def fundamentals(identifier, type='FY', statement='calculations'):
"""
Get available periods with standardized fundamental data for a company.
Args:
identifier: stock market ticker symbol associated with the company's
common stock. If the company is foreign, use the stock exchange
code, followed by a colon, then the ticker.
type: Period type: FY (default) | QTR | TTM | YTD
statement: Type of fundamental data: calculations (default) |
income_statement | balance_sheet | cash_flow_statement
Returns:
Dataset as a Pandas DataFrame
"""
return get('fundamentals/standardized',
identifier=identifier.upper(),
statement=statement.lower(),
type=type.upper())
def securities(identifier=None, query=None, exch_symbol=None):
"""
Get securities with optional filtering using parameters.
Args:
identifier: Identifier for the legal entity or a security associated
with the company: TICKER SYMBOL | FIGI | OTHER IDENTIFIER
query: Search of security name or ticker symbol
exch_symbol: Exchange symbol
Returns:
Dataset as a Pandas DataFrame
"""
if identifier is not None:
identifier = str.upper(identifier)
return get('securities',
identifier=identifier,
query=query,
exch_symbol=exch_symbol)
def prices(identifier, start_date=None, end_date=None, frequency='daily',
sort_order='desc'):
"""
Get historical stock market prices or indices.
Args:
identifier: Stock market symbol or index
start_date: Start date of prices (default no filter)
end_date: Last date (default today)
frequency: Frequency of prices: daily (default) | weekly | monthly |
quarterly | yearly
sort_order: Order of prices: asc | desc (default)
Returns:
Dataset as a Pandas DataFrame
"""
if identifier is not None:
identifier = str.upper(identifier)
df = get('prices', identifier=identifier, start_date=start_date,
end_date=end_date, frequency=frequency, sort_order=sort_order)
df.index = pd.DatetimeIndex(df.date)
df.drop('date', axis=1, inplace=True)
return df
def test_get_companies_data_with_query():
companies = get('companies', query='Cola')
assert len(companies) > 1
assert companies.name.str.contains('Cola').any()
def test_get_missing_endpoint():
with pytest.raises(HTTPError):
get('missing_endpoint')
def test_get_companies_data_with_query_that_returns_many_pages():
companies = get('companies', query='Corp')
assert len(companies) > get_page_size('companies')
assert len(companies) > 300
assert companies.name.str.contains('Corp').any()
