def get_tick_data(self, symbol, date, expire=60 * 24 * 365 * 10):
"""
获取一支股票一天的tick数据保存到本地
--------
symbol: string,股票代码
date: string,1900-01-01
"""
if not os.path.exists(CT.TICK_DIR):
os.makedirs(CT.TICK_DIR)
if not os.path.exists(CT.TICK_DIR + symbol):
os.makedirs(CT.TICK_DIR + symbol)
file_path = CT.TICK_DIR + symbol + '/' + date
expired = date_time.check_file_expired(file_path, expire)
if expired:
d = ts.get_tick_data(symbol, date)
#过掉当天没数据的
if len(d) > 10:
d.to_csv(file_path)
else:
d = pd.read_csv(file_path)
#过掉当天没数据的
if len(d) > 10:
return d
else:
return ''
def get_tick_data(self, symbol, date, expire=60*24*365*10):
"""
获取一支股票一天的tick数据保存到本地
--------
symbol: string,股票代码
date: string,1900-01-01
"""
if not os.path.exists(CT.TICK_DIR):
os.makedirs(CT.TICK_DIR)
if not os.path.exists(CT.TICK_DIR + symbol):
os.makedirs(CT.TICK_DIR + symbol)
file_path = CT.TICK_DIR + symbol + '/' + date
expired = date_time.check_file_expired(file_path, expire)
if expired or not os.path.exists(file_path):
d = ts.get_tick_data(symbol, date)
#过掉当天没数据的
if d is None or len(d) < 10:
return None
d.to_csv(file_path, sep='\t')
if not os.path.exists(file_path):
return None
d = pd.read_csv(file_path, sep='\t', index_col=1)
#过掉当天没数据的
if d is None or len(d) < 10:
return None
return d
def get_stock_basics(self, expire=60*6):
"""
获取沪深上市公司基本情况
:param expire: 本地数据失效时间(分)，超过时间更新本地数据,强制更新传0
@result:
code,代码
name,名称
industry,所属行业
area,地区
pe,市盈率
outstanding,流通股本
totals,总股本(万)
totalAssets,总资产(万)
liquidAssets,流动资产
fixedAssets,固定资产
reserved,公积金
reservedPerShare,每股公积金
eps,每股收益
bvps,每股净资
pb,市净率
timeToMarket,上市日期
"""
if not os.path.exists(CT.BASICS_DIR):
os.makedirs(CT.BASICS_DIR)
basics_file_path = CT.BASICS_DIR + './basics.csv'
expired = date_time.check_file_expired(basics_file_path, expire)
if expired or not os.path.exists(basics_file_path):
d = ts.get_stock_basics()
d = d.sort_index()
#d.to_csv(CT.BASICS_DIR + './basics.csv', sep='\t', index=True)
d.to_csv(CT.BASICS_DIR + './basics.csv', sep='\t')
all_stock_symbol = open(CT.BASICS_DIR + './symbols.csv', 'w')
stock_symbol = []
for symbol in d['name'].index:
stock_symbol.append(symbol + '\n')
all_stock_symbol.writelines(stock_symbol)
all_stock_symbol.close()
#return d
d = pd.read_csv(basics_file_path, sep='\t', index_col=0)
#d = pd.read_csv(basics_file_path)
return d
def get_hsgt_his(self, days=30, market_type=1, expire=60 * 6):
"""
得到沪股通、深股通 历史资金数据
资金单位百万
"""
if not os.path.exists(CT.HSGT_DIR):
os.makedirs(CT.HSGT_DIR)
file_path = CT.HSGT_DIR + 'hsgt_his_%d_%d' % (days, market_type)
expired = date_time.check_file_expired(file_path, expire)
if expired or not os.path.exists(file_path):
hsgt_his_detail = self._request(self.hsgt_his_api %
(market_type, days))
hsgt_his_result = json.loads(hsgt_his_detail)
date = []
zjlr = []
jme = []
mrcje = []
mccje = []
for v in hsgt_his_result:
date.append(v['DetailDate'][:10])
zjlr.append(v['DRZJLR'])
jme.append(v['DRCJJME'])
mrcje.append(v['MRCJE'])
mccje.append(v['MCCJE'])
data = {
'date': date,
'zjlr': zjlr,
'jme': jme,
'mrcje': mrcje,
'mccje': mccje
}
d = pd.DataFrame(data,
columns=['date', 'zjlr', 'jme', 'mrcje', 'mccje'])
d.to_csv(file_path, sep='\t', index=False)
if not os.path.exists(file_path):
return None
d = pd.read_csv(file_path, sep='\t', index_col='date')
return d
def get_h_data(self, symbol, expire=60):
"""
获取一支股票所有历史数据保存到本地
"""
if not os.path.exists(CT.HIS_DIR):
os.makedirs(CT.HIS_DIR)
file_path = CT.HIS_DIR + symbol
expired = date_time.check_file_expired(file_path, expire)
if expired:
today = date_time.get_today_str()
d = ts.get_h_data(symbol,
autype=None,
start=CT.START,
end=today,
drop_factor=False)
d.to_csv(CT.HIS_DIR + symbol)
return d
else:
d = pd.read_csv(file_path)
return d
def get_h_data(self, symbol, expire=60*6):
"""
获取一支股票所有历史数据保存到本地
"""
if not os.path.exists(CT.HIS_DIR):
os.makedirs(CT.HIS_DIR)
file_path = CT.HIS_DIR + symbol
expired = date_time.check_file_expired(file_path, expire)
if expired or not os.path.exists(file_path):
today = date_time.get_today_str()
d = ts.get_h_data(symbol, autype=None, start=CT.START, end=today, drop_factor=False)
#index = []
#for i in list(d.index):
# index.append(date_time.date_to_str(i))
#d = d.reindex(index, method='ffill')
if d is None:
return d
d.to_csv(CT.HIS_DIR + symbol, sep='\t')
#return d
if not os.path.exists(file_path):
return None
d = pd.read_csv(file_path, sep='\t', index_col=0)
return d
def get_hsgt_top(self, date_str, expire=60 * 24 * 30):
"""
得到沪股通、深股通 十大成交股
"""
if not os.path.exists(CT.HSGT_DIR):
os.makedirs(CT.HSGT_DIR)
file_path = CT.HSGT_DIR + date_str
expired = date_time.check_file_expired(file_path, expire)
if expired or not os.path.exists(file_path):
hgt_top_detail = self._request(self.hsgt_top_api %
('HGT', date_str, 1))
hgt_grep_result = self.hsgt_top_format.finditer(hgt_top_detail)
hgt_top_result = []
for stock_match_object in hgt_grep_result:
groups = stock_match_object.groups()
hgt_top_result = json.loads(groups[0])
sgt_top_result = []
sgt_top_detail = self._request(self.hsgt_top_api %
('SGT', date_str, 3))
sgt_grep_result = self.hsgt_top_format.finditer(sgt_top_detail)
for stock_match_object in sgt_grep_result:
groups = stock_match_object.groups()
sgt_top_result = json.loads(groups[0])
code = []
name = []
change = []
jme = []
mrje = []
mcje = []
cjje = []
ratio = []
market = []
if hgt_top_result:
for v in hgt_top_result:
code.append(v['Code'])
name.append(v['Name'].encode('utf-8'))
change.append(v['ChangePercent'])
if v['HGTJME'] == '-':
v['HGTJME'] = 0
if v['HGTMRJE'] == '-':
v['HGTMRJE'] = 0
if v['HGTMCJE'] == '-':
v['HGTMCJE'] = 0
if v['HGTCJJE'] == '-':
v['HGTCJJE'] = 0.1 / (2 ^ 64 - 1)
jme.append(v['HGTJME'])
mrje.append(v['HGTMRJE'])
mcje.append(v['HGTMCJE'])
cjje.append(v['HGTCJJE'])
ratio.append(v['HGTMRJE'] / v['HGTCJJE'])
market.append(1)
if sgt_top_result:
for v in sgt_top_result:
code.append(v['Code'])
name.append(v['Name'].encode('utf-8'))
change.append(v['ChangePercent'])
jme.append(v['SGTJME'])
mrje.append(v['SGTMRJE'])
mcje.append(v['SGTMCJE'])
cjje.append(v['SGTCJJE'])
ratio.append(v['SGTMRJE'] / v['SGTCJJE'])
market.append(3)
data = {
'code': code,
'name': name,
'change': change,
'jme': jme,
'mrje': mrje,
'mcje': mcje,
'cjje': cjje,
'ratio': ratio,
'market': market
}
#d = pd.DataFrame(data, index=code, columns=['name', 'jme', 'mrje', 'mcje', 'cjje', 'market'])
d = pd.DataFrame(data,
columns=[
'code', 'name', 'change', 'jme', 'mrje',
'mcje', 'cjje', 'ratio', 'market'
])
#d.to_csv(file_path, sep='\t')
d.to_csv(file_path, sep='\t', index=False)
if not os.path.exists(file_path):
return pd.DataFrame()
#d = pd.read_csv(file_path, sep='\t', index_col=0)
d = pd.read_csv(file_path, sep='\t', index_col='code')
code = []
for c in d.index:
code.append("{:0>6d}".format(c))
name = list(d['name'])
change = list(d['change'])
jme = list(d['jme'])
mrje = list(d['mrje'])
mcje = list(d['mcje'])
cjje = list(d['cjje'])
ratio = list(d['ratio'])
market = list(d['market'])
data = {
'code': code,
'name': name,
'change': change,
'jme': jme,
'mrje': mrje,
'mcje': mcje,
'cjje': cjje,
'ratio': ratio,
'market': market
}
d = pd.DataFrame(data,
index=code,
columns=[
'code', 'name', 'change', 'jme', 'mrje', 'mcje',
'cjje', 'ratio', 'market'
])
return d
