def record(self, entity, start, end, size, timestamps):
for page in range(1, 5):
resp = requests.get(self.category_stocks_url.format(page, entity.code))
try:
if resp.text == "null" or resp.text is None:
break
category_jsons = demjson3.decode(resp.text)
the_list = []
for category in category_jsons:
stock_code = category["code"]
stock_id = china_stock_code_to_id(stock_code)
block_id = entity.id
the_list.append(
{
"id": "{}_{}".format(block_id, stock_id),
"entity_id": block_id,
"entity_type": "block",
"exchange": entity.exchange,
"code": entity.code,
"name": entity.name,
"timestamp": now_pd_timestamp(),
"stock_id": stock_id,
"stock_code": stock_code,
"stock_name": category["name"],
}
)
if the_list:
df = pd.DataFrame.from_records(the_list)
df_to_db(data_schema=self.data_schema, df=df, provider=self.provider, force_update=True)
self.logger.info("finish recording BlockStock:{},{}".format(entity.category, entity.name))
except Exception as e:
self.logger.error("error:,resp.text:", e, resp.text)
self.sleep()
def record(self, entity, start, end, size, timestamps):
resp = requests.get(self.category_stocks_url.format(entity.code, "1"), headers=DEFAULT_HEADER)
try:
results = json_callback_param(resp.text)
the_list = []
for result in results:
items = result.split(",")
stock_code = items[1]
stock_id = china_stock_code_to_id(stock_code)
block_id = entity.id
the_list.append(
{
"id": "{}_{}".format(block_id, stock_id),
"entity_id": block_id,
"entity_type": "block",
"exchange": entity.exchange,
"code": entity.code,
"name": entity.name,
"timestamp": now_pd_timestamp(),
"stock_id": stock_id,
"stock_code": stock_code,
"stock_name": items[2],
}
)
if the_list:
df = pd.DataFrame.from_records(the_list)
df_to_db(data_schema=self.data_schema, df=df, provider=self.provider, force_update=True)
self.logger.info("finish recording block:{},{}".format(entity.category, entity.name))
except Exception as e:
self.logger.error("error:,resp.text:", e, resp.text)
self.sleep()
def download_sz_etf_component(self, df: pd.DataFrame):
query_url = "http://vip.stock.finance.sina.com.cn/corp/go.php/vII_NewestComponent/indexid/{}.phtml"
self.parse_sz_etf_underlying_index(df)
for _, etf in df.iterrows():
underlying_index = etf["拟合指数"]
etf_code = etf["证券代码"]
if len(underlying_index) == 0:
self.logger.info(f'{etf["证券简称"]} - {etf_code} 非 A 股市场指数，跳过...')
continue
url = query_url.format(underlying_index)
response = requests.get(url)
response.encoding = "gbk"
try:
dfs = pd.read_html(response.text, header=1)
except ValueError as error:
self.logger.error(
f"HTML parse error: {error}, response: {response.text}")
continue
if len(dfs) < 4:
continue
response_df = dfs[3].copy()
response_df = response_df.dropna(axis=1, how="any")
response_df["品种代码"] = response_df["品种代码"].apply(
lambda x: f"{x:06d}")
etf_id = f"etf_sz_{etf_code}"
response_df = response_df[["品种代码", "品种名称"]].copy()
response_df.rename(columns={
"品种代码": "stock_code",
"品种名称": "stock_name"
},
inplace=True)
response_df["entity_id"] = etf_id
response_df["entity_type"] = "etf"
response_df["exchange"] = "sz"
response_df["code"] = etf_code
response_df["name"] = etf["证券简称"]
response_df["timestamp"] = now_pd_timestamp()
response_df["stock_id"] = response_df["stock_code"].apply(
lambda code: china_stock_code_to_id(code))
response_df["id"] = response_df["stock_id"].apply(
lambda x: f"{etf_id}_{x}")
df_to_db(data_schema=self.data_schema,
df=response_df,
provider=self.provider)
self.logger.info(f'{etf["证券简称"]} - {etf_code} 成分股抓取完成...')
self.sleep()
def download_sh_etf_component(self, df: pd.DataFrame):
"""
ETF_CLASS => 1. 单市场 ETF 2.跨市场 ETF 3. 跨境 ETF
5. 债券 ETF 6. 黄金 ETF
:param df: ETF 列表数据
:return: None
"""
query_url = (
"http://query.sse.com.cn/infodisplay/queryConstituentStockInfo.do?"
"isPagination=false&type={}&etfClass={}")
etf_df = df[(df["ETF_CLASS"] == "1") | (df["ETF_CLASS"] == "2")]
etf_df = self.populate_sh_etf_type(etf_df)
for _, etf in etf_df.iterrows():
url = query_url.format(etf["ETF_TYPE"], etf["ETF_CLASS"])
response = requests.get(url, headers=DEFAULT_SH_ETF_LIST_HEADER)
response_dict = demjson3.decode(response.text)
response_df = pd.DataFrame(response_dict.get("result", []))
etf_code = etf["FUND_ID"]
etf_id = f"etf_sh_{etf_code}"
response_df = response_df[["instrumentId",
"instrumentName"]].copy()
response_df.rename(columns={
"instrumentId": "stock_code",
"instrumentName": "stock_name"
},
inplace=True)
response_df["entity_id"] = etf_id
response_df["entity_type"] = "etf"
response_df["exchange"] = "sh"
response_df["code"] = etf_code
response_df["name"] = etf["FUND_NAME"]
response_df["timestamp"] = now_pd_timestamp()
response_df["stock_id"] = response_df["stock_code"].apply(
lambda code: china_stock_code_to_id(code))
response_df["id"] = response_df["stock_id"].apply(
lambda x: f"{etf_id}_{x}")
df_to_db(data_schema=self.data_schema,
df=response_df,
provider=self.provider)
self.logger.info(f'{etf["FUND_NAME"]} - {etf_code} 成分股抓取完成...')
self.sleep()
def get_cn_index_stock(code, timestamp, name=None):
entity_type = "index"
exchange = "sz"
entity_id = f"{entity_type}_{exchange}_{code}"
data_str = to_time_str(timestamp, TIME_FORMAT_MON)
resp = requests.get(url.format(code, data_str), headers=DEFAULT_HEADER)
data = _get_resp_data(resp)
if not data:
return
results = _get_resp_data(resp)["rows"]
the_list = []
for result in results:
# date: 1614268800000
# dateStr: "2021-02-26"
# freeMarketValue: 10610.8
# indexcode: "399370"
# market: null
# seccode: "600519"
# secname: "贵州茅台"
# totalMarketValue: 26666.32
# trade: "主要消费"
# weight: 10.01
stock_code = result["seccode"]
stock_name = result["secname"]
stock_id = china_stock_code_to_id(stock_code)
the_list.append(
{
"id": "{}_{}_{}".format(entity_id, result["dateStr"], stock_id),
"entity_id": entity_id,
"entity_type": entity_type,
"exchange": exchange,
"code": code,
"name": name,
"timestamp": to_pd_timestamp(result["dateStr"]),
"stock_id": stock_id,
"stock_code": stock_code,
"stock_name": stock_name,
"proportion": value_to_pct(result["weight"], 0),
"market_cap": value_multiply(result["freeMarketValue"], 100000000, 0),
}
)
if the_list:
df = pd.DataFrame.from_records(the_list)
return df
def get_cn_index_stock(code, timestamp, name=None):
entity_type = 'index'
exchange = 'sz'
entity_id = f'{entity_type}_{exchange}_{code}'
data_str = to_time_str(timestamp, TIME_FORMAT_MON)
resp = requests.get(url.format(code, data_str), headers=DEFAULT_HEADER)
data = _get_resp_data(resp)
if not data:
return
results = _get_resp_data(resp)['rows']
the_list = []
for result in results:
# date: 1614268800000
# dateStr: "2021-02-26"
# freeMarketValue: 10610.8
# indexcode: "399370"
# market: null
# seccode: "600519"
# secname: "贵州茅台"
# totalMarketValue: 26666.32
# trade: "主要消费"
# weight: 10.01
stock_code = result['seccode']
stock_name = result['secname']
stock_id = china_stock_code_to_id(stock_code)
the_list.append({
'id': '{}_{}_{}'.format(entity_id, result['dateStr'], stock_id),
'entity_id': entity_id,
'entity_type': entity_type,
'exchange': exchange,
'code': code,
'name': name,
'timestamp': to_pd_timestamp(result['dateStr']),
'stock_id': stock_id,
'stock_code': stock_code,
'stock_name': stock_name,
'proportion': value_to_pct(result['weight'], 0),
'market_cap': value_multiply(result['freeMarketValue'], 100000000, 0)
})
if the_list:
df = pd.DataFrame.from_records(the_list)
return df
def record(self, entity, start, end, size, timestamps):
df = run_query(
table="finance.FUND_PORTFOLIO_STOCK",
conditions=f"pub_date#>=#{to_time_str(start)}&code#=#{entity.code}",
parse_dates=None,
)
if pd_is_not_null(df):
# id code period_start period_end pub_date report_type_id report_type rank symbol name shares market_cap proportion
# 0 8640569 159919 2018-07-01 2018-09-30 2018-10-26 403003 第三季度 1 601318 中国平安 19869239.0 1.361043e+09 7.09
# 1 8640570 159919 2018-07-01 2018-09-30 2018-10-26 403003 第三季度 2 600519 贵州茅台 921670.0 6.728191e+08 3.50
# 2 8640571 159919 2018-07-01 2018-09-30 2018-10-26 403003 第三季度 3 600036 招商银行 18918815.0 5.806184e+08 3.02
# 3 8640572 159919 2018-07-01 2018-09-30 2018-10-26 403003 第三季度 4 601166 兴业银行 22862332.0 3.646542e+08 1.90
df["timestamp"] = pd.to_datetime(df["pub_date"])
df.rename(columns={
"symbol": "stock_code",
"name": "stock_name"
},
inplace=True)
df["proportion"] = df["proportion"] * 0.01
df = portfolio_relate_stock(df, entity)
df["stock_id"] = df["stock_code"].apply(
lambda x: china_stock_code_to_id(x))
df["id"] = df[["entity_id", "stock_id", "pub_date",
"id"]].apply(lambda x: "_".join(x.astype(str)),
axis=1)
df["report_date"] = pd.to_datetime(df["period_end"])
df["report_period"] = df["report_type"].apply(
lambda x: jq_to_report_period(x))
df_to_db(df=df,
data_schema=self.data_schema,
provider=self.provider,
force_update=self.force_update)
# self.logger.info(df.tail())
self.logger.info(
f"persist etf {entity.code} portfolio success {df.iloc[-1]['pub_date']}"
)
return None
def record(self, entity, start, end, size, timestamps):
for page in range(1, 5):
resp = requests.get(
self.category_stocks_url.format(page, entity.code))
try:
if resp.text == 'null' or resp.text is None:
break
category_jsons = demjson.decode(resp.text)
the_list = []
for category in category_jsons:
stock_code = category['code']
stock_id = china_stock_code_to_id(stock_code)
block_id = entity.id
the_list.append({
'id': '{}_{}'.format(block_id, stock_id),
'entity_id': block_id,
'entity_type': 'block',
'exchange': entity.exchange,
'code': entity.code,
'name': entity.name,
'timestamp': now_pd_timestamp(),
'stock_id': stock_id,
'stock_code': stock_code,
'stock_name': category['name'],
})
if the_list:
df = pd.DataFrame.from_records(the_list)
df_to_db(data_schema=self.data_schema,
df=df,
provider=self.provider,
force_update=True)
self.logger.info('finish recording BlockStock:{},{}'.format(
entity.category, entity.name))
except Exception as e:
self.logger.error("error:,resp.text:", e, resp.text)
self.sleep()
def record(self, entity, start, end, size, timestamps):
# 忽略退市的
if entity.end_date:
return None
redundant_times = 1
while redundant_times > 0:
df = run_query(
table='finance.FUND_PORTFOLIO_STOCK',
conditions=
f'pub_date#>=#{to_time_str(start)}&code#=#{entity.code}',
parse_dates=None)
df = df.dropna()
if pd_is_not_null(df):
# data format
# id code period_start period_end pub_date report_type_id report_type rank symbol name shares market_cap proportion
# 0 8640569 159919 2018-07-01 2018-09-30 2018-10-26 403003 第三季度 1 601318 中国平安 19869239.0 1.361043e+09 7.09
# 1 8640570 159919 2018-07-01 2018-09-30 2018-10-26 403003 第三季度 2 600519 贵州茅台 921670.0 6.728191e+08 3.50
# 2 8640571 159919 2018-07-01 2018-09-30 2018-10-26 403003 第三季度 3 600036 招商银行 18918815.0 5.806184e+08 3.02
# 3 8640572 159919 2018-07-01 2018-09-30 2018-10-26 403003 第三季度 4 601166 兴业银行 22862332.0 3.646542e+08 1.90
df['timestamp'] = pd.to_datetime(df['pub_date'])
df.rename(columns={
'symbol': 'stock_code',
'name': 'stock_name'
},
inplace=True)
df['proportion'] = df['proportion'] * 0.01
df = portfolio_relate_stock(df, entity)
df['stock_id'] = df['stock_code'].apply(
lambda x: china_stock_code_to_id(x))
df['id'] = df[['entity_id', 'stock_id', 'pub_date',
'id']].apply(lambda x: '_'.join(x.astype(str)),
axis=1)
df['report_date'] = pd.to_datetime(df['period_end'])
df['report_period'] = df['report_type'].apply(
lambda x: jq_to_report_period(x))
saved = df_to_db(df=df,
data_schema=self.data_schema,
provider=self.provider,
force_update=self.force_update)
# 取不到非重复的数据
if saved == 0:
return None
# self.logger.info(df.tail())
self.logger.info(
f"persist fund {entity.code}({entity.name}) portfolio success {df.iloc[-1]['pub_date']}"
)
latest = df['timestamp'].max()
# 取到了最近两年的数据，再请求一次,确保取完最新的数据
if latest.year >= now_pd_timestamp().year - 1:
redundant_times = redundant_times - 1
start = latest
else:
return None
return None
