UserPyScript/monitor/monitor.py at master · youerning/UserPyScript · GitHub

History

437 lines (350 loc) · 12.7 KB

Raw

100

101

102

103

104

105

106

107

108

109

110

111

112

113

114

115

116

117

118

119

120

121

122

123

124

125

126

127

128

129

130

131

132

133

134

135

136

137

138

139

140

141

142

143

144

145

146

147

148

149

150

151

152

153

154

155

156

157

158

159

160

161

162

163

164

165

166

167

168

169

170

171

172

173

174

175

176

177

178

179

180

181

182

183

184

185

186

187

188

189

190

191

192

193

194

195

196

197

198

199

200

201

202

203

204

205

206

207

208

209

210

211

212

213

214

215

216

217

218

219

220

221

222

223

224

225

226

227

228

229

230

231

232

233

234

235

236

237

238

239

240

241

242

243

244

245

246

247

248

249

250

251

252

253

254

255

256

257

258

259

260

261

262

263

264

265

266

267

268

269

270

271

272

273

274

275

276

277

278

279

280

281

282

283

284

285

286

287

288

289

290

291

292

293

294

295

296

297

298

299

300

301

302

303

304

305

306

307

308

309

310

311

312

313

314

315

316

317

318

319

320

321

322

323

324

325

326

327

328

329

330

331

332

333

334

335

336

337

338

339

340

341

342

343

344

345

346

347

348

349

350

351

352

353

354

355

356

357

358

359

360

361

362

363

364

365

366

367

368

369

370

371

372

373

374

375

376

377

378

379

380

381

382

383

384

385

386

387

388

389

390

391

392

393

394

395

396

397

398

399

400

401

402

403

404

405

406

407

408

409

410

411

412

413

414

415

416

417

418

419

420

421

422

423

424

425

426

427

428

429

430

431

432

433

434

435

436

437

#coding: utf-8

"""

monitor change of stock price every period that user set

requirement 1: add specify stock in a way, confile file or web page

requirement 2: add rule of monitor, price change today, price change recent day

requirement 3: inform specify user immediately with specify way of notice, like email,etc.

"""

import pandas as pd

import tushare as ts

import datetime

import os

import json

from configparser import ConfigParser

from utils import cache

confile = "monitor.conf"

name_cache = "stock.json"

sent_cache = "sent.json"

conf = ConfigParser()

conf.read(confile)

class bar(object):

"""a custom data type

"""

def __init__(self, code, code_data):

self.code = code

self._df = code_data

self.data = dict(code_data.iloc[-1])

self.get_stockname()

def get_stockname(self):

if not os.path.exists(name_cache):

down_code()

stocks = json.load(open(name_cache))

stock_name = stocks.get(self.code, "None")

self.name = stock_name

def down_code():

"""download code and name of all of A stock and save as stock.json in working directory

Returns:

None

"""

import requests

import re

from bs4 import BeautifulSoup

import json

url = "http://quote.eastmoney.com/stocklist.html"

headers = {"user-agent": "Mozilla/5.0 (Windows NT 10.0; Win64; x64)\

AppleWebKit/537.36 (KHTML, like Gecko) Chrome/63.0.3239.132 Safari/537.36"}

page = requests.get(url, headers=headers)

soup = BeautifulSoup(page.content.decode("gbk"), "lxml")

pattern = "(.+?)\((\d+)\)"

css_select = "div#quotesearch ul li a"

stock_lis = soup.select(css_select)

stocks = {}

for stock in stock_lis:

ret = re.findall(pattern, stock.text)

stocks[ret[0][1]] = ret[0][0]

with open(name_cache, "w") as wf:

json.dump(stocks, wf)

def trade_time():

"""is ts trade time

Returns:

True or False

"""

now = datetime.datetime.now()

# the trade period of morning

mopen = "9:30"

mend = "11:30"

# the trade period of afternoon

aopen = "13:00"

aend = "15:00"

mopen = gen_time(mopen)

mend = gen_time(mend)

aopen = gen_time(aopen)

aend = gen_time(aend)

# whether now in morning period

morning = mopen < now < mend

# whether now in afternoon period

afternoon = aopen < now < aend

if morning or afternoon:

return True

else:

return False

def gen_time(dt):

"""generate the time for specify hour and minute,like t=9:30

Args:

dt: the specify time in format, 9:30

Returns:

return the datetime with specify hour and minute today

example:

datetime.datetime(2018, 3, 1, 9, 30)

"""

moment = datetime.datetime.strptime(dt, "%H:%M")

ret = datetime.datetime.combine(datetime.datetime.today(), moment.time())

return ret

@cache

def fetch(code):

"""fetch history data of the code of stock

fetch the data of stock in recent year,may be 3 year, use the method get_k_data of tushare

Args:

code: the code of specify stock

Returns:

a dataframe object of pandas

example:

open close high low volume code

date

2015-07-14 4.333 4.333 4.333 4.333 2443864.0 000725

2015-07-15 4.677 3.958 4.677 3.939 20725290.0 000725

2015-07-16 3.939 4.027 4.136 3.762 12367056.0 000725

2015-07-17 4.047 4.254 4.333 4.037 14418724.0 000725

2015-07-20 4.264 4.234 4.342 4.165 13036186.0 000725

"""

df = ts.get_k_data(code)

df.index = pd.to_datetime(df.date)

df.drop("date", axis=1, inplace=True)

return df

def pchange(df):

"""add two column of price-change to the df the args pass

add the column name pchange mean price change ration.

add the column name change mean how many tick changed.

Args:

df: a dataframe of specify stock.

Returns:

a dataframe object of pandas

example:

open close high low volume code pchange change

date

2015-07-14 4.333 4.333 4.333 4.333 2443864.0 000725 NaN NaN

2015-07-15 4.677 3.958 4.677 3.939 20725290.0 000725 -0.086545 -0.375

2015-07-16 3.939 4.027 4.136 3.762 12367056.0 000725 0.017433 0.069

2015-07-17 4.047 4.254 4.333 4.037 14418724.0 000725 0.056370 0.227

2015-07-20 4.264 4.234 4.342 4.165 13036186.0 000725 -0.004701 -0.020

"""

df["pchange"] = df.close.pct_change()

df["change"] = df.close.diff()

return df

def ma(df, days=[10, 20, 50]):

"""add ma to the df

add ma10,20,50 to the dataframe the args pass

Args:

df: a dataframe of specify stock.

Returns:

a dataframe object of pandas

example:

open close high low volume code pchange change \

date

2018-02-22 5.59 5.66 5.68 5.54 5418361.0 000725 0.023508 0.13

2018-02-23 5.64 5.58 5.66 5.51 5013632.0 000725 -0.014134 -0.08

2018-02-26 5.65 5.79 5.86 5.47 11591063.0 000725 0.037634 0.21

2018-02-27 5.80 5.71 5.85 5.68 6707226.0 000725 -0.013817 -0.08

2018-02-28 5.61 5.65 5.73 5.56 4516456.0 000725 -0.010508 -0.06

MA10 MA20 MA50

date

2018-02-22 5.502 5.8915 5.8682

2018-02-23 5.492 5.8380 5.8682

2018-02-26 5.499 5.7950 5.8706

2018-02-27 5.534 5.7560 5.8688

2018-02-28 5.559 5.7110 5.8672

"""

for ma in days:

column_name = "MA{}".format(ma)

df[column_name] = pd.rolling_mean(df.close, ma)

return df

def report(s_lis, h_lis, subject="Breakthrough"):

"""create report for given code

Args:

s_lis: soft list

h_lis: hard list

subject: subject of notification

Returns:

a string of report

example:

breakthrough: soft-breakthrough

Code: 000725 京东方A

Price:5.82 3.2%(Percent change) 0.23(Price change)

MA10/20/50:5.72 5.68 5.56

"""

ret = []

if subject == "Breakthrough":

tpl = """breakthrough: {brk}

Code: {code} {name}

Price: {close} {pchange:.3} {change:.3}

MA10/20/50: {MA10:.5} {MA20:.5} {MA50:.5}

"""

for stock in s_lis:

# print(code.name)

if should_sent(stock.code, "soft-breakthrough"):

msg = tpl.format(name=stock.name, brk="soft-breakthrough(3%)", **stock.data)

ret.append(msg)

for stock in h_lis:

# print(code.name)

if should_sent(stock.code, "hard-breakthrough"):

msg = tpl.format(name=stock.name, brk="hard-breakthrough(5%)", **stock.data)

ret.append(msg)

elif subject == "Withdraw":

tpl = """withdraw: {wd}

Code: {code} {name}

Price: {close} {pchange:.3} {change:.3}

MA10/20/50: {MA10:.5} {MA20:.5} {MA50:.5}

"""

for stock in s_lis:

# print(code.name)

if should_sent(stock.code, "soft-withdown"):

msg = tpl.format(name=stock.name, wd="soft-withdown(3%)", **stock.data)

ret.append(msg)

for stock in h_lis:

# print(code.name)

if should_sent(stock.code, "hard-withdown"):

msg = tpl.format(name=stock.name, wd="hard-withdown(5%)", **stock.data)

ret.append(msg)

elif subject == "Stop loss":

tpl = """stop loss: {sl}

Code: {code} {name}

Price: {close} {pchange:.3} {change:.3}

MA10/20/50: {MA10:.5} {MA20:.5} {MA50:.5}

"""

for stock in s_lis:

# print(code.name)

if should_sent(stock.code, "soft-stoploss"):

msg = tpl.format(name=stock.name, sl="soft-stoploss(3%)", **stock.data)

ret.append(msg)

for stock in h_lis:

# print(code.name)

if should_sent(stock.code, "hard-stoploss"):

msg = tpl.format(name=stock.name, sl="hard-stoploss(5%)", **stock.data)

ret.append(msg)

if ret:

split_line = "".join(["\n", "-" * 30, "\n"])

message = split_line.join(ret)

inform(subject, message)

def inform(subject, msg):

"""inform user

"""

from utils import sendMail

print("send eamil...")

sendMail(subject, msg)

print(subject, "\n", msg)

def should_sent(code, status):

"""have it sent?

if the stock have sent at same price change point before,just ingore.

Args:

code: code of the stock

status: status of the stock, contain soft-withdraw,soft-breakthrough,etc.

Returns:

True or False

example:

if it never sent before, send.

"""

tformat = "%Y-%m-%d %H:%M"

now = datetime.datetime.now()

if not os.path.exists(sent_cache):

# print("not exists")

with open(sent_cache, "w") as wf:

content = {}

content["last_time"] = now.strftime(tformat)

content["status"] = {}

json.dump(content, wf)

content = json.load(open(sent_cache, "r"))

last_time = datetime.datetime.strptime(content["last_time"], tformat)

if now.date() > last_time.date():

# print("before")

content["last_time"] = now.strftime(tformat)

content["status"] = {}

content["status"][code] = status

with open(sent_cache, "w") as wf:

json.dump(content, wf)

return True

elif now.date() == last_time.date():

# print("now")

last_status = content["status"].get(code)

if last_status == status:

return False

else:

content["status"][code] = status

with open(sent_cache, "w") as wf:

json.dump(content, wf)

return True

else:

print("strange date...")

return False

def main():

# define hard-breakthrough,soft-breakthrough list

hbrk_lis = []

sbrk_lis = []

# define hard-withdraw, sort-withdraw list

hwd_lis = []

swd_lis = []

# define soft stop loss,hard stop loss list

ssl_lis = []

hsl_lis = []

attention_lis = conf["default"]["attention"]

attention_lis = attention_lis.split()

position_lis = conf.options("position")

# position_lis = position_lis.split()

# breakthrough, index 0 is soft-breakthrough, index 1 is hard-breakthrough

brk = conf["default"]["breakthrough"]

brk = [float(p) for p in brk.split()]

# withdraw, index 0 is soft,index 1 is hard

wd = conf["default"]["withdraw"]

wd = [float(p) for p in wd.split()]

for stock in attention_lis:

df = fetch(stock)

df = pchange(df)

df = ma(df)

if df.pchange[-1] > brk[1]:

# print(stock)

data = bar(stock, df)

hbrk_lis.append(data)

continue

if df.pchange[-1] > brk[0]:

# print(stock)

data = bar(stock, df)

sbrk_lis.append(data)

if hbrk_lis or sbrk_lis:

report(sbrk_lis, hbrk_lis)

for stock in position_lis:

# the cost of the stock

cost = float(conf["position"][stock])

df = fetch(stock)

df = pchange(df)

df = ma(df)

# check if the percent of price change of stock decrease 5%

if df.pchange[-1] < -wd[1]:

data = bar(stock, df)

hwd_lis.append(data)

continue

# check if the percent of price change of stock decrease 3%

if df.pchange[-1] < -wd[0]:

data = bar(stock, df)

swd_lis.append(data)

if swd_lis or hwd_lis:

report(swd_lis, hwd_lis, subject="Withdraw")

for stock in position_lis:

# the cost of the stock

cost = float(conf["position"][stock])

df = fetch(stock)

df = pchange(df)

df = ma(df)

# position of stop loss

sslp = cost * (1 - wd[0])

hslp = cost * (1 - wd[1])

if df.close[-1] < hslp:

data = bar(stock, df)

hsl_lis.append(data)

continue

if df.close[-1] < sslp:

data = bar(stock, df)

ssl_lis.append(data)

if ssl_lis or hsl_lis:

report(ssl_lis, hsl_lis, subject="Stop loss")

if __name__ == '__main__':

if trade_time:

main()

UserPyScript/monitor/monitor.py at master · youerning/UserPyScript · GitHub

Expand file tree

Breadcrumbs

monitor.py

Latest commit

History

Breadcrumbs

monitor.py

File metadata and controls