def updateAllStocks():
'''
函数功能：
--------
更新所有股票列表。
输入参数：
--------
无
输出参数：
--------
True/False : boolean，是否更新成功。
数据文件
Strategy_Common_AllStock.csv : 参与策略计算的所有股票列表
'''
# Load from Fundamental Stock Basics
allstock = loadStockBasics()
if not u.isNoneOrEmpty(allstock):
# Save to CSV File
allstock.set_index('code', inplace=True)
file_postfix = '_'.join(['Common', 'AllStock'])
u.to_csv(allstock, c.path_dict['strategy'],
c.file_dict['strategy'] % file_postfix)
return True
return False
def get_stock_list(cutoff_date):
'''
函数功能：
--------
获取所有指定日期之前（含）已经上市的股票列表。
输入参数：
--------
date,截止时间 e.g. '2016-12-31'
输出参数：
--------
DataFrame
code,代码
name,名称
industry,所属行业
area,地区
timeToMarket,上市日期
'''
# Check pre-requisite
basics = loadStockBasics()
if u.isNoneOrEmpty(basics):
print('Need to have stock basics!')
raise SystemExit
# Extract Stock List
stocks = basics[basics.timeToMarket <= cutoff_date]
stocks = stocks[['code', 'name', 'industry', 'area', 'timeToMarket']]
stocks = stocks.sort_values('timeToMarket', axis=0, ascending=True)
# Return Dataframe
return stocks
def get_cxg(date):
'''
函数功能：
--------
获取所有次新股的股票列表，根据给定的上市时间。
输入参数：
--------
date,上市时间 e.g. '2016-01-01'
输出参数：
--------
DataFrame
code,代码
name,名称
industry,所属行业
area,地区
timeToMarket,上市日期
'''
# Check pre-requisite
basics = loadStockBasics()
if u.isNoneOrEmpty(basics):
print('Need to have stock basics!')
raise SystemExit
# Extract CXG Data
cxg = basics[basics.timeToMarket >= date]
cxg = cxg[['code', 'name', 'industry', 'area', 'timeToMarket']]
cxg = cxg.sort_values('timeToMarket', axis=0, ascending=True)
# Return Dataframe
return cxg
def plotHPE(period='M', ratio='PE'):
# Check pre-requisite
basics = loadStockBasics()
if u.isNoneOrEmpty(basics):
print('Need to have stock basics!')
raise SystemExit
# Iterate over all stocks
basics_number = len(basics)
for i in range(basics_number):
stock_id = u.stockID(basics.loc[i, 'code'])
# Plot HPE Data
plot_HPE(stock_id=stock_id, period=period, ratio=ratio)
def updateFinanceSummary(force_update=True):
# Check pre-requisite
basics = loadStockBasics()
if u.isNoneOrEmpty(basics):
print('Need to have stock basics!')
raise SystemExit
# Iterate over all stocks
basics_number = len(basics)
for i in range(basics_number):
stock_id = u.stockID(basics.loc[i, 'code'])
# Check if valid data file already exists
if not validFinanceSummary(stock_id, force_update):
getFinanceSummary(stock_id)
print('Update Finance Summary:', stock_id)
def updatePriceStock(incremental=False):
# Check pre-requisite
basics = loadStockBasics()
if u.isNoneOrEmpty(basics):
print('Need to have stock basics!')
raise SystemExit
# Iterate over all stocks
basics_number = len(basics)
for i in range(basics_number):
stock_id = u.stockID(basics.loc[i, 'code'])
time_to_market = u.dateFromStr(basics.loc[i, 'timeToMarket'])
getDailyHFQ(stock_id=stock_id,
is_index=False,
date_start=time_to_market,
date_end=date_end,
time_to_market=time_to_market,
incremental=incremental)
print('Update Price:', stock_id)
def cleanStockBasics():
basics = loadStockBasics()
print(basics.head(10))
# Format columns
basics['code'] = basics['code'].map(lambda x: str(x).zfill(6))
basics['timeToMarket'] = basics['timeToMarket'].map(
u.formatDateYYYYmmddInt64)
if gs.is_debug:
basics_number = len(basics)
for i in range(basics_number):
if basics.loc[i, 'timeToMarket'] == c.magic_date:
print(i, type(basics.loc[i, 'timeToMarket']),
basics.loc[i, 'timeToMarket'], basics.loc[i, 'code'])
# Filter out invalid timeToMarket stocks
basics_nottm = basics[basics.timeToMarket == c.magic_date]
basics = basics[basics.timeToMarket != c.magic_date]
basics_nottm.set_index('code', inplace=True)
basics.set_index('code', inplace=True)
# Save to CSV File
u.to_csv(basics, c.path_dict['basics'], c.file_dict['basics'])
u.to_csv(basics_nottm, c.path_dict['basics'], c.file_dict['basics_nottm'])