def diff(old_html, new_html, cutoff=0.0, plaintext=False, pretty=False):
"""Show the differences between the old and new html document, as html.
Return the document html with extra tags added to show changes. Add <ins>
tags around newly added sections, and <del> tags to show sections that have
been deleted.
"""
if plaintext:
old_dom = parse_text(old_html)
new_dom = parse_text(new_html)
else:
old_dom = parse_minidom(old_html)
new_dom = parse_minidom(new_html)
# If the two documents are not similar enough, don't show the changes.
if not check_text_similarity(old_dom, new_dom, cutoff):
return '<h2>The differences from the previous version are too large to show concisely.</h2>'
dom = dom_diff(old_dom, new_dom)
# HTML-specific cleanup.
if not plaintext:
fix_lists(dom)
fix_tables(dom)
# Only return html for the document body contents.
# body_elements = dom.getElementsByTagName('body')
# if len(body_elements) == 1:
# dom = body_elements[0]
return minidom_tostring(dom, pretty=pretty)
def diff(old_html, new_html, cutoff=0.0, plaintext=False, pretty=False):
"""Show the differences between the old and new html document, as html.
Return the document html with extra tags added to show changes. Add <ins>
tags around newly added sections, and <del> tags to show sections that have
been deleted.
"""
if plaintext:
old_dom = parse_text(old_html)
new_dom = parse_text(new_html)
else:
old_dom = parse_minidom(old_html)
new_dom = parse_minidom(new_html)
# If the two documents are not similar enough, don't show the changes.
if not check_text_similarity(old_dom, new_dom, cutoff):
return '<h2>The differences from the previous version are too large to show concisely.</h2>'
dom = dom_diff(old_dom, new_dom)
# HTML-specific cleanup.
if not plaintext:
fix_lists(dom)
fix_tables(dom)
# Only return html for the document body contents.
body_elements = dom.getElementsByTagName('body')
if len(body_elements) == 1:
dom = body_elements[0]
return minidom_tostring(dom, pretty=pretty)
def index():
if request.method == 'POST':
response = request.get_json()
chat_id = response['message']['chat']['id']
text = response['message']['text']
symbol = parse_text(text)
# Commands not found
if symbol is None:
return jsonify(response)
# Check global commands
if GLOBAL_COMMANDS.get(symbol):
send_message(chat_id, GLOBAL_COMMANDS[symbol])
return jsonify(response)
# Get quote
obj = get_quote(symbol, API_KEY)
if obj is not None:
send_message(chat_id, format_message(obj))
else:
send_message(chat_id, f'Command "{symbol}" is missing.')
return jsonify(response)
def log_bytes(self):
result = []
for entry in self.log:
lentry = [item for sublist in [(x,) if type(x) is not tuple else x for x in entry] for item in sublist]
if lentry[0] == BATTLE_ACTION_MESSAGE:
lentry[0] = BATTLE_ACTION_MESSAGE + len(lentry) - 1
result += lentry
result.append(0xff)
result = [len(result) % 256, len(result) // 256] + result
for entry in self.stringbuf:
result += util.parse_text(entry)
return bytes(result)
def battle_packet_handler(data, player_data):
if data[0] == 1:
q = storage.sql("select battle_data from last_battle where id=?",
(player_data["id"], ))
return bytearray(q[0]["battle_data"])
print(data)
rnd_items_1 = []
rnd_items_2 = []
for i in range(0, 8):
rnd_items_1.append(random.choice(list(items.ITEM_CLASSES.keys())))
for i in range(0, 8):
rnd_items_2.append(random.choice(list(items.ITEM_CLASSES.keys())))
rnd_state = {
"species": random.choice(list(resources.MON_DATA.keys())),
"mon_name": "Shadow",
"moves": ["SCRATCH"],
"name": "X",
"items": rnd_items_1
}
attacking_player = json.loads(player_data["mon"])
defending_player = trainerloader.load_trainer(data[2] * 256 + data[1])
b = battle.battle(attacking_player, defending_player)
r = bytearray(
bytes(defending_player["items"]) + # attacker items
bytes(attacking_player["items"]) + # defender items
bytes([defending_player["class_id"]]) + # trainer class id
bytes(util.bcd(defending_player["bp_reward"])) + # bp reward
bytes(util.bcd(defending_player["credits_reward"])) + # credit reward
bytes([
resources.MON_DATA[attacking_player["species"]]["mon_numeric_id"]
]) + # attacker species id
bytes([
resources.MON_DATA[defending_player["species"]]["mon_numeric_id"]
]) + # defender species id
bytes(util.parse_text(defending_player["name"], 21)) + # defender name
b.log_bytes() # offset to stringbuf, battle data, stringbuf
)
print(r)
storage.sql(
"""
update last_battle set battle_data=? where id=?
""", (r, player_data["id"]))
return r
def handle_question():
image = util.take_screenshot()
image = image[
TOP_LEFT[1] : TOP_LEFT[1] + HEIGHT,
TOP_LEFT[0] : TOP_LEFT[0] + WIDTH
]
"""
cv2.imshow("Image", image)
cv2.waitKey(0)
"""
text = util.image_to_text(image)
parsed = util.parse_text(text)
if parsed is not None:
quest, options = parsed
qt = trivia.TriviaQuestion(quest, options)
answer_index = qt.answer()
util.do_click((800, 315 + answer_index * 60))
model = kenlm.Model(bin_file)
print(model.score('this is a sentence .', bos=True, eos=True))
# 其中， 每个句子通过语言模型都会得到一个概率(0-1),然后对概率值取log得到分数(-\propto ,0],
# 得分值越接近于0越好。 score函数输出的是对数概率，即log10(p('微 信'))，其中字符串可以是gbk，也可以是utf-8
# bos=False, eos=False意思是不自动添加句首和句末标记符,得分值越接近于0越好。
# 一般都要对计算的概率值做log变换，不然连乘值太小了，在程序里会出现 inf 值。
#该模块，可以用来测试词条与句子的通顺度：,注意这里需要空格分割下：
text = '再 心 每 天也 不 会 担 个 大 油 饼 到 了 下 午 顶 着 一 了 '
print(model.score(text, bos=True, eos=True))
#3.2 model.full_scores函数
#score是full_scores是精简版，full_scores会返回： (prob, ngram length, oov) 包括：概率，ngram长度，是否为oov
# Show scores and n-gram matches
sentence = '盘点不怕被税的海淘网站❗️海淘向来便宜又保真，比旗舰店、专柜和代购好太多！'
words = ['<s>'] + parse_text(sentence).split() + ['</s>']
print(words)
for i, (prob, length, oov) in enumerate(model.full_scores(sentence)):
print('{0} {1}: {2}'.format('prob: ', prob, ' length : ', length,
' '.join(words[i + 2 - length:i + 2])))
if oov:
print('\t"{0}" is an OOV'.format(words[i + 1]))
# Find out-of-vocabulary words
for w in words:
if not w in model:
print('"{0}" is an OOV'.format(w))
#3.3 kenlm.State()状态转移概率
'''
状态的累加
def gift_packet_handler(data, player_data):
r = bytearray(b"\x02" + bytes(util.parse_text("Star For Effort")) +
bytes(util.parse_text("Shadowek")))
print(r)
return r