def test_get_china_stock_list():
print(settings.FOOLTRADER_STORE_PATH)
df = quote.get_security_list('stock', exchanges=['sh', 'sz'])
assert '000001' in df.index
assert '金融行业' == df.loc['000001', 'sinaIndustry']
df = quote.get_security_list('stock', exchanges=['sh'])
assert '600000' in df.index
assert '金融行业' == df.loc['600000', 'sinaIndustry']
df = quote.get_security_list('stock',
exchanges=['sh', 'sz'],
start='000338',
end='600388')
assert '000338' in df.index
assert '600388' in df.index
assert '600389' not in df.index
df = quote.get_security_list('stock',
exchanges=['sh', 'sz'],
codes=['300027', '000002'])
assert len(df.index) == 2
df = quote.get_security_list('stock', exchanges=['sh', 'sz'], mode='es')
assert type(df.loc['600004', 'sinaArea']) == list
assert '广州' in (df.loc['600004', 'sinaArea'])
assert '广东' in (df.loc['600004', 'sinaArea'])
def init_env():
if not os.path.exists(FOOLTRADER_STORE_PATH):
print("{} is a wrong path")
print("please set env FOOLTRADER_STORE_PATH to working path or set it in settings.py")
else:
# 初始化股票文件夹
for _, item in get_security_list(exchanges=EXCHANGE_LIST_COL).iterrows():
mkdir_for_stock(item)
# 初始化指数文件夹
for _, item in get_security_list(security_type='index', exchanges=['sh', 'sz', 'nasdaq']).iterrows():
kdata_dir = get_kdata_dir(item)
if not os.path.exists(kdata_dir):
os.makedirs(kdata_dir)
# 初始化期货文件夹
for exchange in ['shfe', 'dce', 'zce']:
exchange_cache_dir = get_exchange_cache_dir(security_type='future', exchange=exchange)
if not os.path.exists(exchange_cache_dir):
os.makedirs(exchange_cache_dir)
exchange_cache_dir = get_exchange_cache_dir(security_type='future', exchange='shfe',
the_year=datetime.today().year,
data_type="day_kdata")
if not os.path.exists(exchange_cache_dir):
os.makedirs(exchange_cache_dir)
exchange_dir = get_exchange_dir(security_type='future', exchange=exchange)
if not os.path.exists(exchange_dir):
os.makedirs(exchange_dir)
def init_env():
if not os.path.exists(settings.FILES_STORE):
os.makedirs(settings.FILES_STORE)
# 初始化股票文件夹
for _, item in get_security_list(exchanges=EXCHANGE_LIST_COL).iterrows():
mkdir_for_security(item)
# 初始化指数文件夹
for _, item in get_security_list(security_type='index', exchanges=['sh', 'sz', 'nasdaq']).iterrows():
kdata_dir = get_kdata_dir(item)
if not os.path.exists(kdata_dir):
os.makedirs(kdata_dir)
def init_env():
if not os.path.exists(settings.FILES_STORE):
os.makedirs(settings.FILES_STORE)
# 初始化股票文件夹
for _, item in get_security_list().iterrows():
mkdir_for_security(item)
# 初始化指数文件夹
for _, item in get_security_list(security_type='index').iterrows():
kdata_dir = get_kdata_dir(item)
if not os.path.exists(kdata_dir):
os.makedirs(kdata_dir)
def init_env():
if not os.path.exists(settings.FOOLTRADER_STORE_PATH):
os.makedirs(settings.FOOLTRADER_STORE_PATH)
# 初始化股票文件夹
for _, item in get_security_list(exchanges=EXCHANGE_LIST_COL).iterrows():
mkdir_for_security(item)
# 初始化指数文件夹
for _, item in get_security_list(security_type='index',
exchanges=['sh', 'sz',
'nasdaq']).iterrows():
kdata_dir = get_kdata_dir(item)
if not os.path.exists(kdata_dir):
os.makedirs(kdata_dir)
def newhighergenerator(start_date,fuquan='qfq',source='163',period=20):
baseindex = 'index_sh_000001'
df = quote.get_kdata(baseindex,start_date=start_date,source=source)
#df = quote.get_kdata('index_sh_000001',start_date='2017-05-10',source='163')
dh = pd.DataFrame(0,index=df.index,columns=['total']) #暂时只添加total，后续需要添加各个市场total
#stocklist = quote.get_security_list(security_type='stock', mode='simple')
stocklist = quote.get_security_list(security_type='stock',start='600000',end='600030', mode='simple')
for _, item in stocklist.iterrows():
print("caculating {}".format(item.id))
for ts in dh.index:
if((ts-datetime.datetime.strptime(item.listDate,'%Y-%m-%d')).days<period):
dh.at[ts,item.id] = 0
else:
ds = quote.get_kdata(item.id,fuquan=fuquan)
indexlist = list(ds['timestamp'])
tsstr = ts.strftime('%Y-%m-%d')
if(tsstr in indexlist):
pos = list(ds['timestamp']).index(ts.strftime('%Y-%m-%d'))
if (ds['close'][pos] >= max(ds['close'][pos -period+1 :pos + 1])):
dh.at[ts, item.id] = 1
else:
dh.at[ts, item.id] = 0
else:
dh.at[ts,item.id] = 0
df['total'] = dh.apply(lambda x:x.sum(),axis=1)
df['index_c'] = df['close']
dh.to_csv('newhigher.csv')
return True
def cash_flow_statement_to_es(force=False):
es_index_mapping('cash_flow_statement', CashFlowStatement)
for _, security_item in get_security_list().iterrows():
try:
start_date = None
if not force:
query = {"term": {"securityId": ""}}
query["term"]["securityId"] = security_item["id"]
latest_record = es_get_latest_record(
index='cash_flow_statement',
time_field='reportDate',
query=query)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['reportDate']
for json_object in get_cash_flow_statement_items(
security_item, start_date=start_date):
if start_date and is_same_date(start_date,
json_object['reportDate']):
continue
cash_flow_statement = CashFlowStatement(
meta={'id': json_object['id']})
fill_doc_type(cash_flow_statement, json_object)
cash_flow_statement.save()
except Exception as e:
logger.warn("wrong CashFlowStatement:{},error:{}", security_item,
e)
def security_meta_to_es(security_type='cryptocurrency', force=False):
if security_type == 'cryptocurrency':
doc_type = CryptoCurrencyMeta
es_index_mapping('crypto_currency_meta', doc_type)
start_date = None
if not force:
latest_record = es_get_latest_record('crypto_currency_meta',
time_field='listDate')
logger.info("latest_record:{}".format(latest_record))
if latest_record and 'listDate' in latest_record:
start_date = latest_record['listDate']
actions = []
for _, item in get_security_list(security_type=security_type).iterrows():
if start_date and item['listDate'] and is_same_date(
start_date, item['listDate']):
continue
try:
security_meta = doc_type(meta={'id': item['id']})
fill_doc_type(security_meta, json.loads(item.to_json()))
actions.append(security_meta.to_dict(include_meta=True))
except Exception as e:
logger.warn("wrong SecurityItem:{},error:{}", item, e)
if actions:
resp = elasticsearch.helpers.bulk(es_client, actions)
logger.info(resp)
def stock_kdata_to_es(start='000001', end='666666', force=False):
for _, security_item in get_security_list(start=start, end=end).iterrows():
# 创建索引
index_name = get_es_kdata_index(security_item['id'])
es_index_mapping(index_name, StockKData)
start_date = None
if not force:
latest_record = es_get_latest_record(index_name)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['timestamp']
for _, kdata_item in get_kdata(security_item,
start_date=start_date).iterrows():
if start_date and is_same_date(start_date,
kdata_item['timestamp']):
continue
try:
id = '{}_{}'.format(kdata_item['securityId'],
kdata_item['timestamp'])
kdata = StockKData(meta={'id': id}, id=id)
fill_doc_type(kdata, json.loads(kdata_item.to_json()))
kdata.save(index=index_name)
except Exception as e:
logger.warn("wrong KdataDay:{},error:{}", kdata_item, e)
def crawl_index_quote():
for _, security_item in get_security_list(security_type='index').iterrows():
# 抓取日K线
logger.info("{} get index kdata start".format(security_item['code']))
start_date = get_latest_download_trading_date(security_item, source='163')
end_date = pd.Timestamp.today()
if start_date > end_date:
logger.info("{} kdata is ok".format(security_item['code']))
else:
process_crawl(StockKdataSpider163, {"security_item": security_item,
"start_date": start_date,
"end_date": end_date})
logger.info("{} get index kdata from 163 end".format(security_item['code']))
# 获取市场概况数据[上海,深圳,中小板,创业板]
if security_item['id'] in ['index_sh_000001', 'index_sz_399106', 'index_sz_399005', 'index_sz_399006']:
# if security_item['id'] in ['index_sz_399106', 'index_sz_399005', 'index_sz_399006']:
df = get_kdata(security_item=security_item)
df = df[df['turnoverRate'].isna() | df['tCap'].isna() | df['mCap'].isna() | df[
'pe'].isna()]
if not df.empty:
dates = df.index.strftime('%Y-%m-%d').tolist()
# if security_item['id'] == 'index_sz_399106':
# dates = [the_date for the_date in dates if
# pd.Timestamp(the_date).date().year >= 2018]
if dates:
process_crawl(StockSummarySpider, {"security_item": security_item,
"the_dates": dates})
def crawl_usa_stock_data():
# crawl the stock list
process_crawl(AmericaListSpider, {})
# crawl the kdata
for _, security_item in get_security_list(security_type='stock', exchanges=['nasdaq'],
codes=US_STOCK_CODES).iterrows():
process_crawl(AmericaStockKdataSpider, {"security_item": security_item})
def legacy_kdata_to_csv():
for index, security_item in get_security_list().iterrows():
for fuquan in (True, False):
dir = get_kdata_dir_old(security_item, fuquan)
if os.path.exists(dir):
files = [os.path.join(dir, f) for f in os.listdir(dir) if
('all' not in f and 'json' in f and os.path.isfile(os.path.join(dir, f)))]
for f in files:
tmp = os.path.basename(f).split('_')
if fuquan:
csv_path = get_kdata_path(security_item, tmp[0], tmp[1], 'hfq')
if not os.path.exists(csv_path):
df = pd.read_json(f, dtype={'code': str})
logger.info("{} to {}".format(f, csv_path))
df = df.loc[:,
['timestamp', 'code', 'low', 'open', 'close', 'high', 'volume', 'turnover',
'securityId',
'fuquan']]
df.columns = KDATA_COLUMN_FQ
df.to_csv(csv_path, index=False)
else:
csv_path = get_kdata_path(security_item, tmp[0], tmp[1], 'bfq')
if not os.path.exists(csv_path):
df = pd.read_json(f, dtype={'code': str})
logger.info("{} to {}".format(f, csv_path))
df = df.loc[:, KDATA_COLUMN]
df.to_csv(csv_path, index=False)
def stock_kdata_to_es(start='000001', end='666666', codes=US_STOCK_CODES, force=False):
for _, security_item in get_security_list(start=start, end=end, exchanges=['sh', 'sz', 'nasdaq'],
codes=codes).iterrows():
# 创建索引
index_name = get_es_kdata_index(security_item['type'], security_item['exchange'])
es_index_mapping(index_name, StockKData)
start_date = None
if not force:
query = {
"term": {"securityId": ""}
}
query["term"]["securityId"] = security_item["id"]
latest_record = es_get_latest_record(index_name, query=query)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['timestamp']
actions = []
for _, kdata_item in get_kdata(security_item, start_date=start_date).iterrows():
if start_date and is_same_date(start_date, kdata_item['timestamp']):
continue
try:
id = '{}_{}'.format(kdata_item['securityId'], kdata_item['timestamp'])
kdata = StockKData(meta={'id': id}, id=id)
kdata.meta['index'] = index_name
fill_doc_type(kdata, json.loads(kdata_item.to_json()))
# kdata.save(index=index_name)
actions.append(kdata.to_dict(include_meta=True))
except Exception as e:
logger.warn("wrong KdataDay:{},error:{}", kdata_item, e)
if actions:
resp = elasticsearch.helpers.bulk(es, actions)
logger.info(resp)
def start_requests(self):
security_item = self.settings.get("security_item")
if security_item is not None:
item = security_item
data_url = self.get_finance_url(item['code'])
data_path = get_finance_path(item)
yield Request(url=data_url,
meta={
'path': data_path,
'item': item
},
callback=self.download_finance_csv)
else:
for _, item in get_security_list(exchanges=['nasdaq']).iterrows():
data_url = self.get_finance_url(item['code'])
data_path = get_finance_path(item)
yield Request(url=data_url,
meta={
'path': data_path,
'item': item
},
callback=self.download_finance_csv)
def income_statement_to_es(force=False):
es_index_mapping('income_statement', IncomeStatement)
for _, security_item in get_security_list().iterrows():
try:
start_date = None
if not force:
query = {"term": {"securityId": ""}}
query["term"]["securityId"] = security_item["id"]
latest_record = es_get_latest_record(index='income_statement',
time_field='reportDate',
query=query)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['reportDate']
actions = []
for json_object in get_income_statement_items(
security_item, start_date=start_date):
if start_date and is_same_date(start_date,
json_object['reportDate']):
continue
income_statement = IncomeStatement(
meta={'id': json_object['id']})
fill_doc_type(income_statement, json_object)
# income_statement.save()
actions.append(income_statement.to_dict(include_meta=True))
if actions:
resp = elasticsearch.helpers.bulk(es, actions)
logger.info(resp)
except Exception as e:
logger.warn("wrong IncomeStatement:{},error:{}", security_item, e)
def check_convert_result():
for index, security_item in get_security_list().iterrows():
for fuquan in ('bfq', 'hfq'):
dayk_path = get_kdata_path(security_item, fuquan=fuquan)
if os.path.exists(dayk_path):
df_result = pd.read_csv(dayk_path)
if fuquan == 'hfq':
df = pd.DataFrame(columns=data_contract.KDATA_COLUMN_FQ)
else:
df = pd.DataFrame(columns=data_contract.KDATA_COLUMN)
dir = get_kdata_dir(security_item, fuquan=fuquan)
if os.path.exists(dir):
files = [
os.path.join(dir, f) for f in os.listdir(dir)
if ('day' not in f and 'csv' in f
and os.path.isfile(os.path.join(dir, f)))
]
for f in files:
df = df.append(pd.read_csv(f), ignore_index=True)
assert_df(df, df_result)
logger.info("{} merge as one ok".format(
security_item['code']))
def cash_flow_statement_to_es(force=False):
es_index_mapping('cash_flow_statement', CashFlowStatement)
for _, security_item in get_security_list().iterrows():
try:
start_date = None
if not force:
query = {
"term": {"securityId": ""}
}
query["term"]["securityId"] = security_item["id"]
latest_record = es_get_latest_record(index='cash_flow_statement', time_field='reportDate', query=query)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['reportDate']
actions = []
for json_object in get_cash_flow_statement_items(security_item, start_date=start_date):
if start_date and is_same_date(start_date, json_object['reportDate']):
continue
cash_flow_statement = CashFlowStatement(meta={'id': json_object['id']})
fill_doc_type(cash_flow_statement, json_object)
# cash_flow_statement.save()
actions.append(cash_flow_statement.to_dict(include_meta=True))
if actions:
resp = elasticsearch.helpers.bulk(es, actions)
logger.info(resp)
except Exception as e:
logger.warn("wrong CashFlowStatement:{},error:{}", security_item, e)
def usa_stock_finance_to_es(force=False):
es_index_mapping('finance_summary', FinanceSummary)
for _, security_item in get_security_list(exchanges=['nasdaq'], codes=US_STOCK_CODES).iterrows():
try:
start_date = None
if not force:
query = {
"term": {"securityId": ""}
}
query["term"]["securityId"] = security_item["id"]
latest_record = es_get_latest_record(index='finance_summary', time_field='reportDate', query=query)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['reportDate']
actions = []
for _, json_object in get_finance_summary_items(security_item, start_date=start_date).iterrows():
if start_date and is_same_date(start_date, json_object['reportDate']):
continue
finance_summary = FinanceSummary(meta={'id': json_object['id']})
fill_doc_type(finance_summary, json_object.to_dict())
actions.append(finance_summary.to_dict(include_meta=True))
if actions:
resp = elasticsearch.helpers.bulk(es, actions)
logger.info(resp)
except Exception as e:
logger.warn("wrong FinanceSummary:{},error:{}", security_item, e)
def stock_meta_to_es(force=False):
es_index_mapping('stock_meta', StockMeta)
start_date = None
if not force:
latest_record = es_get_latest_record('stock_meta',
time_field='listDate')
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['listDate']
actions = []
for _, item in get_security_list(mode='es',
start_date=start_date,
exchanges=EXCHANGE_LIST_COL).iterrows():
if start_date and is_same_date(start_date, item['listDate']):
continue
try:
stock_meta = StockMeta(meta={'id': item['id']})
fill_doc_type(stock_meta, json.loads(item.to_json()))
actions.append(stock_meta.to_dict(include_meta=True))
except Exception as e:
logger.warn("wrong SecurityItem:{},error:{}", item, e)
if actions:
resp = elasticsearch.helpers.bulk(es, actions)
logger.info(resp)
def usa_stock_finance_to_es(force=False):
es_index_mapping('finance_summary', FinanceSummary)
for _, security_item in get_security_list(exchanges=['nasdaq'],
codes=US_STOCK_CODES).iterrows():
try:
start_date = None
if not force:
query = {"term": {"securityId": ""}}
query["term"]["securityId"] = security_item["id"]
latest_record = es_get_latest_record(index='finance_summary',
time_field='reportDate',
query=query)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['reportDate']
actions = []
for _, json_object in get_finance_summary_items(
security_item, start_date=start_date).iterrows():
if start_date and is_same_date(start_date,
json_object['reportDate']):
continue
finance_summary = FinanceSummary(
meta={'id': json_object['id']})
fill_doc_type(finance_summary, json_object.to_dict())
actions.append(finance_summary.to_dict(include_meta=True))
if actions:
resp = elasticsearch.helpers.bulk(es, actions)
logger.info(resp)
except Exception as e:
logger.warn("wrong FinanceSummary:{},error:{}", security_item, e)
def stock_kdata_to_es(start='000001', end='666666', force=False):
for _, security_item in get_security_list(start=start, end=end).iterrows():
# 创建索引
index_name = get_es_kdata_index(security_item['type'],
security_item['exchange'])
es_index_mapping(index_name, StockKData)
start_date = None
if not force:
query = {"term": {"securityId": ""}}
query["term"]["securityId"] = security_item["id"]
latest_record = es_get_latest_record(index_name, query=query)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['timestamp']
actions = []
for _, kdata_item in get_kdata(security_item,
start_date=start_date).iterrows():
if start_date and is_same_date(start_date,
kdata_item['timestamp']):
continue
try:
id = '{}_{}'.format(kdata_item['securityId'],
kdata_item['timestamp'])
kdata = StockKData(meta={'id': id}, id=id)
fill_doc_type(kdata, json.loads(kdata_item.to_json()))
# kdata.save(index=index_name)
actions.append(kdata.to_dict(include_meta=True))
except Exception as e:
logger.warn("wrong KdataDay:{},error:{}", kdata_item, e)
if actions:
resp = elasticsearch.helpers.bulk(es, actions)
logger.info(resp)
def remove_old_kdata():
for index, security_item in get_security_list().iterrows():
for fuquan in (True, False):
dir = get_kdata_dir_old(security_item, fuquan)
if os.path.exists(dir):
if fuquan:
logger.info("remove {}".format(dir))
shutil.rmtree(dir)
def remove_old_kdata():
for index, security_item in get_security_list().iterrows():
for fuquan in (True, False):
dir = get_kdata_dir_old(security_item, fuquan)
if os.path.exists(dir):
if fuquan:
logger.info("remove {}".format(dir))
shutil.rmtree(dir)
def start_requests(self):
item = self.settings.get("security_item")
if item is not None:
for request in self.yield_request(item):
yield request
else:
for _, item in get_security_list().iterrows():
for request in self.yield_request(item):
yield request
def kdata_to_kafka(fuquan):
for _, security_item in get_security_list().iterrows():
for _, kdata_item in get_kdata(security_item, source='sina', fuquan=fuquan).iterrows():
the_json = kdata_item.to_json(force_ascii=False)
producer.send(get_kafka_kdata_topic(security_item['id'], fuquan),
bytes(the_json, encoding='utf8'),
timestamp_ms=int(datetime.datetime.strptime(kdata_item['timestamp'],
TIME_FORMAT_DAY).timestamp()))
logger.debug("kdata_to_kafka {}".format(the_json))
def start_requests(self):
security_item = self.settings.get("security_item")
if security_item is not None:
for request in self.yield_request(security_item):
yield request
else:
for _, item in get_security_list().iterrows():
for request in self.yield_request(item):
yield request
def start_requests(self):
for _, item in get_security_list().iterrows():
url = self.get_forecast_url(item['code'])
yield Request(url=url,
headers=DEFAULT_KDATA_HEADER,
meta={
'item': item,
},
callback=self.download_forecast_data)
def remove_old_tick():
for index, security_item in get_security_list().iterrows():
dir = get_tick_dir(security_item)
if os.path.exists(dir):
files = [os.path.join(dir, f) for f in os.listdir(dir) if
('xls' in f and 'lock' not in f and 'error' not in f and os.path.isfile(os.path.join(dir, f)))]
for f in files:
logger.info("remove {}".format(f))
os.remove(f)
def start_requests(self):
item = self.settings.get("security_item")
trading_dates = self.settings.get("trading_dates")
if item is not None:
for request in self.yield_request(item, trading_dates):
yield request
else:
for _, item in get_security_list().iterrows():
for request in self.yield_request(item):
yield request
def start_requests(self):
item = self.settings.get("security_item")
if item is not None:
for request in self.yield_request(item):
yield request
else:
for _, item in get_security_list(start=STOCK_START_CODE,
end=STOCK_END_CODE).iterrows():
for request in self.yield_request(item):
yield request
def start_requests(self):
security_item = self.settings.get("security_item")
finance_type = self.settings.get("report_type")
if security_item is not None:
for request in self.yield_request(security_item, finance_type):
yield request
else:
for _, item in get_security_list().iterrows():
for request in self.yield_request(item):
yield request
def init_env():
if not os.path.exists(FOOLTRADER_STORE_PATH):
print("{} is a wrong path")
print(
"please set env FOOLTRADER_STORE_PATH to working path or set it in settings.py"
)
else:
# 初始化股票文件夹
for _, item in get_security_list(
exchanges=EXCHANGE_LIST_COL).iterrows():
mkdir_for_security(item)
# 初始化指数文件夹
for _, item in get_security_list(security_type='index',
exchanges=['sh', 'sz',
'nasdaq']).iterrows():
kdata_dir = get_kdata_dir(item)
if not os.path.exists(kdata_dir):
os.makedirs(kdata_dir)
def tick_to_kafka():
for _, security_item in get_security_list().iterrows():
for df in get_ticks(security_item):
for _, tick_item in df.iterrows():
the_json = tick_item.to_json(force_ascii=False)
producer.send(get_kafka_tick_topic(security_item['id']),
bytes(the_json, encoding='utf8'),
timestamp_ms=int(datetime.datetime.strptime(tick_item['timestamp'],
TIME_FORMAT_SEC).timestamp()))
logger.debug("tick_to_kafka {}".format(the_json))
def crawl_finance_data(start_code=STOCK_START_CODE, end_code=STOCK_END_CODE):
for _, security_item in get_security_list(start=start_code, end=end_code).iterrows():
try:
# 先抓事件,有些后续抓取依赖事件
process_crawl(StockFinanceReportEventSpider, {"security_item": security_item})
current_report_date = get_report_date()
# 资产负债表
path = get_balance_sheet_path(security_item)
if not os.path.exists(path):
process_crawl(StockFinanceSpider, {"security_item": security_item,
"report_type": "balance_sheet"})
else:
for balance_sheet_item in get_balance_sheet_items(security_item):
# 当前报告期还没抓取
if balance_sheet_item['reportDate'] != current_report_date:
# 报告出来了
df = event.get_finance_report_event(security_item, index='reportDate')
if current_report_date in df.index:
process_crawl(StockFinanceSpider, {"security_item": security_item,
"report_type": "balance_sheet"})
break
# 利润表
path = get_income_statement_path(security_item)
if not os.path.exists(path):
process_crawl(StockFinanceSpider, {"security_item": security_item,
"report_type": "income_statement"})
else:
for balance_sheet_item in get_income_statement_items(security_item):
if balance_sheet_item['reportDate'] != current_report_date:
# 报告出来了
df = event.get_finance_report_event(security_item, index='reportDate')
if current_report_date in df.index:
process_crawl(StockFinanceSpider, {"security_item": security_item,
"report_type": "income_statement"})
break
# 现金流量表
path = get_cash_flow_statement_path(security_item)
if not os.path.exists(path):
process_crawl(StockFinanceSpider, {"security_item": security_item,
"report_type": "cash_flow"})
else:
for balance_sheet_item in get_cash_flow_statement_items(security_item):
if balance_sheet_item['reportDate'] != current_report_date:
# 报告出来了
df = event.get_finance_report_event(security_item, index='reportDate')
if current_report_date in df.index:
process_crawl(StockFinanceSpider, {"security_item": security_item,
"report_type": "cash_flow"})
break
except Exception as e:
logger.error(e)
def start_requests(self):
item = self.settings.get("security_item")
start_date = self.settings.get("start_date")
end_date = self.settings.get("end_date")
if item is not None:
for request in self.yield_request(item, start_date, end_date):
yield request
else:
for _, item in get_security_list().iterrows():
for request in self.yield_request(item):
yield request
def kdata_to_es(start=None,
end=None,
security_type='stock',
exchanges=['sh', 'sz'],
force=False):
if security_type == 'stock':
doc_type = StockKData
elif security_type == 'index':
doc_type = IndexKData
elif security_type == 'cryptocurrency':
doc_type = CryptoCurrencyKData
for _, security_item in get_security_list(security_type=security_type,
exchanges=exchanges,
start=start,
end=end).iterrows():
# 创建索引
index_name = get_es_kdata_index(security_item['type'],
security_item['exchange'])
es_index_mapping(index_name, doc_type)
start_date = None
if not force:
query = {"term": {"securityId": ""}}
query["term"]["securityId"] = security_item["id"]
latest_record = es_get_latest_record(index_name, query=query)
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['timestamp']
actions = []
df_kdata = get_kdata(security_item, start_date=start_date)
for _, kdata_item in df_kdata.iterrows():
if start_date and is_same_date(start_date,
kdata_item['timestamp']):
continue
try:
id = '{}_{}'.format(kdata_item['securityId'],
kdata_item['timestamp'])
kdata = doc_type(meta={'id': id}, id=id)
kdata.meta['index'] = index_name
kdata_json = json.loads(kdata_item.to_json())
fill_doc_type(kdata, kdata_json)
# kdata.save(index=index_name)
actions.append(kdata.to_dict(include_meta=True))
except Exception as e:
logger.warn("wrong KdataDay:{},error:{}", kdata_item, e)
if actions:
resp = elasticsearch.helpers.bulk(es_client, actions)
logger.info(resp)
def remove_old_tick():
for index, security_item in get_security_list().iterrows():
dir = get_tick_dir(security_item)
if os.path.exists(dir):
files = [
os.path.join(dir, f) for f in os.listdir(dir)
if ('xls' in f and 'lock' not in f and 'error' not in f
and os.path.isfile(os.path.join(dir, f)))
]
for f in files:
logger.info("remove {}".format(f))
os.remove(f)
def tick_to_kafka():
for _, security_item in get_security_list().iterrows():
for df in get_ticks(security_item):
for _, tick_item in df.iterrows():
the_json = tick_item.to_json(force_ascii=False)
producer.send(get_kafka_tick_topic(security_item['id']),
bytes(the_json, encoding='utf8'),
timestamp_ms=int(
datetime.datetime.strptime(
tick_item['timestamp'],
TIME_FORMAT_SEC).timestamp()))
logger.debug("tick_to_kafka {}".format(the_json))
def forecast_event_to_csv():
for index, security_item in get_security_list().iterrows():
the_path = get_forecast_event_path(security_item)
if os.path.exists(the_path):
df = pd.read_json(get_forecast_event_path(security_item))
df = df.rename(columns={'reportDate': 'timestamp'})
df = df.loc[:, EVENT_STOCK_FINANCE_FORECAST_COL]
df.to_csv(get_finance_forecast_event_path(security_item),
index=False)
logger.info("transform {} forecast event".format(
security_item['code']))
os.remove(the_path)
def start_requests(self):
self.category_type = self.settings.get("category_type")
self.sh_df = get_security_list(exchanges=['sh'])
self.sz_df = get_security_list(exchanges=['sz'])
self.file_lock = threading.RLock()
# 清除老数据
self.sh_df[self.category_type] = None
self.sz_df[self.category_type] = None
if self.category_type == 'sinaIndustry':
url = 'http://vip.stock.finance.sina.com.cn/q/view/newSinaHy.php'
elif self.category_type == 'sinaConcept':
url = 'http://money.finance.sina.com.cn/q/view/newFLJK.php?param=class'
elif self.category_type == 'sinaArea':
url = 'http://money.finance.sina.com.cn/q/view/newFLJK.php?param=area'
else:
return
yield Request(url=url, callback=self.download_sina_category)
def kdata_to_kafka(fuquan):
for _, security_item in get_security_list().iterrows():
for _, kdata_item in get_kdata(security_item,
source='sina',
fuquan=fuquan).iterrows():
the_json = kdata_item.to_json(force_ascii=False)
producer.send(get_kafka_kdata_topic(security_item['id'], fuquan),
bytes(the_json, encoding='utf8'),
timestamp_ms=int(
datetime.datetime.strptime(
kdata_item['timestamp'],
TIME_FORMAT_DAY).timestamp()))
logger.debug("kdata_to_kafka {}".format(the_json))
def check_result():
for index, security_item in get_security_list().iterrows():
for fuquan in ('bfq', 'hfq'):
dayk_path = get_kdata_path(security_item, fuquan=fuquan)
if not os.path.exists(dayk_path):
logger.warn(get_security_dir(security_item))
dir = get_tick_dir(security_item)
if os.path.exists(dir):
files = [os.path.join(dir, f) for f in os.listdir(dir) if
('csv' in f and os.path.isfile(os.path.join(dir, f)))]
if not files:
logger.warn(get_security_dir(security_item))
def forecast_event_to_es():
for _, security_item in get_security_list().iterrows():
# 创建索引
index_name = get_es_forecast_event_index(security_item['id'])
es_index_mapping(index_name, ForecastEvent)
for json_object in get_forecast_items(security_item):
try:
forcast_event = ForecastEvent(meta={'id': json_object['id']})
fill_doc_type(forcast_event, json_object)
forcast_event.save()
except Exception as e:
logger.warn("wrong ForecastEvent:{},error:{}", json_object, e)
def start_requests(self):
# 两种模式:
# 1)item,trading_dates不指定,用于全量下载数据
# 2)指定，用于修复
item = self.settings.get("security_item")
trading_dates = self.settings.get("trading_dates")
fuquan = self.settings.get("fuquan")
if item is not None:
for request in self.yield_request(item, trading_dates, fuquan):
yield request
else:
for _, item in get_security_list().iterrows():
for request in self.yield_request(item):
yield request
def handle_error_tick():
for index, security_item in get_security_list().iterrows():
dir = get_tick_dir(security_item)
if os.path.exists(dir):
files = [os.path.join(dir, f) for f in os.listdir(dir) if
(('fatal' in f or 'error' in f) and os.path.isfile(os.path.join(dir, f)))]
for f in files:
try:
the_date = get_file_name(f)
csv_path = get_tick_path(security_item, the_date)
if not os.path.exists(csv_path):
logger.info("{} to {}".format(f, csv_path))
sina_tick_to_csv(security_item, f, the_date)
except Exception as e:
logger.warn(e)
os.rename(f, f + ".fatal")
def start_requests(self):
for _, item in get_security_list().iterrows():
for fuquan in ['hfq', 'bfq']:
data_path = get_kdata_path(item, fuquan=fuquan, source='ths')
data_exist = os.path.isfile(data_path)
if not data_exist or True:
# get day k data
if fuquan == 'hfq':
flag = 2
else:
flag = 0
url = self.get_k_data_url(item['code'], flag)
yield Request(url=url, headers=TONGHUASHUN_KDATA_HEADER,
meta={'path': data_path, 'item': item, 'fuquan': fuquan},
callback=self.download_day_k_data)
else:
self.logger.info("{} kdata existed".format(item['code']))
def start_requests(self):
security_item = self.settings.get("security_item")
if security_item is not None:
item = security_item
data_url = self.get_finance_url(item['code'])
data_path = get_finance_path(item)
yield Request(url=data_url,
meta={'path': data_path,
'item': item},
callback=self.download_finance_csv)
else:
for _, item in get_security_list(exchanges=['nasdaq']).iterrows():
data_url = self.get_finance_url(item['code'])
data_path = get_finance_path(item)
yield Request(url=data_url,
meta={'path': data_path,
'item': item},
callback=self.download_finance_csv)
def start_requests(self):
item = self.settings.get("security_item")
start_date = self.settings.get("start_date")
end_date = self.settings.get("end_date")
today = pd.Timestamp.today()
the_years = None
if start_date and end_date:
if (today - start_date).days <= 5:
pass
else:
the_years = range(start_date.year, end_date.year + 1)
if item is not None and the_years:
for request in self.yield_request(item, the_years):
yield request
else:
for _, item in get_security_list(exchanges=['nasdaq'], codes=US_STOCK_CODES).iterrows():
for request in self.yield_request(item):
yield request
def stock_meta_to_es(force=False):
es_index_mapping('stock_meta', StockMeta)
start_date = None
if not force:
latest_record = es_get_latest_record('stock_meta', time_field='listDate')
logger.info("latest_record:{}".format(latest_record))
if latest_record:
start_date = latest_record['listDate']
actions = []
for _, item in get_security_list(mode='es', start_date=start_date, exchanges=EXCHANGE_LIST_COL).iterrows():
if start_date and is_same_date(start_date, item['listDate']):
continue
try:
stock_meta = StockMeta(meta={'id': item['id']})
fill_doc_type(stock_meta, json.loads(item.to_json()))
actions.append(stock_meta.to_dict(include_meta=True))
except Exception as e:
logger.warn("wrong SecurityItem:{},error:{}", item, e)
if actions:
resp = elasticsearch.helpers.bulk(es, actions)
logger.info(resp)
def check_convert_result():
for index, security_item in get_security_list().iterrows():
for fuquan in ('bfq', 'hfq'):
dayk_path = get_kdata_path(security_item, fuquan=fuquan)
if os.path.exists(dayk_path):
df_result = pd.read_csv(dayk_path)
if fuquan == 'hfq':
df = pd.DataFrame(
columns=data_contract.KDATA_COLUMN_FQ)
else:
df = pd.DataFrame(
columns=data_contract.KDATA_COLUMN)
dir = get_kdata_dir(security_item, fuquan=fuquan)
if os.path.exists(dir):
files = [os.path.join(dir, f) for f in os.listdir(dir) if
('day' not in f and 'csv' in f and os.path.isfile(os.path.join(dir, f)))]
for f in files:
df = df.append(pd.read_csv(f), ignore_index=True)
assert_df(df, df_result)
logger.info("{} merge as one ok".format(security_item['code']))
def remove_old_163_trading_dates():
for index, security_item in get_security_list().iterrows():
the_path = get_trading_dates_path_163(security_item)
if os.path.exists(the_path):
logger.info("remove {}".format(the_path))
os.remove(the_path)
def start_requests(self):
for _, item in get_security_list().iterrows():
url = self.get_forecast_url(item['code'])
yield Request(url=url, headers=DEFAULT_KDATA_HEADER,
meta={'item': item, },
callback=self.download_forecast_data)
def __init__(self, name=None, **kwargs):
super().__init__(name, **kwargs)
self.sh_df = get_security_list(exchanges=['sh'])
self.sz_df = get_security_list(exchanges=['sz'])
self.file_lock = threading.RLock()