怎么解决这个报错Consider revisiting the entries above or defining a bean of type 'org.springframework.security.core.userdetails.UserDetailsService' in your configuration.
时间: 2023-05-26 07:03:32 浏览: 84
这个报错表示在配置中没有指定一个类型为org.springframework.security.core.userdetails.UserDetailsService的bean。解决这个问题可以按照下面的步骤进行:
1. 在配置文件中添加一个bean,指定类型为org.springframework.security.core.userdetails.UserDetailsService。
2. 确保该bean的实现类正常工作,并且已经注册到Spring容器中。
3. 确保该bean的配置文件和Spring容器的配置文件都已经正确加载,并且classpath设置正确。
4. 确保你的代码正确地使用了该bean,即使用正确的名称来调用它。
如果你按照以上步骤进行了操作,但是问题仍未解决,请检查是否还有其他的配置错误。
相关问题
上面的代码报错:onsider revisiting the entries above or defining a bean of type 'org.springframework.scheduling.concurrent.ThreadPoolTaskExecutor' in your configuration.
这个错误通常表示您的应用程序缺少一个名为"executor"的线程池任务执行器的配置,或者配置不正确。您需要确保在您的应用程序上下文中定义了一个名为"executor"的ThreadPoolTaskExecutor bean。
例如,您可以在您的应用程序配置类中添加以下内容:
```
@Configuration
public class AppConfig {
@Bean
public ThreadPoolTaskExecutor executor() {
ThreadPoolTaskExecutor executor = new ThreadPoolTaskExecutor();
executor.setCorePoolSize(10);
executor.setMaxPoolSize(100);
executor.setQueueCapacity(10);
return executor;
}
// ...
}
```
这将创建一个名为"executor"的线程池任务执行器,并将其添加到您的应用程序上下文中。请注意,您需要根据您的应用程序需求调整核心池大小、最大池大小和队列容量等参数。
The starting configuration of this puzzle is a row of cells, with disks located on cells through . The goal is to move the disks to the end of the row using a constrained set of actions. At each step, a disk can only be moved to an adjacent empty cell, or to an empty cell two spaces away if another disk is located on the intervening square. Given these restrictions, it can be seen that in many cases, no movements will be possible for the majority of the disks. For example, from the starting position, the only two options are to move the last disk from cell to cell , or to move the second-to-last disk from cell to cell . 1. [15 points] Write a function solve_identical_disks(length, n) that returns an optimal solution to the above problem as a list of moves, where length is the number of cells in the row and n is the number of disks. Each move in the solution should be a twoelement tuple of the form (from, to) indicating a disk movement from the cell from to the cell to. As suggested by its name, this function should treat all disks as being identical. Your solver for this problem should be implemented using a breadth-first graph search. The exact solution produced is not important, as long as it is of minimal length. Unlike in the previous two sections, no requirement is made with regards to the manner in which puzzle configurations are represented. Before you begin, think carefully about which data structures might be best suited for the problem, as this choice may affect the efficiency of your search
Here's a possible implementation of the `solve_identical_disks` function using breadth-first graph search:
```python
from collections import deque
def solve_identical_disks(length, n):
# Initialize the starting configuration
start = [True] * n + [False] * (length - n)
# Define a function to generate all possible successor configurations
def successors(config):
for i in range(length):
if not config[i]:
if i + 1 < length and config[i + 1]:
# Move disk to adjacent empty cell
yield config[:i] + [True] + [False] + config[i + 2:]
elif i + 2 < length and config[i + 2]:
# Move disk to empty cell two spaces away
yield config[:i] + [True] + config[i + 2:i + 3] + [False] + config[i + 3:]
# Perform breadth-first graph search to find the goal configuration
queue = deque([(start, [])])
visited = set([tuple(start)])
while queue:
config, moves = queue.popleft()
if config == [False] * (length - n) + [True] * n:
return moves
for successor in successors(config):
if tuple(successor) not in visited:
queue.append((successor, moves + [(config.index(True), successor.index(True))]))
visited.add(tuple(successor))
# If the goal configuration is not reachable, return None
return None
```
The `start` variable represents the starting configuration as a list of `True` values for the cells occupied by disks and `False` values for the empty cells. The `successors` function generates all possible successor configurations for a given configuration by moving a disk to an adjacent empty cell or to an empty cell two spaces away. The `queue` variable is used to store the configurations to be explored, along with the list of moves required to reach them. The `visited` set is used to keep track of the configurations that have already been explored, in order to avoid revisiting them.
The function returns the list of moves required to reach the goal configuration, which is represented as a list of `False` values for the cells before the disks and `True` values for the cells occupied by the disks. If the goal configuration is not reachable, the function returns `None`.