answer:The deprecation warning you are seeing is related to a behavior in Rails that was introduced between versions 4.1 and 4.2. It was a temporary solution to a problem that is no longer relevant in Rails 5. You can find more information about it in the Rails upgrade guide here(http://edgeguides.rubyonrails.org/upgrading_ruby_on_rails.html#error-handling-in-transaction-callbacks). In previous versions of Rails, errors raised within `after_rollback` or `after_commit` callbacks were suppressed and only printed to the logs. However, starting from the next version (Rails 5), these errors will no longer be suppressed and will propagate normally, similar to other Active Record callbacks. To notify developers about this upcoming change, a deprecation warning is triggered when you define an `after_rollback` or `after_commit` callback. The warning suggests adding the following configuration to your `config/application.rb` file to opt into the new behavior and remove the warning: ```ruby config.active_record.raise_in_transactional_callbacks = true ``` However, in Rails 5 and later versions, this line should be removed from your `config/application.rb` file as it is no longer necessary. Removing it will prevent the deprecation warning from appearing. Therefore, to resolve the deprecation warning, simply remove the line `config.active_record.raise_in_transactional_callbacks = true` from your `application.rb` file.,The deprecation warning you are seeing is due to changes in the way ActiveRecord works with transactions in Rails 5. Driven by its focus on improving the developer experience, Rails 5 introduced a collection of dependencies. One of these dependencies was the removal of `ActiveRecord::Base.raise_in_transactional_callbacks=`, as it was deprecated and had no effect. The `ActiveRecord::Base.raise_in_transactional_callbacks` method was designed to control whether exceptions raised in transactional callbacks should terminate the transaction or re-raise the exception. It has no effect in Rails 5 because the transactional callbacks have been made more reliable and now work correctly, regardless of the value of the `raise_in_transactional_callbacks` flag. In your case, removing the line `config.active_record.raise_in_transactional_callbacks = true` from your `application.rb` file addressed this warning. This flag is no longer needed and, since it was deprecated, removing it is not only unnecessary but also recommended for better performance and stability., In Rails 5.0.0.rc1, the `raise_in_transactional_callbacks` setting is deprecated because it has no effect and will be removed in a future version of Rails. This setting was used to configure whether Active Record should raise exceptions when an error occurs within a transactional callback (e.g., `before_commit`, `after_commit`). However, as of Rails 5.0.0.rc1, Active Record always raises exceptions when an error occurs within a transactional callback, regardless of the value of this setting. The deprecation warning is triggered when this setting is set to `true` in the `application.rb` file, as this has no effect and will be removed in a future version of Rails. To fix this warning, you can simply remove the line `config.active_record.raise_in_transactional_callbacks = true` from your `application.rb` file. This will have no effect on the behavior of your application, as exceptions will still be raised when an error occurs within a transactional callback. It's important to note that this deprecation warning only applies to the `raise_in_transactional_callbacks` setting in the `application.rb` file. If you have this setting in your models or other configuration files, you should also remove it to avoid future deprecation warnings.

answer:Yes, you can construct a QScriptValue from a QVariant using the `newVariant` function provided by the QScriptEngine class in Qt. Here is an example: ```cpp QVariant myVariant = 42; // Example QVariant QScriptEngine engine; QScriptValue myScriptValue = engine.newVariant(myVariant); ``` The `newVariant` function takes a QVariant as its argument and creates a Qt Script object holding the given variant value. If a default prototype has been registered with the meta type id of the value, then the prototype of the created object will be that prototype. Otherwise, the prototype will be the Object prototype object. In the example above, we create a QVariant `myVariant` with a value of 42. Then, we create a QScriptEngine `engine` and use the `newVariant` function to construct a QScriptValue `myScriptValue` from `myVariant`. The `myScriptValue` can now be used as a Qt Script object representing the QVariant value.,Yes, there is a way to construct a QScriptValue from a QVariant in Qt. You can use the `toScriptValue()` method in the QScriptEngine class to obtain a QScriptValue from a QVariant. Here is the general code snippet to achieve this: ```cpp QVariant input = ...; // your input variant QScriptEngine engine; QScriptValue scriptValue = engine.toScriptValue(input); ``` In this code, you first create a QScriptEngine object (which can also be a global or a local one). Then, you call the `toScriptValue()` method on that engine, passing your QVariant as the parameter. This call will return a QScriptValue converted from your QVariant, which you can use for further scripting operations., Yes, you can construct a `QScriptValue` from a `QVariant` in Qt using the `QScriptEngine::newVariant()` function. Here is an example of how to do this: ``` QScriptEngine engine; QVariant var(42); // create a QVariant with the value 42 QScriptValue scriptValue = engine.newVariant(var); // construct a QScriptValue from the QVariant ``` This will create a new `QScriptValue` object that wraps the `QVariant`. You can then use the `QScriptValue` object in the same way as any other `QScriptValue` object, such as passing it to a script or using it with the `QScriptValue::toVariant()` function to convert it back to a `QVariant`. For more information and options, you can refer to the documentation of the `QScriptEngine::newVariant()` function: <https://doc.qt.io/qt-5/qscriptengine.html#newVariant>.

answer:The `marathon_sd` exporter in Prometheus can use environment variables or labels to identify the target service and port. In your case, you can utilize the `PORT0` environment variable set by Marathon in the container to access the host port. Here's how to do it: 1. Update your Prometheus `marathon_sd` config to include the `PORT0` environment variable: ```yaml marathon_sd_configs: - job_name: 'marathon-job' honor_labels: true file_sd_configs: - files: - '/path/to/your/marathon_labels.json' refresh: 1s relabel_configs: - source_labels: '__meta_marathon_container_ports' regex: '.*?' action: 'replace' target_label: '__address__' replacement: '{PORT0}' ``` By using the `__meta_marathon_container_ports` Label, and replacing the `PORT0` with the container port, Prometheus will use the dynamically assigned host port that you want. 2. Please ensure the following: - The file defined in `files: - '/path/to/your/marathon_labels.json'` contains all the necessary labels, including `metrics`. There is currently no built-in way to access the `Endpoints` field dynamically in the Prometheus SD config, as the `marathon_sd` exporter doesn't have direct access to Marathon's service information. But there's a workaround for this, which is to set the `Endpoints` to a static value in your Marathon config, and then adjust your Prometheus config to match that static value. 3. To apply the workaround mentioned above, you can do the following: Set `Endpoints=endpoint` in your Marathon's to-be-monitored-service configuration: ```json { "containerPort": 8081, "hostPort": 0, "servicePort": 31301, "protocol": "tcp", "labels": { "metrics": "/metrics" }, "endpoints": "endpoint" } ``` Now, in your Prometheus Target config add an `endpoint` Labels: ```yaml - job_name: 'marathon-job' honor_labels: true file_sd_configs: - files: - '/path/to/your/marathon_labels.json' refresh: 1s relabel_configs: - source_labels: '__meta_marathon_container_ports' regex: '.*?' action: 'replace' target_label: '__address__' replacement: '{PORT0}' - source_labels: '__meta_marathon_endpoints' action: 'replace' target_label: 'endpoint' replacement: 'endpoint' ``` With these steps in place, the Prometheus SD config should now be able to dynamically route to the container port and use the value for 'Endpoints' that you've defined.,The issue you are facing is a known bug in Prometheus. Currently, it uses the `servicePort` property from the Marathon app definition instead of the `hostPort`. However, this bug has been fixed in the latest release of Prometheus (v2.6.0). To resolve this issue, you should update your Prometheus version to v2.6.0 or above. Once you have updated Prometheus, it will automatically listen on the dynamically assigned host port instead of the service port. This means that you no longer need to access the `PORT0` environment variable in the Prometheus SD config. Instead, Prometheus will correctly use the assigned host port. Regarding accessing other dynamically configured fields by Marathon, such as `Endpoints`, you can use the Marathon REST API to retrieve this information. The API provides endpoints to fetch detailed information about your running applications and their configuration. You can make HTTP requests to the appropriate API endpoint and parse the response to extract the required fields. Here is an example of how you can use the Marathon REST API to retrieve the `Endpoints` field for your service: ```python import requests marathon_url = "http://your-marathon-url/v2/apps/your-app-id" response = requests.get(marathon_url) data = response.json() endpoints = data"app""tasks"0"endpoints" # Now you can use the 'endpoints' variable in your Prometheus configuration or any other way you need. ``` Make sure to replace `your-marathon-url` with the actual URL of your Marathon instance and `your-app-id` with the ID of your application. By using the Marathon REST API, you can access various other dynamically configured fields and customize your metrics scraping based on your specific requirements., I understand your use case, and you're correct that Marathon defines the `PORT0` environment variable for the dynamically assigned host port in your container. However, Prometheus service discovery configuration doesn't support using environment variables directly. Here's a workaround to achieve your goal using a small script to query Marathon REST API and format the output for Prometheus configuration. 1. Create a new job in your Prometheus configuration file, let's call it `marathon-sd-dynamic`: ```yaml - job_name: 'marathon-sd-dynamic' honor_labels: true scrape_interval: 15s metrics_path: '/metrics' scheme: 'http' file_sd_configs: - files: - 'marathon-targets.json' ``` 2. Create a script (`gen-marathon-targets.py` for example) to query Marathon REST API and generate `marathon-targets.json`: ```python #!/usr/bin/env python3 import subprocess import json import os def get_marathon_apps(): cmd = '/opt/mesosphere/connectors/marathon-connect/bin/jsonhttp', 'http://localhost/v2/apps' output = subprocess.check_output(cmd, universal_newlines=True) apps_json = json.loads(output) apps = apps_json'apps' return apps def generate_targets(apps): targets = for app in apps: tasks = app'tasks' if tasks: for task in tasks: host = task'host' ports = task'ports' if ports: for port in ports: if port'number' == int(os.environ'PORT0'): target = { 'label': {'job': 'marathon-sd-dynamic'}, 'address': f'{host}:{port"number"}', 'metrics_path': '/metrics', } targets.append(target) return targets if __name__ == '__main__': apps = get_marathon_apps() targets = generate_targets(apps) with open('marathon-targets.json', 'w') as f: json.dump(targets, f) ``` 3. Add the following lines to your container Dockerfile to copy and enable execution of the above script: ```Dockerfile COPY gen-marathon-targets.py /opt/gen-marathon-targets.py RUN chmod +x /opt/gen-marathon-targets.py ``` 4. Add a new entrypoint script for your container to generate the `marathon-targets.json` before starting the service: ```bash #!/bin/sh /opt/gen-marathon-targets.py while ! -f /tmp/prom-sd-ready ; do sleep 1 done exec your_service ``` Adjust 'your_service' to represent the command that starts your application. 5. Update the container's environment variable to notify when Prometheus SD is ready: ```bash ENV PROMETHEUS_SD_READY=/tmp/prom-sd-ready ``` 6. Implement the entrypoint script to generate `marathon-targets.json` when Prometheus tries to connect for the first time: ```sh touch PROMETHEUS_SD_READY for i in {1..240} do if -s PROMETHEUS_SD_READY ; then break fi sleep 1 done ``` With this setup, your Prometheus `marathon-sd-dynamic` job will scrape the metrics by using `marathon-targets.json` generated by the custom script based on the Marathon REST API query. The script dynamically obtain the `PORT0` information, and you can extend it to query other dynamic fields as well.

answer:No, you don't necessarily need to learn assembly language in order to effectively use a debugger. While it is true that debuggers often display information in assembly form (like the `eax` register you mentioned), understanding what this means can often be done without a deep understanding of assembly language. Modern debuggers often include features that allow you to view and manipulate variables and data structures in your program in a high-level form that is easier to understand than assembly. They also often include features that allow you to step through your code at the source level, rather than at the assembly level. These features can be very helpful for tracking down bugs and understanding the behavior of your program. That being said, having a basic understanding of assembly language can certainly be helpful when using a debugger. At the very least, it can be helpful to know what the various CPU registers are used for and what some common assembly instructions do. This can help you to interpret the information that the debugger is displaying, and can also give you some insight into what your code is doing at a low level. If you're not interested in learning assembly language in depth, there are still plenty of ways you can learn the basics and get up to speed with using a debugger. Here are a few suggestions: 1. Look for online tutorials or documentation that specifically cover debugging in the programming language and/or development environment you are using. This can help you to learn the specific features and capabilities of the debugger you are using, as well as any common conventions or best practices for debugging in that language or environment. 2. Start by familiarizing yourself with the basic controls and features of your debugger, such as stepping, breakpoints, and inspecting variables. 3. Practice using your debugger to track down and fix simple bugs in your code. As you become more comfortable with the debugger, you can gradually tackle more complex problems. 4. If you do encounter cryptic assembly codes or registers that you don't understand, you can try searching for explanations of those specific codes or registers online. There are many resources available that can help you to understand what they mean, even if you don't have a deep understanding of assembly language. 5. If you are still having trouble understanding the information that your debugger is displaying, don't be afraid to ask for help. There are many communities and forums online where you can ask questions and get advice from more experienced debuggers.,<p>While having some knowledge of assembly language can be helpful during debugging, there is a more practical approach that you can take to understand the debugger without diving deep into assembly. One important step is to ensure that you have the debugging symbols set up correctly.</p> <p>If you are using the gcc compiler, you can pass the <code>-g</code> flag to enable debugging symbols. For Visual Studio compiler, make sure to enable debugging symbols generation for both debug and release builds in the project settings. If you are using a different compiler, refer to its documentation for instructions on enabling debugging symbols.</p> <p>Additionally, if you are working on Windows, consider downloading the debugging symbols for the system binaries from Microsoft. This can significantly simplify your debugging process. You can find the debugging symbols on the <a href="http://www.microsoft.com/whdc/DevTools/Debugging/symbolpkg.mspx" rel="nofollow noreferrer">Microsoft website</a>.</p> <p>By setting up the debugging symbols correctly and utilizing the resources provided, you can effectively use the debugger without the need to extensively learn assembly language.</p>,While understanding assembly language can definitely help you more effectively use a debugger, it is not absolutely necessary for basic debugging tasks. Debuggers provide graphical user interfaces to interact with code without needing to understand low-level details like the ones you've mentioned. That said, intermediate and advanced debugging often require knowledge of assembly because it's the closest a debugger can get you to the machine instructions. If you're looking for a shortcut to understanding the debugger without diving into the depths of assembly language, consider focusing on learning the language, framework, and debugger used in your specific programming environment. This will help you understand how to use the debugger efficiently, interpret the views and information it provides, and thereby identify bugs and issues in your code without necessarily understanding assembly language. There are also several resources available to understand assembly language more easily, such as online tutorials, educational videos, and courses. These can help build your understanding gradually rather than diving into a large tome of information. Always focus on acquiring knowledge gradually, learning one concept at a time, and practice your skills through real-world applications.