def updateInfo(self, item, newlinks, oldlinks):
		'''爬虫爬完之后对数据库内容进行更新'''
		cur = self.conn.cursor()
		cur.execute("SELECT wid,did FROM Websites WHERE url=?", (item['url'],))
		wid, did = cur.fetchone()
		# website记录更新
		cur.execute("UPDATE Websites SET title=?,visited=1 WHERE wid=?", (item['title'], wid,))
		# 对应的domain记录中出度也需要更新
		cur.execute("UPDATE Domains SET outdegree=outdegree+? WHERE did=?", (len(item['links']), did,))

		# 对该网页中所有链接涉及的记录进行更新
		# 外部判断未出现过的链接
		for link,domain in newlinks:
			self.insertWebsite(link, domain)

		# 外部判断出现过的链接
		for link,domain in oldlinks:
			# 对对应的domain记录入度增加
			cur.execute("UPDATE Domains SET outdegree=outdegree+1 WHERE domain=?", (domain,))
		# 写入到文件
		self.conn.commit()
def test_make_gym_stack(name, num_envs, state_shape, reward_scale):
    seed = 0
    frame_op = 'stack'  # used for rnn
    frame_op_len = 4
    venv = make_gym_venv(name, num_envs, seed, frame_op=frame_op, frame_op_len=frame_op_len, reward_scale=reward_scale)
    venv.reset()
    for i in range(5):
        state, reward, done, info = venv.step([venv.action_space.sample()] * num_envs)

    assert isinstance(state, np.ndarray)
    stack_shape = (num_envs, frame_op_len,) + state_shape
    assert state.shape == stack_shape
    assert isinstance(reward, np.ndarray)
    assert reward.shape == (num_envs,)
    assert isinstance(done, np.ndarray)
    assert done.shape == (num_envs,)
    assert len(info) == num_envs
    venv.close()