text-normalization | Text normalization or preprocessing for social media data | Natural Language Processing library

by yasirutomo Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | text-normalization Summary

text-normalization is a Python library typically used in Telecommunications, Media, Advertising, Marketing, Artificial Intelligence, Natural Language Processing applications. text-normalization has no bugs, it has no vulnerabilities and it has high support. However text-normalization build file is not available. You can download it from GitHub.

Text normalization or preprocessing for social media data

Support

Quality

Security

License

Reuse

Support

text-normalization has a highly active ecosystem.

It has 16 star(s) with 6 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 1 open issues and 0 have been closed. On average issues are closed in 1215 days. There are no pull requests.

It has a positive sentiment in the developer community.

The latest version of text-normalization is current.

Quality

text-normalization has 0 bugs and 0 code smells.

Security

text-normalization has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

text-normalization code analysis shows 0 unresolved vulnerabilities.

There are 0 security hotspots that need review.

License

text-normalization does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

text-normalization releases are not available. You will need to build from source code and install.

text-normalization has no build file. You will be need to create the build yourself to build the component from source.

Top functions reviewed by kandi - BETA

kandi has reviewed text-normalization and discovered the below as its top functions. This is intended to give you an instant insight into text-normalization implemented functionality, and help decide if they suit your requirements.

Normalize text
Tokenize a sentence
Normalize wordcale words
Spell normalize text
Replace characters in text
Normalize emoticons
Normalize links
Normalize space characters
Return the most probable spelling for a word
Return all edits that are one edit away
Return possible spelling corrections for a given word
Return all edits that are two edits
Return the set of known words
Return all words in text

Get all kandi verified functions for this library.

text-normalization Key Features

No Key Features are available at this moment for text-normalization.

text-normalization Examples and Code Snippets

No Code Snippets are available at this moment for text-normalization.

Community Discussions

Trending Discussions on text-normalization

when I click a project : 500 Whoops, something went wrong on our end

QUESTION

when I click a project : 500 Whoops, something went wrong on our end

Asked 2021-Oct-28 at 16:29

hellow every one i migrated gitlab-ce into a new instance with new domain name using backup/restore

my problem : when i click a project it gives me "500 Whoops, something went wrong on our end "

i installed the same gitlab-ce version in the new host which is 13.6.2

my gitlab status

...

ANSWER

Answered 2021-Oct-28 at 16:29

To fix this problem I had to migrate gitlab-secrets.json from /etc/gitlab too, because this file contains the database encryption key, CI/CD variables, and variables used for two-factor authentication.
If you fail to restore this encryption key file along with the application data backup, users with two-factor authentication enabled and GitLab Runner lose access to your GitLab server.

Source https://stackoverflow.com/questions/69525251

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

Vulnerabilities

No vulnerabilities reported

Install text-normalization

You can download it from GitHub.
You can use text-normalization like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

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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