def run(self):
for security_item in self.entities:
assert isinstance(security_item, Stock)
if security_item.exchange == 'sh':
fc = "{}01".format(security_item.code)
if security_item.exchange == 'sz':
fc = "{}02".format(security_item.code)
# 基本资料
param = {"color": "w", "fc": fc, "SecurityCode": "SZ300059"}
resp = requests.post(
'https://emh5.eastmoney.com/api/GongSiGaiKuang/GetJiBenZiLiao',
json=param)
resp.encoding = 'utf8'
resp_json = resp.json()['Result']['JiBenZiLiao']
security_item.profile = resp_json['CompRofile']
security_item.main_business = resp_json['MainBusiness']
security_item.date_of_establishment = to_pd_timestamp(
resp_json['FoundDate'])
# 关联行业
industries = ','.join(resp_json['Industry'].split('-'))
security_item.industries = industries
# 关联概念
security_item.concept_indices = resp_json['Block']
# 关联地区
security_item.area_indices = resp_json['Provice']
self.sleep()
# 发行相关
param = {"color": "w", "fc": fc}
resp = requests.post(
'https://emh5.eastmoney.com/api/GongSiGaiKuang/GetFaXingXiangGuan',
json=param)
resp.encoding = 'utf8'
resp_json = resp.json()['Result']['FaXingXiangGuan']
security_item.issue_pe = to_float(resp_json['PEIssued'])
security_item.price = to_float(resp_json['IssuePrice'])
security_item.issues = to_float(resp_json['ShareIssued'])
security_item.raising_fund = to_float((resp_json['NetCollection']))
security_item.net_winning_rate = pct_to_float(
resp_json['LotRateOn'])
self.session.commit()
self.logger.info('finish recording stock meta for:{}'.format(
security_item.code))
self.sleep()
def record(self, entity, start, end, size, timestamps):
the_url = self.url.format("{}".format(entity.code), level_flag(self.level), size,
now_time_str(fmt=TIME_FORMAT_DAY1))
resp = requests.get(the_url)
results = json_callback_param(resp.text)
kdatas = []
if results:
klines = results['data']['klines']
# TODO: ignore the last unfinished kdata now,could control it better if need
for result in klines[:-1]:
# "2000-01-28,1005.26,1012.56,1173.12,982.13,3023326,3075552000.00"
# time,open,close,high,low,volume,turnover
fields = result.split(',')
the_timestamp = to_pd_timestamp(fields[0])
the_id = generate_kdata_id(entity_id=entity.id, timestamp=the_timestamp, level=self.level)
kdatas.append(dict(id=the_id,
timestamp=the_timestamp,
entity_id=entity.id,
code=entity.code,
name=entity.name,
level=self.level.value,
open=to_float(fields[1]),
close=to_float(fields[2]),
high=to_float(fields[3]),
low=to_float(fields[4]),
volume=to_float(fields[5]),
turnover=to_float(fields[6])))
return kdatas
def record(self, entity, start, end, size, timestamps):
url = self.generate_url(category=entity.category,
code=entity.code,
number=size)
resp = requests.get(url)
opendate = "opendate"
avg_price = "avg_price"
avg_changeratio = 'avg_changeratio'
turnover = 'turnover'
netamount = 'netamount'
ratioamount = 'ratioamount'
r0_net = 'r0_net'
r0_ratio = 'r0_ratio'
r0x_ratio = 'r0x_ratio'
cnt_r0x_ratio = 'cnt_r0x_ratio'
json_list = []
try:
json_list = eval(resp.text)
except Exception as e:
resp.encoding = 'GBK'
self.logger.error(resp.text)
time.sleep(60 * 5)
result_list = []
for item in json_list:
result_list.append({
'name':
entity.name,
'timestamp':
to_pd_timestamp(item['opendate']),
'close':
to_float(item['avg_price']),
'change_pct':
to_float(item['avg_changeratio']),
'turnover_rate':
to_float(item['turnover']) / 10000,
'net_inflows':
to_float(item['netamount']),
'net_inflow_rate':
to_float(item['ratioamount']),
'net_main_inflows':
to_float(item['r0_net']),
'net_main_inflow_rate':
to_float(item['r0_ratio'])
})
return result_list
def record(self, entity, start, end, size, time_array):
if entity.type == 'index':
id_flag = "{}1".format(entity.code)
elif entity.type == 'stock':
if entity.exchange == 'sh':
id_flag = "{}1".format(entity.code)
if entity.exchange == 'sz':
id_flag = "{}2".format(entity.code)
the_url = self.url.format("{}".format(id_flag),
eastmoney_map_zvt_trading_level(self.level),
now_time_str(fmt=TIME_FORMAT_MINUTE), size)
resp = requests.get(the_url)
results = json_callback_param(resp.text)
kdatas = []
for result in results:
the_timestamp = to_pd_timestamp(result['time'])
the_id = generate_kdata_id(entity_id=entity.id,
timestamp=the_timestamp,
level=self.level)
if not data_exist(self.session, self.kdata_schema, the_id):
kdatas.append(
self.kdata_schema(id=the_id,
timestamp=the_timestamp,
entity_id=entity.id,
code=entity.code,
name=entity.name,
level=self.level,
open=to_float(result['open']),
close=to_float(result['close']),
high=to_float(result['high']),
low=to_float(result['low']),
volume=to_float(result['volume']),
turnover=to_float(result['amount']),
turnover_rate=to_float(
result['turnoverrate'])))
return kdatas
def record(self, entity, start, end, size, timestamps):
json_results = []
for timestamp in timestamps:
timestamp_str = to_time_str(timestamp)
url = self.url.format(timestamp_str)
response = requests.get(url=url, headers=DEFAULT_SH_SUMMARY_HEADER)
results = demjson.decode(
response.text[response.text.index("(") +
1:response.text.index(")")])['result']
result = [
result for result in results if result['productType'] == '1'
]
if result and len(result) == 1:
result_json = result[0]
# 有些较老的数据不存在,默认设为0.0
json_results.append({
'provider':
'exchange',
'timestamp':
timestamp,
'name':
'上证指数',
'pe':
to_float(result_json['profitRate'], 0.0),
'total_value':
to_float(result_json['marketValue1'] + '亿', 0.0),
'total_tradable_vaule':
to_float(result_json['negotiableValue1'] + '亿', 0.0),
'volume':
to_float(result_json['trdVol1'] + '万', 0.0),
'turnover':
to_float(result_json['trdAmt1'] + '亿', 0.0),
'turnover_rate':
to_float(result_json['exchangeRate'], 0.0),
})
if len(json_results) > self.batch_size:
return json_results
return json_results
def record(self, entity, start, end, size, timestamps):
the_quarters = get_year_quarters(start)
# treat has recorded the season if contains some date
if not is_same_date(entity.timestamp, start) and len(the_quarters) > 1:
the_quarters = the_quarters[1:]
for year, quarter in the_quarters:
kdatas = []
for fuquan in ['bfq', 'hfq']:
the_url = self.get_kdata_url(entity.code, year, quarter,
fuquan)
resp = requests.get(the_url)
trs = Selector(text=resp.text).xpath(
'//*[@id="FundHoldSharesTable"]/tr[position()>1 and position()<=last()]'
).extract()
for idx, tr in enumerate(trs):
tds = Selector(text=tr).xpath('//td//text()').extract()
tds = [x.strip() for x in tds if x.strip()]
open = tds[1]
high = tds[2]
close = tds[3]
low = tds[4]
volume = tds[5]
turnover = tds[6]
if fuquan == 'hfq':
factor = tds[7]
the_timestamp = to_pd_timestamp(tds[0])
the_id = generate_kdata_id(entity_id=entity.id,
timestamp=the_timestamp,
level=self.level)
if fuquan == 'hfq':
# we got bfq at first and then update hfq data
existed = [
item for item in kdatas if item['id'] == the_id
]
if existed:
kdata = existed[0]
else:
self.logger.error(
"bfq not got for:{}".format(the_id))
kdata = {
'id': the_id,
'timestamp': the_timestamp,
'name': entity.name,
'level': self.level.value,
'open': to_float(open) / to_float(factor),
'close': to_float(close) / to_float(factor),
'high': to_float(high) / to_float(factor),
'low': to_float(low) / to_float(factor),
'volume': to_float(volume),
'turnover': to_float(turnover)
}
kdatas.append(kdata)
kdata['hfq_open'] = to_float(open)
kdata['hfq_high'] = to_float(high)
kdata['hfq_close'] = to_float(close)
kdata['hfq_low'] = to_float(low)
kdata['factor'] = to_float(factor)
self.latest_factors[entity.id] = to_float(factor)
else:
kdatas.append({
'id': the_id,
'timestamp': the_timestamp,
'name': entity.name,
'level': self.level.value,
'open': to_float(open),
'close': to_float(close),
'high': to_float(high),
'low': to_float(low),
'volume': to_float(volume),
'turnover': to_float(turnover)
})
return kdatas
def record(self, entity, start, end, size, timestamps):
param = {
'url':
self.generate_url(code='{}{}'.format(entity.exchange, entity.code),
number=size),
'security_item':
entity
}
resp = requests.get(param['url'])
# {opendate:"2019-04-29",trade:"10.8700",changeratio:"-0.0431338",turnover:"74.924",netamount:"-2903349.8500",
# ratioamount:"-0.155177",r0:"0.0000",r1:"2064153.0000",r2:"6485031.0000",r3:"10622169.2100",r0_net:"0.0000",
# r1_net:"2064153.0000",r2_net:"-1463770.0000",r3_net:"-3503732.8500"}
opendate = "opendate"
trade = "trade"
changeratio = 'changeratio'
turnover = 'turnover'
netamount = 'netamount'
ratioamount = 'ratioamount'
r0 = 'r0'
r1 = 'r1'
r2 = 'r2'
r3 = 'r3'
r0_net = 'r0_net'
r1_net = 'r1_net'
r2_net = 'r2_net'
r3_net = 'r3_net'
json_list = []
try:
json_list = eval(resp.text)
except Exception as e:
resp.encoding = 'GBK'
self.logger.error(resp.text)
time.sleep(60 * 5)
result_list = []
for item in json_list:
amount = to_float(item['r0']) + to_float(item['r1']) + to_float(
item['r2']) + to_float(item['r3'])
result = {
'timestamp':
to_pd_timestamp(item['opendate']),
'close':
to_float(item['trade']),
'change_pct':
to_float(item['changeratio']),
'turnover_rate':
to_float(item['turnover']) / 10000,
'net_inflows':
to_float(item['netamount']),
'net_inflow_rate':
to_float(item['ratioamount']),
# # 主力=超大单+大单
# net_main_inflows = Column(Float)
# net_main_inflow_rate = Column(Float)
# # 超大单
# net_huge_inflows = Column(Float)
# net_huge_inflow_rate = Column(Float)
# # 大单
# net_big_inflows = Column(Float)
# net_big_inflow_rate = Column(Float)
#
# # 中单
# net_medium_inflows = Column(Float)
# net_medium_inflow_rate = Column(Float)
# # 小单
# net_small_inflows = Column(Float)
# net_small_inflow_rate = Column(Float)
'net_main_inflows':
to_float(item['r0_net']) + to_float(item['r1_net']),
'net_huge_inflows':
to_float(item['r0_net']),
'net_big_inflows':
to_float(item['r1_net']),
'net_medium_inflows':
to_float(item['r2_net']),
'net_small_inflows':
to_float(item['r3_net']),
}
if amount != 0:
result['net_main_inflow_rate'] = (to_float(
item['r0_net']) + to_float(item['r1_net'])) / amount
result['net_huge_inflows_rate'] = to_float(
item['r0_net']) / amount
result['net_big_inflows_rate'] = to_float(
item['r1_net']) / amount
result['net_medium_inflows_rate'] = to_float(
item['r2_net']) / amount
result['net_small_inflows_rate'] = to_float(
item['r3_net']) / amount
result_list.append(result)
return result_list
