Calculates the time some text takes the average human to read, based on Medium's read time forumula


Keywords
blog, medium, python, read-time
License
BSD-3-Clause
Install
pip install readtime==1.1.1

Documentation

readtime

Tests Coverage

Calculates the time some text takes the average human to read, based on Medium's read time forumula.

Algorithm

Medium's Help Center says,

Read time is based on the average reading speed of an adult (roughly 265 WPM). We take the total word count of a post and translate it into minutes, with an adjustment made for images. For posts in Chinese, Japanese and Korean, it's a function of number of characters (500 characters/min) with an adjustment made for images.

Source: https://help.medium.com/hc/en-us/articles/214991667-Read-time (Read Sept 23rd, 2018)

Double checking with real articles, the English algorithm is:

seconds = num_words / 265 * 60 + img_weight * num_images

With img_weight starting at 12 and decreasing one second with each image encountered, with a minium img_weight of 3 seconds.

Installation

virtualenv venv
. venv/bin/activate
pip install readtime

Or if you like to live dangerously:

sudo pip install readtime

Usage

Import readtime and pass it some text, HTML, or Markdown to get back the time it takes to read:

>>> import readtime
>>> result = readtime.of_text('The shortest blog post in the world!')
>>> result.seconds
2
>>> result.text
u'1 min'

The result can also be used as a string:

>>> str(readtime.of_text('The shortest blog post in the world!'))
u'1 min read'

To calculate read time of Markdown:

>>> readtime.of_markdown('This is **Markdown**')
1 min read

To calculate read time of HTML:

>>> readtime.of_html('This is <strong>HTML</strong>')
1 min read

To customize the WPM (default 265):

>>> result = readtime.of_text('The shortest blog post in the world!', wpm=5)
>>> result.seconds
96
>>> result.text
u'2 min'
>>> result.wpm
5

Contributing

Before contributing a pull request, make sure tests pass:

virtualenv venv
. venv/bin/activate
pip install tox
tox

Many thanks to all contributors!