python编写股票公式_一个用Python编写的股票数据（沪深）爬虫和选股策略测试框架...

一个户外论坛的特点: 列出一些活动，有翻页功能，点向一个活动显示当前活动信息，在二楼一般显示报名名单！ 需要的数据: 就是活动的信息， 报名的名单，价钱，主

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":"[email protected]", "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":"[email protected]", "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

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。

使用python scrapy爬虫框架 爬取科学网自然科学基金数据 fundspider.py文件 # -*- coding: utf-8 -*-from scrapy.selector import Selectorfrom fundsort.ite