def test_predictor_validation(self, logging_mock):
res = main(argv=['testdata/trainer/model.dat'])
self.assertEquals(res, PARAMETERS_REQUIRED)
logging_mock.warn.assert_called_with("Need to either specify -i or -e")
logging_mock.reset_mock()
res = main(argv=['testdata/extractorxml/train-import-handler.xml'])
self.assertEquals(res, INVALID_TRAINER)
self.assertFalse(logging_mock.called)
def test_csv_method(self, logging_mock):
res = main(argv=[
'testdata/trainer/model.dat', '-i',
'testdata/trainer/trainer.data.json', '-m', 'csv'
])
self.assertEquals(res, DONE)
os.remove('result.csv')
def test_extraction(self, db_mock, logging_mock):
res = main(argv=[
'testdata/trainer/model.dat', '-e',
'testdata/extractorxml/train-import-handler.xml', '-U',
'start=2012-12-03', '-U', 'end=2012-12-04'
])
self.assertEquals(res, DONE)
self.assertFalse(logging_mock.called)
def test_predictor(self):
print('\n\n')
dimg1 = util.get_full_imgpath('Al_Cardenas', 1)
dimg2 = util.get_full_imgpath('Mary_Landrieu', 3)
util.set_trained_model_name(ext_cmt='on_ext_features')
base_model_fname = util.get_trained_model_name()
use_batchnorm = False
th = 0.5
output = predictor.main(base_model_fname, dimg1, dimg2, use_batchnorm, th)
print(output)
def loaded():
target = os.path.join(APP_ROOT, 'files/')
print(target)
if not os.path.isdir(target):
os.mkdir(target)
print(request.files.getlist("file"))
for upload in request.files.getlist("file"):
print(upload)
print("{} is the file name".format(upload.filename))
filename = upload.filename
# This is to verify files are supported
ext = os.path.splitext(filename)[1]
if (ext == ".txt") or (ext == ".pdf"):
print("File supported moving on...")
else:
pass
destination = "/".join([target, filename])
print("Accept incoming file:", filename)
print("Save it to:", destination)
upload.save(destination)
label, intro_text, main_text, end_text = predictor.main()
if label == 0:
language = 'русский'
if label == 1:
language = 'английский'
if label == 2:
language = 'украинский'
# return send_from_directory("images", filename, as_attachment=True)
return render_template('loaded.html',
lang=language,
intro_text=intro_text,
main_text=main_text,
end_text=end_text)
import easytrader
import predictor
import datetime
import time
import sys
import tushare as ts
try:
predictor.sendMessage("新的交易开始啦:" + str(datetime.datetime.now()))
except:
pass
code = predictor.main()
#code = '600875'
#amount = 600
print("-----马上开始交易_%s -----" % code)
user = easytrader.use('ths')
while 1:
try:
user.connect(r'D:\Program Files\ths\xiadan.exe')
break
except:
pass
balance = user.balance
print(balance['总资产'])
print("waiting at:%s" % datetime.datetime.today())
while datetime.datetime.now().hour != 14 or datetime.datetime.now().minute != 56:
time.sleep(30)
while 1:
try:
price = ts.get_today_ticks(code).iloc[0]['price']
def test_roc_method(self, logging_mock):
res = main(argv=[
'testdata/trainer/model.dat', '-i',
'testdata/trainer/trainer.data.json', '-m', 'roc'
])
self.assertEquals(res, DONE)
def test_input_data(self, logging_mock):
res = main(argv=[
'testdata/trainer/model.dat', '-i',
'testdata/trainer/trainer.data.csv'
])
self.assertEquals(res, DONE)
def invocations():
return main(flask.request.get_data(cache=False))