在期货交易市场，无论是私募机构还是普通散户，争论技术分析和基本面分析谁好谁坏，从来就没有停止过。技术分析者认为价格已经包含了一切，相信未来价格还以趋势方式演变，只关心图表上价格行为本身的变化，判断它能卖多少钱。基本面分析者认为真正价值最终将会反映在价格上，并不需要关心短期价格走势，更多的是分析影响价格背后的因素，判断它值多少钱。 点击阅读更多内容
'''backtest
start: 2019-01-01 00:00:00
end: 2019-08-09 00:00:00
period: 1d
exchanges: [{"eid":"Futures_CTP","currency":"FUTURES"}]
'''
import requests
import re
from bs4 import BeautifulSoup
import time
import datetime
import random
import json
import threading
# 请求头文件
request_headers = {
'Connection': 'keep-alive',
'accept': 'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,image/apng,*/*;q=0.8,application/signed-exchange;v=b3;q=0.9',
'accept-language': 'zh-CN,zh;q=0.9,en;q=0.8',
'accept-encoding': 'gzip, deflate',
'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/80.0.3987.132 Safari/537.36',
'Referer': 'http://www.100ppi.com/sf2/day-2019-01-02.html'
}
# ip代理
proxies = {
'http': 'http://182.35.82.128:9999', 'https': 'https://182.35.82.128:9999'
}
diff_data = 0
reserve_data = 0
receipt_data = 0
profit_data = 0
# 日期转时间戳
def to_timestamp(date_str):
times = date_str + " 00:00:00"
time_array = time.strptime(times, "%Y-%m-%d %H:%M:%S")
return int(round(time.mktime(time_array) * 1000))
# 返回日期数组
def date_arr(year, month, day):
begin = datetime.date(year, month, day)
end = datetime.date.today()
arr = []
for i in range((end - begin).days + 1):
day = begin + datetime.timedelta(days=i)
arr.append([str(day).replace('-', ''), str(day),
day.weekday() + 1, to_timestamp(str(day))])
return arr
# 获取基差
def spot_futures_diff_data(date, futures_name):
global diff_data
url = f"http://www.100ppi.com/sf2/day-{date}.html"
try:
url_text = requests.get(
url, headers=request_headers).text # , proxies=proxies
except BaseException:
Log('获取基差数据失败')
return int(diff_data)
soup = BeautifulSoup(url_text, "html5lib")
if len(soup.select("#fdata")) > 0:
results = soup.select("#fdata")[0]
for i in results.find_all('tr'):
if len(i.find_all('td', text=futures_name)) > 0:
data = i.find_all('font')[0].text
if data is not None:
diff_data = data
return int(diff_data)
# 获取库存
def spot_reserve_data(date, futures_name):
global reserve_data
url = f'http://www.shfe.com.cn/data/dailydata/{date}weeklystock.dat'
try:
url_text = requests.get(url, headers=request_headers).text
except BaseException:
print('获取库存数据失败')
return reserve_data
total = 0
count = 0
if url_text[0] == '{':
for i in json.loads(url_text)['o_cursor']:
if futures_name in i['VARNAME']:
if '合计' not in i['WHABBRNAME'] and '总计' not in i['WHABBRNAME']:
try:
inventory = int(i['WHSTOCKS'])
except BaseException:
return reserve_data
if inventory > 0:
total = total + inventory
count = count + 1
if count > 0:
reserve_data = int(total / count)
return reserve_data
# 获取仓单
def spot_receipt_data(date, futures_name):
global receipt_data
url = f'http://www.shfe.com.cn/data/dailydata/{date}dailystock.dat'
try:
url_text = requests.get(url, headers=request_headers).text
except BaseException:
print('获取库存数据失败')
return receipt_data
total = 0
count = 0
if url_text[0] == '{':
for i in json.loads(url_text)['o_cursor']:
if futures_name in i['VARNAME']:
if '合计' not in i['WHABBRNAME'] and '总计' not in i['WHABBRNAME']:
try:
inventory = int(i['WRTWGHTS'])
except BaseException:
return receipt_data
if inventory > 0:
total = total + inventory
count = count + 1
if count > 0:
receipt_data = int(total / count)
return receipt_data
# 虚拟利润
def get_profit_data():
global profit_data
profit_data = profit_data + random.randint(-100, 150)
return profit_data
def main():
# threading.Thread(target=spot_futures_diff_arr, args=('天然橡胶',)).start()
# threading.Thread(target=commodity_inventory_arr, args=('天然橡胶',)).start()
# threading.Thread(target=commodity_warehouse_receipt_arr, args=('天然橡胶',)).start()
cfgA = {
"extension": {
"layout": 'single',
"col": 6,
"height": "500px",
},
"title": {
"text": "基差图表"
},
"xAxis": {
"type": "datetime"
},
"series": [{
"name": "基差",
"data": [],
}]
}
cfgB = {
"extension": {
"layout": 'single',
"col": 6,
"height": "500px",
},
"title": {
"text": "库存图表"
},
"xAxis": {
"type": "datetime"
},
"series": [{
"name": "库存",
"data": [],
}]
}
cfgC = {
"extension": {
"layout": 'single',
"col": 6,
"height": "500px",
},
"title": {
"text": "仓单图表"
},
"xAxis": {
"type": "datetime"
},
"series": [{
"name": "仓单",
"data": [],
}]
}
cfgD = {
"extension": {
"layout": 'single',
"col": 6,
"height": "500px",
},
"title": {
"text": "利润图表"
},
"xAxis": {
"type": "datetime"
},
"series": [{
"name": "利润",
"data": [],
}]
}
LogReset()
chart = Chart([cfgA, cfgB, cfgC, cfgD])
chart.reset()
for i in date_arr(2018, 1, 1):
diff = spot_futures_diff_data(i[1], '天然橡胶')
reserve = spot_reserve_data(i[0], '天然橡胶')
receipt = spot_receipt_data(i[0], '天然橡胶')
profit = get_profit_data()
if diff != 0 and reserve != 0 and receipt != 0:
chart.add(0, [i[3], diff])
chart.add(1, [i[3], reserve])
chart.add(2, [i[3], receipt])
chart.add(3, [i[3], profit])
chart.update([cfgA, cfgB, cfgC, cfgD])
time.sleep(1)
Log(f'基差：{diff} 库存：{reserve} 仓单：{receipt} 日期：{i[1]}')
Hukybo win+r >>> 输入cmd >>> 点击确定 >>> 输入pip install beautifulsoup4 >>> 回车
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