def merge_length(start, end):
lens = np.arange(start=0.0100, stop=0.0200, step=0.0001)
columns = []
for x in lens:
columns.append("%.4f" % x)
print(columns)
df = pd.DataFrame(columns=columns)
eq = ts.Equity()
all = eq.Equ(equTypeCD='A', listStatusCD='L', field='ticker')
all['ticker'] = all['ticker'].map(lambda x: str(x).zfill(6))
for i, row in all.iterrows():
path = cfg.get_length_ratio_path(row['ticker'], start, end)
try:
if os.path.exists(path):
len_df = pd.DataFrame.from_csv(path)
len_df.index = len_df.index.map(lambda x: "%.4f" % x)
# print(len_df.index)
for len in columns:
# print(len_df.loc[len, 'ratio'])
df.loc[row['ticker'], len] = len_df.loc[len, 'ratio']
print(row['ticker'])
except Exception as e:
print(e.message)
continue
df.to_csv("/home/chengang/tab.csv")
def stock_open_data_download():
# 获取沪深A股正常股票信息，listStatusCD上市状态，可选状态有L——上市，S——暂停，DE——已退市，UN——未上市
eq = ts.Equity()
df = eq.Equ(equTypeCD='A',
listStatusCD='L',
field='ticker,secShortName,totalShares,nonrestFloatShares')
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
df.to_csv("./data/stock_open.csv")
def fetch_stock_list_to_mongo():
eq = ts.Equity()
df = eq.Equ(equTypeCD='A', listStatusCD='L', field='')
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
mongo = Mongo()
db = mongo.getDB()
cursor = db.stock_list.find()
if cursor.count() == 0:
db.stock_list.insert(json.loads(df.to_json(orient='records')))
def get_float_share(code, date):
'''
every day will update local storage
:param code:
:param start: 20100101
:param end: 20100101
:return:
'''
share_path = cfg.get_today_share_path(code)
# if os.path.exists(share_path)
eq = ts.Equity()
def find_nonrest():
eq = ts.Equity()
df = eq.Equ(equTypeCD='A', listStatusCD='L', field='ticker')
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
for i, row in df.iterrows():
print(row['ticker'])
dff = eq.EquShare(
ticker=row['ticker'],
field='ticker,changeDate,totalShares,sharesA,floatA,nonrestfloatA')
for j, first in dff.iterrows():
print(j)
if j != 0:
break
if first['floatA'] != first['nonrestfloatA']:
print(first)
def get_share_online(code):
'''
get share from ipo till now
:param code:
:return:
'''
eq = ts.Equity()
ipo = eq.EquIPO(ticker=code, field='publishDate,onlineIssueDate,listDate')
start = '2006-01-01'
if not ipo.empty:
print(ipo)
start = ipo.iat[0, 0]
start = start.replace("-", "")
# end = datetime.date.today().strftime("%Y%m%d")
# print(start, end)
share = eq.EquShare(ticker=code, beginDate=start)
print(share)
def fetch_():
ts.set_token(cfg.get_datayes_key())
eq = ts.Equity()
df = eq.Equ(equTypeCD='A', listStatusCD='L', field='ticker')
df['ticker'] = df['ticker'].map(lambda x: str(x).zfill(6))
start, end = '20150901', '20160326'
# thread can not make full use of cpu
for i, row in df.iterrows():
csv = cfg.get_ratio_table_path(row['ticker'], start, end)
if os.path.exists(csv):
print("{0}/{1} {2} exists.".format(i, len(df.index), row['ticker']))
continue
# code_queue.put(row['ticker'])
# code_list.append(str(row['ticker']))
proc_queue.put(row['ticker'])
# for i in range(3):
# thread = ExportThread(thread_id, code_queue, start, end)
# thread.start()
# threads.append(thread)
# thread_id += 1
#
# get_code_and_export(0, code_queue, start, end)
#
# for t in threads:
# t.join()
#
# print("Exit main thread.")
processes = 4
for i in range(processes):
p = ExportProcess(i+1, start, end, proc_queue)
p.start()
procs.append(p)
for p in procs:
p.join()
print("Exit main")
#-*- coding: UTF-8 -*-
import sys
reload(sys)
sys.setdefaultencoding('utf8')
from sqlalchemy import create_engine
import tushare as ts
#import pandas as pd
#import numpy as np
import time
#nowtime = datetime.datetime.now()
nowtime = time.strftime('%Y-%m-%d %H:%M:%S')
engine = create_engine('mysql://*****:*****@127.0.0.1/db_equ?charset=utf8')
eq = ts.Equity()
import MySQLdb
# 打开数据库连接
db = MySQLdb.connect("127.0.0.1","root","root","db_mkt" )
# 使用cursor()方法获取操作游标
cursor = db.cursor()
#股票列表: 获取沪深上市公司基本情况
def stock():
dflist = ts.get_stock_basics()
dflist.insert(0,'uploadtime',nowtime)
dflist.to_sql('tb_list',engine,if_exists='append')
#dflist.to_excel('E:/Anaconda/getdata/test.xlsx')
def insertid():
sql = """ALTER TABLE tb_list
ADD list_id int(20) not null auto_increment ,
import matplotlib.pyplot as plt
#%matplotlib inline
import tushare as ts
ts.set_token(
'6cbc132dcf304322dc7b6f1d714d792fe224049b2038abf29e7711bf71334b52')
'''
股票数据：名称、上市交易所 上市时间， 历史日数据
历史某天的分笔数据
'''
#DataAPI.TickRTIntraDayMoneyFlowOrderGet(securityID=u"000001.XSHE",startTime=u"09:30",endTime=u"11:00",field=u"",pandas="1")
eq_mt = ts.Master()
SecID = eq_mt.SecID(cnSpell='gxgk')
eq_tl = ts.Equity()
candi_stock_ipo = eq_tl.EquIPO(secID='002074.XSHE')
candi_stock_d = ts.get_h_data('002074', start='2006-10-18', end='2016-04-12')
## 获取历史分笔数据
candi_stock_fb = ts.get_tick_data('002074', date='2016-04-12')
candi_stock_fb.head(10)
dates = pd.to_datetime(shz.index)
## 第一种作图方法
def simple_plot(dates, data):
fig = plt.figure(figsize=(10, 4))
plt_sh = fig.add_subplot(1, 1, 1)