import requests
from lxml import etree
headers = {
    'User-Agent':'Mozilla/5.0 (Windows NT 6.1; WOW64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/60.0.3112.101 Safari/537.36'
}
def parse_url(url):
    response = requests.get(url,headers=headers)
    if response.status_code == 200:
        return etree.HTML(response.content)
    return False
def get_date(response):
    # 得到股票代码，开始和结束的日期
    start_date = ''.join(response.xpath('//input[@name="date_start_type"]/@value')[0].split('-'))
    end_date = ''.join(response.xpath('//input[@name="date_end_type"]/@value')[0].split('-'))
    code = response.xpath('//h1[@class="name"]/span/a/text()')[0]
    return code,start_date,end_date
def download(code,start_date, end_date):
    download_url = "http://quotes.money.163.com/service/chddata.html?code=1"+code+"&start="+start_date+"&end="+end_date+\
    "&fields=TCLOSE;HIGH;LOW;TOPEN;LCLOSE;CHG;PCHG;TURNOVER;VOTURNOVER;VATURNOVER;TCAP;MCAP"
    print(download_url) 
    data = requests.get(download_url,headers=headers)
    f = open(code + '.csv', 'wb')
    for chunk in data.iter_content(chunk_size=10000):
        if chunk:
            f.write(chunk)
    print('股票---',code,'历史数据正在下载')
download(code,'20210401', end_date)

from urllib import request
import json
import pandas as pd

def get_stock_data(id, scale, data_len):
    '''
    symnol = 股票代码
    scale = 5,15,30,60
    datalen = 获取数据长度，最大1023
    '''
    # 拼接API的url
    url = 'http://quotes.sina.cn/cn/api/json_v2.php/CN_MarketDataService.getKLineData?symbol={0}&scale={1}&datalen={2}'.format(id, scale, data_len)
    # 发起请求
    req = request.Request(url)
    # 获取响应
    rsp = request.urlopen(req)
    # 读取响应结果
    res = rsp.read()
    # 将json序列转换为Python对象
    res_json = json.loads(res)
    # bar列表
    bar_list = []
    # 将结果逆序
    res_json.reverse()
    # 遍历列表
    for dict in res_json:
        bar = {}
        bar['date'] = dict['day']
        bar['open'] = float(dict['open'])
        bar['high'] = float(dict['high'])
        bar['low'] = float(dict['low'])
        bar['close'] = float(dict['close'])
        bar['vol'] = int(dict['volume'])
        bar_list.append(bar)
    # 将结果转换为DataFrame对象
    df = pd.DataFrame(data=bar_list)
    return df
df = get_stock_data('sz002415', 30, 30)
df.head()

def get_future_data(id, scale):
    # 拼接API的url
    url = 'http://stock2.finance.sina.com.cn/futures/api/json.php/IndexService.getInnerFuturesMiniKLine{0}m?symbol={1}'.format(scale, id)
    # 发起请求
    req = request.Request(url)
    # 获取响应
    rsp = request.urlopen(req)
    # 读取响应结果
    res = rsp.read()
    # 将json序列转换为Python对象
    res_json = json.loads(res)
    # bar列表
#     print(res_json)
    bar_list = []
    # 将结果逆序
    res_json.reverse()
    # 遍历列表
    for line in res_json:
        bar = {}
        bar['date'] = line[0]
        bar['open'] = float(line[1])
        bar['high'] = float(line[2])
        bar['low'] = float(line[3])
        bar['close'] = float(line[4])
        bar['vol'] = int(line[5])
        bar_list.append(bar)
    # 将结果转换为DataFrame对象
    df = pd.DataFrame(data=bar_list)
    return df
df = get_future_data('rb1910', 5)
df.head()

import baostock as bs
import pandas as pd

#### 登陆系统 ####
lg = bs.login()
# 显示登陆返回信息
print('login respond error_code:'+lg.error_code)
print('login respond  error_msg:'+lg.error_msg)
login success!
login respond error_code:0
login respond  error_msg:success
#### 获取历史K线数据 ####
# 详细指标参数，参见“历史行情指标参数”章节
rs = bs.query_history_k_data_plus("sz.002415",
    "date,code,open,high,low,close,preclose,volume,amount,adjustflag,turn,tradestatus,pctChg,peTTM,pbMRQ,psTTM,pcfNcfTTM,isST",
    start_date='2020-01-01', end_date='2020-12-28', 
    frequency="d", adjustflag="3") #frequency="d"取日k线，adjustflag="3"默认不复权
#### 打印结果集 ####
data_list = []
while (rs.error_code == '0') & rs.next():
    # 获取一条记录，将记录合并在一起
    data_list.append(rs.get_row_data())
result = pd.DataFrame(data_list, columns=rs.fields)
#### 结果集输出到csv文件 ####
# result.to_csv("D:/history_k_data.csv", encoding="gbk", index=False)
# print(result)
result.tail()

import tushare as ts
pro = ts.pro_api('****************************')

df = pro.daily(ts_code='002415.SZ', start_date='20200101', end_date='20201228')  # 海康威视
df.head()

df = pro.limit_list() # 获取涨跌数据，需要权限
df.head()