py-readability-metrics | 📗 Score text readability using a number of formulas
kandi X-RAY | py-readability-metrics Summary
kandi X-RAY | py-readability-metrics Summary
py-readability-metrics is a Python library. py-readability-metrics 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 py-readability-metrics' or download it from GitHub, PyPI.
Score text readability using a number of formulas: Flesch-Kincaid Grade Level, Gunning Fog, ARI, Dale Chall, SMOG, and more
Score text readability using a number of formulas: Flesch-Kincaid Grade Level, Gunning Fog, ARI, Dale Chall, SMOG, and more
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py-readability-metrics has a low active ecosystem.
It has 274 star(s) with 46 fork(s). There are 9 watchers for this library.
It had no major release in the last 12 months.
There are 9 open issues and 7 have been closed. On average issues are closed in 25 days. There are 6 open pull requests and 0 closed requests.
It has a neutral sentiment in the developer community.
The latest version of py-readability-metrics is 1.4.5
Quality
py-readability-metrics has 0 bugs and 0 code smells.
Security
py-readability-metrics has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.
py-readability-metrics code analysis shows 0 unresolved vulnerabilities.
There are 0 security hotspots that need review.
License
py-readability-metrics is licensed under the MIT License. This license is Permissive.
Permissive licenses have the least restrictions, and you can use them in most projects.
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py-readability-metrics releases are available to install and integrate.
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.
py-readability-metrics saves you 299 person hours of effort in developing the same functionality from scratch.
It has 721 lines of code, 105 functions and 22 files.
It has medium code complexity. Code complexity directly impacts maintainability of the code.
Top functions reviewed by kandi - BETA
kandi has reviewed py-readability-metrics and discovered the below as its top functions. This is intended to give you an instant insight into py-readability-metrics implemented functionality, and help decide if they suit your requirements.
- Calculate statistics for smog text
- Compute statistics for a given text
- Count word number
- Return a AnalyzerStatistics object
- Load a set of lines from the Dale - Chall report
- Load spache data
- Return True if token is a noun
- Calculate the score for the assessment
- Calculate the scoring score
- Return a list of grade levels
- Calculates the age of a given score
- Calculates the score of the score
- Calculates the similarity score
- Calculate the score of the score
- Calculate the score of a word
- Calculates the score for the object
- Calculate the score
- Computes the score for the score
- Calculate the similarity score
- Calculate the score for the object
Get all kandi verified functions for this library.
py-readability-metrics Key Features
No Key Features are available at this moment for py-readability-metrics.
py-readability-metrics Examples and Code Snippets
No Code Snippets are available at this moment for py-readability-metrics.
Community Discussions
No Community Discussions are available at this moment for py-readability-metrics.Refer to stack overflow page for discussions.
Community Discussions, Code Snippets contain sources that include Stack Exchange Network
Vulnerabilities
No vulnerabilities reported
Install py-readability-metrics
You can install using 'pip install py-readability-metrics' or download it from GitHub, PyPI.
You can use py-readability-metrics 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.
You can use py-readability-metrics 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
Flesch Kincaid Grade LevelFlesch Reading EaseDale Chall ReadabilityAutomated Readability Index (ARI)Coleman Liau IndexGunning FogSMOGSpacheLinsear Write
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