Package Health Score

77 / 100

security
Security review needed
popularity
Influential project
maintenance
Healthy
community
Sustainable

Popularity

Influential project

GitHub Stars: 1.15K
Forks: 165
Contributors: 40

Direct Usage Popularity

Based on project statistics from the GitHub repository for the PyPI package textstat, we found that it has been starred 1,147 times.

Security

Security review needed

Security and license risk for latest version

Release Date: Jul 17, 2024
Direct Vulnerabilities: 0
C
0
H
0
M
0
L
Indirect Vulnerabilities: 0
C
0
H
0
M
0
L
License Risk: 1
H
0
M
0
L

All security vulnerabilities belong to production dependencies of direct and indirect packages.

License

MIT

Security Policy

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Maintenance

Healthy

Commit Frequency

Open Issues: 21
Open PR: 0
Last Release: 4 months ago
Last Commit: 6 months ago

Further analysis of the maintenance status of textstat based on released PyPI versions cadence, the repository activity, and other data points determined that its maintenance is Healthy.

We found that textstat demonstrates a positive version release cadence with at least one new version released in the past 12 months.

In the past month we didn't find any pull request activity or change in issues status has been detected for the GitHub repository.

Community

Sustainable

Readme: Yes
Contributing.md: No
Code of Conduct: Yes
Contributors: 40
Funding: No

With more than 10 contributors for the textstat repository, this is possibly a sign for a growing and inviting community.

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Package

Python Versions Compatibility: >=3.6

Age: 10 years
Latest Release: 4 months ago
Dependencies: 2 Direct / 2 Total
Versions: 27
Maintainers: 2
Wheels: OS Independent

Not sure how to use textstat?

To help you get started, we've collected the most common ways that textstat is being used within popular public projects.

AWegnerGitHub / SE_Zephyr_VoteRequest_bot / utils / utils.py View on Github

num_letters = sum(1 for c in no_code_text if c.isalpha())
    num_numbers = sum(1 for c in no_code_text if c.isdigit())
    num_alphanum = sum(1 for c in no_code_text if c.isalnum())
    num_otherchars = num_chars - num_alphanum
    results.append(TextFeature('Number of characters', num_chars, group_by))
    results.append(TextFeature('Number of letters', num_letters, group_by))
    results.append(TextFeature('Number of numbers', num_numbers, group_by))
    results.append(TextFeature('Number of other characters', num_otherchars, group_by))
    character_counts = Counter(no_code_text.lower())
    for c in sorted(character_counts.items()):
        try:
            results.append(TextFeature('Character count for "{}"'.format(c[0].encode('unicode_escape')), c[1], group_by))
        except AttributeError:
            results.append(TextFeature('Character count for "{}"'.format(c[0]), c[1], group_by))

    results.append(TextFeature('Number of syllables', textstat.syllable_count(no_code_text), group_by))
    results.append(TextFeature('Lexicon Count (without punctuation)', textstat.lexicon_count(no_code_text, True), group_by))
    results.append(TextFeature('Lexicon Count (with punctuation)', textstat.lexicon_count(no_code_text, False), group_by))
    results.append(TextFeature('Number of lower case characters', num_lower, group_by))
    results.append(TextFeature('Number of upper case characters', num_upper, group_by))
    return results

View more ways to use textstat

Textstat

Textstat is an easy to use library to calculate statistics from text. It helps determine readability, complexity, and grade level.

^{Photo by Patrick Tomasso
on Unsplash}

Usage

&gt;&gt;&gt; import textstat

&gt;&gt;&gt; test_data = (
    "Playing games has always been thought to be important to "
    "the development of well-balanced and creative children; "
    "however, what part, if any, they should play in the lives "
    "of adults has never been researched that deeply. I believe "
    "that playing games is every bit as important for adults "
    "as for children. Not only is taking time out to play games "
    "with our children and other adults valuable to building "
    "interpersonal relationships but is also a wonderful way "
    "to release built up tension."
)

&gt;&gt;&gt; textstat.flesch_reading_ease(test_data)
&gt;&gt;&gt; textstat.flesch_kincaid_grade(test_data)
&gt;&gt;&gt; textstat.smog_index(test_data)
&gt;&gt;&gt; textstat.coleman_liau_index(test_data)
&gt;&gt;&gt; textstat.automated_readability_index(test_data)
&gt;&gt;&gt; textstat.dale_chall_readability_score(test_data)
&gt;&gt;&gt; textstat.difficult_words(test_data)
&gt;&gt;&gt; textstat.linsear_write_formula(test_data)
&gt;&gt;&gt; textstat.gunning_fog(test_data)
&gt;&gt;&gt; textstat.text_standard(test_data)
&gt;&gt;&gt; textstat.fernandez_huerta(test_data)
&gt;&gt;&gt; textstat.szigriszt_pazos(test_data)
&gt;&gt;&gt; textstat.gutierrez_polini(test_data)
&gt;&gt;&gt; textstat.crawford(test_data)
&gt;&gt;&gt; textstat.gulpease_index(test_data)
&gt;&gt;&gt; textstat.osman(test_data)

The argument (text) for all the defined functions remains the same - i.e the text for which statistics need to be calculated.

Install

You can install textstat either via the Python Package Index (PyPI) or from source.

Install using pip

pip install textstat

Install using easy_install

easy_install textstat

Install latest version from GitHub

git clone https://github.com/shivam5992/textstat.git
cd textstat
pip install .

Install from PyPI

Download the latest version of textstat from http://pypi.python.org/pypi/textstat/

You can install it by doing the following:

tar xfz textstat-*.tar.gz
cd textstat-*/
python setup.py build
python setup.py install # as root

Language support

By default functions implement algorithms for english language. To change language, use:

textstat.set_lang(lang)

The language will be used for syllable calculation and to choose variant of the formula.

Language variants

All functions implement en_US language. Some of them has also variants for other languages listed below.

Function	en	de	es	fr	it	nl	pl	ru
flesch_reading_ease	✔	✔	✔	✔	✔	✔		✔
gunning_fog	✔						✔

Spanish-specific tests

The following functions are specifically designed for spanish language. They can be used on non-spanish texts, even though that use case is not recommended.

&gt;&gt;&gt; textstat.fernandez_huerta(test_data)
&gt;&gt;&gt; textstat.szigriszt_pazos(test_data)
&gt;&gt;&gt; textstat.gutierrez_polini(test_data)
&gt;&gt;&gt; textstat.crawford(test_data)

Additional information on the formula they implement can be found in their respective docstrings.

List of Functions

Formulas

The Flesch Reading Ease formula

textstat.flesch_reading_ease(text)

Returns the Flesch Reading Ease Score.

The following table can be helpful to assess the ease of readability in a document.

The table is an example of values. While the maximum score is 121.22, there is no limit on how low the score can be. A negative score is valid.

Score	Difficulty
90-100	Very Easy
80-89	Easy
70-79	Fairly Easy
60-69	Standard
50-59	Fairly Difficult
30-49	Difficult
0-29	Very Confusing

> Further reading on Wikipedia

The Flesch-Kincaid Grade Level

textstat.flesch_kincaid_grade(text)

Returns the Flesch-Kincaid Grade of the given text. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

> Further reading on Wikipedia

The Fog Scale (Gunning FOG Formula)

textstat.gunning_fog(text)

Returns the FOG index of the given text. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

> Further reading on Wikipedia

The SMOG Index

textstat.smog_index(text)

Returns the SMOG index of the given text. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

Texts of fewer than 30 sentences are statistically invalid, because the SMOG formula was normed on 30-sentence samples. textstat requires at least 3 sentences for a result.

> Further reading on Wikipedia

Automated Readability Index

textstat.automated_readability_index(text)

Returns the ARI (Automated Readability Index) which outputs a number that approximates the grade level needed to comprehend the text.

For example if the ARI is 6.5, then the grade level to comprehend the text is 6th to 7th grade.

> Further reading on Wikipedia

The Coleman-Liau Index

textstat.coleman_liau_index(text)

Returns the grade level of the text using the Coleman-Liau Formula. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

> Further reading on Wikipedia

Linsear Write Formula

textstat.linsear_write_formula(text)

Returns the grade level using the Linsear Write Formula. This is a grade formula in that a score of 9.3 means that a ninth grader would be able to read the document.

> Further reading on Wikipedia

Dale-Chall Readability Score

textstat.dale_chall_readability_score(text)

Different from other tests, since it uses a lookup table of the most commonly used 3000 English words. Thus it returns the grade level using the New Dale-Chall Formula.

Score	Understood by
4.9 or lower	average 4th-grade student or lower
5.0–5.9	average 5th or 6th-grade student
6.0–6.9	average 7th or 8th-grade student
7.0–7.9	average 9th or 10th-grade student
8.0–8.9	average 11th or 12th-grade student
9.0–9.9	average 13th to 15th-grade (college) student

> Further reading on Wikipedia

Readability Consensus based upon all the above tests

textstat.text_standard(text, float_output=False)

Based upon all the above tests, returns the estimated school grade level required to understand the text.

Optional float_output allows the score to be returned as a float. Defaults to False.

Spache Readability Formula

textstat.spache_readability(text)

Returns grade level of english text.

Intended for text written for children up to grade four.

> Further reading on Wikipedia

McAlpine EFLAW Readability Score

textstat.mcalpine_eflaw(text)

Returns a score for the readability of an english text for a foreign learner or English, focusing on the number of miniwords and length of sentences.

It is recommended to aim for a score equal to or lower than 25.

> Further reading on This blog post

Reading Time

textstat.reading_time(text, ms_per_char=14.69)

Returns the reading time of the given text.

Assumes 14.69ms per character.

> Further reading in This academic paper

Language Specific Formulas

Índice de lecturabilidad Fernandez-Huerta (Spanish)

textstat.fernandez_huerta(text)

Reformulation of the Flesch Reading Ease Formula specifically for spanish. The results can be interpreted similarly

> Further reading on This blog post

Índice de perspicuidad de Szigriszt-Pazos (Spanish)

textstat.szigriszt_pazos(text)

Adaptation of Flesch Reading Ease formula for spanish-based texts.

Attempts to quantify how understandable a text is.

> Further reading on This blog post

Fórmula de comprensibilidad de Gutiérrez de Polini (Spanish)

textstat.gutierrez_polini(text)

Returns the Guttiérrez de Polini understandability index.

Specifically designed for the texts in spanish, not an adaptation. Conceived for grade-school level texts.

Scores for more complex text are not reliable.

> Further reading on This blog post

Fórmula de Crawford (Spanish)

textstat.crawford(text)

Returns the Crawford score for the text.

Returns an estimate of the years of schooling required to understand the text.

The text is only valid for elementary school level texts.

> Further reading on This blog post

Osman (Arabic)

textstat.osman(text)

Returns OSMAN score for text.

Designed for Arabic, an adaption of Flesch and Fog Formula. Introduces a new factor called "Faseeh".

> Further reading in This academic paper

Gulpease Index (Italian)

textstat.gulpease_index(text)

Returns the Gulpease index of Italian text, which translates to level of education completed.

Lower scores require higher level of education to read with ease.

> Further reading on Wikipedia

Wiener Sachtextformel (German)

textstat.wiener_sachtextformel(text, variant)

Returns a grade level score for the given text.

A value of 4 means very easy text, whereas 15 means very difficult text.

> Further reading on Wikipedia

Aggregates and Averages

Syllable Count

textstat.syllable_count(text)

Returns the number of syllables present in the given text.

Uses the Python module Pyphen for syllable calculation.

Lexicon Count

textstat.lexicon_count(text, removepunct=True)

Calculates the number of words present in the text. Optional removepunct specifies whether we need to take punctuation symbols into account while counting lexicons. Default value is True, which removes the punctuation before counting lexicon items.

Sentence Count

textstat.sentence_count(text)

Returns the number of sentences present in the given text.

Character Count

textstat.char_count(text, ignore_spaces=True)

Returns the number of characters present in the given text.

Letter Count

textstat.letter_count(text, ignore_spaces=True)

Returns the number of characters present in the given text without punctuation.

Polysyllable Count

textstat.polysyllabcount(text)

Returns the number of words with a syllable count greater than or equal to 3.

Monosyllable Count

textstat.monosyllabcount(text)

Returns the number of words with a syllable count equal to one.

Contributing

If you find any problems, you should open an issue.

If you can fix an issue you've found, or another issue, you should open a pull request.

Fork this repository on GitHub to start making your changes to the master branch (or branch off of it).
Write a test which shows that the bug was fixed or that the feature works as expected.
Send a pull request!

Development setup

> It is recommended you use a virtual environment, or Pipenv to keep your development work isolated from your systems Python installation.

$ git clone https://github.com//textstat.git  # Clone the repo from your fork
$ cd textstat
$ pip install -r requirements.txt  # Install all dependencies

$ # Make changes

$ python -m pytest test.py  # Run tests

textstat dependencies

pyphen setuptools

FAQs

What is textstat?

Calculate statistical features from text. Visit Snyk Advisor to see a full health score report for textstat, including popularity, security, maintenance & community analysis.

Is textstat popular?

The python package textstat receives a total of 117,568 weekly downloads. As such, textstat popularity was classified as an influential project. Visit the popularity section on Snyk Advisor to see the full health analysis.

Is textstat well maintained?

We found that textstat demonstrated a healthy version release cadence and project activity. It has a community of 40 open source contributors collaborating on the project. See the full package health analysis to learn more about the package maintenance status.

Is textstat safe to use?

While scanning the latest version of textstat, we found that a security review is needed. A total of 0 vulnerabilities or license issues were detected. See the full security scan results.

Last updated on 22 November-2024, at 16:59 (UTC).

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Package Health Score

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Commit Frequency

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Not sure how to use textstat?

Textstat

Usage

Install

Install using pip

Install using easy_install

Install latest version from GitHub

Install from PyPI

Language support

Language variants

Spanish-specific tests

List of Functions

Formulas

The Flesch Reading Ease formula

The Flesch-Kincaid Grade Level

The Fog Scale (Gunning FOG Formula)

The SMOG Index

Automated Readability Index

The Coleman-Liau Index

Linsear Write Formula

Dale-Chall Readability Score

Readability Consensus based upon all the above tests

Spache Readability Formula

McAlpine EFLAW Readability Score

Reading Time

Language Specific Formulas

Índice de lecturabilidad Fernandez-Huerta (Spanish)

Índice de perspicuidad de Szigriszt-Pazos (Spanish)

Fórmula de comprensibilidad de Gutiérrez de Polini (Spanish)

Fórmula de Crawford (Spanish)

Osman (Arabic)

Gulpease Index (Italian)

Wiener Sachtextformel (German)

Aggregates and Averages

Syllable Count

Lexicon Count

Sentence Count

Character Count

Letter Count

Polysyllable Count

Monosyllable Count

Contributing

Development setup

textstat dependencies

FAQs

What is textstat?

Is textstat popular?

Is textstat well maintained?

Is textstat safe to use?

Build a secure application checklist

Select a recommended open source package

Scan your app for vulnerabilities

Source Code

Open Source

Container

Config

Fix identified vulnerabilities

Monitor for new issues