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Move get 'trailingPegRatio' into _get_info(), simplify & optimise #1138

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merged 1 commit into from Nov 2, 2022
Merged

Move get 'trailingPegRatio' into _get_info(), simplify & optimise #1138

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86 changes: 44 additions & 42 deletions yfinance/base.py
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Expand Up @@ -712,6 +712,50 @@ def _get_info(self, proxy=None):
except Exception:
pass

# Complementary key-statistics. For now just want 'trailing PEG ratio'
session = self.session or _requests
keys = {"trailingPegRatio"}
if len(keys)>0:
# Simplified the original scrape code for key-statistics. Very expensive for fetching
# just one value, best if scraping most/all:
#
# p = _re.compile(r'root\.App\.main = (.*);')
# url = 'https://finance.yahoo.com/quote/{}/key-statistics?p={}'.format(self.ticker, self.ticker)
# try:
# r = session.get(url, headers=utils.user_agent_headers)
# data = _json.loads(p.findall(r.text)[0])
# key_stats = data['context']['dispatcher']['stores']['QuoteTimeSeriesStore']["timeSeries"]
# for k in keys:
# if k not in key_stats or len(key_stats[k])==0:
# # Yahoo website prints N/A, indicates Yahoo lacks necessary data to calculate
# v = None
# else:
# # Select most recent (last) raw value in list:
# v = key_stats[k][-1]["reportedValue"]["raw"]
# self._info[k] = v
# except Exception:
# raise
# pass
#
# For just one/few variable is faster to query directly:
url = "https://query1.finance.yahoo.com/ws/fundamentals-timeseries/v1/finance/timeseries/{}?symbol={}".format(self.ticker, self.ticker)
for k in keys:
url += "&type="+k
# Request 6 months of data
url += "&period1={}".format(int((_datetime.datetime.now()-_datetime.timedelta(days=365//2)).timestamp()))
url += "&period2={}".format(int((_datetime.datetime.now()+_datetime.timedelta(days=1)).timestamp()))
json_str = session.get(url=url, proxies=proxy, headers=utils.user_agent_headers).text
json_data = _json.loads(json_str)
key_stats = json_data["timeseries"]["result"][0]
if k not in key_stats:
# Yahoo website prints N/A, indicates Yahoo lacks necessary data to calculate
v = None
else:
# Select most recent (last) raw value in list:
v = key_stats[k][-1]["reportedValue"]["raw"]
self._info[k] = v


def _get_fundamentals(self, proxy=None):
def cleanup(data):
'''
Expand Down Expand Up @@ -860,48 +904,6 @@ def cleanup(data):
except Exception:
pass

# Complementary key-statistics (currently fetching the important trailingPegRatio which is the value shown in the website)
res = {}
try:
my_headers = {'user-agent': 'curl/7.55.1', 'accept': 'application/json', 'content-type': 'application/json',
'referer': 'https://finance.yahoo.com/', 'cache-control': 'no-cache', 'connection': 'close'}
p = _re.compile(r'root\.App\.main = (.*);')
r = _requests.session().get('https://finance.yahoo.com/quote/{}/key-statistics?p={}'.format(self.ticker,
self.ticker), headers=my_headers)
q_results = {}
my_qs_keys = ['pegRatio'] # QuoteSummaryStore
# , 'quarterlyPegRatio'] # QuoteTimeSeriesStore
my_ts_keys = ['trailingPegRatio']

# Complementary key-statistics
data = _json.loads(p.findall(r.text)[0])
key_stats = data['context']['dispatcher']['stores']['QuoteTimeSeriesStore']
q_results.setdefault(self.ticker, [])
for i in my_ts_keys:
# j=0
try:
# res = {i: key_stats['timeSeries'][i][1]['reportedValue']['raw']}
# We need to loop over multiple items, if they exist: 0,1,2,..
zzz = key_stats['timeSeries'][i]
for j in range(len(zzz)):
if key_stats['timeSeries'][i][j]:
res = {i: key_stats['timeSeries']
[i][j]['reportedValue']['raw']}
q_results[self.ticker].append(res)

# print(res)
# q_results[ticker].append(res)
except:
q_results[ticker].append({i: np.nan})

res = {'Company': ticker}
q_results[ticker].append(res)
except Exception:
pass

if 'trailingPegRatio' in res:
self._info['trailingPegRatio'] = res['trailingPegRatio']

# Analysis Data/Analyst Forecasts
try:
analysis_data = utils.get_json_data_stores(ticker_url+'/analysis',proxy,self.session)
Expand Down