net_worths
def _net_worth_in_intervals(self, interval):
interval_tuples = self._interval_tuples(interval, self.entries)
interval_totals = []
end_dates = [p[1] for p in interval_tuples]
for (begin_date, end_date), holdings_list in \
zip(interval_tuples,
holdings_at_dates(self.entries, end_dates,
self.price_map, self.options)):
totals = {}
for currency in self.options['operating_currency']:
currency_holdings_list = \
holdings.convert_to_currency(self.price_map, currency,
holdings_list)
if not currency_holdings_list:
continue
holdings_ = holdings.aggregate_holdings_by(
currency_holdings_list,
operator.attrgetter('cost_currency'))
holdings_ = [holding
for holding in holdings_
if holding.currency and holding.cost_currency]
# If after conversion there are no valid holdings, skip the
# currency altogether.
if holdings_:
totals[currency] = holdings_[0].market_value
interval_totals.append({
'date': end_date - datetime.timedelta(1),
'totals': totals
})
return interval_totals
def generate_table(self, entries, errors, options_map):
holdings_list, price_map = holdings.get_assets_holdings(
entries, options_map)
holdings_list_orig = holdings_list
# Keep only the holdings where currency is the same as the cost-currency.
holdings_list = [
holding for holding in holdings_list
if (holding.currency == holding.cost_currency
or holding.cost_currency is None)
]
# Keep only those holdings held in one of the operating currencies.
if self.args.operating_only:
operating_currencies = set(options_map['operating_currency'])
holdings_list = [
holding for holding in holdings_list
if holding.currency in operating_currencies
]
# Compute the list of ignored holdings and optionally report on them.
if self.args.ignored:
ignored_holdings = set(holdings_list_orig) - set(holdings_list)
holdings_list = ignored_holdings
# Convert holdings to a unified currency.
if self.args.currency:
holdings_list = holdings.convert_to_currency(
price_map, self.args.currency, holdings_list)
return table.create_table(holdings_list, FIELD_SPEC)
def _net_worth_in_periods(self):
month_tuples = self._interval_tuples('month', self.entries)
monthly_totals = []
end_dates = [p[1] + timedelta(days=1) for p in month_tuples]
for (begin_date, end_date), holdings_list in zip(month_tuples,
holdings_at_dates(entries=self.entries,
dates=end_dates,
options_map=self.options,
price_map=self.price_map)):
totals = dict()
for currency in self.options['operating_currency']:
total = ZERO
for holding in holdings.convert_to_currency(self.price_map, currency, holdings_list):
if holding.cost_currency == currency and holding.market_value:
total += holding.market_value
if total != ZERO:
totals[currency] = total
monthly_totals.append({
'begin_date': begin_date,
'end_date': end_date,
'totals': totals
})
return monthly_totals
def _net_worth_in_periods(self):
month_tuples = self._interval_tuples('month', self.entries)
monthly_totals = []
end_dates = [p[1] + timedelta(days=1) for p in month_tuples]
for (begin_date, end_date), holdings_list in zip(
month_tuples,
holdings_at_dates(entries=self.entries,
dates=end_dates,
options_map=self.options,
price_map=self.price_map)):
totals = dict()
for currency in self.options['operating_currency']:
total = ZERO
for holding in holdings.convert_to_currency(
self.price_map, currency, holdings_list):
if holding.cost_currency == currency and holding.market_value:
total += holding.market_value
if total != ZERO:
totals[currency] = total
monthly_totals.append({
'begin_date': begin_date,
'end_date': end_date,
'totals': totals
})
return monthly_totals
def load_csv_and_prices(holdings_filename, prices_filename, currency):
"""Load the holdings and prices from filenames and convert to a common currency.
Args:
holdings_filename: A string, the name of a CSV file containing the list of Holdings.
prices_filename: A string, the name of a Beancount file containing price directives.
currency: A string, the target currency to convert all the holdings to.
Returns:
Two lists of holdings: a list in the original currencies, and a list all
converted to the target currency.
"""
# Load the price database.
# Generate with "bean-query LEDGER holdings"
price_entries, errors, options_map = loader.load(prices_filename)
price_map = prices.build_price_map(price_entries)
# Load the holdings list.
# Generate with "bean-query LEDGER print_prices"
mixed_holdings_list = list(
holdings_reports.load_from_csv(open(holdings_filename)))
# Convert all the amounts to a common currency (otherwise summing market
# values makes no sense).
holdings_list = holdings.convert_to_currency(price_map, currency,
mixed_holdings_list)
return mixed_holdings_list, holdings_list
def get_assets_holdings(entries, options_map, currency=None):
"""Return holdings for all assets and liabilities.
Args:
entries: A list of directives.
options_map: A dict of parsed options.
currency: If specified, a string, the target currency to convert all
holding values to.
Returns:
A list of Holding instances and a price-map.
"""
# Compute a price map, to perform conversions.
price_map = prices.build_price_map(entries)
# Get the list of holdings.
account_types = options.get_account_types(options_map)
holdings_list = holdings.get_final_holdings(
entries, (account_types.assets, account_types.liabilities), price_map)
# Convert holdings to a unified currency.
if currency:
holdings_list = holdings.convert_to_currency(price_map, currency,
holdings_list)
return holdings_list, price_map
def get_networth(entries, options_map, args):
net_worths = []
index = 0
current_entries = []
dtend = datetime.date.today()
period = rrule.rrule(rrule.MONTHLY, bymonthday=1, dtstart=args.min_date, until=dtend)
for dtime in period:
date = dtime.date()
# Append new entries until the given date.
while True:
entry = entries[index]
if entry.date >= date:
break
current_entries.append(entry)
index += 1
# Get the list of holdings.
raw_holdings_list, price_map = holdings.get_assets_holdings(current_entries,
options_map)
# Remove any accounts we don't in our final total
filtered_holdings_list = [n for n in raw_holdings_list if n.account not in args.ignore_account]
# Convert the currencies.
holdings_list = holdings.convert_to_currency(price_map,
args.currency,
filtered_holdings_list)
holdings_list = holdings.aggregate_holdings_by(
holdings_list, lambda holding: holding.cost_currency)
holdings_list = [holding
for holding in holdings_list
if holding.currency and holding.cost_currency]
# If after conversion there are no valid holdings, skip the currency
# altogether.
if not holdings_list:
continue
# TODO: How can something have a book_value but not a market_value?
value = holdings_list[0].market_value or holdings_list[0].book_value
net_worths.append((date, float(value)))
logging.debug("{}: {:,.2f}".format(date, value))
return pandas.Series(dict(net_worths))
def _holdings_to_net_worth(self, holdings_list):
totals = {}
for currency in self.options['operating_currency']:
currency_holdings_list = \
holdings.convert_to_currency(self.price_map, currency,
holdings_list)
holdings_ = holdings.aggregate_holdings_by(
currency_holdings_list,
operator.attrgetter('cost_currency'))
holdings_ = [holding
for holding in holdings_
if holding.currency and holding.cost_currency]
if holdings_:
totals[currency] = holdings_[0].market_value
else:
totals[currency] = 0
return totals
def _holdings_to_net_worth(self, holdings_list):
totals = {}
for currency in self.options['operating_currency']:
currency_holdings_list = \
holdings.convert_to_currency(self.price_map, currency,
holdings_list)
if not currency_holdings_list:
continue
holdings_ = holdings.aggregate_holdings_by(
currency_holdings_list,
operator.attrgetter('cost_currency'))
holdings_ = [holding
for holding in holdings_
if holding.currency and holding.cost_currency]
# If after conversion there are no valid holdings, skip the
# currency altogether.
if holdings_:
totals[currency] = holdings_[0].market_value
return totals
def generate_table(self, entries, errors, options_map):
holdings_list, price_map = get_assets_holdings(entries, options_map)
net_worths = []
for currency in options_map['operating_currency']:
# Convert holdings to a unified currency.
#
# Note: It's entirely possible that the price map does not have all
# the necessary rate conversions here. The resulting holdings will
# simply have no cost when that is the case. We must handle this
# gracefully below.
currency_holdings_list = holdings.convert_to_currency(
price_map, currency, holdings_list)
if not currency_holdings_list:
continue
holdings_list = holdings.aggregate_holdings_by(
currency_holdings_list, lambda holding: holding.cost_currency)
holdings_list = [
holding for holding in holdings_list
if holding.currency and holding.cost_currency
]
# If after conversion there are no valid holdings, skip the currency
# altogether.
if not holdings_list:
continue
net_worths.append((currency, holdings_list[0].market_value))
field_spec = [
(0, 'Currency'),
(1, 'Net Worth', '{:,.2f}'.format),
]
return table.create_table(net_worths, field_spec)
def _net_worth_in_periods(self):
month_tuples = self._interval_tuples('month', self.entries)
monthly_totals = []
end_dates = [p[1] for p in month_tuples]
for (begin_date, end_date), holdings_list in \
zip(month_tuples,
holdings_at_dates(self.entries, end_dates,
self.price_map, self.options)):
totals = {}
for currency in self.options['operating_currency']:
currency_holdings_list = \
holdings.convert_to_currency(self.price_map, currency,
holdings_list)
if not currency_holdings_list:
continue
holdings_list = holdings.aggregate_holdings_by(
currency_holdings_list,
operator.attrgetter('cost_currency'))
holdings_list = [holding
for holding in holdings_list
if holding.currency and holding.cost_currency]
# If after conversion there are no valid holdings, skip the
# currency altogether.
if holdings_list:
totals[currency] = holdings_list[0].market_value
monthly_totals.append({
'begin_date': begin_date,
'end_date': end_date,
'totals': totals
})
return monthly_totals
def main():
import argparse, logging
logging.basicConfig(level=logging.INFO,
format='%(levelname)-8s: %(message)s')
parser = argparse.ArgumentParser(description=__doc__.strip())
parser.add_argument('--min-date',
action='store',
type=lambda string: parse(string).date(),
help="Minimum date")
parser.add_argument('-o',
'--output',
action='store',
help="Save the figure to the given file")
parser.add_argument('--hide',
action='store_true',
help="Mask out the vertical axis")
parser.add_argument('--period',
choices=['weekly', 'monthly', 'daily'],
default='weekly',
help="Period of aggregation")
parser.add_argument('filename', help='Beancount input filename')
args = parser.parse_args()
entries, errors, options_map = loader.load_file(args.filename)
if args.min_date:
dtstart = args.min_date
else:
for entry in entries:
if isinstance(entry, data.Transaction):
dtstart = entry.date
break
net_worths_dict = collections.defaultdict(list)
index = 0
current_entries = []
dtend = datetime.date.today()
if args.period == 'weekly':
period = rrule.rrule(rrule.WEEKLY,
byweekday=rrule.FR,
dtstart=dtstart,
until=dtend)
elif args.period == 'monthly':
period = rrule.rrule(rrule.MONTHLY,
bymonthday=1,
dtstart=dtstart,
until=dtend)
elif args.period == 'daily':
period = rrule.rrule(rrule.DAILY, dtstart=dtstart, until=dtend)
for dtime in period:
date = dtime.date()
logging.info(date)
# Append new entries until the given date.
while True:
entry = entries[index]
if entry.date >= date:
break
current_entries.append(entry)
index += 1
# Get the list of holdings.
raw_holdings_list, price_map = holdings_reports.get_assets_holdings(
current_entries, options_map)
# Convert the currencies.
for currency in options_map['operating_currency']:
holdings_list = holdings.convert_to_currency(
price_map, currency, raw_holdings_list)
holdings_list = holdings.aggregate_holdings_by(
holdings_list, lambda holding: holding.cost_currency)
holdings_list = [
holding for holding in holdings_list
if holding.currency and holding.cost_currency
]
# If after conversion there are no valid holdings, skip the currency
# altogether.
if not holdings_list:
continue
net_worths_dict[currency].append(
(date, holdings_list[0].market_value))
# Extrapolate milestones in various currencies.
days_interp = 365
if args.period == 'weekly':
num_points = int(days_interp / 7)
elif args.period == 'monthly':
num_points = int(days_interp / 30)
elif args.period == 'daily':
num_points = 365
lines = []
today = datetime.date.today()
for currency, currency_data in net_worths_dict.items():
recent_data = currency_data[-num_points:]
dates = [time.mktime(date.timetuple()) for date, _ in recent_data]
values = [float(value) for _, value in recent_data]
poly = numpy.poly1d(numpy.polyfit(dates, values, 1))
logging.info("Extrapolations based on the last %s data points for %s:",
num_points, currency)
for amount in EXTRAPOLATE_WORTHS:
try:
date_reach = date.fromtimestamp(
(amount - poly.c[1]) / poly.c[0])
if date_reach < today:
continue
time_until = (date_reach - today).days / 365.
logging.info("%10d %s: %s (%.1f years)", amount, currency,
date_reach, time_until)
except OverflowError:
pass
logging.info("Time to save 1M %s: %.1f years", currency,
(1000000 / poly.c[0]) / (365 * 24 * 60 * 60))
dates = [today - datetime.timedelta(days=days_interp), today]
amounts = [
time.mktime(date.timetuple()) * poly.c[0] + poly.c[1]
for date in dates
]
lines.append((dates, amounts))
# Plot each operating currency as a separate curve.
for currency, currency_data in net_worths_dict.items():
dates = [date for date, _ in currency_data]
values = [float(value) for _, value in currency_data]
pyplot.plot(dates, values, '-', label=currency)
pyplot.tight_layout()
pyplot.title("Net Worth")
pyplot.legend(loc=2)
if args.hide:
pyplot.yticks([])
for dates, amounts in lines:
pyplot.plot(dates, amounts, 'k--')
# Output the plot.
if args.output:
pyplot.savefig(args.output, figsize=(11, 8), dpi=600)
pyplot.show()
def test_convert_to_currency(self, entries, _, __):
"""
2013-01-01 price CAD 1.1 USD
; We don't include a price point for NOK. It's unknown.
; 2013-01-01 open Assets:Account2
"""
test_holdings = list(itertools.starmap(holdings.Holding, [
# ------------ cost currency == target currency
# currency != target currency
(None, D('100.00'), 'IVV', D('200'), 'USD', D('10'), D('11'), D('12'), None),
# currency == target currency
(None, D('100.00'), 'USD', D('200'), 'USD', D('10'), D('11'), D('12'), None),
# currency == None
(None, D('100.00'), None, D('200'), 'USD', D('10'), D('11'), D('12'), None),
# ------------ cost currency == other currency
# cost currency available in price map
(None, D('100.00'), 'XSP', D('200'), 'CAD', D('10'), D('11'), D('12'), None),
# cost currency not available in price map
(None, D('100.00'), 'AGF', D('200'), 'NOK', D('10'), D('11'), D('12'), None),
# currency == target currency, available in price map
(None, D('100.00'), 'USD', D('200'), 'CAD', D('10'), D('11'), D('12'), None),
# currency == target currency, not available in price map
(None, D('100.00'), 'USD', D('200'), 'NOK', D('10'), D('11'), D('12'), None),
# cost currency available in price map, and currency == None
(None, D('100.00'), None, D('200'), 'CAD', D('10'), D('11'), D('12'), None),
# ------------ cost currency == None
# currency available in price map
(None, D('100.00'), 'CAD', D('1.2'), None, D('10'), D('11'), D('12'), None),
# currency available in price map, with no values (should be filled in)
(None, D('100.00'), 'CAD', D('1.2'), None, None, None, None, None),
# currency not available in price map
(None, D('100.00'), 'EUR', D('1.2'), None, D('10'), D('11'), D('12'), None),
# currency = target currency
(None, D('100.00'), 'USD', D('1.2'), None, D('10'), D('11'), D('12'), None),
]))
price_map = prices.build_price_map(entries)
converted_holdings = holdings.convert_to_currency(price_map, 'USD', test_holdings)
expected_holdings = list(itertools.starmap(holdings.Holding, [
(None, D('100.00'), 'IVV', D('200'), 'USD', D('10'), D('11'), D('12'), None),
(None, D('100.00'), 'USD', D('200'), 'USD', D('10'), D('11'), D('12'), None),
(None, D('100.00'), None, D('200'), 'USD', D('10'), D('11'), D('12'), None),
(None, D('100.00'), 'XSP', D('220.0'), 'USD', D('11.0'), D('12.1'), D('13.2'),
None),
(None, D('100.00'), 'AGF', None, None, None, None, None, None),
(None, D('100.00'), 'USD', D('220.0'), 'USD', D('11.0'), D('12.1'), D('13.2'),
None),
(None, D('100.00'), 'USD', None, None, None, None, None, None),
(None, D('100.00'), None, D('220.0'), 'USD', D('11.0'), D('12.1'), D('13.2'),
None),
(None, D('100.00'), 'CAD', D('1.32'), 'USD', D('11.0'), D('12.1'), D('13.2'),
None),
(None, D('100.00'), 'CAD', D('1.32'), 'USD', D('110.0'), D('110.0'), None,
None),
(None, D('100.00'), 'EUR', None, None, None, None, None, None),
(None, D('100.00'), 'USD', D('1.2'), 'USD', D('10'), D('11'), D('12'), None),
]))
self.assertEqual(expected_holdings, converted_holdings)
# Fail elegantly if the currency itself is None.
none_holding = holdings.Holding(None, D('100.00'), None, D('200'), None,
None, None, None, None)
with self.assertRaises(ValueError):
converted_holdings = holdings.convert_to_currency(price_map, 'USD',
[none_holding])
