def cash_flow(l_args, s_ticker):
parser = argparse.ArgumentParser(
prog='cash',
description=
"""Prints a complete cash flow statement over time. This can be either
quarterly or annually. The following fields are expected: Accepted date, Accounts payables,
Accounts receivables, Acquisitions net, Capital expenditure, Cash at beginning of period,
Cash at end of period, Change in working capital, Common stock issued, Common stock repurchased,
Debt repayment, Deferred income tax, Depreciation and amortization, Dividends paid,
Effect of forex changes on cash, Filling date, Final link, Free cash flow, Inventory,
Investments in property plant and equipment, Link, Net cash provided by operating activities,
Net cash used for investing activities, Net cash used provided by financing activities, Net
change in cash, Net income, Operating cash flow, Other financing activities, Other investing
activities, Other non cash items, Other working capital, Period, Purchases of investments,
Sales maturities of investments, Stock based compensation. [Source: Alpha Vantage]"""
)
parser.add_argument('-n',
"--num",
action="store",
dest="n_num",
type=check_positive,
default=1,
help='Number of latest years/quarters.')
parser.add_argument('-q',
"--quarter",
action="store_true",
default=False,
dest="b_quarter",
help='Quarter fundamental data flag.')
try:
(ns_parser, l_unknown_args) = parser.parse_known_args(l_args)
if l_unknown_args:
print(
f"The following args couldn't be interpreted: {l_unknown_args}\n"
)
return
if ns_parser.n_num == 1:
pd.set_option('display.max_colwidth', -1)
else:
pd.options.display.max_colwidth = 40
fd = FundamentalData(key=cfg.API_KEY_ALPHAVANTAGE,
output_format='pandas')
if ns_parser.b_quarter:
df_fa, d_fd_metadata = fd.get_cash_flow_quarterly(symbol=s_ticker)
else:
df_fa, d_fd_metadata = fd.get_cash_flow_annual(symbol=s_ticker)
df_fa = df_fa.set_index('fiscalDateEnding')
df_fa = df_fa.head(n=ns_parser.n_num).T
df_fa = df_fa.mask(
df_fa.astype(object).eq(ns_parser.n_num * ['None'])).dropna()
df_fa = df_fa.mask(df_fa.astype(object).eq(ns_parser.n_num *
['0'])).dropna()
df_fa = df_fa.applymap(lambda x: long_number_format(x))
df_fa.index = [
''.join(' ' + char if char.isupper() else char.strip()
for char in idx).strip() for idx in df_fa.index.tolist()
]
df_fa.index = [s_val.capitalize() for s_val in df_fa.index]
df_fa.columns.name = "Fiscal Date Ending"
print(df_fa)
print("")
except:
print("")
return
def cashflow_init_quarterly(request):
if request.method == 'GET':
symbol = request.GET.get('symbol')
data = FundamentalData(key='I7WB8M63PERU90OY', output_format='pandas')
qcashflows, vasymbol = data.get_cash_flow_quarterly(symbol=symbol)
for fical in qcashflows['fiscalDateEnding']:
cashflow = qcashflows[qcashflows['fiscalDateEnding'] == fical]
for col in cashflow.columns:
if col not in ['fiscalDateEnding', 'reportedCurrency']:
if cashflow[col].values[0] == 'None':
cashflow[col] = 0.0
else:
pass
else:
pass
cash = CashFlow(
symbol=symbol,
report_type='annualReport',
fiscal_date_ending=datetime.strptime(
cashflow['fiscalDateEnding'].values[0], '%Y-%m-%d'),
reported_currency=cashflow['reportedCurrency'].values[0],
investments=cashflow['investments'].values[0],
change_in_liabilities=cashflow['changeInLiabilities'].
values[0],
cashflow_from_investment=cashflow['cashflowFromInvestment'].
values[0],
other_cashflow_from_investment=cashflow[
'otherCashflowFromInvestment'].values[0],
net_borrowings=cashflow['netBorrowings'].values[0],
cashflow_from_financing=cashflow['cashflowFromFinancing'].
values[0],
other_cashflow_from_financing=cashflow[
'otherCashflowFromFinancing'].values[0],
change_in_operating_activities=cashflow[
'changeInOperatingActivities'].values[0],
net_income=cashflow['netIncome'].values[0],
change_in_cash=cashflow['changeInCash'].values[0],
operating_cashflow=cashflow['operatingCashflow'].values[0],
other_operating_cashflow=cashflow['otherOperatingCashflow'].
values[0],
depreciation=cashflow['depreciation'].values[0],
dividend_payout=cashflow['dividendPayout'].values[0],
stock_sale_and_purchase=cashflow['stockSaleAndPurchase'].
values[0],
change_in_inventory=cashflow['changeInInventory'].values[0],
change_in_account_receivables=cashflow[
'changeInAccountReceivables'].values[0],
change_in_net_income=cashflow['changeInNetIncome'].values[0],
capital_expenditures=cashflow['capitalExpenditures'].values[0],
change_in_receivables=cashflow['changeInReceivables'].
values[0],
change_in_exchange_rate=cashflow['changeInExchangeRate'].
values[0],
change_in_cash_and_cash_equivalents=cashflow[
'changeInCashAndCashEquivalents'].values[0])
cash.save()
return JsonResponse({'message': 'Quarterly Data Save successlly'},
status=status.HTTP_200_OK)
def cash_flow(other_args: List[str], ticker: str):
"""Alpha Vantage cash flow
Parameters
----------
other_args : List[str]
argparse other args
ticker : str
Fundamental analysis ticker symbol
"""
parser = argparse.ArgumentParser(
add_help=False,
prog="cash",
description="""
Prints a complete cash flow statement over time. This can be either quarterly or
annually. The following fields are expected: Accepted date, Accounts payables, Accounts
receivables, Acquisitions net, Capital expenditure, Cash at beginning of period, Cash
at end of period, Change in working capital, Common stock issued, Common stock
repurchased, Debt repayment, Deferred income tax, Depreciation and amortization,
Dividends paid, Effect of forex changes on cash, Filling date, Final link, Free cash
flow, Inventory, Investments in property plant and equipment, Link, Net cash provided
by operating activities, Net cash used for investing activities, Net cash used provided
by financing activities, Net change in cash, Net income, Operating cash flow, Other
financing activities, Other investing activities, Other non cash items, Other working
capital, Period, Purchases of investments, Sales maturities of investments, Stock based
compensation. [Source: Alpha Vantage]
""",
)
parser.add_argument(
"-n",
"--num",
action="store",
dest="n_num",
type=check_positive,
default=1,
help="Number of latest years/quarters.",
)
parser.add_argument(
"-q",
"--quarter",
action="store_true",
default=False,
dest="b_quarter",
help="Quarter fundamental data flag.",
)
try:
ns_parser = parse_known_args_and_warn(parser, other_args)
if not ns_parser:
return
if ns_parser.n_num == 1:
pd.set_option("display.max_colwidth", None)
else:
pd.options.display.max_colwidth = 40
fd = FundamentalData(key=cfg.API_KEY_ALPHAVANTAGE,
output_format="pandas")
if ns_parser.b_quarter:
# pylint: disable=unbalanced-tuple-unpacking
df_fa, _ = fd.get_cash_flow_quarterly(symbol=ticker)
else:
# pylint: disable=unbalanced-tuple-unpacking
df_fa, _ = fd.get_cash_flow_annual(symbol=ticker)
df_fa = clean_fundamentals_df(df_fa, num=ns_parser.n_num)
print(df_fa)
print("")
except Exception as e:
print(e)
print("")
return
period = input('Period- annual, quarterly : ')
statement = input('Statement- balance sheet, income statement, cash flow : ')
fd = FundamentalData(key,output_format = 'pandas')
if period == 'annual':
if statement == 'balance sheet':
state = fd.get_balance_sheet_annual(symbol)[0].T[2:]
state.columns = list(fd.get_balance_sheet_annual(symbol)[0].T.iloc[0])
elif statement == 'income statement':
state = fd.get_income_statement_annual(symbol)[0].T[2:]
state.columns = list(fd.get_income_statement_annual(symbol)[0].T.iloc[0])
elif statement == 'cash flow':
state = fd.get_cash_flow_annual(symbol)[0].T[2:]
state.columns = list(fd.get_cash_flow_annual(symbol)[0].T.iloc[0])
else:
print("wrong input given by the user ")
elif period == 'quarterly':
if statement == 'balance sheet':
state = fd.get_balance_sheet_quarterly(symbol)[0].T[2:]
state.columns = list(fd.get_balance_sheet_quarterly(symbol)[0].T.iloc[0])
elif statement == 'income statement':
state = fd.get_income_statement_quarterly(symbol)[0].T[2:]
state.columns = list(fd.get_income_statement_quarterly(symbol)[0].T.iloc[0])
elif statement == 'cash flow':
state = fd.get_cash_flow_quarterly(symbol)[0].T[2:]
state.columns = list(fd.get_cash_flow_quarterly(symbol)[0].T.iloc[0])
else:
print('Wrong Entry')
else:
print('Wrong Entry')
print(state)