def store(self):
now = datetime.datetime.now()
total = 0
for site in self.sites:
v = getattr(self, site)
m = v()
num = m.replace("$", "")
total += Decimal(num)
site_list = dumper.load(site, silent=True, path=BASE_DIR) or []
site_list.append({'site': site, 'datetime': now, 'total': num})
dumper.dump(site_list, site, path=BASE_DIR)
total_list = dumper.load('total', silent=True, path=BASE_DIR) or []
total_list.append({'site': total, 'datetime': now, 'total': total})
dumper.dump(total_list, "total", path=BASE_DIR)
print "store file {}".format(now)
def main():
parser = argparse.ArgumentParser(description='Formatter for C language')
parser.add_argument('--train', dest='train', type=str, help='Train classifier on that folder')
parser.add_argument('--classifier_filename', dest='classifier_filename', type=str, default='linux_classificators.data',
help='In which file save classifier')
parser.add_argument('--clftab', dest='clftab', type=str,
choices=['solving_tree', 'kneighbors', 'svm', 'random_forest'], default='random_forest',
help='Type of classifier for tabs')
parser.add_argument('--clfspace', dest='clfspace', type=str,
choices=['solving_tree', 'kneighbors', 'svm', 'random_forest'], default='random_forest',
help='Type of classifier for spaces')
parser.add_argument('--clfnl', dest='clfnewline', type=str,
choices=['solving_tree', 'kneighbors', 'svm', 'random_forest'], default='random_forest',
help='Type of classifier for newlines')
parser.add_argument('--load_clfs', dest='clfs', type=str, help='Load previously saved classifiers')
parser.add_argument('file', help='File to process', nargs='?')
args = parser.parse_args()
clfs = None
if args.train is not None:
clfs = learning.generate_classifiers(args)
dumper.dump(clfs, learning.vectorizer, args.classifier_filename)
elif args.clfs is not None:
data = dumper.load(args.clfs)
clfs = data['classifiers']
learning.vectorizer = data['vectorizer']
if args.file is not None:
print("Processing file...")
data = learning.format_file(args.file, clfs['newline'], clfs['space'], clfs['tab'])
print(data)
def graph_site(self, site):
x, y, data = [], [], []
site_list = dumper.load(site, path=BASE_DIR)
y_old = float(site_list[0]["total"])
for i in site_list:
t = float(i["total"]) - y_old
y_old = float(i["total"])
if t != 0:
x.append(i['datetime'])
y.append(t)
data.append(go.Scatter(x=x, y=y, name=site))
l = dict(layout={'title': site}, data=data)
print(site,
py.plot(l, filename=site, fileopt="overwrite", auto_open=False))
def main():
nimilista = {}
nimilista = dumper.load()
mainwindow = tkinter.Tk()
mainwindow.wm_title('Asiakashallintaohjelmisto')
menubar = tkinter.Menu(mainwindow)
#mainwindow.iconbitmap(default='transparent.ico') keksi uusi ikoni
asiakasGUI = AsiakasGUI(nimilista,mainwindow)
menubar.add_command(label='Lataa',command=lambda: asiakasGUI.newlistbox(1))
menubar.add_command(label='Tallenna',command=lambda: asiakasGUI.newlistbox(2))
mainwindow.protocol("WM_DELETE_WINDOW",asiakasGUI.eventhandler)
mainwindow.config(menu=menubar)
mainwindow.mainloop()
def newlistbox(self,choice):
if choice == 1:
dumper.dump(self.nimilista)
self.nimilista = {}
a = tkinter.simpledialog.askstring('Anna etsittävän tiedoston nimi', 'Tiedoston nimi:')
self.nimilista = dumper.specificload(a)
if self.nimilista == {}:
tkinter.messagebox.showinfo('File not found','Specific file not found')
self.nimilista = dumper.load()
self.listbox.delete(0,'end')
for i in self.nimilista:
self.listbox.insert('end',i)
if choice == 2:
a = tkinter.simpledialog.askstring('Anna tallennettavan tiedoston nimi','Tiedoston nimi: ')
dumper.specificdump(self.nimilista,a)
def graph_total(self):
data = dumper.load("total", path=BASE_DIR)
days = [x["datetime"] for x in data]
values = ["%s" % x["total"] for x in data]
g = [go.Scatter(x=days, y=values)]
py.plot(dict(data=g,
layout={
"title": "Growth",
'xaxis': {
'title': "Year days"
},
'yaxis': {
'title': "Money"
}
}),
filename="nekototal",
fileopt="overwrite",
auto_open=False)
def graph(self):
data = []
for site in self.sites:
site_list = dumper.load(site, path=BASE_DIR)
x = [i['datetime'] for i in site_list]
y = [i["total"] for i in site_list]
data.append(go.Scatter(x=x, y=y, name=site))
data.append(
go.Scatter(y=[self.limit for i in range(0, len(x))],
x=x,
name="limit"))
opts = dict(data=data,
layout={
'title': 'Total earns',
'xaxis': {
'title': "Timeline"
},
'yaxis': {
'title': "Money"
}
})
py.plot(opts, filename="neko", fileopt="overwrite", auto_open=False)