Add the word doc to the project to the solution (drag and drop). Right click on the file in the solution explorer - Select Copy to Output Directory option (copy always) or (copy if newer).
Searching for nested attributes is not supported by default in SAP Commerce (Hybris) when using the Backoffice advanced search. If you are required to implement such a feature, the two options would be:
1) Extend the advanced search logic (see AdvancedSearchController class)
Not recommended due to its complexity.
Your particular change is item-type specific rather than a general improvement, making the effort less worthwhile.
2) Add a productCode attribute to CustomerReview and use a PrepareInterceptor.
This is the simpler and more practical solution for your use case.
The interceptor ensures that when the product changes in a CustomerReview, the productCode is updated accordingly.
You can then use the productCode attribute in the advanced search widget.
Thanks for @Koboo's response. My code worked with his solution. But I found other simpler solution. You need just change java time zone inside bootstrap class's main method:
@SpringBootApplication
public class ApiApplication {
public static void main(String[] args) {
TimeZone.setDefault(TimeZone.getTimeZone(ZoneOffset.UTC));
SpringApplication.run(ReflectBusinessApiApplication.class, args);
}
}
The error "org.codehaus.groovy.control.MultipleCompilationErrorsException: startup failed" usually occurs due to Groovy/Gradle script issues or JDK incompatibility. In my case, the problem was caused by Android Studio’s default JDK.
Solution: Change JDK to a Locally Installed Version
Open Android Studio.
Go to File → Settings → Build, Execution, Deployment → Build Tools → Gradle.
Under Gradle JDK, change the selection from the default Embedded JDK to your locally installed JDK.
Click Apply and OK, then restart Android Studio.
Sync Gradle again: File → Sync Project with Gradle Files.
Why Does This Happen?
The default JDK bundled with Android Studio might not be fully compatible with the Gradle version.
Some third-party libraries require a specific JDK version to compile successfully.
Gradle might be referencing an older or incompatible JDK, causing Groovy compilation issues.
Alternative Fixes:
If changing the JDK doesn't work, try:
Upgrading Gradle: Update gradle-wrapper.properties to a newer Gradle version.
Deleting .gradle and .idea folders and then syncing again.
Running Gradle from the command line for more details:enter image description here
./gradlew clean
./gradlew build --stacktrace
Gradle Setting
Reasons:
Blacklisted phrase (1): enter image description here
I do not understand why Item keep a compact format.
Using expand function on an OData endpoint doesn't mean it will return a flat table.
It means that you are requesting related data, that are not by default provided in the response. Expand function can be used for complex types and collections.
How should I proceed to do so?
By the image, I guess, you are working in Power Query which offers JSON and XML parsing functionality. I would suggest following Parse text as JSON or XML (Power Query).
I discovered that Firebase configuration and the service worker have limitations in in-app browsers. To address this, I wrapped the Firebase app initialization in a try-catch block.
let firebaseApp;
let messaging;
try {
firebaseApp = initializeApp(firebaseConfig);
messaging = getMessaging(firebaseApp);
} catch (err) {
console.error("Failed to initialize Firebase Messaging", err);
}
const flatListRef = useRef<FlatList>(null);
// Scroll to the end after updating messages
setTimeout(() => {
flatListRef.current?.scrollToEnd({animated: true});
}, 100); // Small delay to ensure the list is updated
I would start by looking at Retrieval Augmented Generation to include only the relevant parts of the video for a query instead of sending the transcript fully
Yes, you can pull the API Gateway Rules to local using Catalyst CLI. After enabling the APIG in Catalyst console, we can pull the rules as JSON file in local, test and deploy it.
This is a classic stream / buffer reading issue. Instead of bulk processing the entire streaming response from Solr, the intention is that the client will read it chunk by chunk and make sense of it as you go.
I have not tried this myself but there are streaming json parsers for the Python ecosystem (https://pypi.org/project/json-stream/) which seems to fit the bill at a glance. I believe you will be able to configure it so that your code consumes each doc at a time while still reading the stream from your streaming request.
I did not remove the Debug lines but hey, you know what it was for ;)
For anyone interested, there you go. Now I can use it in my ‘target’ nethod that retrieves the QR code value, appends the rest to make it a valid endpoint adress and finally send the POST request to that API endpoint.
Happy Coding !
do you have any info if this error is still occurring? I'm a QlikCloud admin and I'm evaluating a possible migration to MySql of my source database.
Thanks
I just want to add that after much research, I've come to the conclusion that there is no way currently to write a constexpr offset() in C++ (at least with version 20 and below, no clue about the next version), as crazy as it might sound…
No solutions suggested above actually work because they all use reinterpret_cast which is forbidden in constexpr. Edit : and to be more specific, c style cast (raw cast) equivalent to reinterpret_cast are forbidden too, quite obviously…
The problem is with the version code (the number after the + symbol), not the version name (the numbers before it). In Flutter/Android, the version code has to be unique and higher than any previous version you've uploaded to the Play Console.
No matter if it’s a major, minor, or patch update, the build number (version code) always needs to increase. This is because the Play Console relies on it to track releases and make sure updates are installed in the right order.
Taking the comments about a Timer in a stopwatch app into consideration, if you absolutely need to use the Timer in the class, you can mark it as @Transient and SwiftData will not persist it.
Export the Table from the Dev Environment: First, you'll need to extract the table data and its metadata from the dev environment. You can use Spark SQL along with Databricks utilities to achieve this.
You can go for some third party services and tools like Sentry, Loggly etc. Most of them have everything you would need. Takes care of performance monitoring, error tracking etc in production.
Looks like the issue is with how the dynamic query is being formed in ADF. The error 'The template function 'iem' is not defined or not valid' suggests there might be a syntax issue in your expression. Make sure you're properly escaping the double quotes in your dynamic query. Try using @concat('"', variables('schema'), '"."', variables('table'), '"') to explicitly wrap the schema and table names in double quotes. Also, verify that there are no extra spaces or unexpected characters in the variable values. If you're using @{} syntax, double-check that all functions and variables are correctly referenced.
Im facing an issue where I’m unable to establish a connection between two peers. We have created a peer connection factory, but whenever I write code for the connection factory, Unreal Editor crashes.
Do you have any insights into what might be causing this issue? Any guidance would be greatly appreciated.
Solution from @Kalind worked for me. If you don`t have firebase project attached, try make one and attach to your project. It would make API key and service account for itself, and consent screen would pass.
As Rob Spoor answered in comments, everything is correct, NotNull works before validator.
first each validation takes place without throwing any errors, then all validation errors are collected and wrapped in a single ConstraintViolationException. That's why it has a set of violations. That's why when implementing a constraint validator, the first step is to return true if the thing to validate is null. If it shouldn't be null then let @NotNull handle that.
You can also disable inspection for this in PyCharm:
File -> Settings -> Inspection -> Type "static" in Python -> Turn off "method is not delared static"
The increased bucket limits fundamentally change the landscape for S3 multi-tenant data partitioning. The old recommendations were heavily influenced by the bucket limits. Let's break down the implications and discuss when each strategy might be suitable now:
Prefix-per-Tenant:
Pros:
Simpler Management (Initially): One bucket means fewer IAM policies and less overhead at first. You manage permissions within the prefix structure.
Cost Optimization (Potentially): Data lifecycle management is easier to configure at the bucket level. You can transition all tenants' data to cheaper storage classes (e.g., Glacier) simultaneously. Aggregate usage across tenants can help qualify for bulk pricing or discounts.
Reduced Operational Overhead (Potentially): Easier to monitor and maintain a single bucket than thousands.
Strong eventual consistency: Accesses and updates to a single prefix are strongly consistent, although this is the case for all accesses with S3.
Cons:
IAM Complexity at Scale: Managing granular permissions per tenant becomes extremely complex using IAM policies and prefix conditions. Maintaining and auditing these policies can be a nightmare. As complexity increases, you end up building your own permissioning system on top of S3.
Potential Performance Bottlenecks: While S3 scales incredibly well, you can hit performance limitations within a single bucket if a particular tenant generates a disproportionate amount of traffic to their prefix. S3's key-naming guidelines can help mitigate this, but it's a factor. The more diverse the traffic, the less likely you are to face such problems
Difficult Usage Tracking per Tenant: While S3 Storage Lens can provide insights, getting accurate, real-time cost and usage attribution per tenant is more challenging. You often need to rely on custom logging and analytics.
Data Isolation Concerns: While IAM policies should enforce isolation, any misconfiguration can lead to one tenant accessing another's data. This risk is lower with bucket-per-tenant.
Reduced Granularity of Security and Compliance: Bucket-level compliance features (like object locking) or security features (like S3 Inventory for audit) apply to all tenants in the bucket. This can make it harder to tailor security and compliance policies to individual tenants.
Bucket-per-Tenant:
Pros:
Strongest Data Isolation: Each tenant has their own isolated environment. Misconfiguration of one bucket is less likely to impact other tenants.
Simplified IAM Management: IAM policies are simpler because you are managing permissions at the bucket level, which aligns naturally with tenant boundaries. Each bucket has its own set of IAM permissions.
Granular Control: You can apply different lifecycle policies, security settings, and compliance controls to each tenant's bucket as needed. This allows for customized experiences.
Improved Usage Tracking and Cost Attribution: Native S3 features and AWS Cost Explorer can easily provide accurate cost and usage data per bucket (and therefore, per tenant).
Easier Scaling and Management with Automation: Infrastructure-as-Code (IaC) tools like CloudFormation, Terraform, or the AWS CDK make it easy to automate the creation and management of thousands of buckets.
Simplified Data Replication: You can replicate buckets to different regions or accounts on a per-tenant basis.
Cons:
Increased Initial Complexity: Setting up thousands of buckets can seem daunting initially, but IaC tools make this manageable.
Increased Operational Overhead (Potentially, but addressed by automation): Monitoring and managing thousands of buckets can be more complex than a single bucket, but automation and centralized logging/monitoring solutions can mitigate this.
Potential for Resource Exhaustion: You need to carefully manage your AWS resource limits (IAM roles, policies, etc.) to avoid hitting account limits.
Potential for Inconsistent Application of Organization Policies. You need to take extra measures to verify that the application of policies like KMS key usage is consistent.
So, When to Use Which?
The increased bucket limits make bucket-per-tenant the preferred approach in many, if not most, situations that involve a high degree of isolation. However, there are still cases where prefix-per-tenant may be appropriate:
Very Small Number of Tenants (e.g., < 10): If you have a very small number of tenants and predictable usage patterns, the simplicity of a single bucket might outweigh the cons.
Very Low Security/Compliance Requirements: If data isolation is not a primary concern, and you prioritize simplicity over granular control.
Aggregated Billing/Pricing Requirements: If you only offer an "all in one" service, and offer no granularity around tenants, aggregating the cost savings into a single bucket might be ideal
Extreme Cost Sensitivity and Consistent Tenant Requirements: If all tenants require the exact same lifecycle policies, data retention, security controls, and you have extreme budget limitations, a single bucket with prefix-per-tenant might be a cost-effective solution (but be aware of the trade-offs).
I ended up creating different functions for different HTTP methods. So, each of those methods will be decorated with either @Get, @Post, @Patch, @Put and @Delete.
All of them will call the same method underneath, and then I can achieve the logic I was looking for.
Sounds like your TXT record might not have fully propagated yet. Even though Terraform says it was created successfully, DNS changes can take some time to propagate across the internet, sometimes up to 48 hours. Try using dig or nslookup to check if the TXT record is actually resolving. Also, make sure you're adding the TXT record to the correct domain and that there are no conflicting records. If the issue persists, check your DNS provider’s UI to confirm it was created as expected—sometimes Terraform applies changes but they don’t fully sync with the provider.
With thanks to @Paulo Marques for the suggestion: I converted the latitude and longitude fields to str type while the data were still in a pandas dataframe.\
The block that converts to Spark and writes to table now looks like this:
basic_df = pd.DataFrame(basic_data_list)
basic_df.latitude = basic_df.latitude.astype(str)
basic_df.longitude = basic_df.longitude.astype(str)
if not basic_df.empty:
basic_spark_df = spark.createDataFrame(basic_df, schema=basic_schema)
basic_spark_df.write.mode("append").option("mergeSchema", "true").format("delta").saveAsTable("api_test")
And all the data now pull through without any errors.
To display the PlayGames profile image URI and compose an image on API 35, you would need to retrieve the URI of the profile image and then use it in your application. For example, if you're integrating it with a system like Steam Wallet Gift Code / Steam Key -50$, you can structure your code to fetch and display the profile image URI as follows:
java
Copy
// Assuming you are using an API that fetches the user's PlayGames profile image URI
String profileImageUri = getPlayGamesProfileImageUri();
// Here, you would use the URI to display the image in your app (API 35 or similar)
// Example function to compose the image using the URI
composeImage(profileImageUri);
They should not be executed if the weight is 0. I also sanity-checked that statement by trying it locally and the constraint is not executed while solving.
This issue is likely caused by a recent pre-release of astroid, which seems to be causing compatibility issues with sphinx-autoapi.
Read permissions errors for sphinx-autoapi, only on readthedocs #11975
I pinned the astroid version to the actual 3.3.8. and this worked fine for me
I saw that in the initialization code I got from STM32 was incorrcet. I just copied and pasted the code. Only change I did was the refresh rate, but I did not see that it's initializing BANK2. My SDRAM bank is 1, so I wrote:
Command.CommandMode = FMC_SDRAM_CMD_CLK_ENABLE; /* Set MODE bits to "001" */
Command.CommandTarget = FMC_SDRAM_CMD_TARGET_BANK1; /* configure the Target Bank bits */
Command.AutoRefreshNumber = 1;
Command.ModeRegisterDefinition = 0;
HAL_SDRAM_SendCommand(&hsdram2, &Command, 0xfff);
You run your application in local machine or in docker?
If you run in your local machine, i think correct property config is that: spring.datasource.url=jdbc:postgresql://localhost:5432/postgres
If you run your application in docker, you have to make sure that both your application and db image are sharing same network. You can config docker network like this:
Checkout my blog on this topic. You will get a complete but brief explanation. I also mention how can you switch between different python versions effectively.
How to Check if a File Exists on an SFTP Server Using JSch in Java?
If you're working with JSch to interact with an SFTP server in Java, you might need to verify whether a file exists before performing operations like reading, downloading, or deleting it. The stat() method of ChannelSftp can be used for this purpose.
Implementation:
The following method attempts to retrieve the file attributes using channelSftp.stat(remoteFilePath). If the file exists, the method returns true. If the file does not exist, it catches the SftpException and checks if the error code is SSH_FX_NO_SUCH_FILE, indicating that the file is missing.
private boolean verifyFileExists(ChannelSftp channelSftp, String remoteFilePath) {
try {
// Attempt to get the file attributes
channelSftp.stat(remoteFilePath);
System.out.println("File exists on the remote server: " + remoteFilePath);
return true;
} catch (SftpException e) {
if (e.id == ChannelSftp.SSH_FX_NO_SUCH_FILE) {
System.out.println("File does not exist on the remote server: " + remoteFilePath);
} else {
System.out.println("Error checking file existence: " + e.getMessage());
}
return false;
}
}
Explanation:
The method tries to retrieve the file metadata using stat(remoteFilePath).
If the file exists, stat() executes successfully, and we return true.
If an SftpException occurs:
i)If an SftpException occurs:
If the error code is SSH_FX_NO_SUCH_FILE, the file does not exist, and we return false.
ii)For any other exception, an error message is printed, and false is returned.
Why Use stat() Instead of ls()?
While ls() can list files, it is inefficient for checking a single file's existence because it retrieves a list of files and requires additional processing. Using stat() is more efficient for this specific use case.
I'm trying to extract image data from documents like quotes and purchase orders. It works when given instructions to only extract dates, but won't extract names, addresses and other data of that nature.
Can anybody please send me a working C program that uses the decimal data type (and decimaL.decimal). Just to declare two numbers as decimals, then print out their:
add, subtract,multiply.
Reasons:
RegEx Blacklisted phrase (2.5): Can anybody please send me
Managing ball-to-ball collisions in a simulation involving multiple interacting objects necessitates an understanding of several fundamental principles, such as collision detection, the application of physical laws (including momentum conservation and restitution), and the efficient resolution of these interactions.
When utilizing the Verlet integration method, a numerical approach for simulating object motion, the process of managing ball-to-ball collisions can be executed in a series of steps:
Fundamentals of Verlet Integration
Position Update: The Verlet algorithm modifies an object's position by referencing its previous and current positions:
r(t + Δt) = 2r(t) - r(t - Δt) + a(t)Δt²
Where:
r(t) represents the position of the ball at time t,
a(t) denotes the acceleration (resulting from gravity, friction, etc.) at time t,
Δt signifies the time increment.
Velocity Calculation: The velocity can be estimated by the change in position over the time interval:
v(t) = (r(t) - r(t - Δt)) / Δt
Collision Detection
To ascertain whether two balls collide, it is essential to evaluate if the distance between their centers is less than the sum of their radii:
∥r₁ - r₂∥ < r₁ + r₂
Where:
r₁ and r₂ indicate the positions of balls 1 and 2,
r₁ and r₂ represent the radii of the respective balls.
If this condition holds true, a collision is confirmed.
Collision Response (Elastic Collision)
Upon the occurrence of a collision, the velocities of the balls are modified in accordance with the principles of momentum conservation and the coefficient of restitution. The primary steps include:
Relative Velocity: The relative velocity between the balls along the line of contact is expressed as:
v_rel = v₁ - v₂
Normal Vector: The unit normal vector n̂ directed from ball 2 to ball 1 is defined as:
n̂ = (r₁ - r₂) / ∥r₁ - r₂∥
Good afternoon, hope this helps if you have any questions feel free to ask.
You need a new library, install this:
pip install opencv-python
import pyautogui as ac
from time import sleep
procurar = "yes"
while procurar == "yes":
try:
x, y = ac.locateCenterOnScreen('92.png', confidence=0.9)
ac.click(x, y)
sleep(1)
except:
sleep(2)
ac.click(1479,218)
sleep(2)
I'm new. ive installed ffmpeg via choco, but when I enter via cmd ffmpeg -version still "ffmpeg is not recognized as an internal or external command, operable program or batch file" I've also tried changing the path from https://www.geeksforgeeks.org/how-to-install-ffmpeg-on-windows/ but still not getting any progress.
I was attempting to run a snapshot on Docker. In my case, after running also the commands to switch the owner to mongodb, what worked was the following command
Been given a legacy DB that has been sitting on a shelf for 2 decades, and I'd like to extract data from it. It was a scientific research project.
I've figured out I've got *.4db, *.4dd files.
I suspect the DB was developed and maintained in 4D 6.7.1 version on MacOS.
I've tried installing the available 4D versions from the official website. Both v20, v18 give an error of "DB version to old".
Now, where can I obtain a trial/freemium copy of 4D app of 6.7.5, or at least some other version from the 2000's?
The legacy versions of the software are only open for download to "dev partners" (that's a $300 license). Perhaps someone with access could help me get a freemium version of that era (pref. Windows version) so that I could attempt to access the data?
While most discussions of mapping Azure B2C identities to an external source only mention an email address a number MS pages mention email address or user object id.
The following GitHub repo on a remote profile will hopefully help.
