def test_key_is_unique(fs):
contents = [
'0650000', '1-fidles|FLAG_1', '1-fidles|FLAG_1', '1-fidles|FLAG_1'
]
fs.create_file('/foo', contents='\n'.join(contents))
with pytest.raises(KeyError):
main('/foo', [])
def test_multiple_ansfile(fs, capsys):
i1 = [
'0650000',
'foo|F1',
'bar|F4'
]
i2 = [
'0650000',
'foo|F3',
'bar|F4'
]
a1 = [
'foo|F1|20',
'bar|F2|30'
]
a2 = [
'foo|F3|20',
'bar|F4|30'
]
fs.create_file('/a1', contents='\n'.join(a1))
fs.create_file('/a2', contents='\n'.join(a2))
fs.create_file('/i1', contents='\n'.join(i1))
fs.create_file('/i2', contents='\n'.join(i2))
main('/i1', ['/a1', '/a2'])
captured = capsys.readouterr()
assert captured.out == '0650000: 50\n'
main('/i2', ['/a1', '/a2'])
captured = capsys.readouterr()
assert captured.out == '0650000: 50\n'
def main():
if os.path.exists("config.yml"):
with open("config.yml", "r", encoding="utf-8") as cfg:
cy = yaml.load(cfg)
if cy["status"]["urp_code"]:
account = cy["user"]["account"]
password = cy["user"]["password"]
else:
account = input("请输入你的学号：")
password = input("请输入你的密码：")
cy["user"]["account"] = account
cy["user"]["password"] = password
stu = student.Student(account, password)
response_status = stu.login()
if not response_status:
cy["status"]["urp_code"] = 0
return 0
else:
print("登录成功！")
cy["status"]["urp_code"] = 1
while(True):
pt = prettytable.PrettyTable(["操作类型"])
# 设置prettytable靠左对齐
pt.align = "l"
pt.add_row(["1、成绩查询"])
pt.add_row(["2、一键评教"])
pt.add_row(["3、四六级查询"])
print(pt)
choice = input("请按序号输入你要进行的操作，或者按其他任意键退出程序\r\n# ").strip()
if choice.isdigit():
choice = int(choice)
if choice == 1:
score.main(stu)
elif choice == 2:
judge.judge_all(stu)
elif choice == 3:
cet.main(cy)
else:
print("你选择退出程序，好的，再见。")
save_config(cy)
return 0
else:
print("你选择退出程序，好的，再见。")
save_config(cy)
return 0
else:
print("配置文件已丢失，正在重新生成···")
init_config()
print("配置文件重新生成成功，请重新运行本程序进行登录")
def test_filename():
with pytest.raises(ValueError):
main('', [])
with pytest.raises(ValueError):
main('foo.txt', [])
with pytest.raises(ValueError):
main('foo.', [])
def main(args):
output_eval = args["output_eval"]
output_score = args["output_score"]
if args["algo"]:
module_name = args["input"]
score_args = {
"module": module_name,
"params": args["params"],
"output": output_score,
"align": args["align"]
}
scores_file_name = score.main(score_args)
else:
scores_file_name = args["input"]
result = evaluate_from_file(scores_file_name)
dump(output_eval, result)
bestAcc = -100.0
learnedNetworkFiles = sorted(learnedNetworkFiles)
for learnedNetworkFile in learnedNetworkFiles:
#-pre-process
if os.path.exists("LSTM.rnnw"):
os.remove("LSTM.rnnw")
shutil.copy(learnedNetworkFile, "LSTM.rnnw")
#-evaluate
LSTMWithBOW.main([
'--dataset', 'dstc4_dev', '--dataroot', 'data', '--trackfile',
'baseline_dev.json', '--ontology',
'scripts/config/ontology_dstc4.json'
])
score.main([
'--dataset', 'dstc4_dev', '--dataroot', 'data', '--trackfile',
'baseline_dev.json', '--scorefile', 'baseline_dev.score.csv',
'--ontology', 'scripts/config/ontology_dstc4.json'
])
#-write result
res.write(learnedNetworkFile + ":" + "\n")
for line in open("baseline_dev.score.csv", "r"):
#Accuracy
m1 = re.search(
"all, all, 1, acc,", line
) #Only see schedule 1 (Consider all turn in evaluation)
if m1 != None:
m2 = re.search("([0-9]|\.)+$", line)
res.write("-" + line)
if bestAcc < float(m2.group(0)):
bestAcc = float(m2.group(0))
bestAccNet = learnedNetworkFile
learnedNetworkFiles=glob.glob("*.rnnw")
if "LSTM.rnnw" in learnedNetworkFiles:
learnedNetworkFiles.remove("LSTM.rnnw")
bestf1Net=None
bestf1=-100.0
bestAccNet=None
bestAcc=-100.0
learnedNetworkFiles=sorted(learnedNetworkFiles)
for learnedNetworkFile in learnedNetworkFiles:
#-pre-process
if os.path.exists("LSTM.rnnw"):
os.remove("LSTM.rnnw")
shutil.copy(learnedNetworkFile, "LSTM.rnnw")
#-evaluate
LSTMWithBOW.main(['--dataset', 'dstc4_dev', '--dataroot', 'data', '--trackfile', 'baseline_dev.json', '--ontology', 'scripts/config/ontology_dstc4.json'])
score.main(['--dataset', 'dstc4_dev', '--dataroot', 'data', '--trackfile', 'baseline_dev.json', '--scorefile', 'baseline_dev.score.csv', '--ontology', 'scripts/config/ontology_dstc4.json'])
#-write result
res.write(learnedNetworkFile+":"+"\n")
for line in open("baseline_dev.score.csv","r"):
#Accuracy
m1=re.search("all, all, 1, acc,",line)#Only see schedule 1 (Consider all turn in evaluation)
if m1 != None:
m2=re.search("([0-9]|\.)+$",line)
res.write("-"+line)
if bestAcc < float(m2.group(0)):
bestAcc=float(m2.group(0))
bestAccNet=learnedNetworkFile
#L1
m1=re.search("all, all, 1, f1,",line)#Only see schedule 1 (Consider all turn in evaluation)
if m1 != None:
m2=re.search("([0-9]|\.)+$",line)
def score_labeled_data(main_config_fpath):
'''Score ConvNet precision and accuracy on labeled data'''
score.main(main_config_fpath)
def test_student_id(fs):
fs.create_file('/foo', contents='06')
with pytest.raises(ValueError):
main('/foo', [])
def index(request):
main()
return render(request, "index.html")
def run_script():
loop = asyncio.new_event_loop()
thread = threading.Thread(target=loop.run_until_complete(main(loop)))
thread.start()
thread.join()
def index():
form = MyForm()
if form.validate_on_submit():
filename = resumes.save(form.resume.data)
return "<h1>" + score.main(filename, form.description.data) + "</h1>"
return render_template('index.html', form=form)
