def test_to_excel(example_ledger):
types, rows = run_query(
example_ledger.all_entries,
example_ledger.options,
'balances',
numberify=True)
assert excel.to_excel(types, rows, 'ods', 'balances')
def test_AnyMeta(self, entries, _, options_map):
"""
2016-11-20 *
name: "TheName"
address: "1 Wrong Way"
empty: "NotEmpty"
Assets:Banking 1 USD
color: "Green"
address: "1 Right Way"
empty:
"""
rtypes, rrows = query.run_query(entries, options_map,
'SELECT ANY_META("name") as m')
self.assertEqual([('TheName', )], rrows)
rtypes, rrows = query.run_query(entries, options_map,
'SELECT ANY_META("color") as m')
self.assertEqual([('Green', )], rrows)
rtypes, rrows = query.run_query(entries, options_map,
'SELECT ANY_META("address") as m')
self.assertEqual([('1 Right Way', )], rrows)
rtypes, rrows = query.run_query(entries, options_map,
'SELECT ANY_META("empty") as m')
self.assertEqual([(None, )], rrows)
def make_table(self):
"""An account tree based on matching regex patterns."""
cash = self.ledger.all_root_account.get('Assets')
credit = self.ledger.all_root_account.get('Liabilities')
_, wrows = query.run_query(
self.ledger.entries, self.ledger.options, '''
select account,number(only("USD", sum(position)))
from not "future" in tags
where account ~ "^(Assets|Liabilities)"
and (meta('_cleared') = True or number < 0)
group by 1''')
_, crows = query.run_query(
self.ledger.entries, self.ledger.options, '''
select account,number(only("USD", sum(position)))
from not "future" in tags
where account ~ "^(Assets|Liabilities)"
and (meta('_cleared') = True)
group by 1''')
_, trows = query.run_query(
self.ledger.entries, self.ledger.options, '''
select account,number(only("USD", sum(position)))
from not "future" in tags
where account ~ "^(Assets|Liabilities)"
group by 1''')
self.wrows = dict(wrows)
self.crows = dict(crows)
self.trows = dict(trows)
return [cash, credit]
def _wct(self, account_name):
if not account_name:
account_name = '^(Assets:|Liabilities:)'
_, wrow = query.run_query(
self.ledger.entries, self.ledger.options, '''
select number(only("USD", sum(position)))
where account = "{}"
and (meta('_cleared') = True or number < 0)
''', account_name)
if not wrow:
wrow = [[Decimal()]]
_, crow = query.run_query(
self.ledger.entries, self.ledger.options, '''
select number(only("USD", sum(position)))
where account = "{}"
and (meta('_cleared') = True)
''', account_name)
if not crow:
crow = [[Decimal()]]
_, trow = query.run_query(
self.ledger.entries, self.ledger.options, '''
select number(only("USD", sum(position)))
where account = "{}"
''', account_name)
if not trow:
trow = [[Decimal()]]
return wrow[0][0], crow[0][0], trow[0][0]
def test_GrepN(self, entries, _, options_map):
"""
2016-11-20 * "prev match in context next"
Assets:Banking 1 USD
"""
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT GREPN("in", narration, 0) as m
''')
self.assertEqual([('in', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT GREPN("match (.*) context", narration, 1) as m
''')
self.assertEqual([('in', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT GREPN("(.*) in (.*)", narration, 2) as m
''')
self.assertEqual([('context next', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT GREPN("ab(at)hing", "abathing", 1) as m
''')
self.assertEqual([('at', )], rrows)
def test_Date(self, entries, _, options_map):
"""
2016-11-20 * "ok"
Assets:Banking 1 USD
"""
rtypes, rrows = query.run_query(entries, options_map,
'SELECT date(2020, 1, 2) as m')
self.assertEqual([(datetime.date(2020, 1, 2), )], rrows)
rtypes, rrows = query.run_query(entries, options_map,
'SELECT date(year, month, 1) as m')
self.assertEqual([(datetime.date(2016, 11, 1), )], rrows)
with self.assertRaisesRegex(ValueError,
"day is out of range for month"):
rtypes, rrows = query.run_query(entries, options_map,
'SELECT date(2020, 2, 32) as m')
rtypes, rrows = query.run_query(entries, options_map,
'SELECT date("2020-01-02") as m')
self.assertEqual([(datetime.date(2020, 1, 2), )], rrows)
rtypes, rrows = query.run_query(entries, options_map,
'SELECT date("2016/11/1") as m')
self.assertEqual([(datetime.date(2016, 11, 1), )], rrows)
def test_to_csv(example_ledger):
types, rows = run_query(example_ledger.all_entries, example_ledger.options,
'balances', numberify=True)
assert excel.to_csv(types, rows)
types, rows = run_query(example_ledger.all_entries, example_ledger.options,
'select account, tags, date, day', numberify=True)
assert excel.to_csv(types, rows)
def test_to_csv(example_ledger):
types, rows = run_query(
example_ledger.all_entries,
example_ledger.options,
'balances',
numberify=True)
assert excel.to_csv(types, rows)
types, rows = run_query(
example_ledger.all_entries,
example_ledger.options,
'select account, tags, date, day',
numberify=True)
assert excel.to_csv(types, rows)
def test_to_csv(example_ledger: FavaLedger) -> None:
types, rows = run_query(
example_ledger.all_entries,
example_ledger.options,
"balances",
numberify=True,
)
assert excel.to_csv(types, rows)
types, rows = run_query(
example_ledger.all_entries,
example_ledger.options,
"select account, tags, date, day",
numberify=True,
)
assert excel.to_csv(types, rows)
def find_funds(self, price):
bql = "SELECT flag, filename, lineno, location, account, other_accounts, year, month, day, number, currency where account = \"{}\" and currency = \"CNY\" and number = {}".format(
FundAccount, price)
items = query.run_query(self.entries, self.option_map, bql)
# length = len(items[1])
feePrice = round(price * fee, 2)
for item in items[1]:
current_date = date(item.year, item.month, item.day)
date_string = current_date.strftime("%Y%m%d")
print('Updating ' + date_string)
for fund_item in fund_data:
if fund_item[0] == date_string:
fund_price = float(fund_item[1])
count = (price - feePrice) / fund_price
self.update_line_to_new_line(
item.location,
transactionTemplate.substitute(
fundAccount=FundAccount,
fundCount=round(count, 2),
fundCurrency=currency,
costPrice=round(fund_price, 5),
feeAccount=FeeAccount,
fee=feePrice,
deviationAccount=DeviationAccount,
otherAccount=item.other_accounts[0],
originalPrice=price), 1)
def get_allocations(entries, options_map, portfolio):
allocation_query = r"""
SELECT currency,
GETITEM(CURRENCY_META(currency), "asset-class") as c,
GETITEM(CURRENCY_META(currency), "asset-subclass") as s,
account,
getprice(currency, "{1}", today()) as price,
convert(value(sum(position)), "{1}") as market_value,
convert(cost(sum(position)), "{1}") as book_value,
GETITEM(OPEN_META(account), "asset-class") as act_class,
GETITEM(OPEN_META(account), "asset-subclass") as act_subclass
WHERE GETITEM(OPEN_META(account), "portfolio") = "{0}"
GROUP BY currency, c, s, account, price, act_class, act_subclass
"""
target_currency = options_map['operating_currency'][0]
rtypes, rrows = query.run_query(entries,
options_map,
allocation_query,
portfolio,
target_currency,
numberify=True)
allocations = Allocations()
for row in rrows:
position = _position_from_row(row)
allocations.append(position)
return allocations
def find_duplicate(self, entry, money, replace_account = ''):
bql = "SELECT flag, filename, lineno, location, account, year, month, day, str(entry_meta('timestamp')) as timestamp, metas() as metas WHERE year = {} AND month = {} AND day = {} AND number = {} AND currency = 'CNY' ORDER BY timestamp ASC".format(entry.date.year, entry.date.month, entry.date.day, -money)
items = query.run_query(self.entries, self.option_map, bql)
length = len(items[1])
if (length == 0):
return False
updated_items = []
for item in items[1]:
item_timestamp = item.timestamp.replace("'", '')
if (
(not 'timestamp' in entry.meta) or
item_timestamp == entry.meta['timestamp'] or
item.timestamp == 'None' or
item.timestamp == ''
):
updated_items.append(item)
if replace_account != '' and item.account in public_accounts:
self.update_transaction_account(item.location, item.account, replace_account)
for key, value in entry.meta.items():
if key == 'filename' or key == 'lineno':
continue
if not key in item.metas:
self.append_text_to_transaction(item.filename, item.lineno, '{}: "{}"'.format(key, value))
if 'timestamp' in entry.meta and item_timestamp == entry.meta['timestamp']:
break
if len(updated_items) > 1:
for item in updated_items:
self.update_transaction_flag(item.location, item.flag, '!')
return len(updated_items) > 0
def test_to_excel(example_ledger):
types, rows = run_query(
example_ledger.all_entries,
example_ledger.options,
"balances",
numberify=True,
)
assert excel.to_excel(types, rows, "ods", "balances")
def find_duplicate(self,
entry,
money,
unique_no=None,
replace_account='',
currency='CNY'):
# 要查询的是实际付款的账户，而不是支出信息
bql = "SELECT flag, filename, lineno, location, account, year, month, day, str(entry_meta('timestamp')) as timestamp, metas() as metas WHERE year = {} AND month = {} AND day = {} AND number(convert(units(position), '{}')) = {} ORDER BY timestamp ASC".format(
entry.date.year, entry.date.month, entry.date.day, currency, money)
items = query.run_query(self.entries, self.option_map, bql)
length = len(items[1])
if (length == 0):
return False
updated_items = []
for item in items[1]:
same_trade = False
item_timestamp = item.timestamp.replace("'", '')
# 如果已经被录入了，且unique_no相同，则判定为是同导入器导入的同交易，啥都不做
if unique_no != None:
if unique_no in entry.meta and unique_no in item.metas:
if item.metas[unique_no] == entry.meta[unique_no]:
same_trade = True
# unique_no存在但不同，那就绝对不是同一笔交易了
# 这个时候就直接返回不存在同订单
else:
continue
if same_trade:
return True
# 否则，可能是不同账单的同交易，此时判断时间
# 如果时间戳相同，或某个导入器的数据没有时间戳，则判断其为「还需进一步处理」的同笔交易
# 例如，手工输入的交易，打上支付宝订单号。
# 另外因为支付宝的傻逼账单，这里还需要承担支付手段更新的功能
if ((not 'timestamp' in entry.meta)
or item_timestamp == entry.meta['timestamp']
or item.timestamp == 'None' or item.timestamp == ''):
updated_items.append(item)
if replace_account != '' and item.account in public_accounts:
self.update_transaction_account(item.location,
item.account,
replace_account)
for key, value in entry.meta.items():
if key == 'filename' or key == 'lineno':
continue
if not key in item.metas:
self.append_text_to_transaction(
item.filename, item.lineno,
'{}: "{}"'.format(key, value))
# 如果有时间戳，且时间戳相同，则判定为同交易
# 100%确认是同一笔交易后，就没必要再给其他的「金额相同」的交易加信息了
if 'timestamp' in entry.meta and item_timestamp == entry.meta[
'timestamp']:
break
if len(updated_items) > 1:
for item in updated_items:
self.update_transaction_flag(item.location, item.flag, '!')
return len(updated_items) > 0
def test_Lower(self, entries, _, options_map):
"""
2016-11-20 * "I love candy"
Assets:Banking -1 USD
"""
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT Lower(narration) as m where date = 2016-11-20
''')
self.assertEqual([('i love candy', )], rrows)
def test_Coalesce(self, entries, _, options_map):
"""
2016-11-20 *
Assets:Banking 1 USD
"""
rtypes, rrows = query.run_query(
entries, options_map, 'SELECT COALESCE(account, price) as m')
self.assertEqual([('Assets:Banking', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, 'SELECT COALESCE(price, account) as m')
self.assertEqual([('Assets:Banking', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, 'SELECT COALESCE(price, cost_number) as m')
self.assertEqual([(None, )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, 'SELECT COALESCE(narration, account) as m')
self.assertEqual([('', )], rrows)
def query_to_file(self, query_string, result_format):
"""Get query result as file.
Arguments:
query_string: A string, the query to run.
result_format: The file format to save to.
Returns:
A tuple (name, data), where name is either 'query_result' or the
name of a custom query if the query string is 'run name_of_query'.
``data`` contains the file contents.
Raises:
FavaAPIException: If the result format is not supported or the
query failed.
"""
name = "query_result"
try:
statement = self.parser.parse(query_string)
except query_parser.ParseError as exception:
raise FavaAPIException(str(exception))
if statement.__class__.__name__ == "RunCustom":
name = statement.query_name
try:
query = next(
(query for query in self.queries if query.name == name)
)
except StopIteration:
raise FavaAPIException('Query "{}" not found.'.format(name))
query_string = query.query_string
try:
types, rows = run_query(
self.ledger.all_entries,
self.ledger.options,
query_string,
numberify=True,
)
except (
query_compile.CompilationError,
query_parser.ParseError,
) as exception:
raise FavaAPIException(str(exception))
if result_format == "csv":
data = to_csv(types, rows)
else:
if not HAVE_EXCEL:
raise FavaAPIException("Result format not supported.")
data = to_excel(types, rows, result_format, query_string)
return name, data
def test_DateDiffAdjust(self, entries, _, options_map):
"""
2016-11-20 * "ok"
Assets:Banking -1 STOCK { 5 USD, 2016-10-30 }
"""
rtypes, rrows = query.run_query(
entries, options_map, 'SELECT date_diff(date, cost_date) as m')
self.assertEqual([(21, )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, 'SELECT date_diff(cost_date, date) as m')
self.assertEqual([(-21, )], rrows)
rtypes, rrows = query.run_query(entries, options_map,
'SELECT date_add(date, 1) as m')
self.assertEqual([(datetime.date(2016, 11, 21), )], rrows)
rtypes, rrows = query.run_query(entries, options_map,
'SELECT date_add(date, -1) as m')
self.assertEqual([(datetime.date(2016, 11, 19), )], rrows)
def test_execute_query(example_ledger):
query_shell = QueryShell(example_ledger)
assert query_shell.execute_query("help exit") == (
QueryShell.noop.__doc__ + "\n",
None,
None,
)
assert query_shell.execute_query("help")[1:] == (None, None)
assert query_shell.execute_query("balances")[1:] == query.run_query(
query_shell.entries, query_shell.options_map, "balances")
def find_plac_actuals(self):
actuals = []
for account in self.accounts:
query_str = "select COST(SUM(position)) where account ~ \'" + str(
account) + "\' and date >= " + str(
self.start_date) + " and date <= " + str(
self.end_date) + ";"
query_temp = query.run_query(self.entries,
self.options_map,
query_str,
numberify=True)
actuals.append(query_temp[1][0][0])
return actuals
def test_execute_query(example_ledger):
query_shell = QueryShell(example_ledger)
assert query_shell.execute_query('help exit') == \
(QueryShell.noop.__doc__ + '\n', None, None)
assert query_shell.execute_query('help')[1:] == \
(None, None)
assert query_shell.execute_query('balances', add_to_history=True)[1:] == \
query.run_query(query_shell.entries, query_shell.options_map,
'balances')
assert query_shell.get_history(1) == ['balances']
def test_execute_query(example_ledger):
query_shell = QueryShell(example_ledger)
assert query_shell.execute_query('help exit') == \
(QueryShell.noop.__doc__ + '\n', None, None)
assert query_shell.execute_query('help')[1:] == \
(None, None)
assert query_shell.execute_query('balances', add_to_history=True)[1:] == \
query.run_query(query_shell.entries, query_shell.options_map,
'balances')
assert query_shell.get_history(1) == ['balances']
def query_to_file(self, query_string, result_format):
"""Get query result as file.
Arguments:
query_string: A string, the query to run.
result_format: The file format to save to.
Returns:
A tuple (name, data), where name is either 'query_result' or the
name of a custom query if the query string is 'run name_of_query'.
``data`` contains the file contents.
Raises:
FavaAPIException: If the result format is not supported or the
query failed.
"""
name = 'query_result'
try:
statement = self.parser.parse(query_string)
except query_parser.ParseError as exception:
raise FavaAPIException(str(exception))
if statement.__class__.__name__ == 'RunCustom':
name = statement.query_name
try:
query = next((query for query in self.queries
if query.name == name))
except StopIteration:
raise FavaAPIException('Query "{}" not found.'.format(name))
query_string = query.query_string
try:
types, rows = run_query(
self.ledger.all_entries,
self.ledger.options,
query_string,
numberify=True)
except (query_compile.CompilationError,
query_parser.ParseError) as exception:
raise FavaAPIException(str(exception))
if result_format == 'csv':
data = to_csv(types, rows)
else:
if not HAVE_EXCEL:
raise FavaAPIException('Result format not supported.')
data = to_excel(types, rows, result_format, query_string)
return name, data
def test_Subst(self, entries, _, options_map):
"""
2016-11-20 * "I love candy"
Assets:Banking -1 USD
2016-11-21 * "Buy thing thing"
Assets:Cash -1 USD
"""
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT SUBST("[Cc]andy", "carrots", narration) as m where date = 2016-11-20
''')
self.assertEqual([('I love carrots', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT SUBST("thing", "t", narration) as m where date = 2016-11-21
''')
self.assertEqual([('Buy t t', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT SUBST("random", "t", narration) as m where date = 2016-11-21
''')
self.assertEqual([('Buy thing thing', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT SUBST("(love)", "\\1 \\1", narration) as m where date = 2016-11-20
''')
self.assertEqual([('I love love candy', )], rrows)
rtypes, rrows = query.run_query(
entries, options_map, '''
SELECT SUBST("Assets:.*", "Savings", account) as a, str(sum(position)) as p
''')
self.assertEqual([('Savings', '(-2 USD)')], rrows)
def main():
parser = argparse.ArgumentParser(description=__doc__.strip())
parser.add_argument('filename', help='Beancount input filename')
parser.add_argument('--from',
dest='dfrom',
action='store',
default='1970-01-01')
parser.add_argument('--to',
dest='dto',
action='store',
default='2199-01-01')
args = parser.parse_args()
# Create a SQL query.
date_from = parse(args.dfrom).date()
date_to = parse(args.dto).date()
sql = """
SELECT
year, month, root(account, 1) as ar, sum(position) as pos
FROM
date > {date_from} AND date < {date_to}
WHERE
account ~ "Expenses" OR
account ~ "Liabilities:Loans" OR
account ~ "Income"
GROUP BY year, month, ar
ORDER BY year, month, ar
FLATTEN
""".format(**locals())
# Load the file and run a query on it.
entries, _, options_map = loader.load_file(args.filename)
rtypes, rrows = query.run_query(entries, options_map, sql)
# Pivot on the year/month + currency
out = collections.defaultdict(lambda: collections.defaultdict(dict))
for row in rrows:
d = out['{}/{:02d}'.format(row.year, row.month)][row.pos.lot.currency]
d[row.ar] = row.pos.number
# Write this out to a CSV file.
wr = csv.writer(sys.stdout)
for month, currencies in sorted(out.items()):
for currency, accounts in sorted(currencies.items()):
exp = accounts.get('Expenses', ZERO)
loans = accounts.get('Liabilities:Loans', ZERO)
inc = accounts.get('Income', ZERO)
wr.writerow((month, exp, loans, -inc, exp + loans - inc, currency))
def test_run_query(self):
rootdir = test_utils.find_repository_root(__file__)
filename = path.join(rootdir, 'examples', 'example.beancount')
entries, errors, options_map = loader.load_file(filename)
assert not errors
sql_query = r"""
SELECT
account,
SUM(position) AS amount
WHERE account ~ 'Expenses:'
GROUP BY 1
ORDER BY 2 DESC
"""
rtypes, rrows = query.run_query(entries, options_map,
sql_query, 'Martin',
numberify=True)
self.assertEqual(['account', 'amount (USD)', 'amount (IRAUSD)', 'amount (VACHR)'],
[rt[0] for rt in rtypes])
self.assertEqual(len(rrows[0]), 4)
def test_query() -> None:
assert run_text("help")
assert (
run_text("help exit") == "Doesn't do anything in Fava's query shell.")
assert run("lex select date, balance")[0] == "\n".join([
"LexToken(SELECT,'SELECT',1,0)",
"LexToken(ID,'date',1,7)",
"LexToken(COMMA,',',1,11)",
"LexToken(ID,'balance',1,13)",
])
assert run_text("run") == "custom_query\ncustom query with space"
bal = run("balances")
assert run("run custom_query") == bal
assert run("run 'custom query with space'") == bal
assert run("balances")[1:] == run_query(LEDGER.entries, LEDGER.options,
"balances")
assert (run_text("asdf") ==
"ERROR: Syntax error near 'asdf' (at 0)\n asdf\n ^")
def test_run_query(self):
rootdir = test_utils.find_repository_root(__file__)
filename = path.join(rootdir, 'examples', 'sharing',
'cozumel2015.beancount')
entries, _, options_map = loader.load_file(filename)
sql_query = r"""
SELECT
PARENT(account) AS account,
SUM(position) AS amount
WHERE account ~ 'Expenses.*\b{}'
GROUP BY 1
ORDER BY 2 DESC
"""
rtypes, rrows = query.run_query(entries,
options_map,
sql_query,
'Martin',
numberify=True)
self.assertEqual(['account', 'amount (USD)', 'amount (MXN)'],
[rt[0] for rt in rtypes])
self.assertEqual(13, len(rrows))
def load_beancount_file(file_name):
entries, _, opts = load_file(file_name)
currency = opts["operating_currency"][0]
cols, rows = run_query(entries, opts,
"SELECT account, YEAR(date) AS year,\
MONTH(date) as month,\
SUM(convert(position, '{}', date)) AS amount\
WHERE account ~ 'Expenses'\
OR account ~ 'Income'\
GROUP BY account, year, month\
ORDER BY account, year, month".format(currency)
)
cols, rows = numberify_results(cols, rows)
df = pd.DataFrame(rows, columns=[k[0] for k in cols])
df.rename(columns={"account": "Account", "year": "Year", "month": "Month",
"amount ({})".format(currency): "Amount ({})".format(currency)}, inplace=True)
df = df.astype({"Account": str, "Year": int, "Month": int, "Amount ({})".format(currency): np.float})
df = df[["Account", "Year", "Month", "Amount ({})".format(currency)]].fillna(0)
df["YearMonth"] = df.apply(lambda x: "{}-{:0>2d}".format(x["Year"], x["Month"]), axis=1)
df = df[["Account", "YearMonth", "Amount ({})".format(currency)]]
os.remove(file_name)
return df
def query_func(self, sql):
entries, _, options_map = loader.load_file(self.f)
rtypes, rrows = query.run_query(entries, options_map, sql)
return rtypes, rrows
def save_query(title,
participant,
entries,
options_map,
sql_query,
*format_args,
boxed=True,
spaced=False,
args=None):
"""Save the multiple files for this query.
Args:
title: A string, the title of this particular report to render.
participant: A string, the name of the participant under consideration.
entries: A list of directives (as per the loader).
options_map: A dict of options (as per the loader).
sql_query: A string with the SQL query, possibly with some placeholders left for
*format_args to replace.
*format_args: A tuple of arguments to be formatted into the SQL query string.
This is provided as a convenience.
boxed: A boolean, true if we should render the results in a fancy-looking ASCII box.
spaced: If true, leave an empty line between each of the rows. This is useful if the
results have a lot of rows that render over multiple lines.
args: A dummy object with the following attributes:
output_text: An optional directory name, to produce a text rendering of
the report.
output_csv: An optional directory name, to produce a CSV rendering of
the report.
output_stdout: A boolean, if true, also render the output to stdout.
currency: An optional currency (a string). If you use this, you should
wrap query targets to be converted with the pseudo-function
"CONV[...]" and it will get replaced to CONVERT(..., CURRENCY)
automatically.
"""
# Replace CONV() to convert the currencies or not; if so, replace to
# CONVERT(..., currency).
replacement = (r'\1' if args.currency is None else
r'CONVERT(\1, "{}")'.format(args.currency))
sql_query = re.sub(r'CONV\[(.*?)\]', replacement, sql_query)
# Run the query.
rtypes, rrows = query.run_query(entries,
options_map,
sql_query,
*format_args,
numberify=True)
# The base of all filenames.
filebase = title.replace(' ', '_')
fmtopts = dict(boxed=boxed, spaced=spaced)
# Output the text files.
if args.output_text:
basedir = (path.join(args.output_text, participant)
if participant else args.output_text)
os.makedirs(basedir, exist_ok=True)
filename = path.join(basedir, filebase + '.txt')
with open(filename, 'w') as file:
query_render.render_text(rtypes, rrows, options_map['dcontext'],
file, **fmtopts)
# Output the CSV files.
if args.output_csv:
basedir = (path.join(args.output_csv, participant)
if participant else args.output_csv)
os.makedirs(basedir, exist_ok=True)
filename = path.join(basedir, filebase + '.csv')
with open(filename, 'w') as file:
query_render.render_csv(rtypes,
rrows,
options_map['dcontext'],
file,
expand=False)
if args.output_stdout:
# Write out the query to stdout.
query_render.render_text(rtypes, rrows, options_map['dcontext'],
sys.stdout, **fmtopts)
def get_spending(entries, options_map, min_date):
query_rows = query.run_query(entries, options_map, QUERY, numberify=True)
spending = [(datetime.date(n[0], n[1], 1), float(n[2])) for n in query_rows[1]]
filtered = [n for n in spending if n[0] >= min_date]
return pandas.Series(dict(filtered))
def query_func(self, sql):
rtypes, rrows = query.run_query(self.entries, self.options_map, sql)
return rtypes, rrows
def query(self, bql_query_string):
return query.run_query(self.entries, self.options, bql_query_string)
def query(self, query_string, numberify=False):
return query.run_query(self.all_entries, self.options,
query_string, numberify=numberify)
def query(self, bql_query_string):
return query.run_query(self.entries, self.options, bql_query_string)
