通达信交易接口-用Python筛选底部股票代码

大家好，今天学习一下用Python筛选底部股票代码

获取全量股票数据

先创建用于保存股票数据的mysql数据库表

创建表语句如下：

create table stock
(
    id       bigint auto_increment comment "自增主键"
        primary key,
    bs_code  varchar(16)  null comment "bs股票代码",
    code     varchar(16)  null comment "股票代码",
    name     varchar(32)  null comment "股票名称",
    link     varchar(128) null comment "链接",
    ipo_date varchar(32)  null comment "上市日期"
)
    comment "股票基础信息表" charset = utf8mb4;

写Python代码调用股票列表接口获取股票列表并保存到mysql数据库表中

运行结果如下：

股票列表存入数据库

获取每天历史交易数据

创建用于保存历史交易数据的MYSQL数据表

create table day
(
    id         bigint auto_increment comment "自增主键"
        primary key,
    code       varchar(16) null comment "股票代码",
    trade_date varchar(32) null comment "交易日期",
    open       float       null comment "开盘价",
    high       float       null comment "最高价",
    low        float       null comment "最低价",
    close      float       null comment "收盘价",
    pre_close  float       null comment "昨收价",
    amt_chg    float       null comment "涨跌额",
    pct_chg    float       null comment "涨跌幅",
    vol        float       null comment "成交量",
    amount     float       null comment "成交额"
)
    comment "日线行情表" charset = utf8mb4;

create index code
    on day (code);

create index pct_chg
    on day (pct_chg);

create index trade_date
    on day (trade_date);

调用tushare接口获取全量股票数据

注册tushare并获取TOKEN

写Python代码调用tushare的daily接口获取日数据并保存到mysql表中

import pymysql as pymysql
import numpy as np
import tushare as ts
import baostock as bs
import time
import datetime

begin_trade_date = "20220727"

bs.login()
time_start = time.time()
token = "这里换成自己的TOKEN（上面有截图如何获取接口TOKEN）"
ts.set_token(token)
pro = ts.pro_api()
# 打开数据库连接
db = pymysql.connect(host="localhost", port=3306, user="root", passwd="123456", db="tushare", charset="utf8mb4")
cursor = db.cursor()


def day(trade_date):
    day_data = pro.daily(trade_date=trade_date,
                         fields="ts_code,trade_date,open,high,low,close,pre_close,change,pct_chg,vol,amount")
    day_data_list = np.array(day_data).tolist()
    insert_day_data_list = []
    for index, val in enumerate(day_data_list):
        if not val[0].startswith("0") and not val[0].startswith("6"):
            continue
        val[0] = val[0].split(".")[0]
        insert_day_data_list.append(val)

    delete_day_sql = "delete from day where trade_date=" + trade_date
    try:
        # 先删除此交易日数据
        cursor.execute(delete_day_sql)
        db.commit()
        print(trade_date + " 数据已删除")
    except Exception as e:
        print(e)
        db.rollback()

    insert_day_sql = "INSERT INTO day (code, trade_date, open, high, low, close, pre_close, amt_chg, pct_chg, vol, amount) VALUES (%s,%s,%s,%s,%s,%s,%s,%s,%s,%s,%s)"
    try:
        # 插入此交易日数据
        cursor.executemany(insert_day_sql, insert_day_data_list)
        db.commit()
        print(trade_date + " 数据已插入")
    except Exception as e:
        print(e)
        db.rollback()


compare_date = datetime.datetime.strptime(begin_trade_date, "%Y%m%d")
now_time = time.strftime("%Y%m%d", time.localtime())
now_date = datetime.datetime.strptime(now_time, "%Y%m%d")
while compare_date <= now_date:
    # 调一次方法
    trade_date = compare_date.strftime("%Y%m%d")
    day(trade_date)
    compare_date = compare_date + datetime.timedelta(days=1)

# 关闭游标
cursor.close()
bs.logout()
# 关闭数据库连接
time_end = time.time()
time_sum = round((time_end - time_start) / 60, 2)
print("执行结束 共耗时" + str(time_sum) + "分钟")

查看获取效果：

股票日数据保存到数据库

筛选底部股票数据

创建一个用于保存筛选数据的MYSQL数据库表

create table pick
(
    link varchar(128) null comment "链接"
)
    comment "选股表" charset = utf8mb4;

查询近7天有6天收阴的股票数据，代码如下

from datetime import datetime as dtime
import datetime
import pymysql as pymysql
import baostock as bs
import numpy as np
import math
import time

# 最小市值
cir_min = 50
# 最大市值
cir_max = 3000
# 时间跨度
duration = 7
# 收阴个数
board = 6
now_time = "20221024"
sevenDayAgo = (datetime.datetime.strptime(now_time, "%Y%m%d") - datetime.timedelta(days=duration)).strftime("%Y%m%d")

# now_time = time.strftime("%Y%m%d", time.localtime())
# sevenDayAgo = (datetime.datetime.now() - datetime.timedelta(days=duration)).strftime("%Y%m%d")


bs.login()
time_start = time.time()
# 打开数据库连接
db = pymysql.connect(host="localhost", port=3306, user="root", passwd="123456", db="tushare", charset="utf8mb4")
cursor = db.cursor()

query_top_sql = " 
select b.bs_code,b.link,a.vol,a.close 
from day a inner join stock b on a.code=b.code 
where 
a.trade_date = %s" % now_time + " 
and a.code in ( 
select 
code 
from day 
WHERE 
1=1 
and pct_chg < 0 
and trade_date >= %s" % sevenDayAgo + " 
and trade_date <= %s" % now_time + " 
group by code 
HAVING count(trade_date)>=%s" % board + ")"
cursor.execute(query_top_sql)
top_list_all = cursor.fetchall()
top_list = np.array(top_list_all).tolist()
# 筛选这些票里流通值介于30亿到150亿的票
pic_top_list = []
start_date = dtime.strptime(now_time, "%Y%m%d").strftime("%Y-%m-%d")
end_date = dtime.strptime(now_time, "%Y%m%d").strftime("%Y-%m-%d")
for index, val in enumerate(top_list):
    bs_code = val[0]
    link = val[1]
    vol = val[2]
    close = val[3]
    turn_rs = bs.query_history_k_data_plus(bs_code, "turn",
                                           start_date=start_date, end_date=end_date, frequency="d")

    while turn_rs.next():
        turn_row_list = turn_rs.get_row_data()
        turn_rate = turn_row_list[0]
        if turn_rate:
            cir = math.ceil(float(vol) / float(turn_rate) * float(close) / 10000)
            if cir_min < cir < cir_max:
                print(link)
                pic_top_list.append([link])
# 将这些筛选出来的票入表
delete_pick_table = "delete from pick"
try:
    cursor.execute(delete_pick_table)
    db.commit()
except Exception as e:
    print(e)
    db.rollback()
insert_pick_sql = "INSERT INTO pick (link) VALUES (%s)"
try:
    cursor.executemany(insert_pick_sql, pic_top_list)
    db.commit()
except Exception as e:
    print(e)
    db.rollback()

# 关闭游标
cursor.close()
bs.logout()
# 关闭数据库连接
time_end = time.time()
time_sum = round((time_end - time_start) / 60, 2)
print("执行结束 共耗时" + str(time_sum) + "分钟")

执行效果如下：

执行记录

存入pick表的数据如下

存入pick表的数据

打开每一行的链接直接链接到雪球网。

注：例子里的股票代码只供数据筛选学习使用，不构成任何投资建议！

完结！

文章为作者独立观点，不代表股票配资公司观点

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