async def run(self):
# 抓取股票列表
df_entity = self.bao_get_all_securities(
to_bao_entity_type(EntityType.Stock))
if pd_valid(df_entity):
df_stock = self.to_entity(df_entity, entity_type=EntityType.Stock)
# persist to Stock
await df_to_db(region=self.region,
provider=self.provider,
data_schema=Stock,
db_session=get_db_session(self.region,
self.provider, Stock),
df=df_stock)
# persist StockDetail too
await df_to_db(region=self.region,
provider=self.provider,
data_schema=StockDetail,
db_session=get_db_session(self.region,
self.provider,
StockDetail),
df=df_stock)
self.logger.info("persist stock list success")
async def on_finish(self):
last_year = str(now_pd_timestamp(self.region).year)
codes = [item.code for item in self.entities]
db_session = get_db_session(self.region, self.provider,
DividendFinancing)
need_filleds, column_names = DividendFinancing.query_data(
region=self.region,
provider=self.provider,
db_session=db_session,
codes=codes,
end_timestamp=last_year,
filters=[DividendFinancing.rights_raising_fund.is_(None)])
if need_filleds:
desc = self.data_schema.__name__ + ": update relevant table"
db_session_1 = get_db_session(self.region, self.provider,
self.data_schema)
kafka_producer = connect_kafka_producer(findy_config['kafka'])
for item in need_filleds:
result, column_names = self.data_schema.query_data(
region=self.region,
provider=self.provider,
db_session=db_session_1,
entity_id=item.entity_id,
start_timestamp=item.timestamp,
end_timestamp=f"{item.timestamp.year}-12-31",
func=func.sum(self.data_schema.rights_raising_fund))
if isinstance(result, (int, float)):
item.rights_raising_fund = result
data = {
"task": 'rig',
"total": len(need_filleds),
"desc": desc,
"leave": True,
"update": 1
}
publish_message(kafka_producer, progress_topic,
bytes(progress_key, encoding='utf-8'),
bytes(json.dumps(data), encoding='utf-8'))
try:
db_session.commit()
except Exception as e:
self.logger.error(f'{self.__class__.__name__}, error: {e}')
db_session.rollback()
await super().on_finish()
async def on_finish(self):
desc = DividendFinancing.__name__ + ": update relevant table"
db_session = get_db_session(self.region, self.provider, DividendFinancing)
kafka_producer = connect_kafka_producer(findy_config['kafka'])
for entity in self.entities:
code_security = {}
code_security[entity.code] = entity
need_fill_items, column_names = DividendFinancing.query_data(
region=self.region,
provider=self.provider,
db_session=db_session,
codes=list(code_security.keys()),
filters=[
DividendFinancing.ipo_raising_fund.is_(None),
DividendFinancing.ipo_issues != 0])
if need_fill_items and len(need_fill_items) > 0:
for need_fill_item in need_fill_items:
need_fill_item.ipo_raising_fund = code_security[entity.code].raising_fund
data = {"task": 'div', "total": len(self.entities), "desc": desc, "leave": True, "update": 1}
publish_message(kafka_producer, progress_topic, bytes(progress_key, encoding='utf-8'), bytes(json.dumps(data), encoding='utf-8'))
try:
db_session.commit()
except Exception as e:
self.logger.error(f'{self.__class__.__name__}, error: {e}')
db_session.rollback()
await super().on_finish()
async def run(self):
db_session = get_db_session(self.region, self.provider, self.data_schema)
kafka_producer = connect_kafka_producer(findy_config['kafka'])
if not hasattr(self, 'entities'):
self.entities: List = None
await self.init_entities(db_session)
if self.entities and len(self.entities) > 0:
http_session = get_async_http_session()
throttler = asyncio.Semaphore(self.share_para[0])
(taskid, desc) = self.share_para[1]
data = {"task": taskid, "total": len(self.entities), "desc": desc, "leave": True, "update": 0}
publish_message(kafka_producer, progress_topic, bytes(progress_key, encoding='utf-8'), bytes(json.dumps(data), encoding='utf-8'))
# tasks = [asyncio.ensure_future(self.process_loop(entity, http_session, db_session, throttler)) for entity in self.entities]
tasks = [self.process_loop(entity, http_session, db_session, kafka_producer, throttler) for entity in self.entities]
# for result in asyncio.as_completed(tasks):
# await result
[await _ for _ in asyncio.as_completed(tasks)]
await self.on_finish()
return await http_session.close()
async def get_stocks(cls, region: Region, provider: Provider, timestamp, code=None, codes=None, ids=None):
"""
the publishing policy of portfolio positions is different for different types,
overwrite this function for get the holding stocks in specific date
:param code: portfolio(etf/block/index...) code
:param codes: portfolio(etf/block/index...) codes
:param ids: portfolio(etf/block/index...) ids
:param timestamp: the date of the holding stocks
:param provider: the data provider
:return:
"""
from findy.database.plugins.register import get_schema_by_name
from findy.database.context import get_db_session
schema_str = f'{cls.__name__}Stock'
portfolio_stock = get_schema_by_name(schema_str)
db_session = get_db_session(region, provider, data_schema=portfolio_stock)
data, column_names = portfolio_stock.query_data(
region=region,
provider=provider,
db_session=db_session,
code=code,
codes=codes,
timestamp=timestamp,
ids=ids)
if data and len(data) > 0:
return pd.DataFrame([s.__dict__ for s in data], columns=column_names)
else:
return pd.DataFrame()
async def run(self):
http_session = get_sync_http_session()
db_session = get_db_session(self.region, self.provider, self.data_schema)
# 上证、中证
await self.fetch_csi_index(http_session, db_session)
# 深证
await self.fetch_szse_index(http_session, db_session)
def load_data(self):
self.logger.info('load_data start')
start_time = time.time()
db_session = get_db_session(self.region, self.provider,
self.data_schema)
# params = dict(entity_ids=self.entity_ids, provider=self.provider,
# columns=self.columns, start_timestamp=self.start_timestamp,
# end_timestamp=self.end_timestamp, filters=self.filters,
# order=self.order, limit=self.limit, level=self.level,
# index=[self.category_field, self.time_field],
# time_field=self.time_field)
# self.logger.info(f'query_data params:{params}')
# 转换成标准entity_id
if self.entity_schema and not self.entity_ids:
entities, column_names = get_entities(
region=self.region,
provider=self.provider,
db_session=db_session,
entity_schema=self.entity_schema,
exchanges=self.exchanges,
codes=self.codes,
columns=[self.entity_schema.entity_id])
if len(entities) > 0:
self.entity_ids = [entity.entity_id for entity in entities]
else:
return
data, column_names = self.data_schema.query_data(
region=self.region,
provider=self.provider,
db_session=db_session,
entity_ids=self.entity_ids,
columns=self.columns,
start_timestamp=self.start_timestamp,
end_timestamp=self.end_timestamp,
filters=self.filters,
order=self.order,
limit=self.limit,
level=self.level,
index=[self.category_field, self.time_field],
time_field=self.time_field)
if data and not self.columns:
self.data_df = pd.DataFrame([s.__dict__ for s in data],
columns=column_names)
else:
self.data_df = pd.DataFrame(data, columns=column_names)
cost_time = time.time() - start_time
self.logger.info(f'load_data finished, cost_time:{cost_time}')
for listener in self.data_listeners:
listener.on_data_loaded(self.data_df)
def load_company_info(tickers=None):
entity_schema = get_entity_schema_by_type(EntityType.StockDetail)
db_session = get_db_session(Region.US, Provider.Yahoo, entity_schema)
entities, column_names = get_entities(region=Region.US,
provider=Provider.Yahoo,
entity_schema=entity_schema,
db_session=db_session,
codes=tickers)
df = pd.DataFrame([s.__dict__ for s in entities], columns=column_names)
df.reset_index(drop=True, inplace=True)
return df
async def run(self):
db_session = get_db_session(self.region, self.provider, self.data_schema)
trade_days, column_names = StockTradeDay.query_data(
region=self.region,
provider=self.provider,
db_session=db_session,
order=StockTradeDay.timestamp.desc())
if trade_days and len(trade_days) > 0:
self.trade_day = [day.timestamp for day in trade_days]
else:
self.trade_day = []
self.logger.warning("load trade days failed")
return await super().run()
async def persist_index(self, df) -> None:
df['timestamp'] = df['timestamp'].apply(lambda x: to_pd_timestamp(x))
df['list_date'] = df['list_date'].apply(lambda x: to_pd_timestamp(x))
df['id'] = df['code'].apply(lambda code: f'index_cn_{code}')
df['entity_id'] = df['id']
df['exchange'] = 'cn'
df['entity_type'] = EntityType.Index.value
df = df.dropna(axis=0, how='any')
df = df.drop_duplicates(subset='id', keep='last')
db_session = get_db_session(self.region, self.provider, Index)
await df_to_db(region=self.region,
provider=self.provider,
data_schema=Index,
db_session=db_session,
df=df)
async def persist(self, df, db_session):
start_point = time.time()
# persist to Stock
saved = await df_to_db(region=self.region,
provider=self.provider,
data_schema=self.data_schema,
db_session=db_session,
df=df)
# persist StockDetail too
await df_to_db(region=self.region,
provider=self.provider,
data_schema=StockDetail,
db_session=get_db_session(self.region, self.provider, StockDetail),
df=df,
force_update=True)
return True, time.time() - start_point, saved
async def init_main_index(region: Region, provider=Provider.Exchange):
if region == Region.CHN:
for item in CHINA_STOCK_MAIN_INDEX:
item['timestamp'] = to_pd_timestamp(item['timestamp'])
df = pd.DataFrame(CHINA_STOCK_MAIN_INDEX)
elif region == Region.US:
for item in US_STOCK_MAIN_INDEX:
item['timestamp'] = to_pd_timestamp(item['timestamp'])
df = pd.DataFrame(US_STOCK_MAIN_INDEX)
else:
print("index not initialized, in file: init_main_index")
df = pd.DataFrame()
if pd_valid(df):
await df_to_db(region=region,
provider=provider,
data_schema=Index,
db_session=get_db_session(region, provider, Index),
df=df)
async def run(self):
http_session = get_sync_http_session()
db_session = get_db_session(self.region, self.provider,
self.data_schema)
# 抓取沪市 ETF 列表
url = 'http://query.sse.com.cn/commonQuery.do?sqlId=COMMON_SSE_ZQPZ_ETFLB_L_NEW'
text = sync_get(http_session,
url,
headers=DEFAULT_SH_ETF_LIST_HEADER,
return_type='text')
if text is None:
return
response_dict = demjson.decode(text)
df = pd.DataFrame(response_dict.get('result', []))
await self.persist_etf_list(df, ChnExchange.SSE.value, db_session)
self.logger.info('沪市 ETF 列表抓取完成...')
# 抓取沪市 ETF 成分股
await self.download_sh_etf_component(df, http_session, db_session)
self.logger.info('沪市 ETF 成分股抓取完成...')
# 抓取深市 ETF 列表
url = 'http://www.szse.cn/api/report/ShowReport?SHOWTYPE=xlsx&CATALOGID=1945'
content = sync_get(http_session, url, return_type='content')
if content is None:
return
df = pd.read_excel(io.BytesIO(content), dtype=str)
await self.persist_etf_list(df, ChnExchange.SZSE.value, db_session)
self.logger.info('深市 ETF 列表抓取完成...')
# 抓取深市 ETF 成分股
await self.download_sz_etf_component(df, http_session, db_session)
self.logger.info('深市 ETF 成分股抓取完成...')
async def load_window_df(self, data_schema, window):
window_df = None
db_session = get_db_session(self.region, self.provider, data_schema)
dfs = []
for entity_id in self.entity_ids:
data, column_names = data_schema.query_data(
region=self.region,
provider=self.provider,
db_session=db_session,
index=[self.category_field, self.time_field],
order=data_schema.timestamp.desc(),
entity_id=entity_id,
limit=window)
if data and len(data) > 0:
df = pd.DataFrame([s.__dict__ for s in data],
columns=column_names)
dfs.append(df)
if dfs:
window_df = pd.concat(dfs)
window_df = window_df.sort_index(level=[0, 1])
return window_df
async def get_portfolio_stocks(region: Region,
provider: Provider,
timestamp,
portfolio_entity=Fund,
code=None,
codes=None,
ids=None):
portfolio_stock = f'{portfolio_entity.__name__}Stock'
data_schema: PortfolioStockHistory = get_schema_by_name(portfolio_stock)
db_session = get_db_session(region, provider, data_schema)
latests, column_names = data_schema.query_data(
region=region,
provider=provider,
db_session=db_session,
code=code,
end_timestamp=timestamp,
order=data_schema.timestamp.desc(),
limit=1)
if latests and len(latests) > 0:
latest_record = latests[0]
# 获取最新的报表
data, column_names = data_schema.query_data(
region=region,
provider=provider,
db_session=db_session,
code=code,
codes=codes,
ids=ids,
end_timestamp=timestamp,
filters=[data_schema.report_date == latest_record.report_date])
if data and len(data) > 0:
df = pd.DataFrame([s.__dict__ for s in data], columns=column_names)
# 最新的为年报或者半年报
if latest_record.report_period == ReportPeriod.year or latest_record.report_period == ReportPeriod.half_year:
return df
# 季报，需要结合 年报或半年报 来算持仓
else:
step = 0
while step <= 20:
report_date = get_recent_report_date(
latest_record.report_date, step=step)
data, column_names = data_schema.query_data(
region=region,
provider=provider,
db_session=db_session,
code=code,
codes=codes,
ids=ids,
end_timestamp=timestamp,
filters=[
data_schema.report_date == to_pd_timestamp(
report_date)
])
if data and len(data) > 0:
pre_df = pd.DataFrame.from_records(
[s.__dict__ for s in data], columns=column_names)
df = df.append(pre_df)
# 半年报和年报
if (ReportPeriod.half_year.value
in pre_df['report_period'].tolist()) or (
ReportPeriod.year.value
in pre_df['report_period'].tolist()):
# 保留最新的持仓
df = df.drop_duplicates(subset=['stock_code'],
keep='first')
return df
step = step + 1
async def on_finish_entity(self, entity, http_session, db_session):
total_time = await super().on_finish_entity(entity, http_session,
db_session)
if not self.fetch_jq_timestamp:
return total_time
now = time.time()
# fill the timestamp for report published date
the_data_list, column_names = self.data_schema.query_data(
region=self.region,
provider=self.provider,
db_session=db_session,
entity_id=entity.id,
order=self.data_schema.timestamp.asc(),
filters=[
self.data_schema.timestamp == self.data_schema.report_date
])
if the_data_list and len(the_data_list) > 0:
data, column_names = FinanceFactor.query_data(
region=self.region,
provider=self.provider,
db_session=get_db_session(self.region, self.provider,
FinanceFactor),
entity_id=entity.id,
columns=[
FinanceFactor.timestamp, FinanceFactor.report_date,
FinanceFactor.id
],
filters=[
FinanceFactor.timestamp != FinanceFactor.report_date,
FinanceFactor.report_date >= the_data_list[0].report_date,
FinanceFactor.report_date <= the_data_list[-1].report_date
])
if data and len(data) > 0:
df = pd.DataFrame(data, columns=column_names)
df = index_df(df,
index='report_date',
time_field='report_date')
if pd_valid(df):
for the_data in the_data_list:
if the_data.report_date in df.index:
the_data.timestamp = df.at[the_data.report_date,
'timestamp']
self.logger.info(
'db fill {} {} timestamp:{} for report_date:{}'
.format(self.data_schema.__name__, entity.id,
the_data.timestamp,
the_data.report_date))
try:
db_session.commit()
except Exception as e:
self.logger.error(
f'{self.__class__.__name__}, error: {e}')
db_session.rollback()
return total_time + time.time() - now
