def get_stock_current(ticker: str) -> StockCurrent:
quote: Dict[str, Any] = http.get_json(
f'https://api.iextrading.com/1.0/stock/{ticker}/quote')
return StockCurrent(
after_hours_price=quote['extendedPrice'],
after_hours_updated_time=datetime.utcfromtimestamp(
quote['extendedPriceTime'] / 1000),
current_price=quote['latestPrice'],
high=quote['high'],
last_updated_time=datetime.utcfromtimestamp(quote['latestUpdate'] /
1000),
low=quote['low'],
open_=quote['open'],
previous_close=quote['previousClose'],
volume=quote['latestVolume'],
)
def get_stock_metadata(tickers):
if len(tickers) > 100:
raise Exception('More than 100 tickers is not supported.')
symbols = ','.join(tickers)
all_company_data = http.get_json(
f'https://api.iextrading.com/1.0/stock/market/batch?symbols={symbols}&types=company,stats'
)
metadatas = []
for symbol, data in all_company_data.items():
metadatas.append(
StockMetadata(symbol.upper(), data['company']['companyName'],
data['stats']['marketcap'],
data['company']['sector']))
return metadatas
def get_sector_performances() -> List[SectorPerformance]:
key_to_sector_id: Dict[str, SectorId] = {
"Communication Services": SectorId.TELECOMMUNICATION_SERVICES,
"Consumer Discretionary": SectorId.CONSUMER_DISCRETIONARY,
"Consumer Staples": SectorId.CONSUMER_STAPLES,
"Energy": SectorId.ENERGY,
"Financials": SectorId.FINANCIALS,
"Health Care": SectorId.HEALTH_CARE,
"Industrials": SectorId.INDUSTRIALS,
"Information Technology": SectorId.TECHNOLOGY,
"Materials": SectorId.MATERIALS,
"Real Estate": SectorId.REAL_ESTATE,
"Utilities": SectorId.UTILITIES
}
key_to_time_window: Dict[str, TimeWindow] = {
"Rank C: 5 Day Performance": TimeWindow.ONE_WEEK,
"Rank D: 1 Month Performance": TimeWindow.ONE_MONTH,
"Rank E: 3 Month Performance": TimeWindow.THREE_MONTHS,
"Rank G: 1 Year Performance": TimeWindow.ONE_YEAR,
"Rank H: 3 Year Performance": TimeWindow.THREE_YEARS,
"Rank I: 5 Year Performance": TimeWindow.FIVE_YEARS
}
sector_json: Any = http.get_json(get_url('SECTOR'))
sector_performances: List[SectorPerformance] = []
for time_window_key in sector_json:
if time_window_key not in key_to_time_window:
continue
for sector_key in sector_json[time_window_key]:
if sector_key not in key_to_sector_id:
continue
sector_performances.append(
SectorPerformance(
id=key_to_sector_id[sector_key],
time_window=key_to_time_window[time_window_key],
percent_change=float(
sector_json[time_window_key][sector_key].rstrip('%'))))
return sector_performances
def get_ticker_list():
stock_array = http.get_json(
'https://api.iextrading.com/1.0/ref-data/symbols')
return [s['symbol'].upper() for s in stock_array if s['type'] == 'cs']
def get_stock_dailies(tickers: List[str],
range_: str) -> Dict[str, List[StockDaily]]:
"""
Gets a dictionary of ticker to list of StockDaily. If there is no data for the given ticker, then it will
be omitted from the dictionary.
:param range_: Supported values: '1m', '2y'
"""
if len(tickers) > 100:
raise Exception('More than 100 tickers is not supported.')
symbols = ','.join(tickers)
all_dailies = http.get_json(
f'https://api.iextrading.com/1.0/stock/market/batch?symbols={symbols}&types=chart,quote&range={range_}'
)
dailies: Dict[str, List[StockDaily]] = {}
for symbol, data in all_dailies.items():
chart = data['chart']
max_date = None
dailies[symbol] = []
for daily in chart:
try:
stock_daily = StockDaily(daily['date'], daily['open'],
daily['high'], daily['low'],
daily['close'], daily['volume'])
max_date = stock_daily.date if not max_date else max(
max_date, stock_daily.date)
if None in [
stock_daily.date, stock_daily.open, stock_daily.high,
stock_daily.low, stock_daily.close, stock_daily.volume
]:
continue
dailies[symbol].append(stock_daily)
except KeyError:
# For some reason, sometimes IEX is missing some data.
# Just skip the data for that date.
print("Missed day of data for " + symbol)
# Try to get the latest day from the quote if it wasn't already added
# to the chart data.
try:
quote = data['quote']
quote_datetime = datetime.utcfromtimestamp(quote['closeTime'] /
1000)
open_datetime = datetime.utcfromtimestamp(quote['openTime'] / 1000)
if open_datetime > quote_datetime:
print('Open date > close date, skipping this quote')
elif quote_datetime and max_date and quote_datetime.date(
) > max_date:
formatted_date = quote_datetime.strftime('%Y-%m-%d')
quote_daily = StockDaily(formatted_date, quote['open'],
quote['high'], quote['low'],
quote['close'],
quote['avgTotalVolume'])
if None in [
quote_daily.date, quote_daily.open, quote_daily.high,
quote_daily.low, quote_daily.close, quote_daily.volume
]:
raise ValueError("One of the values are None")
dailies[symbol].append(quote_daily)
except Exception as e:
print("Could not parse quote for " + symbol)
print(e)
return dailies