laco | ️Ultra lightweight state management for React and Inferno | Frontend Utils library

by deamme TypeScript Version: v1.1.0 License: MIT

X-Ray Key Features Code Snippets Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | laco Summary

laco is a TypeScript library typically used in User Interface, Frontend Utils, React applications. laco has no bugs, it has no vulnerabilities, it has a Permissive License and it has low support. You can download it from GitHub.

⚡️Ultra lightweight state management for React and Inferno

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Quality

Security

License

Reuse

Support

laco has a low active ecosystem.

It has 203 star(s) with 12 fork(s). There are 4 watchers for this library.

It had no major release in the last 12 months.

There are 1 open issues and 2 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of laco is v1.1.0

Quality

laco has 0 bugs and 0 code smells.

Security

laco has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

laco code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

laco is licensed under the MIT License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

laco releases are available to install and integrate.

Installation instructions are not available. Examples and code snippets are available.

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laco Key Features

No Key Features are available at this moment for laco.

laco Examples and Code Snippets

No Code Snippets are available at this moment for laco.

Community Discussions

Trending Discussions on laco

Insert into PDO with IF clause

How i can change the top of my stack in C++?

Good accuracy, bad predictions - CNN with TensorFlow Python

QUESTION

Insert into PDO with IF clause

Asked 2021-May-11 at 21:36

I need some help with inserting some data into a sql server table using the IF clause. I have the return of an API that I insert in the table of the sql server. However, as I will schedule my code every day to get the update from the API to see if there is anything new, but every time it executes the code it inserts the same information into the table.

The most logical thing I thought was to make a select in the table where I will insert the data and create an IF, where it compares what is in the table and my return from the array. If it’s the same, it doesn’t do anything, if it’s different, insert it. However, the else is not being validated, even if the return of the IF is false.

I've tryed If, ifelse, If(): else: endif; but i couldnt.

Can someone help me please?

...

ANSWER

Answered 2021-May-11 at 21:36

good afternoon. I identified what was going on in that case. In the second foreach I asked for the opening from each row found in the query (I believe it is the normal behavior of the foreach). Therefore, when inserting the data, I ended up inserting a duplicate, as it was 36 skillIds for each line found in the select.

I solved this issue leaving the rule inside the insert, changing it to insert select instead of making the select and then compare with what would be inserted.

Here's how it went:

Source https://stackoverflow.com/questions/67426113

QUESTION

How i can change the top of my stack in C++?

Asked 2020-May-29 at 04:43

Whats is wrong in this code, i need to change the top of my stack. That's is my code and i need to change the top of my stack Also, i need to change my function imprime to print from the bottom to the top.

Something like 10 15 20, in the function pilha_imprime will print 20 15 10.

I need to understand how do that i'm learning stack in C++ and how it`s works.

...

ANSWER

Answered 2020-May-29 at 04:43

Some functions are easier to write recursive, printing the stack backwards is one of them;

Source https://stackoverflow.com/questions/62077564

QUESTION

Good accuracy, bad predictions - CNN with TensorFlow Python

Asked 2020-May-21 at 12:48

I'm trying to create a binary classifier with TensorFlow, capable of detecting with a person is wearing a surgical Mask. The thing is, I've created a dataset for training containing 2.2k cropped faces of people wearing masks and another 2.2k cropped faces of people NOT wearing masks (my face included). Trainned the CNN for 100 epochs(almost 24hrs) and got an accuracy around 84.25%(val_acc). But my CNN still predicting wrong most of the time! I've tried more than a dozen CNN architectures and even Transfer Learning using MobileNetV2 but my results still pretty bad. Am I doing something wrong?

Part of my training code is:

...

ANSWER

Answered 2020-May-15 at 14:42

You don't seem to normalise the data. It's recommended you do that in the training and inference process.

Source https://stackoverflow.com/questions/61821775

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install laco

You can download it from GitHub.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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