An appservice plan autoscale settings can accommodate more than one app service. This can be configured under single profile and maximum of ten rules per profile and at a time only one profile will be in use.
For Ex:
Appservice Plan - Compute Metric rule - 2(scale up and scale down)
Appservices - No.Of Requests rule - 8 (4 appservice * 2 rules (scale up and down)) can be configured.
We have managed to include Microsoft Intune MAM support in to our flutter app. Currently having million of users, some of our customers wanted to manage the app from intune.
When accompanied with the company portal app on the device, we've shipped a version in the play and apple store with MAM intune policies enforced. We used the Android aar and the IOS framework. No need for MSAL was needed, as we did not know the MSAL clientid at compile time.
Android: Added the aar file and used the gradle script provided by Microsoft to handle all the class renames. Used the MAMComponents for a channel call from flutter to check on policies and user entraid.
IOS: Added the MAM swift frameworks and msal framework. Used AutoEnrollOnLaunch to enroll the known entra id from company portal.
States in React are asynchronous and the value will only update after the function has finished running. Since your function never stops running (as it loops the setTimeout), the asynchronous call never gets a chance to finish and update the state value, thus it remains at 1. For this reason, state is not the best way to do what you are currently trying to do. Define counter using let outside of the scope of TestComponent instead.
duckdb：
duckdb.query("""
select od.time,od.orderPrice,prc.time marketPriceTime
from orders od
asof join prices prc on od.orderPrice=prc.price and od.time>=prc.time
""")
dunno if this is still relevant, apperantly not, but this feature exists ootb in the meantime, any text passages / words can be highlighted and an inline comment can be saved right there, that then will appear as makred yellow and after clicking this, something like a chat bubble on the right side with the comment.
thanks for these instructions, i could manage to find the path for SQL EXPRESS 2022.
here it is:
HKEY_LOCAL_MACHINE\SOFTWARE\Microsoft\Microsoft SQL Server\MSSQL16.SQLEXPRESS\MSSQLServer\SuperSocketNetLib\Tcp\IPAll
Yes, you can train an OpenAI Custom GPT with thousands of small PDF files. However, there are some considerations and steps involved:
Considerations:
File Size: OpenAI has limitations on the total file size you can upload at once. You might need to split your PDFs into smaller chunks or upload them in batches.
Data Preparation: PDF files need to be converted into text format before training. This can be done using various tools like OCR (Optical Character Recognition) or libraries like PyPDF2.
Model Size: The number of PDFs and their total size will influence the required model size. Larger datasets might necessitate larger models, which can be more computationally expensive to train and run.
Fine-tuning vs. Embedding: You can either fine-tune a pre-trained GPT model on your PDF data or use embeddings to create a vector database for semantic search. Fine-tuning is more powerful but requires more computational resources and expertise. Embeddings are simpler but might be less accurate for complex queries.
Steps:
Data Preparation:
Convert PDFs to text using OCR or libraries.
Clean and preprocess the text data (remove noise, normalize, etc.).
Split the data into training and validation sets.
Model Selection:
Choose a pre-trained GPT model (e.g., GPT-3) suitable for your task.
Consider the model size and computational resources required.
Training:
Use OpenAI's API or a compatible framework (e.g., Hugging Face) to fine-tune the model on your prepared data.
Experiment with different hyperparameters (learning rate, batch size, etc.) to optimize performance.
Deployment:
Deploy the trained model to an API or integrate it into your application.
Use the model to generate text, answer questions, or perform other tasks based on the PDF content.
Additional Tips:
Data Quality: Ensure the quality of the extracted text from the PDFs.
Data Quantity: More data generally leads to better model performance.
Model Architecture: Experiment with different model architectures (e.g., GPT-3, GPT-4) to find the best fit for your task.
Evaluation: Continuously evaluate the model's performance on a validation set and make adjustments as needed.
By following these steps and considering the factors mentioned above, you can effectively train a Custom GPT model on your thousands of small PDF files.
(
df1.sql.select("*,date_trunc('second',event_timestamp::datetime) event_timestamp2")
.select("*,avg(value) over(partition by event_timestamp2 rows between current row and unbounded following) col1")
)
$filter->getRequestVar() is the correct way because if you have category in filter then $filter->getAttributeModel()->getAttributeCode() will throw error "The attribute model is not defined".
The compatibility of the packages react-native-vision-camera, react-native-worklets, and vision-camera-face-detector with each other depends on the versions of these packages that you are using.
To determine which versions are compatible with each other, you should check the documentation and release notes for each package to see if they specify any version requirements or compatibility issues with other packages.
In general, it’s a good practice to use the latest stable versions of packages whenever possible, as these versions are more likely to be compatible with each other and have fewer bugs and security vulnerabilities.
If you encounter any compatibility issues, you may need to update or downgrade one or more of the packages to a different version that is compatible with the others. You can also try searching for solutions online or asking for help on forums or developer communities.
The Mil installation should come with an examples folder.
There should be a link to this in the Mil Control Center app.
The MdigProcess.cpp is a good example.
A list of image buffers is setup to use in a ring or circular way by the capture callback function. Each time a new image is acquired, the callback is invoked and you can query which image in the ring buffer is the latest captured image.
Be aware that there are threading and timing issues here. The callback is in a separate thread and if your frame rate is high, then there is not much time to process between frames. At 50 fps, there is only 20 ms to process a frame.
This Answer is okay for few dates ...but for historic data like two to three months,we need the jobs to run in parallel for several dates while running 5 jobs concurrently so that dataload will be faster
the header can be in a absolutely position scrollView with horizontal scroll and you render the remaining data in another flatlist.
use 2 flatlists, top one horizontal with the header data, second vertical with remaining data, top flatList should be absolutely positioned so it becomes sticky
I have a similar problem while bitbakeing scipy.
The problem is the inherit setuptools3 in the older recipe.
The setuptool wants to work with the setup.py, but newer python packages use a pyproject.toml instead, so there is no setup.py.
The reason ehy the newer recipe works just fine is, that it doesn't use setuptools
I had a similar problem. I wanted to ignore 'backup' folder. I've removed it from the project directory, pushed the changes to Github and then copied the the folder back again again. This time it was ignored. I also suggest using GitHub Desktop it makes life much easier!
The generate_values function lazily produces values (e.g., squares of integers from 1 to 10).
Conversion to std::vector:
Since ::testing::ValuesIn requires an iterable container, the generator_to_vector function iterates through the generator and collects its values in a std::vector.
Google Test Integration:
INSTANTIATE_TEST_SUITE_P uses the vector produced by generator_to_vector to parameterize the test cases.
Test Case Execution:
Each value generated by the generator becomes a parameter for a test case.
The AWS Well-Architected Tool has extensive API integration. You can do all sorts of things with that like create automation around creation of workloads, answer questions automatically, get risk scores for workloads and see things down to how individual questions were answered within the workload. Doing that would also give you the ability to retrieve the recommendations from the tool based on how the question was answered. I've personally built automation like this and found the easiest way to interact was by creating a series of Step Functions with Lambdas (python) to accomplish the tasks I needed while interacting with the APIs but I'm sure you could come up with all kinds of solutions. You can find the AWS API docs for well-architected here:
Main Features of the Illustration
Works perfectly on desktop along with mobile devices including Smartphones: iPhone, iPad, Tablets, etc.
Responsive and fully resizable.
Each organ or spot can be activated or deactivated individually.
SVG (Scalable Vector Graphics) based, so it can be enlarged to any size up to preserving the quality.
I'm still not convinced that it's a necessary approach, but here's a really simple option how to achieve this:
from pydantic import BaseModel
class MyModel(BaseModel):
x: int
def __init__(self, x: int | str):
super().__init__(x=len(x) if isinstance(x, str) else x)
MyModel(x='test')
Yes, your understanding is correct. In Azure App Service, autoscale settings are configured at the App Service Plan level, and you can define multiple autoscale profiles within a single autoscale setting. @Dilly B
i meet the same error as your, i use airflow's default user [admin] for openmetadata's config,but openmetadata's airflow pipeline always happen error,last i create a new user on airflow web ui as role admin, magical，it's success
Update your dependencies block in build.gradle (Project level) as follows:
dependencies {
// Remove the older version of the Gradle plugin
// classpath 'com.android.tools.build:gradle:7.4.2'
// Use the updated version instead
classpath 'com.android.tools.build:gradle:8.3.1'
}
I had the same problem and later realized it was because I forgot to draw the line from OLD DB Source (box) to OLD DB Destination (box), simple as that. Without the line, it does not know the inputting columns to create the table, thus the "New" button was missing.
If you're having trouble using Falstad on a Mac, it might be due to Java compatibility issues. Make sure Java is installed and updated to the latest version. Sometimes, browser settings block Java-based apps; try enabling it or switching browsers. If you're using macOS Ventura or newer, security settings might block the app—allow it in "System Preferences > Security & Privacy." If the problem persists, consider using an online version or downloading a standalone simulator.
onDateChange(event: any): void {
const inputDate = event.target.value; // Get the value from the input
// Convert to Date object
const date = new Date(inputDate);
// Validate if the date is valid
if (this.isValidDate(date)) {
// Call your function if the date is valid
console.log("Valid date:", date);
this.someFunction();
} else {
console.log("Invalid date");
}
}
isValidDate(date: Date): boolean {
return !isNaN(date.getTime()); // Returns false if the date is invalid
}
someFunction(): void {
// Your custom logic here
}
To complete the previous answers, especially the one from @Devil, there is a bug for the Try It Out button on the springdoc-openapi 2.6.0. It is always visible, whatever values you set in the properties springdoc.swagger-ui.supportedSubmitMethods and springdoc.swagger-ui.try-it-out-enabled. The previous version 2.5.0 works fine, and the bug is supposed to be fixed for the future version 2.7.0.
My intellisense started working again after removing the include and exclude settings in tsconfig, despite them being correct. Very odd! Need to troubleshoot this a bit more.
In web development, choosing the right software development life-cycle (SDLC) model is essential to ensure the project is delivered on time, within budget, and meets quality standards. Several SDLC models are widely used, each with its unique approach to handling the phases of development. Below are some common SDLC models used in web development:
Waterfall Model
The Waterfall model is a traditional, linear approach where each phase must be completed before the next begins. This model is best for small projects with clear, fixed requirements.
Phases:
Requirements gathering: Define all project requirements up front.
System design: Create a blueprint for the website’s architecture.
Implementation: Develop the website based on the design.
Testing: Test the website for bugs, performance issues, and usability.
Deployment: Make the website live.
Maintenance: Regular updates and fixes after launch.
Advantages:
Easy to understand and manage.
Well-suited for small projects with well-defined requirements.
Disadvantages:
Inflexible to changes during the development process.
Testing is done late in the cycle, making it difficult to address issues early.
2. Agile Model
The Agile model is an iterative and flexible approach, emphasizing collaboration, customer feedback, and the delivery of small, functional pieces of the project at regular intervals (sprints).
Phases:
Planning: Define initial requirements and priorities.
Design and development: Build small, functional sections of the website.
Testing: Continuous testing throughout the development process.
Deployment: Deploy the working increments.
Review and feedback: Collect user feedback, refine the project.
Iteration: Repeat the cycle for each sprint or phase.
Advantages:
Flexible and adaptable to changes.
Regular feedback from stakeholders helps ensure the product meets business needs.
Faster delivery of working product versions.
Disadvantages:
Requires active collaboration with stakeholders and clients.
Can become chaotic if not well-managed.
3. Iterative Model
The Iterative model focuses on repetition and refinement. The project is divided into small iterations, each improving upon the previous one. Unlike Waterfall, development begins with a basic version, and subsequent iterations add more features.
Phases:
Planning: Define the broad requirements.
Design: Create the initial design.
Implementation: Build a basic version of the website.
Testing: Identify bugs and improvements.
Iteration: Refine and add features in the next iteration.
Advantages:
Allows changes to be incorporated throughout the development.
Features are added incrementally, which reduces risk.
Disadvantages:
Can lead to scope creep if not carefully managed.
May not be ideal for projects with fixed timelines or budgets.
4. V-Model (Verification and Validation Model)
The V-Model is an extension of the Waterfall model, where each development phase is directly associated with a testing phase. It emphasizes validation and verification at every step.
Phases:
Requirement Analysis
System Design
Unit Design
Coding
Unit Testing: Verifies each individual part of the website.
Integration Testing
System Testing
Acceptance Testing
Advantages:
Clear structure and defined deliverables.
Testing is integrated with development, improving quality.
Disadvantages:
Inflexible to changes once the development process begins.
Not suitable for complex projects with uncertain requirements.
5. Spiral Model
The Spiral model combines elements of both iterative and waterfall models, focusing on risk management. It allows for multiple iterations through the phases of design, development, and testing, incorporating user feedback and risk analysis at every step.
Phases:
Planning and Requirements Gathering
Risk Analysis
Engineering and Design
Testing
Evaluation and Review
Advantages:
Risk management is a core component, making it ideal for complex or high-risk projects.
Flexibility to adapt to changes and evolving requirements.
Disadvantages:
Can be complex and costly to implement.
May require extensive documentation.
6. RAD (Rapid Application Development) Model
The RAD model is focused on rapid prototyping and quick iterations. Instead of lengthy planning phases, this model emphasizes delivering a working product quickly, followed by iterative improvements based on feedback.
Phases:
Requirements Planning
User Design: Prototypes are developed and reviewed by the client.
Construction: The actual coding and development.
Cutover: Final deployment after testing and feedback.
Advantages:
Faster development time.
Close collaboration with stakeholders for continuous feedback.
Disadvantages:
Requires well-defined requirements from the start.
May lack proper documentation or control in the initial stages.
7. DevOps Model
The DevOps model integrates development and operations teams to work together continuously throughout the project. This model emphasizes automation, continuous testing, integration, and delivery, reducing manual intervention.
Phases:
Development: Continuous development and integration.
Testing: Automated testing ensures the quality of code.
Deployment: Continuous delivery and deployment to production.
Monitoring and Feedback: Real-time monitoring and client feedback.
Advantages:
Continuous improvement and deployment.
Strong collaboration between development and operations teams.
Better quality control through automated testing.
Disadvantages:
Requires significant cultural and organizational changes.
Initial setup can be resource-intensive.
Choosing the Right Model for Web Development
Waterfall is best for simple, well-defined projects.
Agile is ideal for projects with evolving requirements and a need for flexibility.
Iterative is useful for medium-sized projects requiring frequent updates.
V-Model is suitable for projects where rigorous testing is essential.
Spiral is best for complex, high-risk projects.
RAD is ideal for projects needing rapid delivery with client feedback.
DevOps works well for ongoing web development with continuous integration and deployment.
Let me know if you need further details on any of these models or their specific applications in web development!
I thought socket was used for communication. Not sure but as per Google the best way to accomplish this is using signal and that's what I'm trying to do but my signal not working.
Yes, WP-Ecommerce does work with LinkPoint, but you may need to use a third-party integration plugin or custom development to set it up properly. WP-Ecommerce has built-in payment gateways, but LinkPoint may require some additional configuration or a custom API to make it work seamlessly. It's worth checking with WP-Ecommerce support or browsing the forums for any plugins that could simplify this integration.
to see if the solver can find a feasible solution, or is there a bug in your program. It sometimes helps to relax the problem to help solver find initial feasible solution which might be difficult to reach in a more constrained original problem.
For some reason the gradient returns to the first color (red) when background-position is at 0 -96px to 0 -100px. Why is that? I didn't expect that. I also can't make it work with positive numbers going from 0px to 100px. If someone can explain that as well it will be great.
type RecurrenceType = 'once a year' | 'twice a year' | 'quarterly' | 'monthly';
function calculateEndDate(startDate: Date, recurrence: RecurrenceType): Date {
const endDate = new Date(startDate); // Copy the start date to calculate the end date
switch (recurrence) {
case 'once a year':
endDate.setFullYear(startDate.getFullYear() + 1); // Add 1 year
break;
case 'twice a year':
endDate.setMonth(startDate.getMonth() + 6); // Add 6 months
break;
case 'quarterly':
endDate.setMonth(startDate.getMonth() + 3); // Add 3 months
break;
case 'monthly':
endDate.setMonth(startDate.getMonth() + 1); // Add 1 month
break;
default:
throw new Error('Invalid recurrence type');
}
When you give the specific width to the grid div element, it starts from the left align just add the justify-items: center; to the set image center. To use the display:grid use the justify-items instead of justify-content.
Also, in the link below the image link-wrapper div, add the column-gap: 10px; as you need to change the value. So all the links set the gap from links.
The outer horizontal ScrollView allows the entire table to scroll horizontally if it exceeds the screen width.
The inner vertical ScrollView (or alternatively FlatList) is used for scrolling the rows vertically.
Rendering the Table:
The header (headers) is rendered first.
Then, we use a FlatList to render the rows of data (data). It maps through the data and renders a row for each item in the data.
Styling:
The table cells are styled using a border to create a table-like look. You can adjust padding, borders, and other styling properties to match your design.
The flexDirection: 'row' ensures that each row is laid out horizontally.
Horizontal Scrolling:
The outer ScrollView with horizontal prop allows horizontal scrolling for the whole table. This will be triggered if the table's width exceeds the available screen width.
Vertical Scrolling:
The inner ScrollView or FlatList allows scrolling the rows vertically.
Key Notes:
This approach uses both FlatList and ScrollView to achieve the desired table layout with both horizontal and vertical scrolling.
You can customize the table further with dynamic data, pagination, or more complex interactions.
This will create a responsive table where you can scroll both horizontally (to see more columns) and vertically (to see more rows).
Given $u \sim U[0,1]$, (u is a uniform random variable in [0,1]), then for any distribution $\mathbb{P}$ with cumulative distribution function (CDF) $F$, holds $F^{-1}(u) \sim \mathbb{P}$.
I.E., in general you can obtain samples from any distribution, just as the image of a uniform random variable through the inverse CDF of the desired distribution.
In this case, to sample from a normal distribution, your $F^{-1}$ is the inverse normal cdf of a normal, which is not implemented in native js nor in the Math package, but you can find efficients numerical approximations such as Peter J. Acklam's method which are easy to implement in js.
Of course if you need your variable to have a mean $\mu$ and standard deviation $\sigma$, you can always consider $x = \sigma invNormalCDF(u) + \mu \sim \mathcal{N}(\mu, \sigma^2)$.
This is a very powerful trick to generate samples for a distribution, even if you don't know the distribution of data, you can estimate the CDF from a sample.
There are tools available for demoing code in the browser such as Stackblitz or codepen that could serve this purpose. You can create basic websites and preview them, there is also the option of opening the console.
I personally prefer codepen as it does not require someone to register and you can access the console (bottom left button) and see it's contents. To open codepen without registering go to the link
codepen.io/pen
This suggestion was done in the comments by @Bergi so credits to him.
For whatever reason this problem still exists - and it's almost 2025...
My fix to the problem after creating/editing a run config and hitting the Store as project file button was to simply close the project File > Close Project and reopen it again.
Judging from your logs, everything is ok and MySQL is already listening on the port. Can you connect to MySQL? If not, what error message is being reported?
It seems like you might want to share a question or information via email or social media. I can help you draft a message, or you can easily share a link to this page through your preferred platform.
If you need assistance with how to share this, feel free to let me know!
In standard Django templates, there is no dynamic re-rendering when a model changes. You can use WebSockets for this functionality. Take a look at this example with Channels
The whole serviceOf is no longer necessary; it has already been removed from the main branch.
You can follow this PR to create a patch-package and fix the issue:
Edit file node_modules/react-native-gradle-plugin/build.gradle.kts as shown in the PR
Not setting up the authentication is the reason you are facing this problem. Please try to integrate django-rest-framework-simplejwt on django side. This token usually contains the user id and on frontend side you can save this token in localstorage to make the calls for rest of the endpionts.
