def processing_section(self, section, dict_data_pre):
"""
处理切片，分3、5、10等切片数据
:param section:
DataFrame切片数据
example amount close code high low open vol
date
1991-11-29 8557000 0.11 1 0.13 0.11 0.13 306200
1991-11-30 3962000 0.11 1 0.11 0.11 0.11 142900
1991-12-02 11099000 0.10 1 0.11 0.10 0.11 410500
1991-12-03 6521000 0.12 1 0.12 0.10 0.10 234800
1991-12-04 6853000 0.11 1 0.12 0.11 0.12 242700
1991-12-05 3458000 0.10 1 0.11 0.10 0.11 126000
1991-12-06 4341000 0.11 1 0.11 0.10 0.10 159400
1991-12-07 2218000 0.11 1 0.11 0.11 0.11 80600
:param dict_data_pre:
前一交易日数据 格式类似本次返回的数据
:return:
"""
dict_data = {
'security_code': Utils.quotes_surround(self.security_code)
}
# 日涨跌幅计算
section_tail1 = section.tail(1)
idx = section_tail1.index.values[0]
if isinstance(idx, datetime.datetime) or isinstance(
idx, datetime.date):
the_date = idx
else:
the_date = idx.astype('M8[ms]').astype('O')
week_day = Utils.format_week_day(the_date)
dict_data['week_day'] = week_day
the_date = Utils.format_date(the_date)
dict_data['the_date'] = Utils.quotes_surround(the_date)
if dict_data_pre is None:
print('secuirty_code', self.security_code, '第一次dict_data_pre为None')
# 转换时间格式，结果为<class 'datetime.datetime'> 1991-11-29 00:00:00
dict_data_pre = self.get_dict_data_pre(the_date)
if dict_data_pre is None:
print('secuirty_code', self.security_code,
'查询后dict_data_pre还是为None，只能创建为0的数据')
dict_data_pre = self.create_blank_dict_data()
self.processing_1_day_chg(section_tail1, idx, dict_data, dict_data_pre)
for days in [1, 3, 5, 10]:
self.processing_avg(section.tail(days), days, dict_data,
dict_data_pre)
self.dbService.upsert(dict_data, 'tquant_stock_history_quotation',
['security_code', 'the_date'])
return dict_data
def get_day_kline_chg_upsertsql(security_code, the_date, dict_data):
"""
根据计算得出的股票日K涨跌幅指标数据，生成需要更新的sql语句
:param security_code: 股票代码，字符串类型
:param the_date: 交易日，日期类型
:param dict_data: 股票涨跌幅数据，字典类型
:return:
"""
sql = "update tquant_stock_history_quotation set vol_chg = {vol_chg}, " \
"close_chg = {close_chg}, price_avg = {price_avg}, price_avg_chg = {price_avg_chg}, " \
"close_price_avg_chg = {close_price_avg_chg}, close_open_chg = {close_open_chg} " \
"where security_code = {security_code} and the_date = {the_date} "
sql = sql.format(vol_chg=dict_data['vol_chg'],
close_chg=dict_data['close_chg'],
price_avg=dict_data['price_avg'],
price_avg_chg=dict_data['price_avg_chg'],
close_price_avg_chg=dict_data['close_price_avg_chg'],
close_open_chg=dict_data['close_open_chg'],
security_code=Utils.quotes_surround(security_code),
the_date=Utils.quotes_surround(
Utils.format_date(the_date)))
return sql
def analysis_real_time_kline(self, day_kline, start_date):
"""
解析单只股票的实时行情，并入库
:param day_kline:
:param start_date:
:return:
"""
try:
if day_kline.empty == False:
indexes_values = day_kline.index.values
if indexes_values is None or len(indexes_values) == 0:
log_list = [
Utils.get_now(),
Utils.get_warn(),
self.get_classs_name(), self.security_code,
self.get_method_name(), '当日全部5分钟实时行情 开始时间', start_date,
'【行情为空】'
]
Utils.print_log(log_list)
return
the_date = None
first_idx = None
last_idx = indexes_values[len(indexes_values) - 1]
for idx in indexes_values:
idx_datetime = idx.astype('M8[ms]').astype('O')
# idx_datetime = datetime.datetime.utcfromtimestamp(idx.astype('O') / 1e9)
# 由于第三方接口返回的数据是最近1000个5分钟K，所以需要剔除不是今天的数据
if idx_datetime >= start_date:
first_idx = idx
day_kline = day_kline[idx:]
the_date = idx_datetime
the_date = Utils.format_date(the_date)
break
if the_date is not None:
# 统计数据，包括min， max 等
day_kline_describe = day_kline.describe()
open = Utils.base_round_zero(
day_kline.at[first_idx, 'open'], 2)
high = Utils.base_round_zero(
day_kline_describe.at['max', 'high'], 2)
low = Utils.base_round_zero(
day_kline_describe.at['min', 'low'], 2)
close = Utils.base_round_zero(
day_kline.at[last_idx, 'close'], 2)
# sum统计
day_kline_sum = day_kline.sum()
amount_count = Utils.base_round_zero(
day_kline_sum['amount'] * 100, 2)
vol_count = Utils.base_round_zero(
day_kline_sum['vol'] * 100, 2)
dict_data = {
'security_code':
Utils.quotes_surround(self.security_code),
'the_date': Utils.quotes_surround(the_date),
'amount': amount_count,
'vol': vol_count,
'open': open,
'high': high,
'low': low,
'close': close
}
self.dbService.upsert(dict_data,
'tquant_stock_history_quotation',
['security_code', 'the_date'])
print('secuirty_code', self.security_code, '实时行情基础数据入库成功')
self.calculate_last_10_day(the_date)
except Exception:
traceback.print_exc()
def processing_day_kline(self):
"""
股票日K数据处理，分全量还是增量
:return:
"""
try:
if self.is_reset:
max_the_date = datetime.datetime.now().replace(year=1970,
month=1,
day=1)
else:
max_the_date = self.get_max_the_date()
diff_days = Utils.diff_days(max_the_date)
log_list = [
Utils.get_now(),
Utils.get_info(),
self.get_classs_name(), self.security_code,
self.get_method_name(), '最大交易日', max_the_date, '距今',
Utils.format_date(datetime.date.today()), '差', diff_days, '天'
]
Utils.print_log(log_list)
dict_data_pre = None
if diff_days is None:
result = tt.get_all_daybar(self.security_code, 'bfq')
else:
result = tt.get_last_n_daybar(self.security_code, diff_days,
'bfq')
if result.empty == False:
# 按照正序排序，时间小的排前面
result.sort_index(ascending=True)
# 需要处理的单只股票进度计数
add_up = 0
# 需要处理的单只股票进度打印字符
process_line = '='
len_indexes = len(result.index.values)
for i in range(len_indexes):
add_up += 1
if i < 9:
continue
end = i + 1
start = i - 9
section = result.iloc[start:end, :]
dict_data = self.processing_section(section, dict_data_pre)
dict_data_pre = dict_data
# 批量打印日志
if add_up % 200 == 0:
process_line += '='
progress = Utils.base_round(
Utils.division_zero(add_up, len_indexes) * 100, 2)
log_list = [
Utils.get_now(),
Utils.get_info(),
self.get_classs_name(), self.security_code,
self.get_method_name(), '处理进度', add_up,
len_indexes, process_line,
str(progress) + '%'
]
Utils.print_log(log_list)
process_line += '='
progress = Utils.base_round(
Utils.division_zero(add_up, len_indexes) * 100, 2)
log_list = [
Utils.get_now(),
Utils.get_info(),
self.get_classs_name(), self.security_code,
self.get_method_name(), '处理进度', add_up, len_indexes,
process_line,
str(progress) + '%'
]
Utils.print_log(log_list)
# self.dbService.upsert_many(list_db_data, 'tquant_stock_history_quotation', ['security_code', 'the_date'])
else:
log_list = [
Utils.get_now(),
Utils.get_warn(),
self.get_classs_name(), self.security_code,
self.get_method_name(), '【日K DataFrame为空】'
]
Utils.print_log(log_list)
except Exception:
traceback.print_exc()
