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downloadFile.py
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downloadFile.py
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''''
下载分钟数据到本地csv文件函数：downloadMinutesToCsv
下载日线数据到本地csv文件函数：downloadDailyToCsv
'''
import tushare as ts
import pandas as pd
import csv
import time
import datetime
import os.path
import os
ts.set_token('85a6e863fa91060204e5339228932e52c4f90863d773778f3040f14a')
#保存从20100104到今天的可交易日期到本地
def saveTradeCalendarToLocal(calendarFile):
startDate = '20100104'
now = datetime.datetime.now()
endDate = now.strftime('%Y%m%d')
pro = ts.pro_api()
df = pro.trade_cal(exchange='', start_date=startDate, end_date=endDate, is_open=1)
readAndCheckCsv.deleteFile(calendarFile)
df.to_csv(calendarFile, columns=['exchange','cal_date'])
#获得交易日
def getTradeCalendarFromWeb(startDate, endDate):
listTempCalendar = []
listTradeCalendar = []
startDate2010 = '20100104'
now = datetime.datetime.now()
currentDate = now.strftime('%Y%m%d')
#获取从2010年到今天的可交易日期，并保存到一个列表里
try:
pro = ts.pro_api()
df = pro.trade_cal(exchange='', start_date=startDate2010, end_date=currentDate, is_open=1, fields='cal_date')
except Exception as e:
print(f'get calendar failed, e={str(e)}')
return
listTempCalendar = list(df.cal_date)
if 0 == len(listTempCalendar):
print(f'日期文件不存在!')
exit(0)
begin_date = datetime.datetime.strptime(startDate, "%Y%m%d")
calendarFileBeginDate = datetime.datetime.strptime(listTempCalendar[0], "%Y%m%d")
if begin_date < calendarFileBeginDate:
print(f'起始日期太早了，startDate = {startDate}, calendarFileBeginDate = {listTempCalendar[0]}')
exit(0)
end_date = datetime.datetime.strptime(endDate, "%Y%m%d")
calendarFileEndDate = datetime.datetime.strptime(listTempCalendar[len(listTempCalendar)-1], "%Y%m%d")
if end_date > calendarFileEndDate:
print(f'结束日期太晚了，end_date = {end_date}, calendarFileEndDate = {listTempCalendar[len(listTempCalendar)-1]}')
exit(0)
startDataFlag = False
endDateFlag = False
if (startDate not in listTempCalendar) or (endDate not in listTempCalendar):
begin_date = datetime.datetime.strptime(startDate, "%Y%m%d")
end_date = datetime.datetime.strptime(endDate, "%Y%m%d")
if startDate in listTempCalendar:
startDataFlag = True
if endDate in listTempCalendar:
endDateFlag = True
for i in range(12):
if False == startDataFlag:
delta = datetime.timedelta(days=1)
begin_date = begin_date + delta
tempDate = str(begin_date.date())
tempDate = tempDate.replace('-', '')
if tempDate in listTempCalendar:
startDate = tempDate
startDataFlag = True
if False == endDateFlag:
delta = datetime.timedelta(days=-1)
end_date = end_date + delta
tempDate = str(end_date.date())
tempDate = tempDate.replace('-', '')
if tempDate in listTempCalendar:
endDate = tempDate
endDateFlag = True
i = listTempCalendar.index(startDate)
j = listTempCalendar.index(endDate)
listTradeCalendar = listTempCalendar[i:(j+1)]
return startDate, endDate, listTradeCalendar
#获取所有股票,1)非深圳，上海股票剔除 2)ST股票剔除
def getAllStocks(Date):
listAllStocks = []
stList = []
pro = ts.pro_api()
try:
df = pro.query('daily_basic', ts_code='', trade_date=Date,fields='ts_code')
for index, row in df.iterrows():
if (True == row['ts_code'].startswith('00')) or (True == row['ts_code'].startswith('60')):
listAllStocks.append(row['ts_code'])
except Exception as e:
print(f'getAllStocks daily basic failed!')
return
try:
df = pro.query('stock_basic', exchange='', list_status='L', fields='ts_code,symbol,name,fullname,enname')
except Exception as e:
print(f'getAllStocks stock basic failed!')
return
#保存ST股票，需要剔除
for index, row in df.iterrows():
if 'ST' in row['name']:
stList.append(row['ts_code'])
#把ST股票从保存的股票里面剔除
listAllStocks = list(set(listAllStocks).difference(stList))
print(f'AllStocks num = {len(listAllStocks)}, ST: num={len(stList)}')
return listAllStocks
#下载日线数据，startDate = '20190202', endDate = '20200818', filePaht = 'C:/python/csv/zhangting/daily/2019to2020/'
def downloadDailyToCsv(startDate, endDate, filePath):
startDate, endDate, listTradeCalendar = getTradeCalendarFromWeb(startDate, endDate)
listAllStocks = getAllStocks(startDate)
for i in range(len(listAllStocks)):
fileName = filePath + listAllStocks[i] + '.csv'
if True == os.path.isfile(fileName):
os.remove(name)
pro = ts.pro_api()
try:
df = pro.query('daily', ts_code=listAllStocks[i], start_date=startDate, end_date=endDate)
except:
print(f'skip stock={listAllStocks[i]}')
continue
df = df.sort_index(ascending=False)
df.to_csv(fileName, mode='a', header=True, columns=['trade_date', 'open', 'high', 'low', 'close', 'pre_close'])
def convertDate(date):
str_list = list(date)
str_list.insert(4, '-')
str_list.insert(7, '-')
dateStr = ''.join(str_list)
return dateStr
#下载分钟数据到本地csv文件
def downloadMinutesToCsv(startDate, endDate, filePath):
listStartCanlender = []
listEndCanlender = []
startTime = convertDate(startDate)
endTime = convertDate(endDate)
startTime = startTime + ' 09:30:00'
endTime = endTime + ' 15:00:00'
startDate, endDate, listTradeCalendar = getTradeCalendarFromWeb(startDate, endDate)
listAllStocks = getAllStocks(startDate)
for i in range(len(listAllStocks)): #轮询所有股票
fileName = filePath + listAllStocks[i] + '.csv'
if True == os.path.isfile(fileName):
os.remove(name)
df = ts.pro_bar(ts_code=listAllStocks[i], freq='1min', start_date=startTime, end_date=endTime)
df = df.sort_index(ascending=False)
df.to_csv(fileName, mode='a', header=True, columns=['ts_code', 'trade_time', 'open', 'close', 'high', 'low'])
startDate = '20200827'
endDate = '20190110'
g_dailyCsv = 'C:/python/csv/temp/mini/'
getAllStocks(startDate)
#downloadDailyToCsv(startDate, endDate, g_dailyCsv) #把日线数据下载到本地
#downloadMinutesToCsv(startDate, endDate, g_dailyCsv) #把分钟数据下载到本地