def get(self):
uname = self.get_current_user()
user = User.get_user_by_name(uname)
order = get_order()
card = Card.get_by_porder(order)
cid = self.get_argument("cid",None)
if cid is not None:
card=Card.get_by_cid(cid)
article = Article.get_all_Acard(200)
usedCard = Card.get_all_card()
temp = []
for one in usedCard:
if 0 < one.porder and one.porder <= order:
temp.append(one)
usedCard = temp
reArticles = Article.get_all(200)
Rarticle = sorted(reArticles,BaseHandler.rank)
if len(Rarticle) > 6:
Rarticle = Rarticle[:6]
Ruser = User.get_all_user(100)
if len(Ruser)>9:
Ruser = Ruser[:9]
if len(usedCard)>3:
usedCard = usedCard[:3]
self.render("card.html",user=user,Rarticle=Rarticle,Article=article,usedCard=usedCard,Ruser=Ruser,card=card)
def get(self):
uname = self.get_current_user()
user = User.get_user_by_name(uname)
order = get_order()
story = Story.get_by_porder(order)
sid = self.get_argument("sid",None)
if sid is not None:
story=Story.get_by_sid(sid)
article = Article.get_all_Astory(200)
usedStory = Story.get_all_story()
temp = []
for one in usedStory:
if one.porder > 0 and one.porder <= order:
temp.append(one)
usedStory = temp
reArticles = Article.get_all(200)
Rarticle = sorted(reArticles,BaseHandler.rank)
Ruser = User.get_all_user(100)
if len(Rarticle) > 6:
Rarticle=Rarticle[:6]
if len(usedStory)>3:
usedStory=usedStory[:3]
if len(Ruser)>9:
Ruser=Ruser[:9]
self.render("story.html",user=user,Rarticle=Rarticle,Article=article,usedStory=usedStory,Ruser=Ruser,story=story)
def get(self):
root = self.get_secure_cookie('root')
if root=='suiyue':
current_order = get_order()
cards = Card.get_all_card()
stories = Story.get_all_story()
self.render("control.html", order=current_order, cards=cards, stories=stories)
else:
self.redirect('/rootlogin')
async def complete_orders(request):
json = await request.json()
courier_id = 0
order_id = 0
complete_time = 0
for k, v in json.items():
if k == "courier_id" and type(v) is int and v > 0:
courier_id = v
elif k == "order_id" and type(v) is int and v > 0:
order_id = v
elif k == "complete_time" and type(v) is str:
complete_time = parse(v)
else:
return web.Response(status=400)
if courier_id == 0 or order_id == 0 or complete_time == 0:
return web.Response(status=400)
order = get_order(order_id, request.app['db'])
if order is None or order.courier_id != courier_id:
return web.Response(status=400)
if order.complete == 0:
order.set_complete(request.app['db'], complete_time)
return web.json_response(status=200, data={"order_id": order.id})
#print url_text_dictionary
#now that we have the entire dictionary of url:text mappings, we can analyze instead
wiki_text = process.get_text('http://en.wikipedia.org/wiki/' + term)
#creates dictionaries for the summarability and order scores
ordered_keywords = order.get_ordered_keywords(wiki_text, keywords)
wiki_distribution = process.get_density(wiki_text, keywords)
summarability = {}
orderability = {}
#calculates the summarability score in a dictionary
for url, text in url_text_dictionary.iteritems():
current_distribution = process.get_density(text,keywords)
summarability[url] = order.get_difference(wiki_distribution, current_distribution)
orderability[url] = order.get_order(current_distribution, ordered_keywords)
print summarability
print "\n\n"
print orderability
#gets the urls sorted by summarability as a list of (url, score) tuples
sorted_summarability = sorted(summarability.iteritems(), key=operator.itemgetter(1))
f = open('dump/sorted_summarability_' + term + ".txt",'w')
for (url, score) in sorted_summarability:
try:
f.write(" URL: " + url + "\n\n")
text = url_text_dictionary[url]
#print text
f.write(text)
f.write("\n\n")
#now that we have the entire dictionary of url:text mappings, we can analyze instead
wiki_text = process.get_text('http://en.wikipedia.org/wiki/' + term)
#creates dictionaries for the summarability and order scores
ordered_keywords = order.get_ordered_keywords(wiki_text, keywords)
wiki_distribution = process.get_density(wiki_text, keywords)
summarability = {}
orderability = {}
#calculates the summarability score in a dictionary
for url, text in url_text_dictionary.iteritems():
current_distribution = process.get_density(text, keywords)
summarability[url] = order.get_difference(wiki_distribution,
current_distribution)
orderability[url] = order.get_order(current_distribution, ordered_keywords)
print summarability
print "\n\n"
print orderability
#gets the urls sorted by summarability as a list of (url, score) tuples
sorted_summarability = sorted(summarability.iteritems(),
key=operator.itemgetter(1))
f = open('generator/dump/sorted_summarability_' + term + ".txt", 'w')
for (url, score) in sorted_summarability:
try:
f.write(" URL: " + url + "\n\n")
text = url_text_dictionary[url]
#print text
f.write(text)
def index(request):
if 'query' in request.GET:
term = request.GET['query']
#replaces spaces with underscores
term = term.replace(" ", "_")
print error("****THE TERM IS " + term)
else:
#defines a term to search for
term = "Manifold"
#gets the list of all words with associated tf-idf scores
words = tfidf.get_tf_idf(term, "wikipedia")
#gets the cleaned list after removing list elements with non-alphanumeric charachters
cleaned = tfidf.parse(words)
cleaned = tfidf.remove_duplicates(cleaned)
#gets the list of top words (keywords)
keywords = tfidf.get_top_words(10, cleaned)
print error(str(keywords))
#gets all combinations of the keywords; this is a list of tuples
combinations = process.get_combinations(keywords)
try:
urls = pickle.load(open("generator/dump/urls_" + term + ".p", "rb"))
except:
#otherwise, creates and searches for the keywords
print "Searching for each keyword set instead, and saving as pickle"
urls = []
for (word1, word2) in combinations:
print "Searching for " + word1 + ", " + word2 + "."
try:
results = google.search(term + " " + word1 + " " + word2,
"com", "en", 1, 0, 3, 2.0)
for i in range(3):
next_result = results.next()
if not next_result in urls:
urls.append(next_result)
except:
print "HTML request overload."
break
pickle.dump(urls, open("generator/dump/urls_" + term + ".p", "wb"))
#gets the cleaned text for each url
try:
url_text_dictionary = pickle.load(
open("generator/dump/url_text_dictionary_" + term + ".p", "rb"))
except:
url_text_dictionary = process.get_text_dictionary(urls)
pickle.dump(
url_text_dictionary,
open("generator/dump/url_text_dictionary_" + term + ".p", "wb"))
urls = url_text_dictionary.keys()
pickle.dump(urls, open("generator/dump/urls_" + term + ".p", "wb"))
#gets the titles for each url
try:
print error("Loading titles.")
url_titles = pickle.load(
open("generator/dump/url_titles_" + term + ".p", "rb"))
print error("Loaded existing titles.")
except:
print error("Getting titles.")
url_titles = process.get_titles(urls)
pickle.dump(url_titles,
open("generator/dump/url_titles_" + term + ".p", "wb"))
#print url_text_dictionary
#now that we have the entire dictionary of url:text mappings, we can analyze instead
wiki_text = process.get_text('http://en.wikipedia.org/wiki/' + term)
#creates dictionaries for the summarability and order scores
ordered_keywords = order.get_ordered_keywords(wiki_text, keywords)
#print error(str(ordered_keywords))
wiki_distribution = process.get_density(wiki_text, keywords)
summarability = {}
orderability = {}
#calculates the summarability score in a dictionary
for url, text in url_text_dictionary.iteritems():
current_distribution = process.get_density(text, keywords)
summarability[url] = order.get_difference(wiki_distribution,
current_distribution)
orderability[url] = order.get_order(current_distribution,
ordered_keywords)
#print summarability
print "\n\n"
#print orderability
#gets the urls sorted by summarability as a list of (url, score) tuples
sorted_summarability = sorted(summarability.iteritems(),
key=operator.itemgetter(1))
sorted_orderability = sorted(orderability.iteritems(),
key=operator.itemgetter(1))
combined = order.combine_summarability_and_orderability(
sorted_summarability, orderability, url_titles)
print "Titles: " + str(url_titles)
with_titles = []
#adds in the title to the tuple
for (url, score) in combined:
with_titles.append((url, score, url_titles[url]))
return render(request, 'generator/index.html',
({
'summarability': json.dumps(sorted_summarability),
'orderability': json.dumps(sorted_orderability),
'combined': json.dumps(combined),
'with_titles': json.dumps(with_titles)
}))
def main():
global stage
global tiket
file = open('last_tiket.txt', 'r')
tiket = int(file.read())
file.close()
while True:
answer = get_message()
if answer != None:
chat_id = answer['chat_id']
text = answer['text']
message_id = answer['message_id']
time_stop = 0
try:
if text in command or stage != 0:
if text == '/start':
send_messege(
chat_id,
'Добрый день!\nВы обратились к автоматизированной системе приема и обработки заявок отдела Цифровой дистрибьюции компании 1С:Северо-Запад.'
)
send_messege(
chat_id,
'Для составления заявки используйте комманду /order и сделуйте инструкциям или комманду /help для получения данных о всех доступных коммандах!'
)
send_messege(
chat_id,
'\n\nПРЕДУПРЕЖДЕНИЕ!\n\nПри продолжении работы с ботом, вы соглашаетесь на обработку Ваших персональных данных.\nОзнакомиться с договором - link'
)
stage = 0
file = open('chat_ID.txt', 'r+')
text = file.read()
if str(chat_id) in text:
continue
else:
file.write('\n' + str(chat_id))
file.close()
continue
if text == '/help':
send_messege(
chat_id,
'Комманда:\n/help - получения данных о всех доступных коммандах\n/contact - данные для обратной связи\n/start - для начала работы с ботом\n/order - для составления заявки\n/check - для проверки существующей заявки'
)
stage = 0
continue
if text == '/contact':
send_messege(
chat_id,
'Обратная связь.\nСайт: http://1cpd.businesscatalyst.com/\ne-mail: [email protected]\nтел.: 8 (812) 385-15-99'
)
stage = 0
continue
if text == '/order':
stage = 1
tiket = tiket + 1
while True:
if stage != 8:
messege = 'Ошибка'
messege = order.get_order(
chat_id, text, stage, tiket)
send_messege(chat_id, messege)
stage = stage + 1
# pull = [chat_id, tiket, stage]
# stage = get_order(chat_id, text, stage, tiket)
# time_stop = message_id
continue
if text == '/check':
send_messege(chat_id, 'Введите номер Вашей заявки.')
stage = 16
continue
if stage == 16:
try:
if '№' in text:
file = open(
' От ' + str(chat_id) + ' заявка ' +
str(text) + '.txt', 'r')
else:
file = open(
' От ' + str(chat_id) + ' заявка №' +
str(text) + '.txt', 'r')
except Exception:
send_messege(
chat_id,
'Введены неверные данные или использовался символ "#".\nВведите номер Вашей заявки.'
)
else:
order_check = file.read()
stage = 0
file.close()
r = order_check.find('Статус:')
print('----' + str(r))
print(len(order_check))
send_messege(chat_id,
order_check[r:len(order_check)])
print(order_check[r:len(order_check)])
file.close()
continue
if message_id != time_stop:
stage = get_order(chat_id, text, stage, tiket)
time_stop = message_id
continue
else:
send_messege(
chat_id,
'\n\nПРЕДУПРЕЖДЕНИЕ!\n\nВоспользуйтесь встроенными коммандами:\n/start - для начала работы с ботом\n/order - для составления заявки\n/check - для проверки существующей заявки'
)
except:
send_messege(
chat_id,
'\n\nПРЕДУПРЕЖДЕНИЕ!\n\nПрограмная ошибка, перезапустите диалог коммандой /start'
)
print(Exception)
else:
continue
sleep(2)
def index(request):
if 'query' in request.GET:
term = request.GET['query']
#replaces spaces with underscores
term = term.replace(" ", "_")
print error("****THE TERM IS " + term)
else:
#defines a term to search for
term = "Manifold"
#gets the list of all words with associated tf-idf scores
words = tfidf.get_tf_idf(term, "wikipedia")
#gets the cleaned list after removing list elements with non-alphanumeric charachters
cleaned = tfidf.parse(words)
cleaned = tfidf.remove_duplicates(cleaned)
#gets the list of top words (keywords)
keywords = tfidf.get_top_words(10, cleaned)
print error(str(keywords))
#gets all combinations of the keywords; this is a list of tuples
combinations = process.get_combinations(keywords)
try:
urls = pickle.load(open ("generator/dump/urls_" + term + ".p", "rb"))
except:
#otherwise, creates and searches for the keywords
print "Searching for each keyword set instead, and saving as pickle"
urls = []
for (word1, word2) in combinations:
print "Searching for " + word1 + ", " + word2 + "."
try:
results = google.search(term + " " + word1 + " " + word2, "com", "en", 1, 0, 3, 2.0)
for i in range(3):
next_result = results.next()
if not next_result in urls:
urls.append(next_result)
except:
print "HTML request overload."
break
pickle.dump(urls, open("generator/dump/urls_" + term + ".p", "wb"))
#gets the cleaned text for each url
try:
url_text_dictionary = pickle.load(open("generator/dump/url_text_dictionary_" + term + ".p", "rb"))
except:
url_text_dictionary = process.get_text_dictionary(urls)
pickle.dump(url_text_dictionary, open("generator/dump/url_text_dictionary_" + term + ".p", "wb"))
urls = url_text_dictionary.keys()
pickle.dump(urls, open("generator/dump/urls_" + term + ".p", "wb"))
#gets the titles for each url
try:
print error("Loading titles.")
url_titles = pickle.load(open("generator/dump/url_titles_" + term + ".p", "rb"))
print error("Loaded existing titles.")
except:
print error("Getting titles.")
url_titles = process.get_titles(urls)
pickle.dump(url_titles, open("generator/dump/url_titles_" + term + ".p", "wb"))
#print url_text_dictionary
#now that we have the entire dictionary of url:text mappings, we can analyze instead
wiki_text = process.get_text('http://en.wikipedia.org/wiki/' + term)
#creates dictionaries for the summarability and order scores
ordered_keywords = order.get_ordered_keywords(wiki_text, keywords)
#print error(str(ordered_keywords))
wiki_distribution = process.get_density(wiki_text, keywords)
summarability = {}
orderability = {}
#calculates the summarability score in a dictionary
for url, text in url_text_dictionary.iteritems():
current_distribution = process.get_density(text,keywords)
summarability[url] = order.get_difference(wiki_distribution, current_distribution)
orderability[url] = order.get_order(current_distribution, ordered_keywords)
#print summarability
print "\n\n"
#print orderability
#gets the urls sorted by summarability as a list of (url, score) tuples
sorted_summarability = sorted(summarability.iteritems(), key=operator.itemgetter(1))
sorted_orderability = sorted(orderability.iteritems(), key=operator.itemgetter(1))
combined = order.combine_summarability_and_orderability(sorted_summarability, orderability, url_titles)
print "Titles: " + str(url_titles)
with_titles = []
#adds in the title to the tuple
for (url, score) in combined:
with_titles.append((url, score, url_titles[url]))
return render(request, 'generator/index.html', ({'summarability': json.dumps(sorted_summarability), 'orderability': json.dumps(sorted_orderability), 'combined': json.dumps(combined), 'with_titles': json.dumps(with_titles)}))
