mini.nvim/lua/mini/fuzzy.lua at main · 2KAbhishek/mini.nvim

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--- *mini.fuzzy* Fuzzy matching

---

--- Features:

--- - Minimal and fast fuzzy matching algorithm which prioritizes match width.

---

--- - Functions to for common fuzzy matching operations:

--- - |MiniFuzzy.match()|.

--- - |MiniFuzzy.filtersort()|.

--- - |MiniFuzzy.process_lsp_items()|.

---

--- - Generator of sorter (|MiniFuzzy.get_telescope_sorter()|) for

--- [nvim-telescope/telescope.nvim](https://github.com/nvim-telescope/telescope.nvim)

---

--- # Setup ~

---

--- This module doesn't need setup, but it can be done to improve usability.

--- Setup with `require('mini.fuzzy').setup({})` (replace `{}` with your

--- `config` table). It will create global Lua table `MiniFuzzy` which you can

--- use for scripting or manually (with `:lua MiniFuzzy.*`).

---

--- See |MiniFuzzy.config| for `config` structure and default values.

---

--- You can override runtime config settings locally to buffer inside

--- `vim.b.minifuzzy_config` which should have same structure as

--- `MiniFuzzy.config`.

--- See |mini.nvim-buffer-local-config| for more details.

---

--- # Notes ~

---

--- 1. Currently there is no explicit design to work with multibyte symbols,

--- but simple examples should work.

--- 2. Smart case is used: case insensitive if input word (which is usually a

--- user input) is all lower case. Case sensitive otherwise.

---@tag MiniFuzzy

--- General design uses only width of found match and index of first letter

--- match. No special characters or positions (like in fzy and fzf) are used.

---

--- Given non-empty input `word` and target `candidate`:

--- - The goal is to find matching between `word`'s letters and letters in

--- `candidate` which minimizes certain score. It is assumed that order of

--- letters in `word` and those matched in `candidate` should be the same.

---

--- - Matching is represented by matched positions: an array `positions` of

--- integers with length equal to number of letters in `word`. The following

--- should be always true in case of a match: `candidate`'s letter at index

--- `positions[i]` is letters[i]` for all valid `i`.

---

--- - Matched positions are evaluated based only on two features: their width

--- (number of indexes between first and last positions) and first match

--- (index of first letter match). There is a global setting `cutoff` for

--- which all feature values greater than it can be considered "equally bad".

---

--- - Score of matched positions is computed with following explicit formula:

--- `cutoff * min(width, cutoff) + min(first, cutoff)`. It is designed to be

--- equivalent to first comparing widths (lower is better) and then comparing

--- first match (lower is better). For example, if `word = 'time'`:

--- - '_time' (width 4) will have a better match than 't_ime' (width 5).

--- - 'time_a' (width 4, first 1) will have a better match than 'a_time'

--- (width 4, first 3).

---

--- - Final matched positions are those which minimize score among all possible

--- matched positions of `word` and `candidate`.

---@tag MiniFuzzy-algorithm

-- Module definition ==========================================================

local MiniFuzzy = {}

local H = {}

--- Module setup

---

---@param config table|nil Module config table. See |MiniFuzzy.config|.

---

---@usage >lua

--- require('mini.fuzzy').setup() -- use default config

--- -- OR

--- require('mini.fuzzy').setup({}) -- replace {} with your config table

--- <

MiniFuzzy.setup = function(config)

-- TODO: Remove after Neovim=0.9 support is dropped

if vim.fn.has('nvim-0.10') == 0 then

vim.notify(

'(mini.fuzzy) Neovim<0.10 is soft deprecated (module works but is not supported).'

.. " It will be deprecated after the next 'mini.nvim' release (module might not work)."

.. ' Please update your Neovim version.'

)

end

-- Export module

_G.MiniFuzzy = MiniFuzzy

-- Setup config

config = H.setup_config(config)

-- Apply config

H.apply_config(config)

end

--- Defaults ~

---@eval return MiniDoc.afterlines_to_code(MiniDoc.current.eval_section)

MiniFuzzy.config = {

-- Maximum allowed value of match features (width and first match). All

-- feature values greater than cutoff can be considered "equally bad".

cutoff = 100,

}

--minidoc_afterlines_end

-- Module functionality =======================================================

--- Compute match data

---

---@param word string Input word (usually user input).

---@param candidate string Target word (usually with which matching is done).

---

---@return table Matching information:

--- - <positions> `(table|nil)` - array with letter indexes inside `candidate`

--- which matched to corresponding letters in `word`. It is empty array if

--- `word` is empty string and `nil` if no match.

--- - <score> `number` - positive number representing how good the match is

--- (lower is better). It is `-1` if no match or word is empty string.

MiniFuzzy.match = function(word, candidate)

-- Use 'smart case'

candidate = word == word:lower() and candidate:lower() or candidate

local positions = H.find_best_positions(H.string_to_letters(word), candidate)

return { positions = positions, score = H.score_positions(positions) }

end

--- Filter string array

---

--- - Keep only input elements which match `word`.

--- - Sort from best to worst matches (based on score and index in original

--- array, both lower is better).

---

---@param word string String which will be searched.

---@param candidate_array table Lua array of strings inside which word will be

--- searched.

---

---@return ... Arrays of matched candidates and their indexes in original input.

MiniFuzzy.filtersort = function(word, candidate_array)

-- Use 'smart case'. Create new array to preserve input for later filtering

local cand_array = word == word:lower() and vim.tbl_map(string.lower, candidate_array) or candidate_array

local filter_ids = H.make_filter_indexes(word, cand_array)

table.sort(filter_ids, H.compare_filter_indexes)

return H.filter_by_indexes(candidate_array, filter_ids)

end

--- Fuzzy matching for `lsp_completion.process_items` of |MiniCompletion.config|

---

---@param items table Array with LSP 'textDocument/completion' response items.

---@param base string Word to complete.

---

---@return table Array of items with text (`filterText` or `label`) fuzzy matching `base`.

MiniFuzzy.process_lsp_items = function(items, base)

local words = vim.tbl_map(function(x) return x.filterText or x.label end, items)

local _, match_inds = MiniFuzzy.filtersort(base, words)

return vim.tbl_map(function(i) return items[i] end, match_inds)

end

--- Custom getter for `telescope.nvim` sorter

---

--- Designed as a value for file and generic sorter of 'telescope.nvim'.

---

---@param opts table|nil Options (currently not used).

---

---@usage >lua

--- require('telescope').setup({

--- defaults = {

--- generic_sorter = require('mini.fuzzy').get_telescope_sorter

--- }

--- })

--- <

MiniFuzzy.get_telescope_sorter = function(opts)

opts = opts or {}

return require('telescope.sorters').Sorter:new({

start = function(self, prompt)

-- Cache prompt's letters

self.letters = H.string_to_letters(prompt)

-- Use 'smart case': insensitive if `prompt` is lowercase

self.case_sensitive = prompt ~= prompt:lower()

end,

-- @param self

-- @param prompt (which is the text on the line)

-- @param line (entry.ordinal)

-- @param entry (the whole entry)

scoring_function = function(self, _, line, _)

if #self.letters == 0 then return 1 end

line = self.case_sensitive and line or line:lower()

local positions = H.find_best_positions(self.letters, line)

return H.score_positions(positions)

end,

-- Currently there doesn't seem to be a proper way to cache matched

-- positions from inside of `scoring_function` (see `highlighter` code of

-- `get_fzy_sorter`'s output). Besides, it seems that `display` and `line`

-- arguments might be different. So, extra calls to `match` are made.

highlighter = function(self, _, display)

if #self.letters == 0 or #display == 0 then return {} end

display = self.case_sensitive and display or display:lower()

return H.find_best_positions(self.letters, display)

end,

})

end

-- Helper data ================================================================

-- Module default config

H.default_config = vim.deepcopy(MiniFuzzy.config)

-- Helper functionality =======================================================

-- Settings -------------------------------------------------------------------

H.setup_config = function(config)

H.check_type('config', config, 'table', true)

config = vim.tbl_deep_extend('force', vim.deepcopy(H.default_config), config or {})

if not (type(config.cutoff) == 'number' and config.cutoff >= 1) then

H.error('`cutoff` should be number not less than 1, not ' .. type(config.cutoff))

end

return config

end

H.apply_config = function(config) MiniFuzzy.config = config end

H.is_disabled = function() return vim.g.minifuzzy_disable == true or vim.b.minifuzzy_disable == true end

H.get_config = function(config)

return vim.tbl_deep_extend('force', MiniFuzzy.config, vim.b.minifuzzy_config or {}, config or {})

end

-- Fuzzy matching -------------------------------------------------------------

---@param letters table Array of letters from input word

---@param candidate string String of interest

---

---@return table|nil Table with matched positions (in `candidate`) if there is a

--- match, `nil` otherwise.

---@private

H.find_best_positions = function(letters, candidate)

local n_candidate, n_letters = #candidate, #letters

if n_letters == 0 then return {} end

if n_candidate < n_letters then return nil end

-- Search forward to find matching positions with left-most last letter match

local pos_last = 0

for let_i = 1, #letters do

pos_last = candidate:find(letters[let_i], pos_last + 1)

if not pos_last then break end

end

-- Candidate is matched only if word's last letter is found

if not pos_last then return nil end

-- If there is only one letter, it is already the best match (there will not

-- be better width and it has lowest first match)

if n_letters == 1 then return { pos_last } end

-- Compute best match positions by iteratively checking all possible last

-- letter matches (at and after initial one). At end of each iteration

-- `best_pos_last` holds best match for last letter among all previously

-- checked such matches.

local best_pos_last, best_width = pos_last, math.huge

local rev_candidate = candidate:reverse()

local cutoff = H.get_config().cutoff

while pos_last do

-- Simulate computing best match positions ending exactly at `pos_last` by

-- going backwards from current last letter match. This works because it

-- minimizes width which is the only way to find match with lower score.

-- Not actually creating table with positions and then directly computing

-- score increases speed by up to 40% (on small frequent input word with

-- relatively wide candidate, such as file paths of nested directories).

local rev_first = n_candidate - pos_last + 1

for i = #letters - 1, 1, -1 do

rev_first = rev_candidate:find(letters[i], rev_first + 1)

end

local first = n_candidate - rev_first + 1

local width = math.min(pos_last - first + 1, cutoff)

-- Using strict sign is crucial because when two last letter matches result

-- into positions with similar width, the one which was created earlier

-- (i.e. with smaller last letter match) will have smaller first letter

-- match (hence better score).

if width < best_width then

best_pos_last, best_width = pos_last, width

end

-- Advance iteration

pos_last = candidate:find(letters[n_letters], pos_last + 1)

end

-- Actually compute best matched positions from best last letter match

local best_positions = { best_pos_last }

local rev_pos = n_candidate - best_pos_last + 1

for i = #letters - 1, 1, -1 do

rev_pos = rev_candidate:find(letters[i], rev_pos + 1)

-- For relatively small number of letters (around 10, which is main use

-- case) inserting to front seems to have better performance than

-- inserting at end and then reversing.

table.insert(best_positions, 1, n_candidate - rev_pos + 1)

end

return best_positions

end

-- Compute score of matched positions. Smaller values indicate better match

-- (i.e. like distance). Reasoning behind the score is for it to produce the

-- same ordering as with sequential comparison of match's width and first

-- position. So it shouldn't really be perceived as linear distance (difference

-- between scores don't really matter, only their comparison with each other).

-- Reasoning behind comparison logic (based on 'time' input):

-- - '_time' is better than 't_ime' (width is smaller).

-- - 'time_aa' is better than 'aa_time' (same width, first match is smaller).

-- Returns -1 if `positions` is `nil` or empty.

H.score_positions = function(positions)

if positions == nil or #positions == 0 then return -1 end

local first, last = positions[1], positions[#positions]

local cutoff = H.get_config().cutoff

return cutoff * math.min(last - first + 1, cutoff) + math.min(first, cutoff)

end

H.make_filter_indexes = function(word, candidate_array)

local res, letters = {}, H.string_to_letters(word)

for i, cand in ipairs(candidate_array) do

local positions = H.find_best_positions(letters, cand)

if positions ~= nil then table.insert(res, { index = i, score = H.score_positions(positions) }) end

end

return res

end

H.compare_filter_indexes = function(a, b) return a.score < b.score or (a.score == b.score and a.index < b.index) end

H.filter_by_indexes = function(candidate_array, ids)

local res, res_ids = {}, {}

for _, id in pairs(ids) do

table.insert(res, candidate_array[id.index])

table.insert(res_ids, id.index)

end

return res, res_ids

end

-- Utilities ------------------------------------------------------------------

H.error = function(msg) error('(mini.fuzzy) ' .. msg, 0) end

H.check_type = function(name, val, ref, allow_nil)

if type(val) == ref or (ref == 'callable' and vim.is_callable(val)) or (allow_nil and val == nil) then return end

H.error(string.format('`%s` should be %s, not %s', name, ref, type(val)))

end

H.string_to_letters = function(s) return vim.tbl_map(vim.pesc, vim.split(s, '')) end

return MiniFuzzy

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