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
import requests
from bs4 import BeautifulSoup
import time
import datetime
import json
diff_data = reserve_data = receipt_data = 0
def to_timestamp(date_str):
time_array = time.strptime(date_str + " 00:00:00", "%Y-%m-%d %H:%M:%S")
return int(round(time.mktime(time_array) * 1000))
def date_arr(year, month, day):
begin, end = datetime.date(year, month, day), 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
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).text
except BaseException:
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)
def spot_data(date, futures_name, url_type, types):
global reserve_data, receipt_data
data_type = reserve_data if types == 'WHSTOCKS' else receipt_data
url = f'http://www.shfe.com.cn/data/dailydata/{date}{url_type}.dat'
Log(url)
try:
url_text = requests.get(url).text
except BaseException:
return data_type
total = 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']:
if '总计' not in i['WHABBRNAME']:
try:
inventory = int(i[types])
except BaseException:
return data_type
if inventory > 0:
total, count = total + inventory, count + 1
if count > 0:
data_type = int(total / count)
return data_type
def main():
cfgA = {
"extension": {"layout": 'single', "col": 4, "height": "500px"},
"title": {"text": "基差图表"},
"series": [{"name": "基差", "data": []}]
}
cfgB = {
"extension": {"layout": 'single', "col": 4, "height": "500px"},
"title": {"text": "库存图表"},
"series": [{"name": "库存", "data": []}]
}
cfgC = {
"extension": {"layout": 'single', "col": 4, "height": "500px"},
"title": {"text": "仓单图表"},
"series": [{"name": "仓单", "data": []}]
}
LogReset()
chart = Chart([cfgA, cfgB, cfgC])
chart.reset()
for i in date_arr(2018, 1, 1):
diff = spot_futures_diff_data(i[1], '天然橡胶')
reserve = spot_data(i[0], '天然橡胶', 'weeklystock', 'WHSTOCKS')
receipt = spot_data(i[0], '天然橡胶', 'dailystock', 'WRTWGHTS')
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.update([cfgA, cfgB, cfgC])
time.sleep(1)
Log(f'基差：{diff} 库存：{reserve} 仓单：{receipt} 日期：{i[1]}')
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