validify | Simple-as-possible React form validation | Form library

by zackify TypeScript Version: 6.1.1 License: MIT

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

kandi X-RAY | validify Summary

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

single dependency, simplest way to validate and manage form state with hooks in React + React Native! With full test coverage and TS support.

Support

Quality

Security

License

Reuse

Support

validify has a low active ecosystem.

It has 276 star(s) with 14 fork(s). There are 6 watchers for this library.

It had no major release in the last 12 months.

There are 0 open issues and 13 have been closed. On average issues are closed in 106 days. There are 8 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of validify is 6.1.1

Quality

validify has 0 bugs and 0 code smells.

Security

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

validify code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

validify 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

validify releases are available to install and integrate.

Installation instructions, examples and code snippets are available.

It has 20 lines of code, 0 functions and 15 files.

It has low code complexity. Code complexity directly impacts maintainability of the code.

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validify Key Features

No Key Features are available at this moment for validify.

validify Examples and Code Snippets

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Community Discussions

Trending Discussions on validify

Some hr tags have gaps inside them while other doesn't

How to check if an uploaded N x M csv file has certain headers?

Scala Spark: Performance issue renaming huge number of columns

QUESTION

Some hr tags have gaps inside them while other doesn't

Asked 2018-Jul-01 at 15:34

I have a pen, which is basically a todo app. The todo items are actually li elements which have text, button and a hr. Some of them are having hr with spaces inside them while some doesn't.

Image:

HTML:

...

ANSWER

Answered 2018-May-16 at 13:13

Seems like this issue is browser related, since it works fine for most people. Possibly your browser has a default styling for hr elements. It is, however, nowadays bad practice to use a horizontal line for presentational terms. Source

You would be fine by using a border-bottom on your li element. If you want to position the border lower than the default position, you can use padding-bottom on the li element. Your HTML structure also looks a lot more clear with this.

For example, changing the styling of your CSS selector li.td to the following could do the trick:

Source https://stackoverflow.com/questions/50371645

QUESTION

How to check if an uploaded N x M csv file has certain headers?

Asked 2018-Jan-16 at 11:42

How would I check a CSV with unknown amount of rows and columns whether it has some certain headers?

Let's say I have a CSV file called Testy.py and it has M columns with M headers. But I can only validify this CSV file if it has the headers: ID in the first column and Name in the second column. Meaning if the file does not fulfill the requirements, I will set the uploaded file to 0. I have the following code, and I tried to use the if statement under the Cols definition but it doesn't work.

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ANSWER

Answered 2018-Jan-16 at 09:06

The below code will read csv and check the columnnames are right or not.

Source https://stackoverflow.com/questions/48277120

QUESTION

Scala Spark: Performance issue renaming huge number of columns

Asked 2017-Feb-08 at 11:00

To be able to work with columnnames of my DataFrame without escaping the . I need a function to "validify" all columnnames - but none of the methods I tried does the job in a timely manner (I'm aborting after 5 minutes).

The dataset I'm trying my algorithms on is the golub Dataset (get it here). It's a 2.2MB CSV file with 7200 columns. Renaming all columns should be a matter of seconds

Code to read the CSV in

...

ANSWER

Answered 2017-Feb-08 at 11:00

Assuming you know the types you can simply create the schema instead of infering it (infering the schema costs performance and might even be wrong for csv).

Lets assume for simplicity you have the file example.csv as follows:

Source https://stackoverflow.com/questions/42108174

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

Vulnerabilities

No vulnerabilities reported

Install validify

This api has been carefully thought out over the past year. It's been in use on multiple React websites and React Native mobile applications. Using the library is simple. Include the Form component, and wrap your input's and submit buttons. Add useField to your own inputs inside the Form wrapper. This allows you to use the library with any type of input field. It just needs to support a handleChange handleBlur and value prop. This is the Input component you see in the first example. Don't forget to pass the field name to the hook.