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grammar: introduce new grammar package
This package provides a way to convert JSON schemas to equivalent EBNF. It is intended to be a replacement to llama.cpp's schema_to_grammar. This is still an early version and does not yet support all JSON schema features. The to-do list includes: - minumum/maximum constraints on integer types - minLength/maxLength constraints on string types - defs and refs
This commit is contained in:
Blake Mizerany
261
grammar/internal/diff/diff.go
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261
grammar/internal/diff/diff.go
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@@ -0,0 +1,261 @@
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// Copyright 2022 The Go Authors. All rights reserved.
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// Use of this source code is governed by a BSD-style
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// license that can be found in the LICENSE file.
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package diff
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import (
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"bytes"
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"fmt"
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"sort"
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"strings"
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)
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// A pair is a pair of values tracked for both the x and y side of a diff.
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// It is typically a pair of line indexes.
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type pair struct{ x, y int }
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// Diff returns an anchored diff of the two texts old and new
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// in the “unified diff” format. If old and new are identical,
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// Diff returns a nil slice (no output).
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//
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// Unix diff implementations typically look for a diff with
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// the smallest number of lines inserted and removed,
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// which can in the worst case take time quadratic in the
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// number of lines in the texts. As a result, many implementations
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// either can be made to run for a long time or cut off the search
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// after a predetermined amount of work.
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//
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// In contrast, this implementation looks for a diff with the
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// smallest number of “unique” lines inserted and removed,
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// where unique means a line that appears just once in both old and new.
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// We call this an “anchored diff” because the unique lines anchor
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// the chosen matching regions. An anchored diff is usually clearer
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// than a standard diff, because the algorithm does not try to
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// reuse unrelated blank lines or closing braces.
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// The algorithm also guarantees to run in O(n log n) time
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// instead of the standard O(n²) time.
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//
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// Some systems call this approach a “patience diff,” named for
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// the “patience sorting” algorithm, itself named for a solitaire card game.
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// We avoid that name for two reasons. First, the name has been used
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// for a few different variants of the algorithm, so it is imprecise.
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// Second, the name is frequently interpreted as meaning that you have
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// to wait longer (to be patient) for the diff, meaning that it is a slower algorithm,
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// when in fact the algorithm is faster than the standard one.
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func Diff(oldName string, old []byte, newName string, new []byte) []byte {
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if bytes.Equal(old, new) {
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return nil
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}
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x := lines(old)
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y := lines(new)
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// Print diff header.
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var out bytes.Buffer
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fmt.Fprintf(&out, "diff %s %s\n", oldName, newName)
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fmt.Fprintf(&out, "--- %s\n", oldName)
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fmt.Fprintf(&out, "+++ %s\n", newName)
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// Loop over matches to consider,
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// expanding each match to include surrounding lines,
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// and then printing diff chunks.
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// To avoid setup/teardown cases outside the loop,
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// tgs returns a leading {0,0} and trailing {len(x), len(y)} pair
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// in the sequence of matches.
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var (
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done pair // printed up to x[:done.x] and y[:done.y]
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chunk pair // start lines of current chunk
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count pair // number of lines from each side in current chunk
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ctext []string // lines for current chunk
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)
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for _, m := range tgs(x, y) {
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if m.x < done.x {
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// Already handled scanning forward from earlier match.
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continue
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}
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// Expand matching lines as far as possible,
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// establishing that x[start.x:end.x] == y[start.y:end.y].
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// Note that on the first (or last) iteration we may (or definitely do)
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// have an empty match: start.x==end.x and start.y==end.y.
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start := m
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for start.x > done.x && start.y > done.y && x[start.x-1] == y[start.y-1] {
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start.x--
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start.y--
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}
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end := m
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for end.x < len(x) && end.y < len(y) && x[end.x] == y[end.y] {
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end.x++
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end.y++
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}
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// Emit the mismatched lines before start into this chunk.
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// (No effect on first sentinel iteration, when start = {0,0}.)
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for _, s := range x[done.x:start.x] {
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ctext = append(ctext, "-"+s)
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count.x++
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}
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for _, s := range y[done.y:start.y] {
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ctext = append(ctext, "+"+s)
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count.y++
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}
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// If we're not at EOF and have too few common lines,
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// the chunk includes all the common lines and continues.
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const C = 3 // number of context lines
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if (end.x < len(x) || end.y < len(y)) &&
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(end.x-start.x < C || (len(ctext) > 0 && end.x-start.x < 2*C)) {
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for _, s := range x[start.x:end.x] {
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ctext = append(ctext, " "+s)
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count.x++
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count.y++
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}
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done = end
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continue
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}
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// End chunk with common lines for context.
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if len(ctext) > 0 {
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n := end.x - start.x
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if n > C {
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n = C
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}
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for _, s := range x[start.x : start.x+n] {
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ctext = append(ctext, " "+s)
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count.x++
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count.y++
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}
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done = pair{start.x + n, start.y + n}
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// Format and emit chunk.
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// Convert line numbers to 1-indexed.
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// Special case: empty file shows up as 0,0 not 1,0.
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if count.x > 0 {
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chunk.x++
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}
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if count.y > 0 {
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chunk.y++
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}
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fmt.Fprintf(&out, "@@ -%d,%d +%d,%d @@\n", chunk.x, count.x, chunk.y, count.y)
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for _, s := range ctext {
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out.WriteString(s)
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}
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count.x = 0
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count.y = 0
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ctext = ctext[:0]
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}
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// If we reached EOF, we're done.
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if end.x >= len(x) && end.y >= len(y) {
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break
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}
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// Otherwise start a new chunk.
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chunk = pair{end.x - C, end.y - C}
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for _, s := range x[chunk.x:end.x] {
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ctext = append(ctext, " "+s)
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count.x++
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count.y++
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}
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done = end
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}
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return out.Bytes()
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}
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// lines returns the lines in the file x, including newlines.
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// If the file does not end in a newline, one is supplied
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// along with a warning about the missing newline.
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func lines(x []byte) []string {
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l := strings.SplitAfter(string(x), "\n")
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if l[len(l)-1] == "" {
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l = l[:len(l)-1]
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} else {
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// Treat last line as having a message about the missing newline attached,
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// using the same text as BSD/GNU diff (including the leading backslash).
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l[len(l)-1] += "\n\\ No newline at end of file\n"
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}
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return l
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}
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// tgs returns the pairs of indexes of the longest common subsequence
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// of unique lines in x and y, where a unique line is one that appears
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// once in x and once in y.
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//
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// The longest common subsequence algorithm is as described in
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// Thomas G. Szymanski, “A Special Case of the Maximal Common
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// Subsequence Problem,” Princeton TR #170 (January 1975),
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// available at https://research.swtch.com/tgs170.pdf.
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func tgs(x, y []string) []pair {
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// Count the number of times each string appears in a and b.
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// We only care about 0, 1, many, counted as 0, -1, -2
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// for the x side and 0, -4, -8 for the y side.
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// Using negative numbers now lets us distinguish positive line numbers later.
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m := make(map[string]int)
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for _, s := range x {
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if c := m[s]; c > -2 {
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m[s] = c - 1
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}
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}
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for _, s := range y {
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if c := m[s]; c > -8 {
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m[s] = c - 4
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}
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}
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// Now unique strings can be identified by m[s] = -1+-4.
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//
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// Gather the indexes of those strings in x and y, building:
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// xi[i] = increasing indexes of unique strings in x.
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// yi[i] = increasing indexes of unique strings in y.
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// inv[i] = index j such that x[xi[i]] = y[yi[j]].
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var xi, yi, inv []int
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for i, s := range y {
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if m[s] == -1+-4 {
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m[s] = len(yi)
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yi = append(yi, i)
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}
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}
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for i, s := range x {
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if j, ok := m[s]; ok && j >= 0 {
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xi = append(xi, i)
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inv = append(inv, j)
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}
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}
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// Apply Algorithm A from Szymanski's paper.
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// In those terms, A = J = inv and B = [0, n).
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// We add sentinel pairs {0,0}, and {len(x),len(y)}
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// to the returned sequence, to help the processing loop.
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J := inv
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n := len(xi)
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T := make([]int, n)
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L := make([]int, n)
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for i := range T {
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T[i] = n + 1
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}
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for i := range n {
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k := sort.Search(n, func(k int) bool {
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return T[k] >= J[i]
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})
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T[k] = J[i]
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L[i] = k + 1
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}
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k := 0
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for _, v := range L {
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if k < v {
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k = v
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}
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}
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seq := make([]pair, 2+k)
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seq[1+k] = pair{len(x), len(y)} // sentinel at end
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lastj := n
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for i := n - 1; i >= 0; i-- {
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if L[i] == k && J[i] < lastj {
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seq[k] = pair{xi[i], yi[J[i]]}
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k--
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}
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}
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seq[0] = pair{0, 0} // sentinel at start
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return seq
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}
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