def record(self, entity, start, end, size, timestamps):
if not self.end_timestamp:
df = get_bars(
to_jq_entity_id(entity),
count=size,
unit=self.jq_trading_level,
# fields=['date', 'open', 'close', 'low', 'high', 'volume', 'money']
)
else:
end_timestamp = to_time_str(self.end_timestamp)
df = get_bars(
to_jq_entity_id(entity),
count=size,
unit=self.jq_trading_level,
# fields=['date', 'open', 'close', 'low', 'high', 'volume', 'money'],
end_date=end_timestamp,
)
if pd_is_not_null(df):
df["name"] = entity.name
df.rename(columns={
"money": "turnover",
"date": "timestamp"
},
inplace=True)
df["entity_id"] = entity.id
df["timestamp"] = pd.to_datetime(df["timestamp"])
df["provider"] = "joinquant"
df["level"] = self.level.value
df["code"] = entity.code
def generate_kdata_id(se):
if self.level >= IntervalLevel.LEVEL_1DAY:
return "{}_{}".format(
se["entity_id"],
to_time_str(se["timestamp"], fmt=TIME_FORMAT_DAY))
else:
return "{}_{}".format(
se["entity_id"],
to_time_str(se["timestamp"], fmt=TIME_FORMAT_ISO8601))
df["id"] = df[["entity_id", "timestamp"]].apply(generate_kdata_id,
axis=1)
df = df.drop_duplicates(subset="id", keep="last")
df_to_db(df=df,
data_schema=self.data_schema,
provider=self.provider,
force_update=self.force_update)
return None
def record(self, entity, start, end, size, timestamps):
if not self.end_timestamp:
df = get_bars(
to_jq_entity_id(entity),
count=size,
unit=self.jq_trading_level,
# fields=['date', 'open', 'close', 'low', 'high', 'volume', 'money']
)
else:
end_timestamp = to_time_str(self.end_timestamp)
df = get_bars(
to_jq_entity_id(entity),
count=size,
unit=self.jq_trading_level,
# fields=['date', 'open', 'close', 'low', 'high', 'volume', 'money'],
end_date=end_timestamp)
if pd_is_not_null(df):
df['name'] = entity.name
df.rename(columns={
'money': 'turnover',
'date': 'timestamp'
},
inplace=True)
df['entity_id'] = entity.id
df['timestamp'] = pd.to_datetime(df['timestamp'])
df['provider'] = 'joinquant'
df['level'] = self.level.value
df['code'] = entity.code
def generate_kdata_id(se):
if self.level >= IntervalLevel.LEVEL_1DAY:
return "{}_{}".format(
se['entity_id'],
to_time_str(se['timestamp'], fmt=TIME_FORMAT_DAY))
else:
return "{}_{}".format(
se['entity_id'],
to_time_str(se['timestamp'], fmt=TIME_FORMAT_ISO8601))
df['id'] = df[['entity_id', 'timestamp']].apply(generate_kdata_id,
axis=1)
df = df.drop_duplicates(subset='id', keep='last')
df_to_db(df=df,
data_schema=self.data_schema,
provider=self.provider,
force_update=self.force_update)
return None
def jq_get_bars(code="600000.XSHG",
count=10,
unit='1d',
end_date=None,
fq_ref_date=None,
return_type='df',
parse_dates=['date']):
try:
return jq.get_bars(code=code,
count=count,
unit=unit,
end_date=end_date,
fq_ref_date=fq_ref_date,
return_type=return_type,
parse_dates=parse_dates)
except Exception as e:
logger.error(f'jq_get_bars, code: {code}, error: {e}')
return None
def record(self, entity, start, end, size, timestamps):
if self.adjust_type == AdjustType.hfq:
fq_ref_date = '2000-01-01'
else:
fq_ref_date = to_time_str(now_pd_timestamp())
if not self.end_timestamp:
df = get_bars(
to_jq_entity_id(entity),
count=size,
unit=self.jq_trading_level,
# fields=['date', 'open', 'close', 'low', 'high', 'volume', 'money'],
fq_ref_date=fq_ref_date)
else:
end_timestamp = to_time_str(self.end_timestamp)
df = get_bars(
to_jq_entity_id(entity),
count=size,
unit=self.jq_trading_level,
# fields=['date', 'open', 'close', 'low', 'high', 'volume', 'money'],
end_date=end_timestamp,
fq_ref_date=fq_ref_date)
if pd_is_not_null(df):
df['name'] = entity.name
df.rename(columns={
'money': 'turnover',
'date': 'timestamp'
},
inplace=True)
df['entity_id'] = entity.id
df['timestamp'] = pd.to_datetime(df['timestamp'])
df['provider'] = 'joinquant'
df['level'] = self.level.value
df['code'] = entity.code
# 判断是否需要重新计算之前保存的前复权数据
if self.adjust_type == AdjustType.qfq:
check_df = df.head(1)
check_date = check_df['timestamp'][0]
current_df = get_kdata(entity_id=entity.id,
provider=self.provider,
start_timestamp=check_date,
end_timestamp=check_date,
limit=1,
level=self.level,
adjust_type=self.adjust_type)
if pd_is_not_null(current_df):
old = current_df.iloc[0, :]['close']
new = check_df['close'][0]
# 相同时间的close不同，表明前复权需要重新计算
if round(old, 2) != round(new, 2):
qfq_factor = new / old
last_timestamp = pd.Timestamp(check_date)
self.recompute_qfq(entity,
qfq_factor=qfq_factor,
last_timestamp=last_timestamp)
def generate_kdata_id(se):
if self.level >= IntervalLevel.LEVEL_1DAY:
return "{}_{}".format(
se['entity_id'],
to_time_str(se['timestamp'], fmt=TIME_FORMAT_DAY))
else:
return "{}_{}".format(
se['entity_id'],
to_time_str(se['timestamp'], fmt=TIME_FORMAT_ISO8601))
df['id'] = df[['entity_id', 'timestamp']].apply(generate_kdata_id,
axis=1)
df = df.drop_duplicates(subset='id', keep='last')
df_to_db(df=df,
data_schema=self.data_schema,
provider=self.provider,
force_update=self.force_update)
return None
