cn-text-normalizer | python module that convert chinese written string

 by   open-speech Python Version: Current License: MIT

kandi X-RAY | cn-text-normalizer Summary

kandi X-RAY | cn-text-normalizer Summary

cn-text-normalizer is a Python library. cn-text-normalizer has no bugs, it has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. You can install using 'pip install cn-text-normalizer' or download it from GitHub, PyPI.

A python module that convert chinese written string to read string. 一个python包:将中文书面字符串转换为口语字符串。
Support
    Quality
      Security
        License
          Reuse

            kandi-support Support

              cn-text-normalizer has a low active ecosystem.
              It has 108 star(s) with 32 fork(s). There are 5 watchers for this library.
              OutlinedDot
              It had no major release in the last 6 months.
              There are 2 open issues and 0 have been closed. On average issues are closed in 410 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of cn-text-normalizer is current.

            kandi-Quality Quality

              cn-text-normalizer has 0 bugs and 0 code smells.

            kandi-Security Security

              cn-text-normalizer has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
              cn-text-normalizer code analysis shows 0 unresolved vulnerabilities.
              There are 0 security hotspots that need review.

            kandi-License License

              cn-text-normalizer is licensed under the MIT License. This license is Permissive.
              Permissive licenses have the least restrictions, and you can use them in most projects.

            kandi-Reuse Reuse

              cn-text-normalizer releases are not available. You will need to build from source code and install.
              Deployable package is available in PyPI.
              Build file is available. You can build the component from source.
              Installation instructions are not available. Examples and code snippets are available.
              cn-text-normalizer saves you 139 person hours of effort in developing the same functionality from scratch.
              It has 347 lines of code, 23 functions and 4 files.
              It has high code complexity. Code complexity directly impacts maintainability of the code.

            Top functions reviewed by kandi - BETA

            kandi has reviewed cn-text-normalizer and discovered the below as its top functions. This is intended to give you an instant insight into cn-text-normalizer implemented functionality, and help decide if they suit your requirements.
            • Convert a string to a string
            • Convert num_str to CN
            • Convert a num_str to a CN number
            • Convert a cn to a number
            • Read the README md file
            Get all kandi verified functions for this library.

            cn-text-normalizer Key Features

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

            cn-text-normalizer Examples and Code Snippets

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

            Community Discussions

            No Community Discussions are available at this moment for cn-text-normalizer.Refer to stack overflow page for discussions.

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

            Vulnerabilities

            No vulnerabilities reported

            Install cn-text-normalizer

            You can install using 'pip install cn-text-normalizer' or download it from GitHub, PyPI.
            You can use cn-text-normalizer 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 .
            Find more information at:

            Find, review, and download reusable Libraries, Code Snippets, Cloud APIs from over 650 million Knowledge Items

            Find more libraries
            CLONE
          • HTTPS

            https://github.com/open-speech/cn-text-normalizer.git

          • CLI

            gh repo clone open-speech/cn-text-normalizer

          • sshUrl

            git@github.com:open-speech/cn-text-normalizer.git

          • Stay Updated

            Subscribe to our newsletter for trending solutions and developer bootcamps

            Agree to Sign up and Terms & Conditions

            Share this Page

            share link