为了避免在我的redis通道中出现重复,我通过在Redis中设置索引来检查消息是否已经存在。下面是我的实现。然而,它给出了一个例外。
redis.clients.jedis.exceptions.JedisDataException: Please close pipeline or multi block before calling this method.
at redis.clients.jedis.Response.get(Response.java:23)
下面是实现。
Jedis jedis = pool.getResource();
我想从工作流中调用一个简单的方法(无参数,返回void)。假设我有以下类:
public class TestClass
{
public void StartWorkflow()
{
var workflow = new Sequence
{
Activities =
{
new WriteLine { Text = "Before calling method." },
// Here I would like to
我正在异步调用soap服务,但却卡在需要关闭soap客户端连接的地方。上一篇文章也没有太多帮助:
下面是我目前为止的代码。
下面的方法(GetFieldList(....)调用泛型方法ApiClient.GetResponse(....)使用请求参数和要调用的服务
public async Task<ServiceReference.GetFieldListResponse> GetFieldList(string identifier)
{
var request = new GetFieldListRequest
{
Magento 1.8中的错误消息保存在哪里?
例如,结帐页面上的错误消息,
This is a required field.
Please select a valid credit card type
Please agree to all the terms and conditions before placing the order.
Please specify a shipping method.
有什么想法吗?
我有一个用于URL状态检查工具的php脚本,它将检查给定的URL并显示那些带有404错误的URL。
StatusCheckerRequest具有"\n“分隔URL的输入
public function PostStatusChecker(StatusCheckerRequest $request){
$urls = $request->source;
$seperateURLs = explode("\n", $urls);
// -- create all the individual cURL handles and set their
我正在努力学习如何为计算蒙特卡罗模拟实现多处理。我复制了的代码,其中的目的是计算一个积分。我还将其与进行比较并计算错误。我的代码的第一部分没有问题,只需要定义整函数并声明一些常量:
import numpy as np
import multiprocessing as mp
import time
def integrate(iterations):
np.random.seed()
mc_sum = 0
chunks = 10000
chunk_size = int(iterations/chunks)
for i in range(chunks
我正在使用在两个线程之间同步初始化过程,我想知道如何正确处理它可能抛出的。
我最初写的代码是这样的:
private CountDownLatch initWaitHandle = new CountDownLatch(1);
/**
* This method will block until the thread has fully initialized, this should only be called from different threads Ensure that the thread has started before this is cal
main() {
/* code calling another class method
that use multi-threading*/ // A block
sysou("print"); //B block
}
现在的情况是,即使A块首先被处理,然后B块被执行,A块的剩余线程也被执行。
我想要在A块中创建的所有踏步都执行完之后执行B块。
我在ROR应用程序中使用sidekiq运行后台作业。最近,redis宝石版本被更新为4.6.0 (自动作为侧翼依赖项),但是它产生了一些多管道命令,当侧方日志充斥着这些日志时,这些命令会不断地发出警告,并且很难跟踪员工日志。请告诉我如何删除这些警告?
Sidekiq日志
(called from /Users/username/.rvm/gems/ruby-2.7.0/gems/sidekiq-6.4.0/lib/sidekiq/launcher.rb:141:in `block in ❤'}
Pipelining commands on a Redis instance is dep
自从上次我在我的macOS中运行brew update命令以来,我在下面开始遇到这个问题。运行brew style --fix不能解决这个问题。 我该怎么解决它呢? ? Warning: Calling `sha256 "digest" => :tag` in a bottle block is deprecated! Use `brew style --fix` on the formula to update the style or use `sha256 tag: "digest"` instead.
Please report this
我正在尝试使用gst-launch在tcp上传输mp3音频,这就是我正在尝试的:
$ gst-launch-0.10 filesrc location="/path/to/file.mp3" ! tcpserversink host=0.0.0.0 port=3000
但是它不工作,输出如下:
Setting pipeline to PAUSED ...
Pipeline is PREROLLING ...
Pipeline is PREROLLED ...
Setting pipeline to PLAYING ...
New clock: GstSystemClock
ER
我希望有一种干净的解决方案,可以在消费者忙于处理时抑制特定类型的生产者,而不需要编写自己的自定义代码块。我曾希望下面的代码可以做到这一点,但是一旦SendAsync在达到容量限制后阻塞,它的任务就永远不会完成,这暗示着延迟的消息永远不会被使用。
_block = new TransformBlock<int, string>(async i =>
{
// Send the next request to own input queue
// before processing this request, or block
// while pipel
在我的项目中,我有一个Form,就像任务对话框一样,它显示在自己的线程上……这样,当主线程锁定时,仍然可以更新任务对话框的ProgressBar和状态。im的问题是ProgressBar没有更新。状态文本会更新,但直到Form关闭之前,ProgressBar才会移动。Form正在主线程中打开。下面是我的代码:
public partial class TaskForm : Form
{
/// <summary>
/// Gets or Sets whether the task is cancelable
/// </summary>
import math
def ListSqrRoot(nums):
n=len(nums)
for i in range(n):
nums[i]=math.sqrt(nums[i])
def main():
nums=eval(input("Please enter a list of numbers:"))
print( "Before calling the function your list is:")
print (nums)
ListSqrRoo
我使用中可用的答案替换了预标记之外的所有换行符。
\n(?![^<]*<\/pre>)
它可以正常工作,直到pre中的内容具有<或>括号。
例如,输入:
<p>Test contennt for regex
with line breaks</p>
<pre>code block
with multi line content
working fine</pre>
<pre class="brush:C#">
test line break before
open paranthesi
from multiprocessing import Process
a=[]
def one():
for i in range(3):
a.append(i)
def main():
p1=Process(target=one)
p1.start()
if __name__=='__main__':
main()
print('After calling from Multi-process')
print(a)
one()
print('Calling outside Multi-proc
如果同样的方法在子类中被覆盖,我如何在子类中调用超级实现??
`
// This interface is in different File
public Interface ParentClass {
ResponseEntity<byte[]> getName(firstName, LastName) // How can i use this interface defined under getAllData
}
// This method is in different File
public class ChildClass implements
当我试图调用方法中的方法时,如下所示。
@override
void dispose() {
Provider.of<AppProvider>(context, listen: false).close();
super.dispose();
}
我来搞定。
The following assertion was thrown while finalizing the widget tree:
Looking up a deactivated widget's ancestor is unsafe.
At this point the stat
我有下面的代码,并显示错误TypeError: Last step of Pipeline should implement fit or be the string 'passthrough'. '[('sc', StandardScaler()), ('rus', RandomUnderSampler()), ('clf', LogisticRegression(max_iter=10000, multi_class='ovr', solver='sag'))]' (type &
如何使用页面对象从选择列表中选择随机选项?我用:
def select_random_member
lstMembers = self.sltMembers_element.options.map(&:index) # getting all members from select list
lastMember = lstMembers.last
rnmMember = rand(0..lastMember)
self.sltMembers_element.options[rnmMember].click
end
我看到了获取每个选项lstMe
当我尝试与两个数字相乘时,在jupyter中得到了低于错误的值。 import tensorflow as tf
tf.executing_eagerly()
x = tf.constant(2)
y = tf.constant(3)
multi = x*y
with tf.Session() as sess:
print(sess.run(multi))
## error
File "<ipython-input-35-755ab78de6c6>", line 5
print(sess.run(multi))
^
Indentation
我在打印一个函数的返回值时遇到了问题
def readfile(filename):
'''
Reads the entire contents of a file into a single string using
the read() method.
Parameter: the name of the file to read (as a string)
Returns: the text in the file as a large, possibly multi-line, string
''
我想用export_graphviz可视化我的决策树,但是我一直收到以下错误:
File "C:\Users\User\AppData\Local\Continuum\anaconda3\envs\data_science\lib\site-packages\sklearn\utils\validation.py", line 951, in check_is_fitted
raise NotFittedError(msg % {'name': type(estimator).__name__})
NotFittedError: This Pipe
我试图用k-折叠交叉验证来评估一个logistic回归分类器。我想知道在使用cross_validate_predict时是否需要在处理数据之前对数据进行洗牌,以及是否需要在使用之前对数据进行拟合:
# THIS DOES A RANDOM SHUFFLE
X_train, X_test, y_train, y_test = train_test_split(x, y, test_size = 0.33, random_state = 42)
transformer = WEASELMUSE(strategy='uniform',word_size=4, window_size