How to Install and Uninstall python39-scspell3k Package on openSuSE Tumbleweed

Information for package python39-scspell3k:
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Repository : openSUSE-Tumbleweed-Oss
Name : python39-scspell3k
Version : 2.2-4.20
Arch : noarch
Vendor : openSUSE
Installed Size : 1.0 MiB
Installed : No
Status : not installed
Source package : python-scspell3k-2.2-4.20.src
Upstream URL : https://github.com/myint/scspell
Summary : A conservative interactive spell checker for source code
Description :
Scspell is a spell checker for source code. This is an unofficial fork (of
https://launchpad.net/scspell) that runs on both Python 2 and 3.
Scspell does not try to be particularly smart--rather, it does the simplest
thing that can possibly work:
1. All alphanumeric strings (strings of letters, numbers, and
underscores) are spell-checked tokens.
2. Each token is split into one or more subtokens. Underscores and digits
always divide tokens, and capital letters will begin new subtokens. In
other words, ``some_variable`` and ``someVariable`` will both generate
the subtoken list {``some``, ``variable``}.
3. All subtokens longer than three characters are matched against a set of
dictionaries, and a match failure prompts the user for action. When
matching against the included English dictionary, *prefix matching* is
employed; this choice permits the use of truncated words like ``dict``
as valid subtokens.
When applied to code written in most popular programming languages while using
typical naming conventions, this algorithm will usually catch many errors
without an annoying false positive rate.
In an effort to catch more spelling errors, Scspell is able to check each
file against a set of dictionary words selected *specifically for that file*. Up
to three different sub-dictionaries may be searched for any given file:
1. A natural language dictionary. (Scspell provides an American
English dictionary as the default.)
2. A programming language-specific dictionary, intended to contain
oddly-spelled keywords and APIs associated with that language.
(Scspell provides small default dictionaries for a number of popular
programming languages.)
3. A file-specific dictionary, intended to contain uncommon strings which
are not likely to be found in more than a handful of unique files.