一个用Python编写的股票数据（沪深）爬虫和选股策略测试框架
一个股票数据（沪深）爬虫和选股策略测试框架，数据基于雅虎YQL和新浪财经。
- 根据选定的日期范围抓取所有沪深两市股票的行情数据。
- 根据指定的选股策略和指定的日期进行选股测试。
- 计算选股测试实际结果（包括与沪深300指数比较）。
- 保存数据到JSON文件、CSV文件。
- 支持使用表达式定义选股策略。
- 支持多线程处理。
代码
main.py
from stockholm import Stockholm
import option
import os
def checkFoldPermission(path):
if(path == 'USER_HOME/tmp/stockholm_export'):
path = os.path.expanduser('~') + '/tmp/stockholm_export'
try:
if not os.path.exists(path):
os.makedirs(path)
else:
txt = open(path + os.sep + "test.txt","w")
txt.write("test")
txt.close()
os.remove(path + os.sep + "test.txt")
except Exception as e:
print(e)
return False
return True
def main():
args = option.parser.parse_args()
if not checkFoldPermission(args.store_path):
print('\nPermission denied: %s' % args.store_path)
print('Please make sure you have the permission to save the data!\n')
else:
print('Stockholm is starting...\n')
stockh = Stockholm(args)
stockh.run()
print('Stockholm is done...\n')
if __name__ == '__main__':
main()
option.py
import argparse
import datetime
def get_date_str(offset):
if(offset is None):
offset = 0
date_str = (datetime.datetime.today() + datetime.timedelta(days=offset)).strftime("%Y-%m-%d")
return date_str
_default = dict(
reload_data = 'Y',
gen_portfolio = 'N',
output_type = 'json',
charset = 'utf-8',
test_date_range = 60,
start_date = get_date_str(-90),
end_date = get_date_str(None),
target_date = get_date_str(None),
store_path = 'USER_HOME/tmp/stockholm_export',
thread = 10,
testfile_path = './portfolio_test.txt',
db_name = 'stockholm',
methods = ''
)
parser = argparse.ArgumentParser(description='A stock crawler and portfolio testing framework.')
parser.add_argument('--reload', type=str, default=_default['reload_data'], dest='reload_data', help='Reload the stock data or not (Y/N), Default: %s' % _default['reload_data'])
parser.add_argument('--portfolio', type=str, default=_default['gen_portfolio'], dest='gen_portfolio', help='Generate the portfolio or not (Y/N), Default: %s' % _default['gen_portfolio'])
parser.add_argument('--output', type=str, default=_default['output_type'], dest='output_type', help='Data output type (json/csv/all), Default: %s' % _default['output_type'])
parser.add_argument('--charset', type=str, default=_default['charset'], dest='charset', help='Data output charset (utf-8/gbk), Default: %s' % _default['charset'])
parser.add_argument('--testrange', type=int, default=_default['test_date_range'], dest='test_date_range', help='Test date range(days): %s' % _default['test_date_range'])
parser.add_argument('--startdate', type=str, default=_default['start_date'], dest='start_date', help='Data loading start date, Default: %s' % _default['start_date'])
parser.add_argument('--enddate', type=str, default=_default['end_date'], dest='end_date', help='Data loading end date, Default: %s' % _default['end_date'])
parser.add_argument('--targetdate', type=str, default=_default['target_date'], dest='target_date', help='Portfolio generating target date, Default: %s' % _default['target_date'])
parser.add_argument('--storepath', type=str, default=_default['store_path'], dest='store_path', help='Data file store path, Default: %s' % _default['store_path'])
parser.add_argument('--thread', type=int, default=_default['thread'], dest='thread', help='Thread number, Default: %s' % _default['thread'])
parser.add_argument('--testfile', type=str, default=_default['testfile_path'], dest='testfile_path', help='Portfolio test file path, Default: %s' % _default['testfile_path'])
parser.add_argument('--dbname', type=str, default=_default['db_name'], dest='db_name', help='MongoDB DB name, Default: %s' % _default['db_name'])
parser.add_argument('--methods', type=str, default=_default['methods'], dest='methods', help='Target methods for back testing, Default: %s' % _default['methods'])
def main():
args = parser.parse_args()
print(args)
if __name__ == '__main__':
main()
stockholm.py
#coding:utf-8
import requests
import json
import datetime
import timeit
import time
import io
import os
import csv
import re
from pymongo import MongoClient
from multiprocessing.dummy import Pool as ThreadPool
from functools import partial
class Stockholm(object):
def __init__(self, args):
## flag of if need to reload all stock data
self.reload_data = args.reload_data
## flag of if need to generate portfolio
self.gen_portfolio = args.gen_portfolio
## type of output file json/csv or both
self.output_type = args.output_type
## charset of output file utf-8/gbk
self.charset = args.charset
## portfolio testing date range(# of days)
self.test_date_range = args.test_date_range
## stock data loading start date(e.g. 2014-09-14)
self.start_date = args.start_date
## stock data loading end date
self.end_date = args.end_date
## portfolio generating target date
self.target_date = args.target_date
## thread number
self.thread = args.thread
## data file store path
if(args.store_path == 'USER_HOME/tmp/stockholm_export'):
self.export_folder = os.path.expanduser('~') + '/tmp/stockholm_export'
else:
self.export_folder = args.store_path
## portfolio testing file path
self.testfile_path = args.testfile_path
## methods for back testing
self.methods = args.methods
## for getting quote symbols
self.all_quotes_url = 'http://money.finance.sina.com.cn/d/api/openapi_proxy.php'
## for loading quote data
self.yql_url = 'http://query.yahooapis.com/v1/public/yql'
## export file name
self.export_file_name = 'stockholm_export'
self.index_array = ['000001.SS', '399001.SZ', '000300.SS']
self.sh000001 = {'Symbol': '000001.SS', 'Name': '上证指数'}
self.sz399001 = {'Symbol': '399001.SZ', 'Name': '深证成指'}
self.sh000300 = {'Symbol': '000300.SS', 'Name': '沪深300'}
## self.sz399005 = {'Symbol': '399005.SZ', 'Name': '中小板指'}
## self.sz399006 = {'Symbol': '399006.SZ', 'Name': '创业板指'}
## mongodb info
self.mongo_url = 'localhost'
self.mongo_port = 27017
self.database_name = args.db_name
self.collection_name = 'testing_method'
def get_columns(self, quote):
columns = []
if(quote is not None):
for key in quote.keys():
if(key == 'Data'):
for data_key in quote['Data'][-1]:
columns.append("data." + data_key)
else:
columns.append(key)
columns.sort()
return columns
def get_profit_rate(self, price1, price2):
if(price1 == 0):
return None
else:
return round((price2-price1)/price1, 5)
def get_MA(self, number_array):
total = 0
n = 0
for num in number_array:
if num is not None and num != 0:
n += 1
total += num
return round(total/n, 3)
def convert_value_check(self, exp):
val = exp.replace('day', 'quote[\'Data\']').replace('(0)', '(-0)')
val = re.sub(r'\(((-)?\d+)\)', r'[target_idx\g<1>]', val)
val = re.sub(r'\.\{((-)?\w+)\}', r"['\g<1>']", val)
return val
def convert_null_check(self, exp):
p = re.compile('\((-)?\d+...\w+\}')
iterator = p.finditer(exp.replace('(0)', '(-0)'))
array = []
for match in iterator:
v = 'quote[\'Data\']' + match.group()
v = re.sub(r'\(((-)?\d+)\)', r'[target_idx\g<1>]', v)
v = re.sub(r'\.\{((-)?\w+)\}', r"['\g<1>']", v)
v += ' is not None'
array.append(v)
val = ' and '.join(array)
return val
class KDJ():
def _avg(self, array):
length = len(array)
return sum(array)/length
def _getMA(self, values, window):
array = []
x = window
while x <= len(values):
curmb = 50
if(x-window == 0):
curmb = self._avg(values[x-window:x])
else:
curmb = (array[-1]*2+values[x-1])/3
array.append(round(curmb,3))
x += 1
return array
def _getRSV(self, arrays):
rsv = []
x = 9
while x <= len(arrays):
high = max(map(lambda x: x['High'], arrays[x-9:x]))
low = min(map(lambda x: x['Low'], arrays[x-9:x]))
close = arrays[x-1]['Close']
rsv.append((close-low)/(high-low)*100)
t = arrays[x-1]['Date']
x += 1
return rsv
def getKDJ(self, quote_data):
if(len(quote_data) > 12):
rsv = self._getRSV(quote_data)
k = self._getMA(rsv,3)
d = self._getMA(k,3)
j = list(map(lambda x: round(3*x[0]-2*x[1],3), zip(k[2:], d)))
for idx, data in enumerate(quote_data[0:12]):
data['KDJ_K'] = None
data['KDJ_D'] = None
data['KDJ_J'] = None
for idx, data in enumerate(quote_data[12:]):
data['KDJ_K'] = k[2:][idx]
data['KDJ_D'] = d[idx]
if(j[idx] > 100):
data['KDJ_J'] = 100
elif(j[idx] < 0):
data['KDJ_J'] = 0
else:
data['KDJ_J'] = j[idx]
return quote_data
def load_all_quote_symbol(self):
print("load_all_quote_symbol start..." + "\n")
start = timeit.default_timer()
all_quotes = []
all_quotes.append(self.sh000001)
all_quotes.append(self.sz399001)
all_quotes.append(self.sh000300)
## all_quotes.append(self.sz399005)
## all_quotes.append(self.sz399006)
try:
count = 1
while (count < 100):
para_val = '[["hq","hs_a","",0,' + str(count) + ',500]]'
r_params = {'__s': para_val}
r = requests.get(self.all_quotes_url, params=r_params)
if(len(r.json()[0]['items']) == 0):
break
for item in r.json()[0]['items']:
quote = {}
code = item[0]
name = item[2]
## convert quote code
if(code.find('sh') > -1):
code = code[2:] + '.SS'
elif(code.find('sz') > -1):
code = code[2:] + '.SZ'
## convert quote code end
quote['Symbol'] = code
quote['Name'] = name
all_quotes.append(quote)
count += 1
except Exception as e:
print("Error: Failed to load all stock symbol..." + "\n")
print(e)
print("load_all_quote_symbol end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")
return all_quotes
def load_quote_info(self, quote, is_retry):
print("load_quote_info start..." + "\n")
start = timeit.default_timer()
if(quote is not None and quote['Symbol'] is not None):
yquery = 'select * from yahoo.finance.quotes where symbol = "' + quote['Symbol'].lower() + '"'
r_params = {'q': yquery, 'format': 'json', 'env': 'http://datatables.org/alltables.env'}
r = requests.get(self.yql_url, params=r_params)
## print(r.url)
## print(r.text)
rjson = r.json()
try:
quote_info = rjson['query']['results']['quote']
quote['LastTradeDate'] = quote_info['LastTradeDate']
quote['LastTradePrice'] = quote_info['LastTradePriceOnly']
quote['PreviousClose'] = quote_info['PreviousClose']
quote['Open'] = quote_info['Open']
quote['DaysLow'] = quote_info['DaysLow']
quote['DaysHigh'] = quote_info['DaysHigh']
quote['Change'] = quote_info['Change']
quote['ChangeinPercent'] = quote_info['ChangeinPercent']
quote['Volume'] = quote_info['Volume']
quote['MarketCap'] = quote_info['MarketCapitalization']
quote['StockExchange'] = quote_info['StockExchange']
except Exception as e:
print("Error: Failed to load stock info... " + quote['Symbol'] + "/" + quote['Name'] + "\n")
print(e + "\n")
if(not is_retry):
time.sleep(1)
load_quote_info(quote, True) ## retry once for network issue
## print(quote)
print("load_quote_info end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")
return quote
def load_all_quote_info(self, all_quotes):
print("load_all_quote_info start...")
start = timeit.default_timer()
for idx, quote in enumerate(all_quotes):
print("#" + str(idx + 1))
load_quote_info(quote, False)
print("load_all_quote_info end... time cost: " + str(round(timeit.default_timer() - start)) + "s")
return all_quotes
def load_quote_data(self, quote, start_date, end_date, is_retry, counter):
## print("load_quote_data start..." + "\n")
start = timeit.default_timer()
if(quote is not None and quote['Symbol'] is not None):
yquery = 'select * from yahoo.finance.historicaldata where symbol = "' + quote['Symbol'].upper() + '" and startDate = "' + start_date + '" and endDate = "' + end_date + '"'
r_params = {'q': yquery, 'format': 'json', 'env': 'http://datatables.org/alltables.env'}
try:
r = requests.get(self.yql_url, params=r_params)
## print(r.url)
## print(r.text)
rjson = r.json()
quote_data = rjson['query']['results']['quote']
quote_data.reverse()
quote['Data'] = quote_data
if(not is_retry):
counter.append(1)
except:
print("Error: Failed to load stock data... " + quote['Symbol'] + "/" + quote['Name'] + "\n")
if(not is_retry):
time.sleep(2)
self.load_quote_data(quote, start_date, end_date, True, counter) ## retry once for network issue
print("load_quote_data " + quote['Symbol'] + "/" + quote['Name'] + " end..." + "\n")
## print("time cost: " + str(round(timeit.default_timer() - start)) + "s." + "\n")
## print("total count: " + str(len(counter)) + "\n")
return quote
def load_all_quote_data(self, all_quotes, start_date, end_date):
print("load_all_quote_data start..." + "\n")
start = timeit.default_timer()
counter = []
mapfunc = partial(self.load_quote_data, start_date=start_date, end_date=end_date, is_retry=False, counter=counter)
pool = ThreadPool(self.thread)
pool.map(mapfunc, all_quotes) ## multi-threads executing
pool.close()
pool.join()
print("load_all_quote_data end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")
return all_quotes
def data_process(self, all_quotes):
print("data_process start..." + "\n")
kdj = self.KDJ()
start = timeit.default_timer()
for quote in all_quotes:
if(quote['Symbol'].startswith('300')):
quote['Type'] = '创业板'
elif(quote['Symbol'].startswith('002')):
quote['Type'] = '中小板'
else:
quote['Type'] = '主板'
if('Data' in quote):
try:
temp_data = []
for quote_data in quote['Data']:
if(quote_data['Volume'] != '000' or quote_data['Symbol'] in self.index_array):
d = {}
d['Open'] = float(quote_data['Open'])
## d['Adj_Close'] = float(quote_data['Adj_Close'])
d['Close'] = float(quote_data['Close'])
d['High'] = float(quote_data['High'])
d['Low'] = float(quote_data['Low'])
d['Volume'] = int(quote_data['Volume'])
d['Date'] = quote_data['Date']
temp_data.append(d)
quote['Data'] = temp_data
except KeyError as e:
print("Data Process: Key Error")
print(e)
print(quote)
## calculate Change / 5 10 20 30 Day MA
for quote in all_quotes:
if('Data' in quote):
try:
for i, quote_data in enumerate(quote['Data']):
if(i > 0):
quote_data['Change'] = self.get_profit_rate(quote['Data'][i-1]['Close'], quote_data['Close'])
quote_data['Vol_Change'] = self.get_profit_rate(quote['Data'][i-1]['Volume'], quote_data['Volume'])
else:
quote_data['Change'] = None
quote_data['Vol_Change'] = None
last_5_array = []
last_10_array = []
last_20_array = []
last_30_array = []
for i, quote_data in enumerate(quote['Data']):
last_5_array.append(quote_data['Close'])
last_10_array.append(quote_data['Close'])
last_20_array.append(quote_data['Close'])
last_30_array.append(quote_data['Close'])
quote_data['MA_5'] = None
quote_data['MA_10'] = None
quote_data['MA_20'] = None
quote_data['MA_30'] = None
if(i < 4):
continue
if(len(last_5_array) == 5):
last_5_array.pop(0)
quote_data['MA_5'] = self.get_MA(last_5_array)
if(i < 9):
continue
if(len(last_10_array) == 10):
last_10_array.pop(0)
quote_data['MA_10'] = self.get_MA(last_10_array)
if(i < 19):
continue
if(len(last_20_array) == 20):
last_20_array.pop(0)
quote_data['MA_20'] = self.get_MA(last_20_array)
if(i < 29):
continue
if(len(last_30_array) == 30):
last_30_array.pop(0)
quote_data['MA_30'] = self.get_MA(last_30_array)
except KeyError as e:
print("Key Error")
print(e)
print(quote)
## calculate KDJ
for quote in all_quotes:
if('Data' in quote):
try:
kdj.getKDJ(quote['Data'])
except KeyError as e:
print("Key Error")
print(e)
print(quote)
print("data_process end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")
def data_export(self, all_quotes, export_type_array, file_name):
start = timeit.default_timer()
directory = self.export_folder
if(file_name is None):
file_name = self.export_file_name
if not os.path.exists(directory):
os.makedirs(directory)
if(all_quotes is None or len(all_quotes) == 0):
print("no data to export...\n")
if('json' in export_type_array):
print("start export to JSON file...\n")
f = io.open(directory + '/' + file_name + '.json', 'w', encoding=self.charset)
json.dump(all_quotes, f, ensure_ascii=False)
if('csv' in export_type_array):
print("start export to CSV file...\n")
columns = []
if(all_quotes is not None and len(all_quotes) > 0):
columns = self.get_columns(all_quotes[0])
writer = csv.writer(open(directory + '/' + file_name + '.csv', 'w', encoding=self.charset))
writer.writerow(columns)
for quote in all_quotes:
if('Data' in quote):
for quote_data in quote['Data']:
try:
line = []
for column in columns:
if(column.find('data.') > -1):
if(column[5:] in quote_data):
line.append(quote_data[column[5:]])
else:
line.append(quote[column])
writer.writerow(line)
except Exception as e:
print(e)
print("write csv error: " + quote)
if('mongo' in export_type_array):
print("start export to MongoDB...\n")
print("export is complete... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")
def file_data_load(self):
print("file_data_load start..." + "\n")
start = timeit.default_timer()
directory = self.export_folder
file_name = self.export_file_name
all_quotes_data = []
f = io.open(directory + '/' + file_name + '.json', 'r', encoding='utf-8')
json_str = f.readline()
all_quotes_data = json.loads(json_str)
print("file_data_load end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")
return all_quotes_data
def check_date(self, all_quotes, date):
is_date_valid = False
for quote in all_quotes:
if(quote['Symbol'] in self.index_array):
for quote_data in quote['Data']:
if(quote_data['Date'] == date):
is_date_valid = True
if not is_date_valid:
print(date + " is not valid...\n")
return is_date_valid
def quote_pick(self, all_quotes, target_date, methods):
print("quote_pick start..." + "\n")
start = timeit.default_timer()
results = []
data_issue_count = 0
for quote in all_quotes:
try:
if(quote['Symbol'] in self.index_array):
results.append(quote)
continue
target_idx = None
for idx, quote_data in enumerate(quote['Data']):
if(quote_data['Date'] == target_date):
target_idx = idx
if(target_idx is None):
## print(quote['Name'] + " data is not available at this date..." + "\n")
data_issue_count+=1
continue
## pick logic ##
valid = False
for method in methods:
## print(method['name'])
## null_check = eval(method['null_check'])
try:
value_check = eval(method['value_check'])
if(value_check):
quote['Method'] = method['name']
results.append(quote)
valid = True
break
except:
valid = False
if(valid):
continue
## pick logic end ##
except KeyError as e:
## print("KeyError: " + quote['Name'] + " data is not available..." + "\n")
data_issue_count+=1
print("quote_pick end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")
print(str(data_issue_count) + " quotes of data is not available...\n")
return results
def profit_test(self, selected_quotes, target_date):
print("profit_test start..." + "\n")
start = timeit.default_timer()
results = []
INDEX = None
INDEX_idx = 0
for quote in selected_quotes:
if(quote['Symbol'] == self.sh000300['Symbol']):
INDEX = quote
for idx, quote_data in enumerate(quote['Data']):
if(quote_data['Date'] == target_date):
INDEX_idx = idx
break
for quote in selected_quotes:
target_idx = None
if(quote['Symbol'] in self.index_array):
continue
for idx, quote_data in enumerate(quote['Data']):
if(quote_data['Date'] == target_date):
target_idx = idx
if(target_idx is None):
print(quote['Name'] + " data is not available for testing..." + "\n")
continue
test = {}
test['Name'] = quote['Name']
test['Symbol'] = quote['Symbol']
test['Method'] = quote['Method']
test['Type'] = quote['Type']
if('KDJ_K' in quote['Data'][target_idx]):
test['KDJ_K'] = quote['Data'][target_idx]['KDJ_K']
test['KDJ_D'] = quote['Data'][target_idx]['KDJ_D']
test['KDJ_J'] = quote['Data'][target_idx]['KDJ_J']
test['Close'] = quote['Data'][target_idx]['Close']
test['Change'] = quote['Data'][target_idx]['Change']
test['Vol_Change'] = quote['Data'][target_idx]['Vol_Change']
test['MA_5'] = quote['Data'][target_idx]['MA_5']
test['MA_10'] = quote['Data'][target_idx]['MA_10']
test['MA_20'] = quote['Data'][target_idx]['MA_20']
test['MA_30'] = quote['Data'][target_idx]['MA_30']
test['Data'] = [{}]
for i in range(1,11):
if(target_idx+i >= len(quote['Data'])):
print(quote['Name'] + " data is not available for " + str(i) + " day testing..." + "\n")
break
day2day_profit = self.get_profit_rate(quote['Data'][target_idx]['Close'], quote['Data'][target_idx+i]['Close'])
test['Data'][0]['Day_' + str(i) + '_Profit'] = day2day_profit
if(INDEX_idx+i < len(INDEX['Data'])):
day2day_INDEX_change = self.get_profit_rate(INDEX['Data'][INDEX_idx]['Close'], INDEX['Data'][INDEX_idx+i]['Close'])
test['Data'][0]['Day_' + str(i) + '_INDEX_Change'] = day2day_INDEX_change
test['Data'][0]['Day_' + str(i) + '_Differ'] = day2day_profit-day2day_INDEX_change
results.append(test)
print("profit_test end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")
return results
def data_load(self, start_date, end_date, output_types):
all_quotes = self.load_all_quote_symbol()
print("total " + str(len(all_quotes)) + " quotes are loaded..." + "\n")
all_quotes = all_quotes
## self.load_all_quote_info(all_quotes)
self.load_all_quote_data(all_quotes, start_date, end_date)
self.data_process(all_quotes)
self.data_export(all_quotes, output_types, None)
def data_test(self, target_date, test_range, output_types):
## loading test methods
methods = []
path = self.testfile_path
## from mongodb
if(path == 'mongodb'):
print("Load testing methods from Mongodb...\n")
client = MongoClient(self.mongo_url, self.mongo_port)
db = client[self.database_name]
col = db[self.collection_name]
q = None
if(len(self.methods) > 0):
applied_methods = list(map(int, self.methods.split(',')))
q = {"method_id": {"$in": applied_methods}}
for doc in col.find(q, ['name','desc','method']):
print(doc)
m = {'name': doc['name'], 'value_check': self.convert_value_check(doc['method'])}
methods.append(m)
## from test file
else:
if not os.path.exists(path):
print("Portfolio test file is not existed, testing is aborted...\n")
return
f = io.open(path, 'r', encoding='utf-8')
for line in f:
if(line.startswith('##') or len(line.strip()) == 0):
continue
line = line.strip().strip('\n')
name = line[line.find('[')+1:line.find(']:')]
value = line[line.find(']:')+2:]
m = {'name': name, 'value_check': self.convert_value_check(value)}
methods.append(m)
if(len(methods) == 0):
print("No method is loaded, testing is aborted...\n")
return
## portfolio testing
all_quotes = self.file_data_load()
target_date_time = datetime.datetime.strptime(target_date, "%Y-%m-%d")
for i in range(test_range):
date = (target_date_time - datetime.timedelta(days=i)).strftime("%Y-%m-%d")
is_date_valid = self.check_date(all_quotes, date)
if is_date_valid:
selected_quotes = self.quote_pick(all_quotes, date, methods)
res = self.profit_test(selected_quotes, date)
self.data_export(res, output_types, 'result_' + date)
def run(self):
## output types
output_types = []
if(self.output_type == "json"):
output_types.append("json")
elif(self.output_type == "csv"):
output_types.append("csv")
elif(self.output_type == "all"):
output_types = ["json", "csv"]
## loading stock data
if(self.reload_data == 'Y'):
print("Start loading stock data...\n")
self.data_load(self.start_date, self.end_date, output_types)
## test & generate portfolio
if(self.gen_portfolio == 'Y'):
print("Start portfolio testing...\n")
self.data_test(self.target_date, self.test_date_range, output_types)
mongo_scripts.txt
use stockholm
db.counters.insert(
{
_id: "method_id",
seq: 0
}
)
function getNextSequence(name) {
var ret = db.counters.findAndModify(
{
query: { _id: name },
update: { $inc: { seq: 1 } },
new: true
}
);
return ret.seq;
}
db.testing_method.insert({"method_id": getNextSequence("method_id"), "name":"测试方法1", "desc":"这是一个测试方法。", "user_name":"Stockholm", "user_id":"dtnium@gmail.com", "creation_date": new Date(), "modification_date": new Date(), "method":"day(-2).{KDJ_J}<20 and day(-1).{KDJ_J}<20 and day(0).{KDJ_J}-day(-1).{KDJ_J}>=40 and day(0).{Vol_Change}>=1 and day(0).{MA_10}*1.05>day(0).{Close}"})
db.testing_method.insert({"method_id": getNextSequence("method_id"), "name":"测试方法2", "desc":"这是一个测试方法。", "user_name":"Stockholm", "user_id":"dtnium@gmail.com", "creation_date": new Date(), "modification_date": new Date(), "method":"day(-2).{KDJ_J}-day(-1).{KDJ_J}>20 and day(0).{KDJ_J}-day(-1).{KDJ_J}>20 and day(-1).{KDJ_J}<50 and day(0).{Vol_Change}<=1"})
portfolio_test.txt
## Portfolio selection methodology sample file
[测试方法1]:day(-2).{KDJ_J}<20 and day(-1).{KDJ_J}<20 and day(0).{KDJ_J}-day(-1).{KDJ_J}>=40 and day(0).{Vol_Change}>=1 and day(0).{MA_10}*1.05>day(0).{Close}
[测试方法2]:day(-2).{KDJ_J}-day(-1).{KDJ_J}>20 and day(0).{KDJ_J}-day(-1).{KDJ_J}>20 and day(-1).{KDJ_J}<50 and day(0).{Vol_Change}<=1
##[测试方法3]:50<day(-1).{KDJ_J}<80 and day(-2).{KDJ_J}<day(-1).{KDJ_J} and day(0).{KDJ_J}<day(-1).{KDJ_J}
运行时参数
--storepath c://test --output csv --startdate 2015-09-01 --enddate 2015-12-07 --charset utf-8 --testfile ./portfolio_test.txt --reload Y --portfolio Y --thread 10
能干什么
如果你想基于沪深股市行情数据进行一些工作，它可以帮助你导出指定时间范围内所有沪深A股的行情数据和一些技术指标，包括代码、名称、开盘、收盘、最高、最低、成交量、均线、KDJ等。
还有些什么问题
行情数据目前来源于雅虎YQL，每日数据的更新时间不太稳定（一般在中国时间午夜左右）。
环境
Python 3.4以上
pip install requests
pip install pymongo使用
python main.py [-h] [--reload {Y,N}] [--portfolio {Y,N}]
[--output {json,csv,all}] [--storepath PATH] [--thread NUM]
[--startdate yyyy-MM-dd] [--enddate yyyy-MM-dd]
[--targetdate yyyy-MM-dd] [--testrange NUM] [--testfile PATH]可选参数
-h, --help 查看帮助并退出
--reload {Y,N} 是否重新抓取股票数据，默认值：Y
--portfolio {Y,N} 是否生成选股测试结果，默认值：N
--output {json,csv,all} 输出文件格式，默认值：json
--charset {utf-8,gbk} 输出文件编码，默认值：utf-8
--storepath PATH 输出文件路径，默认值：~/tmp/stockholm_export
--thread NUM 线程数，默认值：10
--startdate yyyy-MM-dd 抓取数据的开始日期，默认值：当前系统日期-100天（例如2015-01-01）
--enddate yyyy-MM-dd 抓取数据的结束日期，默认值：当前系统日期
--targetdate yyyy-MM-dd 测试选股策略的目标日期，默认值：当前系统日期
--testrange NUM 测试日期范围天数，默认值：50
--testfile PATH 测试文件路径，默认值：./portfolio_test.txt可用数据/格式
行情数据:
[
{"Symbol": "600000.SS",
"Name": "浦发银行"，
"Data": [
{"Vol_Change": null, "MA_10": null, "Date": "2015-03-26", "High": 15.58, "Open": 15.15, "Volume": 282340700, "Close": 15.36, "Change": null, "Low": 15.04},
{"Vol_Change": -0.22726, "MA_10": null, "Date": "2015-03-27", "High": 15.55, "Open": 15.32, "Volume": 218174900, "Close": 15.36, "Change": 0.0, "Low": 15.17}
]
}
]Date(日期); Open(开盘价); Close(收盘价); High(当日最高); Low(当日最低); Change(价格变化%); Volume(成交量); Vol_Change(成交量较前日变化); MA_5(5日均线); MA_10(10日均线); MA_20(20日均线); MA_30(30日均线); KDJ_K(KDJ指标K); KDJ_D(KDJ指标D); KDJ_J(KDJ指标J);
选股策略测试数据:
[
{
"Symbol": "600000.SS",
"Name": "浦发银行",
"Close": 14.51,
"Change": 0.06456,
"Vol_Change": 2.39592,
"MA_10": 14.171,
"KDJ_K": 37.65,
"KDJ_D": 33.427,
"KDJ_J": 46.096,
"Data": [
{"Day_5_Differ": 0.01869, "Day_9_Profit": 0.08546, "Day_1_Profit": -0.02826, "Day_1_INDEX_Change": -0.00484, "Day_3_INDEX_Change": 0.01557, "Day_5_INDEX_Change": 0.04747, "Day_3_Differ": 0.02647, "Day_9_INDEX_Change": 0.1003, "Day_5_Profit": 0.06616, "Day_3_Profit": 0.04204, "Day_1_Differ": -0.02342, "Day_9_Differ": -0.014840000000000006}
]
}
]Close(收盘价); Change(价格变化%); Vol_Change(成交量较前日变化); MA_10(十天均价); KDJ_K(KDJ指标K); KDJ_D(KDJ指标D); KDJ_J(KDJ指标J); Day_1_Profit(后一天利润率%); Day_1_INDEX_Change(后一天沪深300变化率%); Day_1_Differ(后一天相对利润率%——即利润率-沪深300变化率); Day_n_Profit(后n天利润率%); Day_n_INDEX_Change(后n天沪深300变化率%); Day_n_Differ(后n天相对利润率%——即利润率-沪深300变化率);
行情数据抓取范例
获取从当前日期倒推100天(不是100个交易日)的所有沪深股票行情数据。
执行完成后，数据在当前用户文件夹下./tmp/stockholm_export/stockholm_export.json
python main.py如果想导出csv文件
python main.py --output=csv选股策略测试范例
选股策略范例文件内容如下(包括在源码中)
选股策略”method 1”是:前前个交易日的KDJ指标的J值小于20+前个交易日的KDJ指标J值小于20+当前交易日的KDJ指标J值比上个交易日大40+当前交易日成交量变化大于100%
## Portfolio selection methodology sample file
[method 1]:day(-2).{KDJ_J}<20 and day(-1).{KDJ_J}<20 and day(0).{KDJ_J}-day(-1).{KDJ_J}>=40 and day(0).{Vol_Change}>=1以当前系统日期为目标日期进行倒推60天得选股策略测试。
不重新抓取行情数据并执行测试命令。
执行完毕后，会将测试结果按照每天一个文件的方式保存在./tmp/stockholm_export/。
文件名格式为result_yyyy-MM-dd.json(例如result_2015-03-24.json)。
python main.py --reload=N --portfolio=Y通过更改测试文件中的选股策略公式，可以随意测试指定时间范围内的选股效果。
