def fetch_szse_index_component(self, df: pd.DataFrame):
"""
抓取深证指数成分股
"""
query_url = 'http://www.szse.cn/api/report/ShowReport?SHOWTYPE=xlsx&CATALOGID=1747_zs&TABKEY=tab1&ZSDM={}'
for _, index in df.iterrows():
index_code = index['code']
url = query_url.format(index_code)
response = requests.get(url)
response_df = pd.read_excel(io.BytesIO(response.content),
dtype='str')
index_id = f'index_cn_{index_code}'
response_df = response_df[['证券代码']]
response_df['id'] = response_df['证券代码'].apply(
lambda x: f'{index_id}_{china_stock_code_to_id(str(x))}')
response_df['entity_id'] = response_df['id']
response_df['stock_id'] = response_df['证券代码'].apply(
lambda x: china_stock_code_to_id(str(x)))
response_df['index_id'] = index_id
response_df.drop('证券代码', axis=1, inplace=True)
df_to_db(data_schema=self.data_schema,
df=response_df,
provider=self.provider)
self.logger.info(f'{index["name"]} - {index_code} 成分股抓取完成...')
self.sleep()
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 run(self):
for category, url in self.category_map_url.items():
resp = requests.get(url)
results = json_callback_param(resp.text)
for result in results:
items = result.split(',')
code = items[1]
name = items[2]
id = 'index_cn_{}'.format(code)
if id in self.index_ids:
continue
self.session.add(
Index(id=id,
entity_id=id,
entity_type='index',
exchange='cn',
code=code,
name=name,
category=category.value))
self.session.commit()
indices = get_entities(session=self.session,
entity_type='index',
return_type='domain',
filters=[
Index.category.in_([
StockCategory.concept.value,
StockCategory.industry.value
])
],
provider=self.provider)
for index_item in indices:
resp = requests.get(
self.category_stocks_url.format(index_item.code, '1'))
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)
index_id = index_item.id
the_list.append({
'id': '{}_{}'.format(index_id, stock_id),
'index_id': index_id,
'stock_id': stock_id
})
if the_list:
df = pd.DataFrame.from_records(the_list)
df_to_db(data_schema=self.data_schema,
df=df,
provider=self.provider)
self.logger.info('finish recording index:{},{}'.format(
index_item.category, index_item.name))
except Exception as e:
self.logger.error("error:,resp.text:", e, resp.text)
self.sleep()
def fetch_csi_index_component(self, df: pd.DataFrame):
"""
抓取上证、中证指数成分股
"""
query_url = 'http://www.csindex.com.cn/uploads/file/autofile/cons/{}cons.xls'
for _, index in df.iterrows():
index_code = index['code']
url = query_url.format(index_code)
try:
response = requests.get(url)
response.raise_for_status()
except requests.HTTPError as error:
self.logger.error(f'{index["name"]} - {index_code} 成分股抓取错误 ({error})')
continue
response_df = pd.read_excel(io.BytesIO(response.content))
index_id = f'index_cn_{index_code}'
response_df = response_df[['成分券代码Constituent Code']].rename(columns={'成分券代码Constituent Code': 'stock_code'})
response_df['id'] = response_df['stock_code'].apply(lambda x: f'{index_id}_{china_stock_code_to_id(str(x))}')
response_df['stock_id'] = response_df['stock_code'].apply(lambda x: china_stock_code_to_id(str(x)))
response_df['index_id'] = index_id
response_df.drop('stock_code', axis=1, inplace=True)
df_to_db(data_schema=self.data_schema, df=response_df, provider=self.provider)
self.logger.info(f'{index["name"]} - {index_code} 成分股抓取完成...')
self.sleep()
def record(self, entity, start, end, size, timestamps):
q = query(finance.FUND_PORTFOLIO_STOCK).filter(finance.FUND_PORTFOLIO_STOCK.pub_date >= start).filter(
finance.FUND_PORTFOLIO_STOCK.code == entity.code)
df = finance.run_query(q)
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")
return None
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 = demjson.decode(response.text)
response_df = pd.DataFrame(response_dict.get('result', []))
etf_code = etf['FUND_ID']
index_id = f'index_sh_{etf_code}'
response_df = response_df[['instrumentId']]
response_df['id'] = response_df['instrumentId'].apply(
lambda code: f'{index_id}_{china_stock_code_to_id(code)}')
response_df['stock_id'] = response_df['instrumentId'].apply(
lambda code: china_stock_code_to_id(code))
response_df['index_id'] = index_id
response_df.drop('instrumentId', axis=1, inplace=True)
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 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 run(self):
# get stock category from sina
for category, url in self.category_map_url.items():
resp = requests.get(url)
resp.encoding = 'GBK'
tmp_str = resp.text
json_str = tmp_str[tmp_str.index('{'):tmp_str.index('}') + 1]
tmp_json = json.loads(json_str)
for code in tmp_json:
name = tmp_json[code].split(',')[1]
id = 'index_cn_{}'.format(code)
if id in self.index_ids:
continue
self.session.add(Index(id=id, entity_type='index', exchange='cn', code=code, name=name,
category=category.value))
self.session.commit()
indices = get_entities(session=self.session, entity_type='index',
return_type='domain', filters=[
Index.category.in_([StockCategory.industry.value, StockCategory.concept.value])],
provider=self.provider)
for index_item in indices:
for page in range(1, 5):
resp = requests.get(self.category_stocks_url.format(page, index_item.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)
index_id = index_item.id
the_list.append({
'id': '{}_{}'.format(index_id, stock_id),
'index_id': index_id,
'stock_id': stock_id
})
if the_list:
df = pd.DataFrame.from_records(the_list)
df_to_db(data_schema=self.data_schema, df=df, provider=self.provider)
self.logger.info('finish recording index:{},{}'.format(index_item.category, index_item.name))
except Exception as e:
self.logger.error("error:,resp.text:", e, resp.text)
self.sleep()
def fetch_cni_index_component(self, df: pd.DataFrame):
"""
抓取国证指数成分股
"""
query_url = 'http://www.cnindex.com.cn/docs/yb_{}.xls'
for _, index in df.iterrows():
index_code = index['code']
url = query_url.format(index_code)
try:
response = requests.get(url)
response.raise_for_status()
except requests.HTTPError as error:
self.logger.error(
f'{index["name"]} - {index_code} 成分股抓取错误 ({error})')
continue
response_df = pd.read_excel(io.BytesIO(response.content),
dtype='str')
index_id = f'index_cn_{index_code}'
try:
response_df = response_df[['样本股代码']]
except KeyError:
response_df = response_df[['证券代码']]
response_df['entity_id'] = index_id
response_df['entity_type'] = 'index'
response_df['exchange'] = 'cn'
response_df['code'] = index_code
response_df['name'] = index['name']
response_df['timestamp'] = now_pd_timestamp()
response_df.columns = ['stock_code']
response_df['stock_id'] = response_df['stock_code'].apply(
lambda x: china_stock_code_to_id(str(x)))
response_df['id'] = response_df['stock_id'].apply(
lambda x: f'{index_id}_{x}')
df_to_db(data_schema=self.data_schema,
df=response_df,
provider=self.provider)
self.logger.info(f'{index["name"]} - {index_code} 成分股抓取完成...')
self.sleep()
def record(self, entity, start, end, size, timestamps):
resp = requests.get(self.category_stocks_url.format(entity.code, '1'))
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()
