Update the documentation comment
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//! This implements the core logic of the compression scheme used to compactly
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//! encode Unicode properties.
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//!
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//! We have two primary goals with the encoding: we want to be compact, because
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//! these tables often end up in ~every Rust program (especially the
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//! grapheme_extend table, used for str debugging), including those for embedded
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//! targets (where space is important). We also want to be relatively fast,
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//! though this is more of a nice to have rather than a key design constraint.
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//! It is expected that libraries/applications which are performance-sensitive
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//! to Unicode property lookups are extremely rare, and those that care may find
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//! the tradeoff of the raw bitsets worth it. For most applications, a
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//! relatively fast but much smaller (and as such less cache-impacting, etc.)
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//! data set is likely preferable.
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//!
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//! We have two separate encoding schemes: a skiplist-like approach, and a
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//! compressed bitset. The datasets we consider mostly use the skiplist (it's
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//! smaller) but the lowercase and uppercase sets are sufficiently sparse for
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//! the bitset to be worthwhile -- for those sets the biset is a 2x size win.
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//! Since the bitset is also faster, this seems an obvious choice. (As a
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//! historical note, the bitset was also the prior implementation, so its
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//! relative complexity had already been paid).
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//!
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//! ## The bitset
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//!
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//! The primary idea is that we 'flatten' the Unicode ranges into an enormous
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//! bitset. To represent any arbitrary codepoint in a raw bitset, we would need
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//! over 17 kilobytes of data per character set -- way too much for our
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//! purposes.
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//!
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//! First, the raw bitset (one bit for every valid `char`, from 0 to 0x10FFFF,
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//! not skipping the small 'gap') is associated into words (u64) and
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//! deduplicated. On random data, this would be useless; on our data, this is
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//! incredibly beneficial -- our data sets have (far) less than 256 unique
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//! words.
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//!
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//! This gives us an array that maps `u8 -> word`; the current algorithm does
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//! not handle the case of more than 256 unique words, but we are relatively far
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//! from coming that close.
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//!
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//! With that scheme, we now have a single byte for every 64 codepoints.
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//!
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//! We further chunk these by some constant N (between 1 and 64 per group,
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//! dynamically chosen for smallest size), and again deduplicate and store in an
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//! array (u8 -> [u8; N]).
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//!
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//! The bytes of this array map into the words from the bitset above, but we
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//! apply another trick here: some of these words are similar enough that they
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//! can be represented by some function of another word. The particular
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//! functions chosen are rotation, inversion, and shifting (right).
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//!
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//! ## The skiplist
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//!
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//! The skip list arose out of the desire for an even smaller encoding than the
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//! bitset -- and was the answer to the question "what is the smallest
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//! representation we can imagine?". However, it is not necessarily the
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//! smallest, and if you have a better proposal, please do suggest it!
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//!
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//! This is a relatively straightforward encoding. First, we break up all the
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//! ranges in the input data into offsets from each other, essentially a gap
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//! encoding. In practice, most gaps are small -- less than u8::MAX -- so we
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//! store those directly. We make use of the larger gaps (which are nicely
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//! interspersed already) throughout the dataset to index this data set.
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//!
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//! In particular, each run of small gaps (terminating in a large gap) is
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//! indexed in a separate dataset. That data set stores an index into the
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//! primary offset list and a prefix sum of that offset list. These are packed
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//! into a single u32 (11 bits for the offset, 21 bits for the prefix sum).
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//!
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//! Lookup proceeds via a binary search in the index and then a straightforward
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//! linear scan (adding up the offsets) until we reach the needle, and then the
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//! index of that offset is utilized as the answer to whether we're in the set
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//! or not.
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use std::collections::{BTreeMap, HashMap};
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use std::ops::Range;
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use ucd_parse::Codepoints;
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@ -1,42 +1,3 @@
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//! This implements the core logic of the compression scheme used to compactly
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//! encode the Unicode character classes.
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//!
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//! The primary idea is that we 'flatten' the Unicode ranges into an enormous
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//! bitset. To represent any arbitrary codepoint in a raw bitset, we would need
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//! over 17 kilobytes of data per character set -- way too much for our
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//! purposes.
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//!
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//! We have two primary goals with the encoding: we want to be compact, because
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//! these tables often end up in ~every Rust program (especially the
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//! grapheme_extend table, used for str debugging), including those for embedded
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//! targets (where space is important). We also want to be relatively fast,
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//! though this is more of a nice to have rather than a key design constraint.
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//! In practice, due to modern processor design these two are closely related.
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//!
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//! The encoding scheme here compresses the bitset by first deduplicating the
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//! "words" (64 bits on all platforms). In practice very few words are present
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//! in most data sets.
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//!
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//! This gives us an array that maps `u8 -> word` (if we ever went beyond 256
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//! words, we could go to u16 -> word or have some dual compression scheme
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//! mapping into two separate sets; currently this is not dealt with).
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//!
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//! With that scheme, we now have a single byte for every 64 codepoints. We
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//! further group these by some constant N (between 1 and 64 per group), and
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//! again deduplicate and store in an array (u8 -> [u8; N]). The constant is
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//! chosen to be optimal in bytes-in-memory for the given dataset.
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//!
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//! The indices into this array represent ranges of 64*16 = 1024 codepoints.
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//!
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//! This already reduces the top-level array to at most 1,086 bytes, but in
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//! practice we usually can encode in far fewer (the first couple Unicode planes
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//! are dense).
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//!
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//! The last byte of this top-level array is pulled out to a separate static
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//! and trailing zeros are dropped; this is simply because grapheme_extend and
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//! case_ignorable have a single entry in the 896th entry, so this shrinks them
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//! down considerably.
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use crate::fmt_list;
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use std::collections::{BTreeMap, BTreeSet, HashMap};
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use std::convert::TryFrom;
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