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Copyright (C) 2007 Canonical Ltd
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This program is free software; you can redistribute it and/or modify
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it under the terms of the GNU General Public License as published by
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the Free Software Foundation; either version 2 of the License, or
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(at your option) any later version.
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This program is distributed in the hope that it will be useful,
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but WITHOUT ANY WARRANTY; without even the implied warranty of
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MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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GNU General Public License for more details.
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You should have received a copy of the GNU General Public License
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along with this program; if not, write to the Free Software
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Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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Function equate_lines based on bdiff.c from Mercurial.
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Copyright (C) 2005, 2006 Matt Mackall <mpm@selenic.com>
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Functions unique_lcs/recurse_matches based on _patiencediff_py.py.
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Copyright (C) 2005 Bram Cohen, Copyright (C) 2005, 2006 Canonical Ltd
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/* http://www.python.org/dev/peps/pep-0353/ */
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#if PY_VERSION_HEX < 0x02050000 && !defined(PY_SSIZE_T_MIN)
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typedef int Py_ssize_t;
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#define PY_SSIZE_T_MAX INT_MAX
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#define PY_SSIZE_T_MIN INT_MIN
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# define inline __inline__
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#elif defined(_MSC_VER)
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# define inline __inline
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#define MIN(a, b) (((a) > (b)) ? (b) : (a))
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#define MAX(a, b) (((a) > (b)) ? (a) : (b))
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/* values from this array need to correspont to the order of the enum above */
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static char *opcode_names[] = {
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long hash; /* hash code of the string/object */
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Py_ssize_t next; /* next line from the same equivalence class */
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Py_ssize_t equiv; /* equivalence class */
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Py_ssize_t a_head; /* first item in `a` from this equivalence class */
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Py_ssize_t b_head; /* first item in `b` from this equivalence class */
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Py_ssize_t last_a_pos;
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Py_ssize_t last_b_pos;
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struct matching_line {
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Py_ssize_t a; /* index of the line in `a` */
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Py_ssize_t b; /* index of the line in `b` */
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struct matching_block {
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Py_ssize_t a; /* index of the first line in `a` */
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Py_ssize_t b; /* index of the first line in `b` */
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Py_ssize_t len; /* length of the block */
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struct matching_blocks {
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struct matching_block *matches;
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struct hashtable hashtable;
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Py_ssize_t *backpointers;
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} PatienceSequenceMatcher;
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static inline Py_ssize_t
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bisect_left(Py_ssize_t *list, Py_ssize_t item, Py_ssize_t lo, Py_ssize_t hi)
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Py_ssize_t mid = lo / 2 + hi / 2 + (lo % 2 + hi % 2) / 2;
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if (list[mid] < item)
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compare_lines(struct line *a, struct line *b)
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return ((a->hash != b->hash)
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|| PyObject_Compare(a->data, b->data));
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find_equivalence_class(struct bucket *hashtable, Py_ssize_t hsize,
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struct line *lines, struct line *ref_lines,
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for (j = lines[i].hash & hsize; hashtable[j].b_head != SENTINEL; j = (j + 1) & hsize) {
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if (!compare_lines(lines + i, ref_lines + hashtable[j].b_head)) {
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equate_lines(struct hashtable *result,
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struct line *lines_a, struct line *lines_b,
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Py_ssize_t asize, Py_ssize_t bsize)
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Py_ssize_t i, j, hsize;
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struct bucket *hashtable;
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/* check for overflow, we need the table to be at least bsize+1 */
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if (bsize == PY_SSIZE_T_MAX) {
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PyErr_SetNone(PyExc_OverflowError);
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/* build a hash table of the next highest power of 2 */
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while (hsize < bsize + 1)
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hashtable = (struct bucket *)malloc(sizeof(struct bucket) * hsize);
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if (hashtable == NULL) {
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/* initialise the hashtable */
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for (i = 0; i < hsize; i++) {
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hashtable[i].a_count = 0;
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hashtable[i].b_count = 0;
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hashtable[i].a_head = SENTINEL;
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hashtable[i].b_head = SENTINEL;
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/* add lines from lines_b to the hash table chains. iterating
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backwards so the matching lines are sorted to the linked list
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by the line number (because we are adding new lines to the
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for (i = bsize - 1; i >= 0; i--) {
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/* find the first hashtable entry, which is either empty or contains
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the same line as lines_b[i] */
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j = find_equivalence_class(hashtable, hsize, lines_b, lines_b, i);
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/* set the equivalence class */
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lines_b[i].equiv = j;
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/* add to the head of the equivalence class */
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lines_b[i].next = hashtable[j].b_head;
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hashtable[j].b_head = i;
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hashtable[j].b_count++;
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/* match items from lines_a to their equivalence class in lines_b.
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again, iterating backwards for the right order of the linked lists */
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for (i = asize - 1; i >= 0; i--) {
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/* find the first hash entry, which is either empty or contains
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the same line as lines_a[i] */
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j = find_equivalence_class(hashtable, hsize, lines_a, lines_b, i);
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/* set the equivalence class, even if we are not interested in this
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line, because the values are not pre-filled */
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lines_a[i].equiv = j;
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/* we are not interested in lines which are not also in lines_b */
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if (hashtable[j].b_head == SENTINEL)
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/* add to the head of the equivalence class */
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lines_a[i].next = hashtable[j].a_head;
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hashtable[j].a_head = i;
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hashtable[j].a_count++;
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result->last_a_pos = -1;
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result->last_b_pos = -1;
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result->size = hsize + 1;
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result->table = hashtable;
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/* Finds longest common subsequence of unique lines in a[alo:ahi] and
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Parameter backpointers must have allocated memory for at least
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4 * (bhi - blo) ints. */
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unique_lcs(struct matching_line *answer,
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struct hashtable *hashtable, Py_ssize_t *backpointers,
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struct line *lines_a, struct line *lines_b,
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Py_ssize_t alo, Py_ssize_t blo, Py_ssize_t ahi, Py_ssize_t bhi)
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Py_ssize_t i, k, equiv, apos, bpos, norm_apos, norm_bpos, bsize, stacksize;
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Py_ssize_t *stacks, *lasts, *btoa;
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h = hashtable->table;
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/* "unpack" the allocated memory */
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stacks = backpointers + bsize;
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lasts = stacks + bsize;
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btoa = lasts + bsize;
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/* initialise the backpointers */
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for (i = 0; i < bsize; i++)
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backpointers[i] = SENTINEL;
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if (hashtable->last_a_pos == -1 || hashtable->last_a_pos > alo)
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for (i = 0; i < hashtable->size; i++)
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h[i].a_pos = h[i].a_head;
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hashtable->last_a_pos = alo;
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if (hashtable->last_b_pos == -1 || hashtable->last_b_pos > blo)
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for (i = 0; i < hashtable->size; i++)
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h[i].b_pos = h[i].b_head;
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hashtable->last_b_pos = blo;
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for (bpos = blo; bpos < bhi; bpos++) {
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equiv = lines_b[bpos].equiv;
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/* no lines in a or b */
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if (h[equiv].a_count == 0 || h[equiv].b_count == 0)
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/* find an unique line in lines_a that matches lines_b[bpos]
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if we find more than one line within the range alo:ahi,
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jump to the next line from lines_b immediately */
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/* loop through all lines in the linked list */
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for (i = h[equiv].a_pos; i != SENTINEL; i = lines_a[i].next) {
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/* the index is lower than alo, the the next line */
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/* the index is higher than ahi, stop searching */
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/* if the line is within our range, check if it's a duplicate */
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if (apos != SENTINEL)
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/* save index to the line */
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/* this line has no equivalent in lines_a[alo:ahi] */
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if (apos == SENTINEL)
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/* check for duplicates of this line in lines_b[blo:bhi] */
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/* loop through all lines in the linked list */
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for (i = h[equiv].b_pos; i != SENTINEL; i = lines_b[i].next) {
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/* the index is lower than blo, the the next line */
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/* the index is higher than bhi, stop searching */
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/* if this isn't the line with started with and it's within
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our range, it's a duplicate */
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/* use normalised indexes ([0,ahi-alo) instead of [alo,ahi))
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for the patience sorting algorithm */
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norm_bpos = bpos - blo;
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norm_apos = apos - alo;
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btoa[norm_bpos] = norm_apos;
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Ok, how does this work...
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We have a list of matching lines from two lists, a and b. These
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matches are stored in variable `btoa`. As we are iterating over this
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table by bpos, the lines from b already form an increasing sequence.
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We need to "sort" also the lines from a using the patience sorting
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algorithm, ignoring the lines which would need to be swapped.
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http://en.wikipedia.org/wiki/Patience_sorting
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For each pair of lines, we need to place the line from a on either
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an existing pile that has higher value on the top or create a new
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pile. Variable `stacks` represents the tops of these piles and in
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variable `lasts` we store the lines from b, that correspond to the
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lines from a in `stacks`.
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Whenever we place a new line on top of a pile, we store a
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backpointer to the line (b) from top of the previous pile. This means
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that after the loop, variable `backpointers` will contain an index
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to the previous matching lines that forms an increasing sequence
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(over both indexes a and b) with the current matching lines. If
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either index a or b of the previous matching lines would be higher
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than indexes of the current one or if the indexes of the current
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one are 0, it will contain SENTINEL.
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To construct the LCS, we will just need to follow these backpointers
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from the top of the last pile and stop when we reach SENTINEL.
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/* as an optimization, check if the next line comes at the end,
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because it usually does */
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if (stacksize && stacks[stacksize - 1] < norm_apos)
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/* as an optimization, check if the next line comes right after
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the previous line, because usually it does */
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else if (stacksize && (stacks[k] < norm_apos) &&
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(k == stacksize - 1 || stacks[k + 1] > norm_apos))
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k = bisect_left(stacks, norm_apos, 0, stacksize);
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backpointers[norm_bpos] = lasts[k - 1];
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stacks[k] = norm_apos;
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lasts[k] = norm_bpos;
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stacks[stacksize] = norm_apos;
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lasts[stacksize] = norm_bpos;
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/* backtrace the structures to find the LCS */
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k = lasts[stacksize - 1];
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while (k != SENTINEL) {
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answer[i].a = btoa[k];
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/* Adds a new line to the list of matching blocks, either extending the
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current block or adding a new one. */
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add_matching_line(struct matching_blocks *answer, Py_ssize_t a, Py_ssize_t b)
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Py_ssize_t last_index = answer->count - 1;
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if ((last_index >= 0) &&
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(a == answer->matches[last_index].a +
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answer->matches[last_index].len) &&
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(b == answer->matches[last_index].b +
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answer->matches[last_index].len)) {
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/* enlarge the last block */
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answer->matches[last_index].len++;
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/* create a new block */
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answer->matches[last_index].a = a;
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answer->matches[last_index].b = b;
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answer->matches[last_index].len = 1;
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recurse_matches(struct matching_blocks *answer, struct hashtable *hashtable,
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Py_ssize_t *backpointers, struct line *a, struct line *b,
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Py_ssize_t alo, Py_ssize_t blo, Py_ssize_t ahi, Py_ssize_t bhi,
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Py_ssize_t new, last_a_pos, last_b_pos, lcs_size, nahi, nbhi, i, apos, bpos;
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struct matching_line *lcs;
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if (maxrecursion < 0)
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if (alo == ahi || blo == bhi)
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last_a_pos = alo - 1;
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last_b_pos = blo - 1;
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lcs = (struct matching_line *)malloc(sizeof(struct matching_line) * (bhi - blo));
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lcs_size = unique_lcs(lcs, hashtable, backpointers, a, b, alo, blo, ahi, bhi);
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/* recurse between lines which are unique in each file and match */
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for (i = lcs_size - 1; i >= 0; i--) {
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apos = alo + lcs[i].a;
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bpos = blo + lcs[i].b;
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if (last_a_pos + 1 != apos || last_b_pos + 1 != bpos) {
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res = recurse_matches(answer, hashtable,
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last_a_pos + 1, last_b_pos + 1,
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apos, bpos, maxrecursion - 1);
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add_matching_line(answer, apos, bpos);
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/* find matches between the last match and the end */
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res = recurse_matches(answer, hashtable,
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last_a_pos + 1, last_b_pos + 1,
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ahi, bhi, maxrecursion - 1);
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/* find matching lines at the very beginning */
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else if (a[alo].equiv == b[blo].equiv) {
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while (alo < ahi && blo < bhi && a[alo].equiv == b[blo].equiv)
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add_matching_line(answer, alo++, blo++);
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res = recurse_matches(answer, hashtable,
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alo, blo, ahi, bhi, maxrecursion - 1);
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/* find matching lines at the very end */
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else if (a[ahi - 1].equiv == b[bhi - 1].equiv) {
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while (nahi > alo && nbhi > blo && a[nahi - 1].equiv == b[nbhi - 1].equiv) {
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res = recurse_matches(answer, hashtable,
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last_a_pos + 1, last_b_pos + 1,
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nahi, nbhi, maxrecursion - 1);
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for (i = 0; i < ahi - nahi; i++)
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add_matching_line(answer, nahi + i, nbhi + i);
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load_lines(PyObject *orig, struct line **lines)
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PyObject *seq, *item;
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seq = PySequence_Fast(orig, "sequence expected");
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size = PySequence_Fast_GET_SIZE(seq);
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line = *lines = (struct line *)malloc(sizeof(struct line) * size);
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for (i = 0; i < size; i++) {
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item = PySequence_Fast_GET_ITEM(seq, i);
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line->hash = PyObject_Hash(item);
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if (line->hash == (-1)) {
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/* Propogate the hash exception */
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line->next = SENTINEL;
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py_unique_lcs(PyObject *self, PyObject *args)
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PyObject *aseq, *bseq, *res, *item;
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Py_ssize_t asize, bsize, i, nmatches, *backpointers = NULL;
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struct line *a = NULL, *b = NULL;
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struct matching_line *matches = NULL;
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struct hashtable hashtable;
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if (!PyArg_ParseTuple(args, "OO", &aseq, &bseq))
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hashtable.table = NULL;
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asize = load_lines(aseq, &a);
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bsize = load_lines(bseq, &b);
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if (asize == -1 || bsize == -1)
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if (!equate_lines(&hashtable, a, b, asize, bsize))
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matches = (struct matching_line *)malloc(sizeof(struct matching_line) * bsize);
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backpointers = (Py_ssize_t *)malloc(sizeof(Py_ssize_t) * bsize * 4);
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if (backpointers == NULL)
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nmatches = unique_lcs(matches, &hashtable, backpointers, a, b, 0, 0, asize, bsize);
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res = PyList_New(nmatches);
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for (i = 0; i < nmatches; i++) {
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#if PY_VERSION_HEX < 0x02050000
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item = Py_BuildValue("ii", matches[nmatches - i - 1].a, matches[nmatches - i - 1].b);
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item = Py_BuildValue("nn", matches[nmatches - i - 1].a, matches[nmatches - i - 1].b);
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if (PyList_SetItem(res, i, item) != 0)
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free(hashtable.table);
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free(hashtable.table);
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py_recurse_matches(PyObject *self, PyObject *args)
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PyObject *aseq, *bseq, *item, *answer;
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int maxrecursion, res;
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Py_ssize_t i, j, asize, bsize, alo, blo, ahi, bhi;
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Py_ssize_t *backpointers = NULL;
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struct line *a = NULL, *b = NULL;
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struct hashtable hashtable;
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struct matching_blocks matches;
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#if PY_VERSION_HEX < 0x02050000
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if (!PyArg_ParseTuple(args, "OOiiiiOi", &aseq, &bseq, &alo, &blo,
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&ahi, &bhi, &answer, &maxrecursion))
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if (!PyArg_ParseTuple(args, "OOnnnnOi", &aseq, &bseq, &alo, &blo,
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&ahi, &bhi, &answer, &maxrecursion))
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hashtable.table = NULL;
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matches.matches = NULL;
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asize = load_lines(aseq, &a);
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bsize = load_lines(bseq, &b);
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if (asize == -1 || bsize == -1)
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if (!equate_lines(&hashtable, a, b, asize, bsize))
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matches.matches = (struct matching_block *)malloc(sizeof(struct matching_block) * bsize);
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if (matches.matches == NULL)
686
backpointers = (Py_ssize_t *)malloc(sizeof(Py_ssize_t) * bsize * 4);
687
if (backpointers == NULL)
690
res = recurse_matches(&matches, &hashtable, backpointers,
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a, b, alo, blo, ahi, bhi, maxrecursion);
695
for (i = 0; i < matches.count; i++) {
696
for (j = 0; j < matches.matches[i].len; j++) {
697
#if PY_VERSION_HEX < 0x02050000
698
item = Py_BuildValue("ii", matches.matches[i].a + j,
699
matches.matches[i].b + j);
701
item = Py_BuildValue("nn", matches.matches[i].a + j,
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matches.matches[i].b + j);
706
if (PyList_Append(answer, item) != 0)
712
free(matches.matches);
713
free(hashtable.table);
720
free(matches.matches);
721
free(hashtable.table);
729
PatienceSequenceMatcher_new(PyTypeObject *type, PyObject *args, PyObject *kwds)
731
PyObject *junk, *a, *b;
732
PatienceSequenceMatcher *self;
734
self = (PatienceSequenceMatcher *)type->tp_alloc(type, 0);
737
if (!PyArg_ParseTuple(args, "OOO", &junk, &a, &b)) {
742
self->asize = load_lines(a, &(self->a));
743
self->bsize = load_lines(b, &(self->b));
745
if (self->asize == -1 || self->bsize == -1) {
750
if (!equate_lines(&self->hashtable, self->a, self->b, self->asize, self->bsize)) {
755
self->backpointers = (Py_ssize_t *)malloc(sizeof(Py_ssize_t) * self->bsize * 4);
756
if (self->backpointers == NULL) {
763
return (PyObject *)self;
768
PatienceSequenceMatcher_dealloc(PatienceSequenceMatcher* self)
770
free(self->backpointers);
771
free(self->hashtable.table);
774
self->ob_type->tp_free((PyObject *)self);
778
static char PatienceSequenceMatcher_get_matching_blocks_doc[] =
779
"Return list of triples describing matching subsequences.\n"
781
"Each triple is of the form (i, j, n), and means that\n"
782
"a[i:i+n] == b[j:j+n]. The triples are monotonically increasing in\n"
785
"The last triple is a dummy, (len(a), len(b), 0), and is the only\n"
786
"triple with n==0.\n"
788
">>> s = PatienceSequenceMatcher(None, \"abxcd\", \"abcd\")\n"
789
">>> s.get_matching_blocks()\n"
790
"[(0, 0, 2), (3, 2, 2), (5, 4, 0)]\n";
793
PatienceSequenceMatcher_get_matching_blocks(PatienceSequenceMatcher* self)
795
PyObject *answer, *item;
798
struct matching_blocks matches;
801
matches.matches = (struct matching_block *)malloc(sizeof(struct matching_block) * self->bsize);
802
if (matches.matches == NULL)
803
return PyErr_NoMemory();
805
res = recurse_matches(&matches, &self->hashtable, self->backpointers,
806
self->a, self->b, 0, 0,
807
self->asize, self->bsize, 10);
809
free(matches.matches);
810
return PyErr_NoMemory();
813
answer = PyList_New(matches.count + 1);
814
if (answer == NULL) {
815
free(matches.matches);
819
for (i = 0; i < matches.count; i++) {
820
#if PY_VERSION_HEX < 0x02050000
821
item = Py_BuildValue("iii", matches.matches[i].a,
822
matches.matches[i].b, matches.matches[i].len);
824
item = Py_BuildValue("nnn", matches.matches[i].a,
825
matches.matches[i].b, matches.matches[i].len);
829
if (PyList_SetItem(answer, i, item) != 0)
832
#if PY_VERSION_HEX < 0x02050000
833
item = Py_BuildValue("iii", self->asize, self->bsize, 0);
835
item = Py_BuildValue("nnn", self->asize, self->bsize, 0);
839
if (PyList_SetItem(answer, i, item) != 0)
842
free(matches.matches);
846
free(matches.matches);
852
static char PatienceSequenceMatcher_get_opcodes_doc[] =
853
"Return list of 5-tuples describing how to turn a into b.\n"
855
"Each tuple is of the form (tag, i1, i2, j1, j2). The first tuple\n"
856
"has i1 == j1 == 0, and remaining tuples have i1 == the i2 from the\n"
857
"tuple preceding it, and likewise for j1 == the previous j2.\n"
859
"The tags are strings, with these meanings:\n"
861
"'replace': a[i1:i2] should be replaced by b[j1:j2]\n"
862
"'delete': a[i1:i2] should be deleted.\n"
863
" Note that j1==j2 in this case.\n"
864
"'insert': b[j1:j2] should be inserted at a[i1:i1].\n"
865
" Note that i1==i2 in this case.\n"
866
"'equal': a[i1:i2] == b[j1:j2]\n"
868
">>> a = \"qabxcd\"\n"
869
">>> b = \"abycdf\"\n"
870
">>> s = PatienceSequenceMatcher(None, a, b)\n"
871
">>> for tag, i1, i2, j1, j2 in s.get_opcodes():\n"
872
"... print (\"%7s a[%d:%d] (%s) b[%d:%d] (%s)\" %\n"
873
"... (tag, i1, i2, a[i1:i2], j1, j2, b[j1:j2]))\n"
874
" delete a[0:1] (q) b[0:0] ()\n"
875
" equal a[1:3] (ab) b[0:2] (ab)\n"
876
"replace a[3:4] (x) b[2:3] (y)\n"
877
" equal a[4:6] (cd) b[3:5] (cd)\n"
878
" insert a[6:6] () b[5:6] (f)\n";
881
PatienceSequenceMatcher_get_opcodes(PatienceSequenceMatcher* self)
883
PyObject *answer, *item;
884
Py_ssize_t i, j, k, ai, bj;
886
struct matching_blocks matches;
889
matches.matches = (struct matching_block *)malloc(sizeof(struct matching_block) * (self->bsize + 1));
890
if (matches.matches == NULL)
891
return PyErr_NoMemory();
893
res = recurse_matches(&matches, &self->hashtable, self->backpointers,
894
self->a, self->b, 0, 0,
895
self->asize, self->bsize, 10);
897
free(matches.matches);
898
return PyErr_NoMemory();
901
matches.matches[matches.count].a = self->asize;
902
matches.matches[matches.count].b = self->bsize;
903
matches.matches[matches.count].len = 0;
906
answer = PyList_New(0);
907
if (answer == NULL) {
908
free(matches.matches);
913
for (k = 0; k < matches.count; k++) {
914
ai = matches.matches[k].a;
915
bj = matches.matches[k].b;
918
if (i < ai && j < bj)
926
#if PY_VERSION_HEX < 0x02050000
927
item = Py_BuildValue("siiii", opcode_names[tag], i, ai, j, bj);
929
item = Py_BuildValue("snnnn", opcode_names[tag], i, ai, j, bj);
933
if (PyList_Append(answer, item) != 0)
937
i = ai + matches.matches[k].len;
938
j = bj + matches.matches[k].len;
940
if (matches.matches[k].len > 0) {
941
#if PY_VERSION_HEX < 0x02050000
942
item = Py_BuildValue("siiii", opcode_names[OP_EQUAL], ai, i, bj, j);
944
item = Py_BuildValue("snnnn", opcode_names[OP_EQUAL], ai, i, bj, j);
948
if (PyList_Append(answer, item) != 0)
953
free(matches.matches);
957
free(matches.matches);
963
static char PatienceSequenceMatcher_get_grouped_opcodes_doc[] =
964
"Isolate change clusters by eliminating ranges with no changes.\n"
966
"Return a list of groups with upto n lines of context.\n"
967
"Each group is in the same format as returned by get_opcodes().\n"
969
">>> from pprint import pprint\n"
970
">>> a = map(str, range(1,40))\n"
972
">>> b[8:8] = ['i'] # Make an insertion\n"
973
">>> b[20] += 'x' # Make a replacement\n"
974
">>> b[23:28] = [] # Make a deletion\n"
975
">>> b[30] += 'y' # Make another replacement\n"
976
">>> pprint(PatienceSequenceMatcher(None,a,b).get_grouped_opcodes())\n"
977
"[[('equal', 5, 8, 5, 8), ('insert', 8, 8, 8, 9), ('equal', 8, 11, 9, 12)],\n"
978
" [('equal', 16, 19, 17, 20),\n"
979
" ('replace', 19, 20, 20, 21),\n"
980
" ('equal', 20, 22, 21, 23),\n"
981
" ('delete', 22, 27, 23, 23),\n"
982
" ('equal', 27, 30, 23, 26)],\n"
983
" [('equal', 31, 34, 27, 30),\n"
984
" ('replace', 34, 35, 30, 31),\n"
985
" ('equal', 35, 38, 31, 34)]]\n";
988
PatienceSequenceMatcher_get_grouped_opcodes(PatienceSequenceMatcher* self,
991
PyObject *answer, *group, *item;
992
Py_ssize_t i, j, k, ai, bj, size, ncodes, tag;
993
Py_ssize_t i1, i2, j1, j2;
995
struct matching_blocks matches;
996
struct opcode *codes;
998
if (!PyArg_ParseTuple(args, "|i", &n))
1002
matches.matches = (struct matching_block *)malloc(sizeof(struct matching_block) * (self->bsize + 1));
1003
if (matches.matches == NULL)
1004
return PyErr_NoMemory();
1006
res = recurse_matches(&matches, &self->hashtable, self->backpointers,
1007
self->a, self->b, 0, 0,
1008
self->asize, self->bsize, 10);
1010
free(matches.matches);
1011
return PyErr_NoMemory();
1014
matches.matches[matches.count].a = self->asize;
1015
matches.matches[matches.count].b = self->bsize;
1016
matches.matches[matches.count].len = 0;
1020
codes = (struct opcode *)malloc(sizeof(struct opcode) * matches.count * 2);
1021
if (codes == NULL) {
1022
free(matches.matches);
1023
return PyErr_NoMemory();
1027
for (k = 0; k < matches.count; k++) {
1028
ai = matches.matches[k].a;
1029
bj = matches.matches[k].b;
1032
if (i < ai && j < bj)
1040
codes[ncodes].tag = tag;
1041
codes[ncodes].i1 = i;
1042
codes[ncodes].i2 = ai;
1043
codes[ncodes].j1 = j;
1044
codes[ncodes].j2 = bj;
1048
i = ai + matches.matches[k].len;
1049
j = bj + matches.matches[k].len;
1051
if (matches.matches[k].len > 0) {
1052
codes[ncodes].tag = OP_EQUAL;
1053
codes[ncodes].i1 = ai;
1054
codes[ncodes].i2 = i;
1055
codes[ncodes].j1 = bj;
1056
codes[ncodes].j2 = j;
1062
codes[ncodes].tag = OP_EQUAL;
1063
codes[ncodes].i1 = 0;
1064
codes[ncodes].i2 = 1;
1065
codes[ncodes].j1 = 0;
1066
codes[ncodes].j2 = 1;
1070
/* fixup leading and trailing groups if they show no changes. */
1071
if (codes[0].tag == OP_EQUAL) {
1072
codes[0].i1 = MAX(codes[0].i1, codes[0].i2 - n);
1073
codes[0].j1 = MAX(codes[0].j1, codes[0].j2 - n);
1075
if (codes[ncodes - 1].tag == OP_EQUAL) {
1076
codes[ncodes - 1].i2 = MIN(codes[ncodes - 1].i2,
1077
codes[ncodes - 1].i1 + n);
1078
codes[ncodes - 1].j2 = MIN(codes[ncodes - 1].j2,
1079
codes[ncodes - 1].j1 + n);
1084
answer = PyList_New(0);
1088
group = PyList_New(0);
1094
for (i = 0; i < ncodes; i++) {
1100
/* end the current group and start a new one whenever
1101
there is a large range with no changes. */
1102
if (tag == OP_EQUAL && i2 - i1 > nn) {
1103
#if PY_VERSION_HEX < 0x02050000
1104
item = Py_BuildValue("siiii", opcode_names[tag],
1105
i1, MIN(i2, i1 + n), j1, MIN(j2, j1 + n));
1107
item = Py_BuildValue("snnnn", opcode_names[tag],
1108
i1, MIN(i2, i1 + n), j1, MIN(j2, j1 + n));
1112
if (PyList_Append(group, item) != 0)
1114
if (PyList_Append(answer, group) != 0)
1116
group = PyList_New(0);
1119
i1 = MAX(i1, i2 - n);
1120
j1 = MAX(j1, j2 - n);
1122
#if PY_VERSION_HEX < 0x02050000
1123
item = Py_BuildValue("siiii", opcode_names[tag], i1, i2, j1 ,j2);
1125
item = Py_BuildValue("snnnn", opcode_names[tag], i1, i2, j1 ,j2);
1129
if (PyList_Append(group, item) != 0)
1132
size = PyList_Size(group);
1133
if (size > 0 && !(size == 1 && tag == OP_EQUAL)) {
1134
if (PyList_Append(answer, group) != 0)
1141
free(matches.matches);
1146
free(matches.matches);
1153
static PyMethodDef PatienceSequenceMatcher_methods[] = {
1154
{"get_matching_blocks",
1155
(PyCFunction)PatienceSequenceMatcher_get_matching_blocks,
1157
PatienceSequenceMatcher_get_matching_blocks_doc},
1159
(PyCFunction)PatienceSequenceMatcher_get_opcodes,
1161
PatienceSequenceMatcher_get_opcodes_doc},
1162
{"get_grouped_opcodes",
1163
(PyCFunction)PatienceSequenceMatcher_get_grouped_opcodes,
1165
PatienceSequenceMatcher_get_grouped_opcodes_doc},
1170
static char PatienceSequenceMatcher_doc[] =
1171
"C implementation of PatienceSequenceMatcher";
1174
static PyTypeObject PatienceSequenceMatcherType = {
1175
PyObject_HEAD_INIT(NULL)
1177
"PatienceSequenceMatcher", /* tp_name */
1178
sizeof(PatienceSequenceMatcher), /* tp_basicsize */
1179
0, /* tp_itemsize */
1180
(destructor)PatienceSequenceMatcher_dealloc, /* tp_dealloc */
1186
0, /* tp_as_number */
1187
0, /* tp_as_sequence */
1188
0, /* tp_as_mapping */
1192
0, /* tp_getattro */
1193
0, /* tp_setattro */
1194
0, /* tp_as_buffer */
1195
Py_TPFLAGS_DEFAULT, /* tp_flags*/
1196
PatienceSequenceMatcher_doc, /* tp_doc */
1197
0, /* tp_traverse */
1199
0, /* tp_richcompare */
1200
0, /* tp_weaklistoffset */
1202
0, /* tp_iternext */
1203
PatienceSequenceMatcher_methods, /* tp_methods */
1208
0, /* tp_descr_get */
1209
0, /* tp_descr_set */
1210
0, /* tp_dictoffset */
1213
PatienceSequenceMatcher_new, /* tp_new */
1217
static PyMethodDef cpatiencediff_methods[] = {
1218
{"unique_lcs_c", py_unique_lcs, METH_VARARGS},
1219
{"recurse_matches_c", py_recurse_matches, METH_VARARGS},
1225
init_patiencediff_c(void)
1229
if (PyType_Ready(&PatienceSequenceMatcherType) < 0)
1232
m = Py_InitModule3("_patiencediff_c", cpatiencediff_methods,
1233
"C implementation of PatienceSequenceMatcher");
1237
Py_INCREF(&PatienceSequenceMatcherType);
1238
PyModule_AddObject(m, "PatienceSequenceMatcher_c",
1239
(PyObject *)&PatienceSequenceMatcherType);
added
removed
bzrlib/_patiencediff_c.c
