Also add an apply_to_mentions attribute on Glitch::KeywordMute, which is
used to calculate scope. Next up: additions to the test suite to
demonstrate how scoping works.
=~ made sense when we were passing it through to a regex, but we're no
longer doing that: TagMatcher looks at individual tags and returns a
value that *looks* like what you get out of #=~ but really isn't that
meaningful. Probably a good idea to not subvert convention like this
and instead use a name with guessable intent.
It is reasonable to expect someone to enter #foo to mute hashtag #foo.
However, tags are recorded on statuses without the preceding #.
To adjust for this, we build a separate tag matcher and use
Tag::HASHTAG_RE to extract a hashtag from the hashtag syntax.
When given two regexps, Regexp.union preserves the options set (or not
set) on each regex; this meant that none of the multiline (m),
case-insensitivity (i), or extended syntax (x) options were set. Our
regexps are written expecting the m, i, and x options were set on all of
them, so we need to make sure that we preserve that behavior.
Ditto for ending with \b.
Consider muting the phrase "(hot take)". I stipulate it is reasonable
to enter this with the default "match whole word" behavior. Under the
old behavior, this would be encoded as
\b\(hot\ take\)\b
However, if \b is before the first character in the string and the first
character in the string is not a word character, then the match will
fail. Ditto for after. In our example, "(" is not a word character, so
this will not match statuses containing "(hot take)", and that's a very
surprising behavior.
To address this, we only add leading and trailing \b to keywords that
start or end with word characters.
There are two motivations for this:
1. It looks like we're going to add other features that require
server-side storage (e.g. user notes).
2. Namespacing glitchsoc modifications is a good idea anyway: even if we
do not end up doing (1), if upstream introduces a keyword-mute feature
that also uses a "KeywordMute" model, we can avoid some merge
conflicts this way and work on the more interesting task of
choosing which implementation to use.
Word-boundary matching only works as intended in English and languages
that use similar word-breaking characters; it doesn't work so well in
(say) Japanese, Chinese, or Thai. It's unacceptable to have a feature
that doesn't work as intended for some languages. (Moreso especially
considering that it's likely that the largest contingent on the Mastodon
bit of the fediverse speaks Japanese.)
There are rules specified in Unicode TR29[1] for word-breaking across
all languages supported by Unicode, but the rules deliberately do not
cover all cases. In fact, TR29 states
For example, reliable detection of word boundaries in languages such
as Thai, Lao, Chinese, or Japanese requires the use of dictionary
lookup, analogous to English hyphenation.
So we aren't going to be able to make word detection work with regexes
within Mastodon (or glitchsoc). However, for a first pass (even if it's
kind of punting) we can allow the user to choose whether they want word
or substring detection and warn about the limitations of this
implementation in, say, docs.
[1]: https://unicode.org/reports/tr29/https://web.archive.org/web/20171001005125/https://unicode.org/reports/tr29/
A matcher object that builds a match from KeywordMute data and runs it
over text is, in my view, one of the easier ways to write examples for
this sort of thing.
Gist of the proposed keyword mute implementation:
Keyword mutes are represented server-side as one keyword per record.
For each account, there exists a keyword regex that is generated as one
big alternation of all keywords. This regex is cached (in Redis, I
guess) so we can quickly get it when filtering in FeedManager.
David Yip
Sorin Davidoi