def test_extract_numbers():
assert "160" == extract_numbers("160")
assert "1694" == extract_numbers("1,694")
assert "1806" == extract_numbers("1,806 원")
assert 170 == extract_numbers("170", int)
assert 3925321 == extract_numbers("3,925,321", int)
assert 150.25 == extract_numbers("150.25", float)
with pytest.raises(TypeError):
extract_numbers(1)
with pytest.raises(TypeError):
extract_numbers(b"\x00")
def test_extract_numbers():
assert '160' == extract_numbers('160')
assert '1694' == extract_numbers('1,694')
assert '1806' == extract_numbers('1,806 원')
assert 170 == extract_numbers('170', int)
assert 3925321 == extract_numbers('3,925,321', int)
assert 150.25 == extract_numbers('150.25', float)
with pytest.raises(TypeError):
extract_numbers(1)
with pytest.raises(TypeError):
extract_numbers(b'\x00')
def import_sp500():
app = create_app(__name__)
with app.app_context():
account_checking = Account.get(id=1001)
account_sp500 = Account.get(id=7001)
asset_krw = Asset.query.filter_by(name='KRW').first()
asset_sp500 = Asset.query.filter_by(name='KB S&P500').first()
with open('sample-data/sp500.csv') as fin:
for line in fin:
cols = line.split()
if len(cols) != 5:
continue
date = parse_date(cols[0], '%Y.%m.%d')
_type = cols[1]
quantity_krw, quantity_sp500 = \
[int(extract_numbers(v)) for v in cols[2:4]]
print(cols)
withdraw = _type == '일반입금'
with Transaction.create() as t:
if withdraw:
Record.create(
created_at=date, account=account_checking,
asset=asset_krw, quantity=-quantity_krw,
transaction=t)
Record.create(
created_at=date, account=account_sp500,
asset=asset_sp500, quantity=quantity_sp500,
transaction=t)
print(account_sp500.net_worth(make_date('2016-02-25'), target_asset=asset_krw))
def import_sp500_records():
"""Import S&P500 fund sample data. Expects a tab seprated value document.
"""
app = create_app(__name__)
app.app_context().push()
account_checking = Account.get(id=1001)
account_sp500 = Account.get(id=7001)
asset_krw = Asset.query.filter_by(name='KRW').first()
asset_sp500 = Asset.query.filter_by(name='KB S&P500').first()
# Expected number of columns
expected_col_count = 6
with open('sample-data/sp500.csv') as fin:
# Skip the first row (headers)
headers = next(fin)
col_count = len(headers.split())
if col_count != expected_col_count:
raise Exception(
'Expected number of columns = {}, '
'actual number of columns = {}'.format(
expected_col_count, col_count))
for line in fin:
cols = line.split('\t')
if len(cols) != expected_col_count:
continue
date = parse_date(cols[0], '%Y.%m.%d')
_type = cols[1]
quantity_krw, quantity_sp500 = \
[int(extract_numbers(v)) for v in cols[3:5]]
log.info(', '.join([c.strip() for c in cols]))
if not (_type == '일반입금' or _type == '일반신규'):
log.info('Record type \'{}\' will be ignored', _type)
continue
with Transaction.create() as t:
# NOTE: The actual deposit date and the buying date generally
# differ by a few days. Need to figure out how to parse this
# properly from the raw data.
try:
Record.create(
created_at=date, account=account_checking,
asset=asset_krw, quantity=-quantity_krw,
transaction=t)
except IntegrityError:
log.warn('Identical record exists')
db.session.rollback()
try:
Record.create(
created_at=date, account=account_sp500,
asset=asset_sp500, quantity=quantity_sp500,
transaction=t)
except IntegrityError:
log.warn('Identical record exists')
db.session.rollback()
def import_sp500_records():
"""Import S&P500 fund sample data. Expects a tab seprated value document.
"""
app = create_app(__name__)
app.app_context().push()
account_checking = Account.get(id=1001)
account_sp500 = Account.get(id=7001)
asset_krw = Asset.query.filter_by(name="KRW").first()
asset_sp500 = Asset.query.filter_by(name="KB S&P500").first()
# Expected number of columns
expected_col_count = 6
with open("sample-data/sp500.csv") as fin:
# Skip the first row (headers)
headers = next(fin)
col_count = len(headers.split())
if col_count != expected_col_count:
raise Exception("Expected number of columns = {}, "
"actual number of columns = {}".format(
expected_col_count, col_count))
for line in fin:
cols = line.split("\t")
if len(cols) != expected_col_count:
continue
date = parse_date(cols[0], "%Y.%m.%d")
_type = cols[1]
quantity_krw, quantity_sp500 = [
int(extract_numbers(v)) for v in cols[3:5]
]
log.info(", ".join([c.strip() for c in cols]))
if not (_type == "일반입금" or _type == "일반신규"):
log.info("Record type '{}' will be ignored", _type)
continue
with Transaction.create() as t:
# NOTE: The actual deposit date and the buying date generally
# differ by a few days. Need to figure out how to parse this
# properly from the raw data.
try:
deposit(account_checking, asset_krw, -quantity_krw, date,
t)
except IntegrityError:
log.warn("Identical record exists")
db.session.rollback()
try:
deposit(account_sp500, asset_sp500, quantity_sp500, date,
t)
except IntegrityError:
log.warn("Identical record exists")
db.session.rollback()
def test_extract_numbers():
assert '160' == extract_numbers('160')
assert '1694' == extract_numbers('1,694')
assert '1806' == extract_numbers('1,806 원')
assert 170 == extract_numbers('170', int)
assert 3925321 == extract_numbers('3,925,321', int)
assert 150.25 == extract_numbers('150.25', float)
def import_sp500():
app = create_app(__name__)
with app.app_context():
account_checking = Account.get(id=1001)
account_sp500 = Account.get(id=7001)
asset_krw = Asset.query.filter_by(name='KRW').first()
asset_sp500 = Asset.query.filter_by(name='KB S&P500').first()
with open('sample-data/sp500.csv') as fin:
for line in fin:
cols = line.split()
if len(cols) != 5:
continue
date = parse_date(cols[0], '%Y.%m.%d')
_type = cols[1]
quantity_krw, quantity_sp500 = \
[int(extract_numbers(v)) for v in cols[2:4]]
print(cols)
withdraw = _type == '일반입금'
with Transaction.create() as t:
if withdraw:
Record.create(created_at=date,
account=account_checking,
asset=asset_krw,
quantity=-quantity_krw,
transaction=t)
Record.create(created_at=date,
account=account_sp500,
asset=asset_sp500,
quantity=quantity_sp500,
transaction=t)
print(
account_sp500.net_worth(make_date('2016-02-25'),
target_asset=asset_krw))
def etnc(soup, class_, f):
return f(extract_numbers(extract_div_text(soup, class_=class_)))
def etni(soup, id, f):
return f(extract_numbers(extract_div_text(soup, id=id)))