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 osdef 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 Falsereturn Truedef 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 datetimedef get_date_str(offset):if(offset is None):offset = 0date_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 partialclass Stockholm(object):def __init__(self, args):## flag of if need to reload all stock dataself.reload_data = args.reload_data## flag of if need to generate portfolioself.gen_portfolio = args.gen_portfolio## type of output file json/csv or bothself.output_type = args.output_type## charset of output file utf-8/gbkself.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 dateself.end_date = args.end_date## portfolio generating target dateself.target_date = args.target_date## thread numberself.thread = args.thread## data file store pathif(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 pathself.testfile_path = args.testfile_path## methods for back testingself.methods = args.methods## for getting quote symbolsself.all_quotes_url = 'http://money.finance.sina.com.cn/d/api/openapi_proxy.php'## for loading quote dataself.yql_url = 'http://query.yahooapis.com/v1/public/yql'## export file nameself.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 infoself.mongo_url = 'localhost'self.mongo_port = 27017self.database_name = args.db_nameself.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 columnsdef get_profit_rate(self, price1, price2):if(price1 == 0):return Noneelse:return round((price2-price1)/price1, 5)def get_MA(self, number_array):total = 0n = 0for num in number_array:if num is not None and num != 0:n += 1total += numreturn 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 valdef 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 valclass KDJ():def _avg(self, array):length = len(array)return sum(array)/lengthdef _getMA(self, values, window):array = []x = windowwhile x <= len(values):curmb = 50if(x-window == 0):curmb = self._avg(values[x-window:x])else:curmb = (array[-1]*2+values[x-1])/3array.append(round(curmb,3))x += 1return arraydef _getRSV(self, arrays):rsv = []x = 9while 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 += 1return rsvdef 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'] = Nonedata['KDJ_D'] = Nonedata['KDJ_J'] = Nonefor 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'] = 100elif(j[idx] < 0):data['KDJ_J'] = 0else:data['KDJ_J'] = j[idx]return quote_datadef 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 = 1while (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):breakfor item in r.json()[0]['items']:quote = {}code = item[0]name = item[2]## convert quote codeif(code.find('sh') > -1):code = code[2:] + '.SS'elif(code.find('sz') > -1):code = code[2:] + '.SZ'## convert quote code endquote['Symbol'] = codequote['Name'] = nameall_quotes.append(quote)count += 1except 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_quotesdef 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 quotedef 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_quotesdef 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_dataif(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 issueprint("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 quotedef 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 executingpool.close() pool.join()print("load_all_quote_data end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")return all_quotesdef 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_dataexcept KeyError as e:print("Data Process: Key Error")print(e)print(quote)## calculate Change / 5 10 20 30 Day MAfor 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'] = Nonequote_data['Vol_Change'] = Nonelast_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'] = Nonequote_data['MA_10'] = Nonequote_data['MA_20'] = Nonequote_data['MA_30'] = Noneif(i < 4):continueif(len(last_5_array) == 5):last_5_array.pop(0)quote_data['MA_5'] = self.get_MA(last_5_array)if(i < 9):continueif(len(last_10_array) == 10):last_10_array.pop(0)quote_data['MA_10'] = self.get_MA(last_10_array)if(i < 19):continueif(len(last_20_array) == 20):last_20_array.pop(0)quote_data['MA_20'] = self.get_MA(last_20_array)if(i < 29):continueif(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 KDJfor 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_folderif(file_name is None):file_name = self.export_file_nameif 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_folderfile_name = self.export_file_nameall_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_datadef check_date(self, all_quotes, date):is_date_valid = Falsefor 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 = Trueif not is_date_valid:print(date + " is not valid...\n")return is_date_validdef quote_pick(self, all_quotes, target_date, methods):print("quote_pick start..." + "\n")start = timeit.default_timer()results = []data_issue_count = 0for quote in all_quotes:try:if(quote['Symbol'] in self.index_array):results.append(quote)continuetarget_idx = Nonefor idx, quote_data in enumerate(quote['Data']):if(quote_data['Date'] == target_date):target_idx = idxif(target_idx is None):## print(quote['Name'] + " data is not available at this date..." + "\n")data_issue_count+=1continue## pick logic ##valid = Falsefor 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 = Truebreakexcept:valid = Falseif(valid):continue## pick logic end ##except KeyError as e:## print("KeyError: " + quote['Name'] + " data is not available..." + "\n")data_issue_count+=1print("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 resultsdef profit_test(self, selected_quotes, target_date):print("profit_test start..." + "\n")start = timeit.default_timer()results = []INDEX = NoneINDEX_idx = 0for quote in selected_quotes:if(quote['Symbol'] == self.sh000300['Symbol']):INDEX = quotefor idx, quote_data in enumerate(quote['Data']):if(quote_data['Date'] == target_date):INDEX_idx = idxbreakfor quote in selected_quotes:target_idx = Noneif(quote['Symbol'] in self.index_array):continuefor idx, quote_data in enumerate(quote['Data']):if(quote_data['Date'] == target_date):target_idx = idxif(target_idx is None):print(quote['Name'] + " data is not available for testing..." + "\n")continuetest = {}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")breakday2day_profit = self.get_profit_rate(quote['Data'][target_idx]['Close'], quote['Data'][target_idx+i]['Close'])test['Data'][0]['Day_' + str(i) + '_Profit'] = day2day_profitif(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_changetest['Data'][0]['Day_' + str(i) + '_Differ'] = day2day_profit-day2day_INDEX_changeresults.append(test)print("profit_test end... time cost: " + str(round(timeit.default_timer() - start)) + "s" + "\n")return resultsdef 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 methodsmethods = []path = self.testfile_path## from mongodbif(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 = Noneif(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 fileelse:if not os.path.exists(path):print("Portfolio test file is not existed, testing is aborted...\n")returnf = io.open(path, 'r', encoding='utf-8')for line in f:if(line.startswith('##') or len(line.strip()) == 0):continueline = 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 typesoutput_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 dataif(self.reload_data == 'Y'):print("Start loading stock data...\n")self.data_load(self.start_date, self.end_date, output_types)## test & generate portfolioif(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 stockholmdb.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。

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