def __init__(self, parent=None, csvInPath=None, csvDelimiter = '|' ):
#super(dlgBomImport, self).__init__(parent)
self.dlg = QtWidgets.QDialog(parent)
loader = QtUiTools.QUiLoader()
self.dlg.ui = loader.load('gui/bomImport.ui')
self.dlg.ui.setAttribute(QtCore.Qt.WA_DeleteOnClose);
self.dlg.ui.setModal(1);
self.dlg.ui.show()
#csvInPath = '..\\boms\\funksonde2\\sg04_btmodul\\bom.txt'
self.quoter = Quote(csvInPath,csvDelimiter,self)
fileext = os.path.splitext(csvInPath)
csvOutPath = fileext[0]+datetime.datetime.now().strftime('%d_%m_%Y')+'.bomQuote'
print(csvOutPath)
if os.path.exists(csvOutPath):
newFile = csvOutPath;
counter = 0;
fileext = os.path.splitext(csvOutPath)
newFile = fileext[0]+'_backup_'+str(counter).zfill(3)+'.bomQuote'
while os.path.exists(newFile):
counter += 1;
newFile = fileext[0]+'_backup_'+str(counter).zfill(3)+'.bomQuote'
print(newFile)
os.rename(csvOutPath,newFile)
self.dlg.ui.btnBox.button(QtWidgets.QDialogButtonBox.Ok).setEnabled(0)
self.quoter.doQuote(csvOutPath)
self.dlg.ui.btnBox.button(QtWidgets.QDialogButtonBox.Ok).setEnabled(1)
def scrape_quotes_list():
page = 1
BASE_URL = "http://quotes.toscrape.com"
all_quotes = []
while True:
url = BASE_URL + f"/page/{page}"
print("Scraping page " + page + "...")
response = requests.get(url)
soup = BeautifulSoup(response.text, "html.parser")
quotes = soup.select(".text")
for quote in quotes:
text = quote.get_text()
author = quote.find_next("small").get_text()
details_url = quote.find_next("a")['href']
response_details = requests.get(BASE_URL + details_url)
soup_details = BeautifulSoup(response_details.text, "html.parser")
born_date = soup_details.select(".author-born-date")[0].get_text()
born_location = soup_details.select(
".author-born-location")[0].get_text()
birth = born_date + " " + born_location
bio = soup_details.select(".author-description")[0].get_text()
all_quotes.append(Quote(text, author, birth, bio))
if not soup.select(".next"):
break
page += 1
return all_quotes
def find_quotes_in_transcript(query_words, file_path):
quotes = []
with open(file_path, "r") as f:
all_lines = ((l.strip() if l != "\n" else "\n") for l in f.readlines())
line = next(all_lines, -1)
while line != -1:
if line == "\n":
line = next(all_lines, -1)
continue
quote_index = int(line)
start_timestamp, end_timestamp = next(all_lines).split(" --> ")
quote = ""
line = next(all_lines)
while line != "\n":
quote += " " + line
line = next(all_lines)
quote_words = sanitize_text(quote)
quotes.append(
Quote(path=file_path,
text=quote,
index=quote_index,
start_timestamp=start_timestamp,
end_timestamp=end_timestamp,
quote_query_match=calc_quote_query_match(
query_words, quote_words),
query_quote_match=calc_query_quote_match(
query_words, quote_words)))
return quotes
def main():
quotes1 = QuoteHistory("%s.csv" % (NAME1)).get_quotes(Quote)
quotes2 = QuoteHistory("%s.csv" % (NAME2)).get_quotes(Quote)
amount1 = 0.0
amount2 = 0.0
r_quotes = []
prev_year = None
for i in xrange(len(quotes1)):
quote1 = quotes1[i]
quote2 = quotes2[i]
if (prev_year is None) or (quote1.date.year > prev_year):
prev_year = quote1.date.year
amount1, amount2 = balance(amount1, quote1.price, SHARE1,
amount2, quote2.price, SHARE2,
TAX)
r_quote = Quote(quote1.date, amount1 * quote1.price + amount2 * quote2.price)
r_quotes.append(r_quote)
QuoteHistory(("%.2f-%s-%.2f-%s-tax-%.0f.csv"
% (SHARE1, NAME1, SHARE2, NAME2, TAX * 100))).put_quotes(r_quotes)
print >> sys.stderr, ("%f x %f = %f"
% (amount1, quote1.price, amount1 * quote1.price))
print >> sys.stderr, ("%f x %f = %f"
% (amount2, quote2.price, amount2 * quote2.price))
def format_realtime_quotes(self, realtime_quotes_data):
result = dict()
stocks_detail = ''.join(realtime_quotes_data)
grep_result = self.realtime_quotes_format_zs.finditer(stocks_detail)
for stock_match_object in grep_result:
groups = stock_match_object.groups()
price_A1 = eval(groups[0])
price_A2 = eval(groups[1])
perform = eval('[\'\'%s]' % (',\'0\'' * 26))
g = eval(groups[2])
grep_result = self.realtime_quotes_format.finditer(stocks_detail)
for stock_match_object in grep_result:
groups = stock_match_object.groups()
price_A1 = eval(groups[0])
price_A2 = eval(groups[1])
perform = eval(groups[2])
g = eval(groups[3])
q = Quote()
if 'zs' == price_A1[0][:2]:
q.symbol = zs_symbol_of(price_A1[0][-6:])
if 'cn' == price_A1[0][:2]:
q.symbol = symbol_of(price_A1[0][-6:])
q.code = code_from_symbol(q.symbol)
q.name = price_A1[1].decode('utf-8')
q.now = to_float(price_A1[2])
q.open = to_float(price_A2[3])
q.close = to_float(price_A2[1])
q.high = to_float(price_A2[5])
q.low = to_float(price_A2[7])
q.buy = to_float(perform[12])
q.sell = to_float(perform[10])
q.volume = to_int(price_A2[8]) * 100
q.turnover = to_float(price_A2[12]) * 10000
q.bid1_volume = to_int(perform[13]) * 100
q.bid1 = to_float(perform[12])
q.bid2_volume = to_int(perform[15]) * 100
q.bid2 = to_float(perform[14])
q.bid3_volume = to_int(perform[17]) * 100
q.bid3 = to_float(perform[16])
q.bid4_volume = to_int(perform[19]) * 100
q.bid4 = to_float(perform[18])
q.bid5_volume = to_int(perform[21]) * 100
q.bid5 = to_float(perform[20])
q.ask1_volume = to_int(perform[11]) * 100
q.ask1 = to_float(perform[10])
q.ask2_volume = to_int(perform[9]) * 100
q.ask2 = to_float(perform[8])
q.ask3_volume = to_int(perform[7]) * 100
q.ask3 = to_float(perform[6])
q.ask4_volume = to_int(perform[5]) * 100
q.ask4 = to_float(perform[4])
q.ask5_volume = to_int(perform[3]) * 100
q.ask5 = to_float(perform[2])
t = '%s-%s-%s %s:%s:%s' % (g[0], g[1], g[2], g[3], g[4], g[5])
q.time = date_time.str_to_time(t)
result[q.code] = q
return result
def test_shorten_msg(self):
quote = Quote()
s = '''
1234567890123456789012345678901234567890
1234567890123456789012345678901234567890
1234567890123456789012345678901234567890
1234567890123456789012345678901234567890
'''
ss = quote.shorten_msg(s)
self.assertEquals(len(ss) + 1 + 22, 140)
def load(self):
'''
Loads quotes from the given filepath. (see QuoteManager.__init__())
'''
for line in open(self.filePath, "r", encoding="utf-8"):
quote = line.replace("\n", "").split("@")
if (len(quote) != 2):
continue
self.quotes.append(Quote(quote[0], quote[1]))
def test10():
q = Quote()
filelist = [
f for f in os.listdir(DATA_DIR) if f.endswith('.csv')
and not f.endswith('_analysis.csv') and not f.endswith('_renko.csv')
]
for f in filelist:
sym = f.split('.')[0]
print 'Sanitizing', sym, '....'
q.sanitize(sym)
def main():
quotes = QuoteHistory("%s.csv" % (NAME)).get_quotes(BaseQuote)
d_quotes = QuoteHistory("%s_dividends.csv" % (NAME)).get_quotes(DividendQuote)
b_quotes = QuoteHistory("%s_^IRX.csv" % (NAME)).get_quotes(Quote)
prev_quote = quotes[0]
prev_bill_date = prev_quote.date
leveraged_price = prev_quote.price
leveraged_price = 1.730208
report(prev_quote, leveraged_price)
for i in xrange(len(quotes)):
exp_agregate = get_exp_agregate(BASE_TER, prev_quote.date, quotes[i].date)
quotes[i].original_price = quotes[i].price * (1.0 + exp_agregate)
dividends = {}
for quote in d_quotes[1:]:
dividends[quote.date] = quote.price
bills = {}
for quote in b_quotes[1:]:
bills[quote.date] = quote.price / 100
l_quotes = []
for quote in quotes[1:]:
expenses = get_expenses(prev_quote.date, quote.date)
leveraged_price *= get_leverage(prev_quote.original_price, quote.original_price, expenses)
if quote.date in dividends:
leveraged_price *= 1.0 + dividends[quote.date] / quote.price * STOCKS
del dividends[quote.date]
if quote.date in bills:
exp_agregate = get_exp_agregate(bills[quote.date], prev_bill_date, quote.date)
leveraged_price *= 1.0 + exp_agregate * BONDS
prev_bill_date = quote.date
del bills[quote.date]
l_quote = Quote(quote.date, leveraged_price)
l_quotes.append(l_quote)
prev_quote = quote
if dividends:
raise Exception("Excessive dividends data: %s" % (dividends))
if bills:
raise Exception("Excessive bills data: %s" % (bills))
QuoteHistory("%s-x%0.1f-%0.2f%%.csv" % (NAME, LEVERAGE, TER * 100)).put_quotes(l_quotes)
report(prev_quote, leveraged_price)
def random_page(num_quotes, quotes):
url = "http://quotes.toscrape.com/random"
i = 0
while i < num_quotes:
r = requests.get(url)
soup = BeautifulSoup(r.text, "html.parser")
page_quote = soup.find("span", attrs={"class": "text"})
page_author = soup.find("small", attrs={"class": "author"})
quotes.append(Quote(page_author.text, page_quote.text))
i += 1
return quotes
def checkup(symbols):
print 'Checking up ......'
latest_date = utils.latest_date_str()
q = Quote()
td = TechData()
a = Analysis()
for sym in symbols:
q.update(sym, latest_date)
td.update(sym)
a.update(sym)
def create(self):
try:
response = requests.get(self.API_URL)
response.raise_for_status()
json_data = response.json()
except HTTPError as http_err:
print(f'HTTP error occurred: {http_err}')
except ValueError as err:
print(f'JSON decoding error occurred: {err}')
except Exception as err:
print(f'Other error occurred: {err}')
else:
return Quote(text=json_data['en'], author=json_data['author'])
def format_realtime_quotes(self, realtime_quotes_data):
result = dict()
stocks_detail = ''.join(realtime_quotes_data)
#stock_detail_list = stocks_detail.split(';')
grep_result = self.realtime_quotes_format.finditer(stocks_detail)
for stock_match_object in grep_result:
#i = 0
#for x in stock_match_object.groups():
# print i
# print x.encode('utf-8')
# i += 1
stock = stock_match_object.groups()
q = Quote()
q.symbol = stock[0]
q.code = code_from_symbol(q.symbol)
q.name = stock[2]
q.open = float(stock[6])
q.close = float(stock[5])
q.now = float(stock[4])
q.high = float(stock[34])
q.low = float(stock[35])
q.buy = float(stock[10])
q.sell = float(stock[20])
q.turnover = float(stock[38]) * 10000
q.volume = int(stock[37]) * 100
q.bid1_volume = int(stock[11]) * 100
q.bid1 = float(stock[10])
q.bid2_volume = int(stock[13]) * 100
q.bid2 = float(stock[12])
q.bid3_volume = int(stock[15]) * 100
q.bid3 = float(stock[14])
q.bid4_volume = int(stock[17]) * 100
q.bid4 = float(stock[16])
q.bid5_volume = int(stock[19]) * 100
q.bid5 = float(stock[18])
q.ask1_volume = int(stock[21]) * 100
q.ask1 = float(stock[20])
q.ask2_volume = int(stock[23]) * 100
q.ask2 = float(stock[22])
q.ask3_volume = int(stock[25]) * 100
q.ask3 = float(stock[24])
q.ask4_volume = int(stock[27]) * 100
q.ask4 = float(stock[26])
q.ask5_volume = int(stock[29]) * 100
q.ask5 = float(stock[28])
#q.date = date_time.str_to_date(stock[31])
q.time = datetime.datetime.strptime(stock[31], '%Y%m%d%H%M%S')
result[q.code] = q
return result
def format_realtime_quotes(self, realtime_quotes_data):
result = dict()
stocks_detail = ''.join(realtime_quotes_data)
grep_result = self.realtime_quotes_format.finditer(stocks_detail)
for stock_match_object in grep_result:
q = Quote()
groups = stock_match_object.groups()
l = json.loads(groups[1])
ask_bid = []
for i in l:
ab = re.split(r',', i)
ask_bid.append(ab)
s = re.split(r',', groups[0])
q.symbol = symbol_of(s[1])
q.code = code_from_em_symbol(s[1] + s[0])
q.name = s[2]
q.now = float(s[3])
q.open = float(s[8])
q.close = float(s[9])
q.high = float(s[10])
q.low = float(s[11])
q.buy = float(ask_bid[5][0])
q.sell = float(ask_bid[4][0])
q.volume = int(s[17]) * 100
q.turnover = float(s[19]) * 10000
q.bid1_volume = int(ask_bid[5][1]) * 100
q.bid1 = float(ask_bid[5][0])
q.bid2_volume = int(ask_bid[6][1]) * 100
q.bid2 = float(ask_bid[6][0])
q.bid3_volume = int(ask_bid[7][1]) * 100
q.bid3 = float(ask_bid[7][0])
q.bid4_volume = int(ask_bid[8][1]) * 100
q.bid4 = float(ask_bid[8][0])
q.bid5_volume = int(ask_bid[9][1]) * 100
q.bid5 = float(ask_bid[9][0])
q.ask1_volume = int(ask_bid[4][1]) * 100
q.ask1 = float(ask_bid[4][0])
q.ask2_volume = int(ask_bid[3][1]) * 100
q.ask2 = float(ask_bid[3][0])
q.ask3_volume = int(ask_bid[2][1]) * 100
q.ask3 = float(ask_bid[2][0])
q.ask4_volume = int(ask_bid[1][1]) * 100
q.ask4 = float(ask_bid[1][0])
q.ask5_volume = int(ask_bid[0][1]) * 100
q.ask5 = float(ask_bid[0][0])
q.time = date_time.str_to_time(s[27])
result[q.code] = q
return result
def update_quotes(symbols):
print 'Updating quotes .....'
i = 1
q = Quote()
latest_date = utils.latest_date_str()
for sym in symbols:
new_latest_date, already_up_to_date = q.update(sym, latest_date)
if new_latest_date > latest_date:
latest_date = new_latest_date
if already_up_to_date is False:
i = i + 1
def update_quotes(self, sym_list=None):
if sym_list is None:
return
q = Quote(self.last_date)
self.spy_df, already_up_to_date = q.update('SPY')
if self.spy_df is not None:
latest_date = self.spy_df.index[-1]
else:
latest_date = None
for sym in sym_list:
df, already_up_to_date = q.update(sym, latest_date)
if already_up_to_date == False:
time.sleep(random.randint(1, 5))
def getQuote(self, ticker):
endpoint = 'https://www.alphavantage.co/query?function=TIME_SERIES_DAILY&symbol=%s&apikey=%s' % (ticker, self.key)
response = requests.get(endpoint)
print('Status Code: [%s]' % (response.status_code))
try:
open = Decimal(str(list(json.loads(json.dumps(response.json()['Time Series (Daily)'])).values())[0]['1. open'])).quantize(Decimal('.01'))
high = Decimal(str(list(json.loads(json.dumps(response.json()['Time Series (Daily)'])).values())[0]['2. high'])).quantize(Decimal('.01'))
low = Decimal(str(list(json.loads(json.dumps(response.json()['Time Series (Daily)'])).values())[0]['3. low'])).quantize(Decimal('.01'))
close = Decimal(str(list(json.loads(json.dumps(response.json()['Time Series (Daily)'])).values())[0]['4. close'])).quantize(Decimal('.01'))
volume = Decimal(str(list(json.loads(json.dumps(response.json()['Time Series (Daily)'])).values())[0]['5. volume'])).quantize(Decimal('.01'))
quote = Quote(open, high, low, close, volume)
print('%s,%s,%s,%s,%s' % (quote.open, quote.high, quote.low, quote.close, quote.volume))
self.logger.write('Quote successfully retrieved (status code: [%s]) for ticker [%s]' % (response.status_code, ticker))
return quote
except Exception as e:
self.logger.writeError(e)
print(e)
def init(self,
nick="Botivator",
command_char="!",
owners=["Motivator", "MotivatorAFK"],
password_file="password.py",
host_file="host",
host="irc.snoonet.org",
port="6667",
channel="##arctantest"):
self.host = host
self.port = int(port)
self.nick = nick
self.password = open(password_file).read().strip()
self.command_char = command_char
self.owners = owners
self.owner_host = open(host_file).read().strip()
self.linkresolver = LinkResolver()
self.commands = {
#'command_name': [CommandClass, CanAnyoneUseIt?]
'commands': [Commands(), True],
'help': [Commands(), True],
'join': [Join(), True],
'part': [Part(), True],
'ban': [Ban(), False],
'allow': [Allow(), False],
'source': [Source(), True],
'4chan': [WatchFourChan(self), False],
'hn': [WatchHackerNews(self), False],
'reddit': [WatchReddit(self), False],
'8ch': [WatchEightChan(self), False],
'pastebin': [WatchPasteBin(self), False],
'quote': [Quote(), True],
}
# Add owner to whitelist
self.commands['allow'][0].whitelist.append(self.owner_host)
TCPClient(channel=self.channel).register(self)
IRC(channel=self.channel).register(self)
def format_realtime_quotes(self, realtime_quotes_data):
result = dict()
stocks_detail = ''.join(realtime_quotes_data)
grep_result = self.realtime_quotes_format.finditer(stocks_detail)
for stock_match_object in grep_result:
stock = stock_match_object.groups()
q = Quote()
q.symbol = stock[0]
q.code = code_from_symbol(stock[0])
q.name = stock[1]
q.open = float(stock[2])
q.close = float(stock[3])
q.now = float(stock[4])
q.high = float(stock[5])
q.low = float(stock[6])
q.buy = float(stock[7])
q.sell = float(stock[8])
q.volume = int(stock[9])
q.turnover = float(stock[10])
q.bid1_volume = int(stock[11])
q.bid1 = float(stock[12])
q.bid2_volume = int(stock[13])
q.bid2 = float(stock[14])
q.bid3_volume = int(stock[15])
q.bid3 = float(stock[16])
q.bid4_volume = int(stock[17])
q.bid4 = float(stock[18])
q.bid5_volume = int(stock[19])
q.bid5 = float(stock[20])
q.ask1_volume = int(stock[21])
q.ask1 = float(stock[22])
q.ask2_volume = int(stock[23])
q.ask2 = float(stock[24])
q.ask3_volume = int(stock[25])
q.ask3 = float(stock[26])
q.ask4_volume = int(stock[27])
q.ask4 = float(stock[28])
q.ask5_volume = int(stock[29])
q.ask5 = float(stock[30])
#q.date = date_time.str_to_date(stock[31])
q.time = date_time.str_to_time(stock[31] + ' ' + stock[32])
result[q.code] = q
return result
def test_unduplicate_msg(self):
blog = Blog('tests/data/feed.xml')
post = blog.posts[0]
post.content = u'<div class="nozomi">duplicates</div>'
post.link = 'http://hoge.com/fuga.html'
quote = Quote()
last_tweet = u'duplicates http://hoge.com/fuga.html'
posts = [post]
# 同じセリフしか見つからない場合
msg = quote.unduplicate_msg(last_tweet, posts)
self.assertMultiLineEqual(msg, u'前回と違うつぶやきが見つかりません……。')
# 違うセリフが見つかる場合
post.content = u'<div class="nozomi">duplicates</div><div class="nozomi">new</div>'
msg = quote.unduplicate_msg(last_tweet, posts)
self.assertMultiLineEqual(msg, u'new http://hoge.com/fuga.html')
def test5():
symbol_list = []
lines = open(config.TRADABLE_STOCKS, 'r').read().split('\n')
for line in lines:
if len(line) > 0:
symbol_list.append(line)
#symbol_list = ['CSCO']
q = Quote()
a = Analysis()
p = RenkoPatterns()
spy_df = q.get('spy', 'google')
for sym in symbol_list:
df = q.get(sym, 'google')
if df is not None:
a.analysis(sym, df, spy_df)
df.to_csv(DATA_DIR + sym + '.csv')
def main():
quotes = QuoteHistory("%s.csv" % (NAME)).get_quotes(Quote)
amount = 0.0
r_quotes = []
prev_year = None
for quote in quotes:
if (prev_year is None) or (quote.date.year > prev_year):
prev_year = quote.date.year
amount += SAVINGS / quote.price
r_quote = Quote(quote.date, amount * quote.price)
r_quotes.append(r_quote)
QuoteHistory("%s-%d.csv" % (NAME, SAVINGS)).put_quotes(r_quotes)
last_quote = quotes[len(quotes) - 1]
print >> sys.stderr, (
"%f x %f = %f" % (amount, last_quote.price, amount * last_quote.price))
def test8():
q = Quote()
filelist = [
f for f in os.listdir(DATA_DIR) if f.endswith('.csv')
and not f.endswith('_analysis.csv') and not f.endswith('_renko.csv')
]
for f in filelist:
sym = f.split('.')[0]
if sym == 'SPY':
continue
print 'Analysing', sym, '....'
df = pd.read_csv(DATA_DIR + f, index_col=0)
if df.loc['2017-07-31']['open'] == '-' or df.loc['2017-07-31'][
'high'] == '-' or df.loc['2017-07-31']['low'] == '-' or df.loc[
'2017-07-31']['close'] == '-':
ndf = q.get(sym, 'nasdaq')
print df.loc['2017-07-31']
print ndf.loc['2017-07-31']
df.replace(df.loc['2017-07-31'], ndf.loc['2017-07-31'], True)
print df.loc['2017-07-31']
print ndf.loc['2017-07-31']
df.to_csv(DATA_DIR + sym + '.csv')
def get_quotes(arr_quotes, soup, address):
nb_quotes = len(arr_quotes)
quotes = soup.find_all("span", attrs={"class": "text", "itemprop": "text"})
# instanciation de l'objet quote avec son attribut content
for quote in quotes:
quote_obj = Quote(quote.text)
arr_quotes.append(quote_obj)
authors = soup.find_all("small",
attrs={
"class": "author",
"itemprop": "author"
})
i = nb_quotes
for author in authors:
author_infos = get_author_infos(author.find_next("a"))
arr_quotes[i].author["name"] = author.text
arr_quotes[i].author["born_date"] = author_infos["born_date"]
arr_quotes[i].author["born_location"] = author_infos["born_location"]
arr_quotes[i].author["description"] = author_infos["description"]
i += 1
tags = soup.find_all("meta",
attrs={
"class": "keywords",
"itemprop": "keywords"
})
# complétion du tableau d'objets quotes (ajout du tableau de tags)
i = nb_quotes
for tag in tags:
arr_quotes[i].tags = tag["content"].split(",")
i += 1
print("Scrapping terminé à l'adresse " + address)
return arr_quotes
def loop_pages(num_quotes, pages, url, quotes):
i = 1
while i <= pages:
r = requests.get(url + "/page/" + str(i))
soup = BeautifulSoup(r.text, "html.parser")
check_empty = soup.find(attrs={"class": "col-md-8"})
if check_empty.text.strip() == "No quotes found!":
return []
page_quotes = soup.findAll("span", attrs={"class": "text"})
page_authors = soup.findAll("small", attrs={"class": "author"})
quotes_get = num_quotes
if num_quotes // (i * 10) == 0:
quotes_get = num_quotes % 10
else:
quotes_get = 10
j = 0
while j < quotes_get:
try:
quotes.append(Quote(page_authors[j].text, page_quotes[j].text))
except IndexError:
return quotes
j += 1
i += 1
return quotes
if not anime in json:
json[anime] = {'characters': [], 'image': animeImg}
# print(anime)
if not any(character in x for x in json[anime]['characters']):
json[anime]['characters'].append(
{character: {
'quotes': [],
'image': img
}})
for i in json[anime]['characters']:
character_json = i
if character in i:
# print(type(tags.split(',')))
q = Quote(html_quote, tags.split(','), 0, 0)
i[character]['quotes'].append(q)
ANIME = []
for anime_name in json:
# print(json[anime_name]['image'])
anime = Anime(anime_name, json[anime_name]['image'], [], 0)
for char in json[anime_name]['characters']:
for character_name in char:
quotes = char[character_name]['quotes']
image = char[character_name]['image']
character = Character(character_name, image, quotes, 0)
anime.set_characters(character)
ANIME.append(anime)
def test6(sym):
q = Quote()
q.update(sym)
def test1(sym):
q = Quote()
df = q.get(sym, 'nasdaq')
print df
from quote import Quote
urls = {"Arthur " : 'https://fr.wikiquote.org/wiki/Kaamelott/Arthur',
"Kadoc": 'https://fr.wikiquote.org/wiki/Kaamelott/Kadoc',
"Karadoc":'https://fr.wikiquote.org/wiki/Kaamelott/Karadoc',
"Lancelot":'https://fr.wikiquote.org/wiki/Kaamelott/Lancelot',
"Léodagan":'https://fr.wikiquote.org/wiki/Kaamelott/L%C3%A9odagan',
"Loth":'https://fr.wikiquote.org/wiki/Kaamelott/Loth',
"Maitre d'arme":'https://fr.wikiquote.org/wiki/Kaamelott/Le_ma%C3'
'%AEtre_d%E2%80%99armes',
"Mélagant":'https://fr.wikiquote.org/wiki/Kaamelott/M%C3%A9l%C3'
'%A9agant'
}
quotes = []
for personnage in urls:
page = requests.get(urls[personnage])
soup = BeautifulSoup.BeautifulSoup(page.text.encode('utf-8'), 'html.parser')
temp_quotes = soup.find_all("div", {"class": "citation"})
quotes_str = map(lambda qte : Quote(personnage, qte.get_text().replace(
u'\xa0', u' ')), temp_quotes)
quotes.extend(quotes_str)
print(quotes[0].toJSON())
shuffle(quotes)
with codecs.open("quote.json", "w", "utf-8") as file: # Use file to refer to
# the file object
for quote in quotes :
file.write(quote.toJSON()+"\n")
# import class from another file
from quote import Quote
# create an object of class Quote
q = Quote('The essence of good deeds and evil deeds is the same.'
'They are both no more than a person\’s actions to make up for a defect in themselves.',
'Gaku Yashiro', 491)
# try printing it
print(q)
# TODO
# Read from 'quotes.list', into a list
# Create a Quote object for each quote in list
# Sort the list based on Quote.word_count
# Print top 10 quotes
