def finance_report(start: Timestamp,
end: Timestamp,
market: str,
symbol: str,
report_type: str,
quarter="all") -> DataFrame:
"""
:param start: start time
:param end: end time
:param market: {'HK', 'CN'}
:param symbol: stock symbol
:param report_type: {'indicator', 'balance', 'income', 'business'}
:param quarter: {'all', 'Q1', 'Q2', ‘Q3', 'Q4'}
:return: data frame contains items of financial report
"""
count = (end.to_period(freq='Q') - start.to_period(freq='Q')).n
end_timestamp = int(end.timestamp() * 1000)
urlpath = f"{market}/{report_type}.json?symbol={symbol}&&type={quarter}" \
f"&is_detail=true&count={count}×tamp={end_timestamp}"
url = urljoin(api_ref.finance_base, urlpath)
data = utls.fetch(url)
data_list = data.pop('list')
for d in data_list:
for k in d:
if isinstance(d[k], list):
d[k] = d[k][0]
df = DataFrame(data_list).drop(columns=['ctime']).rename(
columns={
'report_date': 'date'
}).set_index('date')
df.date = df.date.astype('M8[ms]')
df.report_name = df.report_name.str.replace('年报', 'Q4').str.replace('三季报', 'Q3')\
.str.replace('中报', 'Q2').str.replace('一季报', 'Q1')
return df
def bonus(symbol, page=1, size=10):
url = api_ref.f10_bonus + symbol
url += '&page='
url += str(page)
url += '&size='
url += str(size)
return utls.fetch(url)
def his_data(symbols, period='day', def_cnt=1):
url = api_ref.his_data + symbols
url = url + "&begin=" + str(round(time.time() * 1000))
tail = "&period=" + str(period) + "&type=before&count=-" + str(
def_cnt
) + "&indicator=kline,pe,pb,ps,pcf,market_capital,agt,ggt,balance"
url = url + tail
#print('his_data url=%s' % url)
return utls.fetch(url)
def indicator(symbol, is_annals=0, count=10):
url = api_ref.finance_indicator_url+symbol
if is_annals == 1:
url = url + '&type=Q4'
url = url + '&count='+str(count)
return utls.fetch(url)
def business(symbol, is_annals=0, count=10):
url = api_ref.finance_business_url+symbol
if is_annals == 1:
url = url + '&type=Q4'
url = url + '&count='+str(count)
return utls.fetch(url)
def cash_flow(symbol, is_annals=0, count=10):
url = api_ref.finance_cash_flow_url+symbol
if is_annals == 1:
url = url + '&type=Q4'
url = url + '&count='+str(count)
return utls.fetch(url)
def business(symbol, is_annuals=0, count=10):
url = api_ref.finance_business_url + symbol
if is_annuals == 1:
url += '&type=Q4'
else:
url += '&type=all&is_detail=true&count='
url += str(count)
return utls.fetch(url)
def cash_flow(symbol, is_annuals=0, count=10):
url = api_ref.finance_cash_flow_url + symbol
if is_annuals == 1:
url += '&type=Q4&count='
else:
url += '&type=all&is_detail=true&count='
url += str(count)
return utls.fetch(url)
def population_by_market(market: str, batch_size: int = 1000) -> DataFrame:
"""
:param market: {'HK', 'CN'}
:param batch_size: size of one batch
:return: dataframe contains all population
"""
url = api_ref.population_base + "?page=1&size={}&order=asc&order_by=symbol&market={}&type={}".format(
batch_size, market, market.lower())
res = utls.fetch(url)
total_count = res['count']
data: list = res['list']
# noinspection PyTypeChecker
time.sleep(np.clip(nr.normal(1, 0.02), 0.9, 1.1))
for page in range(2, (total_count - 1) // batch_size + 2):
url = api_ref.population_base + "?page={}&size={}&order=asc&order_by=symbol&market={}&type={}".format(
page, batch_size, market, market.lower())
res = utls.fetch(url)
this_count = res.get('count', 0)
if this_count != total_count:
raise RuntimeWarning(
f"Get record number ({this_count}) from page {page}, which is different from first page ({total_count})"
)
this_list = res.get('list', [])
if not this_list:
raise RuntimeWarning("empty page, seemingly missing data")
data.extend(this_list)
# noinspection PyTypeChecker
time.sleep(np.clip(nr.normal(1, 0.02), 0.9, 1.1))
return DataFrame(data).set_index('symbol')
def industry(symbol):
url = api_ref.f10_industry + symbol
return utls.fetch(url)
def watch_stock(id):
url = api_ref.watch_stock + str(id)
return utls.fetch(url)
def watch_list():
url = api_ref.watch_list
return utls.fetch(url)
def pankou(symbol):
url = api_ref.realtime_pankou + symbol
return utls.fetch(url)
def report(symbol):
url = api_ref.report_latest_url+symbol
return utls.fetch(url)
def shareschg(symbol, count=5):
url = api_ref.f10_shareschg + symbol
url = url + '&count=' + str(count)
return utls.fetch(url)
def industry_compare(symbol):
url = api_ref.f10_industry_compare + symbol
return utls.fetch(url)
def main_indicator(symbol):
url = api_ref.f10_indicator + symbol
return utls.fetch(url)
def share_quotec(symbols):
url = api_ref.share_quote + symbols + '&extend=detail'
return utls.fetch(url)
def margin(symbol, page=1, size=180):
url = api_ref.capital_margin_url+symbol
url = url + '&page='+str(page)
url = url + '&size='+str(size)
return utls.fetch(url)
def quote_detail(symbol):
return utls.fetch(api_ref.realtime_quote_detail + symbol)
def earningforecast(symbol):
url = api_ref.report_earningforecast_url+symbol
return utls.fetch(url)
def holders(symbol):
url = api_ref.f10_holders + symbol
return utls.fetch(url)
def org_holding_change(symbol):
url = api_ref.f10_org_holding_change + symbol
return utls.fetch(url)
def capital_flow(symbol):
url = api_ref.capital_flow_url+symbol
return utls.fetch(url)
def business_analysis(symbol):
url = api_ref.f10_business_analysis + symbol
return utls.fetch(url)
def capital_history(symbol, count=20):
url = api_ref.capital_history_url+symbol
url = url + '&count='+str(count)
return utls.fetch(url)
def top_holders(symbol, circula=1):
url = api_ref.f10_top_holders + symbol
url = url + '&circula=' + str(circula)
return utls.fetch(url)
def holders(symbol, size=10):
url = api_ref.f10_holders + symbol
url += '&extend=true&page=1&size='
url += str(size)
return utls.fetch(url)
def skholderchg(symbol):
url = api_ref.f10_skholderchg + symbol
return utls.fetch(url)
def capital_assort(symbol):
url = api_ref.capital_assort_url+symbol
return utls.fetch(url)