diff --git a/NLTK_LICENSE.txt b/NLTK_LICENSE.txt
new file mode 100644
index 0000000..a3d8514
--- /dev/null
+++ b/NLTK_LICENSE.txt
@@ -0,0 +1,205 @@
+This is a copy of the license of the nltk project (), as is required under section 4. Redistribution.
+It is particularly relevant for 'mods/core/modules/modmenu_search.py', and for any other instances of nltk code in this project.
+
+
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+
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\ No newline at end of file
diff --git a/mods/core/download_mods.rpy b/mods/core/download_mods.rpy
index 8cc6714..76cf370 100644
--- a/mods/core/download_mods.rpy
+++ b/mods/core/download_mods.rpy
@@ -153,6 +153,46 @@ init python:
modconfig.steam_modlist_preloader.load()
+ import modmenu_search
+ import time
+
+ def set_query(value):
+ curr_screen_scope = renpy.current_screen().scope
+ curr_screen_scope["query"] = value
+ search_modlist(value, curr_screen_scope["author_query"])
+ return
+
+ def set_author_query(value):
+ curr_screen_scope = renpy.current_screen().scope
+ curr_screen_scope["author_query"] = value
+ search_modlist(curr_screen_scope["query"], value)
+ return
+
+
+ def search_modlist(query, author_query=""):
+ print "searching with {}, {}".format(query, author_query)
+
+ # As renpy input doesn't allow for additional variables to this method, I've had to resort to this cursed thing
+ curr_screen_scope = renpy.current_screen().scope
+ modlist = curr_screen_scope["contents"]
+ page = curr_screen_scope["current_page"]
+ page_size = curr_screen_scope["PAGE_SIZE"]
+ use_steam = curr_screen_scope["use_steam"]
+
+ s_time = time.time()
+ if query.strip() or author_query.strip(): # There's no reason to reorder the modlist if no search has been done.
+ reordered_modlist = modmenu_search.sort_best(query, modlist, author_query=author_query)
+ else:
+ reordered_modlist = curr_screen_scope["contents"]
+ print "Search took: {:.5}".format(time.time() - s_time) # Hopefully this never goes above 0.3
+
+ curr_screen_scope["search_order_contents"] = reordered_modlist
+ _refresh_modlist_page(page, page_size, reordered_modlist, use_steam)
+ renpy.restart_interaction()
+
+ return
+
+
init -1 python:
import sys
import math
@@ -393,6 +433,10 @@ screen modmenu_paged(contents, use_steam):
$ MIN_PAGE = 1 # Do note, modpage numbers are 1-indexed
$ MAX_PAGE = int(math.ceil(len(contents) / float(PAGE_SIZE)))
+ default search_order_contents = contents
+ default query = ""
+ default author_query = ""
+
frame id "modmenu_paged" at alpha_dissolve:
add "image/ui/ingame_menu_bg3.png"
@@ -440,7 +484,7 @@ screen modmenu_paged(contents, use_steam):
ycenter 0.5
# Tried to bind this to shift+scroll, but it didn't work...
action [SetScreenVariable("current_page", max(current_page-5, MIN_PAGE)),
- Function(_refresh_modlist_page, max(current_page-5, MIN_PAGE), PAGE_SIZE, contents, use_steam=use_steam)
+ Function(_refresh_modlist_page, max(current_page-5, MIN_PAGE), PAGE_SIZE, search_order_contents, use_steam=use_steam)
]
sensitive (current_page > 1)
@@ -449,7 +493,7 @@ screen modmenu_paged(contents, use_steam):
ycenter 0.5
keysym "mousedown_4"
action [SetScreenVariable("current_page", current_page-1),
- Function(_refresh_modlist_page, current_page-1, PAGE_SIZE, contents, use_steam=use_steam)
+ Function(_refresh_modlist_page, current_page-1, PAGE_SIZE, search_order_contents, use_steam=use_steam)
]
sensitive (current_page > 1)
@@ -464,7 +508,7 @@ screen modmenu_paged(contents, use_steam):
ycenter 0.5
keysym "mousedown_5"
action [SetScreenVariable("current_page", current_page+1),
- Function(_refresh_modlist_page, current_page+1, PAGE_SIZE, contents, use_steam=use_steam)
+ Function(_refresh_modlist_page, current_page+1, PAGE_SIZE, search_order_contents, use_steam=use_steam)
]
sensitive (current_page < MAX_PAGE)
@@ -473,14 +517,102 @@ screen modmenu_paged(contents, use_steam):
ycenter 0.5
# Also tried to bind this to shift+scroll, but it didn't work...
action [SetScreenVariable("current_page", min(current_page+5, MAX_PAGE)),
- Function(_refresh_modlist_page, min(current_page+5, MAX_PAGE), PAGE_SIZE, contents, use_steam=use_steam)
+ Function(_refresh_modlist_page, min(current_page+5, MAX_PAGE), PAGE_SIZE, search_order_contents, use_steam=use_steam)
]
sensitive (current_page < MAX_PAGE)
- on "show" action [Function(_refresh_modlist_page, current_page, PAGE_SIZE, contents, use_steam=use_steam),
- Function(_preload_mod_images, contents, None)]
- on "hide" action [Function(mod_image_preloader.clear)]
+ hbox:
+ xpos 65
+ ypos 10
+ xanchor 0.0
+ yanchor 0.0
+ xsize 425
+ ysize 70
+
+ spacing 10
+
+ vbox:
+ xalign 0.0
+ ycenter 0.5
+ xsize 75
+ spacing 6
+
+ # For some reason 'label' and 'text' text components insisted on being ever so slightly larger than necessary, which made everything look misaligned
+ textbutton "Author:":
+ background "#00000000"
+ text_size 24
+ ysize 32
+ xalign 0.0
+
+ textbutton "Mod:":
+ background "#00000000"
+ text_size 24
+ ysize 32
+ xalign 0.0
+
+ vbox:
+ xalign 0.0
+ ycenter 0.5
+ spacing 6
+
+ default focus_query_input = False
+ default focus_author_query_input = False
+
+ # input components aggressively capture focus, to the point where you can't use more than one of them in a single screen.
+ # a button is used to circumvent this, as it is a container that can itself hold focus, so it is able to intercept the aggressive behaviour.
+ button:
+ background If(focus_author_query_input, "#FFFFFFCD", "#000000CD")
+ hover_background If(focus_author_query_input, "#BFBFFFCD", "#000040CD")
+ activate_sound None
+ key_events focus_author_query_input
+ action [ToggleScreenVariable("focus_author_query_input"), SetScreenVariable("focus_query_input", False)]
+ xfill True
+ ysize 32
+ xpadding 0
+
+ input:
+ color If(focus_author_query_input, "#000", "#FF7F00")
+ xalign 0.0
+ ycenter 0.5
+ size 24
+ pixel_width 320 # While the horizontal space is supposed to be 340, The inputs have a tendency to drop down a row...
+ changed set_author_query
+
+
+ button:
+ background If(focus_query_input, "#FFFFFFCD", "#000000CD")
+ hover_background If(focus_query_input, "#BFBFFFCD", "#000040CD")
+ activate_sound None
+ key_events focus_query_input
+ action [ToggleScreenVariable("focus_query_input"), SetScreenVariable("focus_author_query_input", False)]
+ xfill True
+ ysize 32
+ xpadding 0
+
+ input:
+ color If(focus_query_input, "#000", "#FFFF00")
+ xalign 0.0
+ ycenter 0.5
+ size 24
+ pixel_width 320
+ changed set_query
+ key "K_ESCAPE" action [SetScreenVariable("focus_query_input", False), SetScreenVariable("focus_author_query_input", False)]
+ key "K_TAB" action [ToggleScreenVariable("focus_author_query_input"),
+ If(focus_author_query_input,
+ ToggleScreenVariable("focus_query_input"),
+ SetScreenVariable("focus_query_input", False))]
+
+
+ on "show" action [Function(_refresh_modlist_page, current_page, PAGE_SIZE, contents, use_steam=use_steam),
+ Function(_preload_mod_images, contents, None),
+ Function(im.cache.clear) # I tended to get 'out of memory' errors on this menu, so we use this precaution
+ ]
+
+ on "hide" action [Function(mod_image_preloader.clear), # Cleanup after ourselves
+ Function(im.cache.clear),
+ Function(modmenu_search.clear_cache),
+ ]
diff --git a/mods/core/modules/modmenu_search.py b/mods/core/modules/modmenu_search.py
new file mode 100644
index 0000000..9ca8256
--- /dev/null
+++ b/mods/core/modules/modmenu_search.py
@@ -0,0 +1,186 @@
+
+# This file contains function definitions from nltk repository, under the Apache License Version 2.0
+# in particular, the function jaro_similarity has been used.
+# Those have been used under these attributions:
+#
+# Copyright (C) 2001-2025 NLTK Project
+# Author: Edward Loper
+# Steven Bird
+# Tom Lippincott
+# URL:
+# For attribution license information, see NLTK_LICENSE.txt
+#
+# All components which are not explicitly licensed under the Apache License Version 2.0 of nltk (NLTK_LICENSE.txt) are licensed under this project's standard license (LICENSE)
+#
+
+def cache(function):
+ def inner(*args):
+ if not hasattr(inner, "results"):
+ inner.results = {args: function(*args)}
+ elif args not in inner.results:
+ inner.results[args] = function(*args)
+ return inner.results[args]
+ def clear_cache():
+ if hasattr(inner, "results"):
+ inner.results.clear()
+ inner.clear_cache = clear_cache
+ return inner
+
+# Copied from nltk (https://www.nltk.org/_modules/nltk/metrics/distance.html#jaro_similarity)
+# This function is copied from nltk, and is therefore licensed under their Apache License Version 2.0 (NLTK_LICENSE.txt)
+@cache
+def jaro_similarity(s1, s2):
+ """
+ Computes the Jaro similarity between 2 sequences from:
+
+ Matthew A. Jaro (1989). Advances in record linkage methodology
+ as applied to the 1985 census of Tampa Florida. Journal of the
+ American Statistical Association. 84 (406): 414-20.
+
+ The Jaro distance between is the min no. of single-character transpositions
+ required to change one word into another. The Jaro similarity formula from
+ https://en.wikipedia.org/wiki/Jaro%E2%80%93Winkler_distance :
+
+ ``jaro_sim = 0 if m = 0 else 1/3 * (m/|s_1| + m/s_2 + (m-t)/m)``
+
+ where
+ - `|s_i|` is the length of string `s_i`
+ - `m` is the no. of matching characters
+ - `t` is the half no. of possible transpositions.
+ """
+ # First, store the length of the strings
+ # because they will be re-used several times.
+ len_s1, len_s2 = len(s1), len(s2)
+
+ # The upper bound of the distance for being a matched character.
+ match_bound = max(int(max(len_s1, len_s2) / 2) - 1, 0) # My one change from the original algorithm: allows two length=1 words to match if they are the same word.
+
+ # Initialize the counts for matches and transpositions.
+ matches = 0 # no.of matched characters in s1 and s2
+ transpositions = 0 # no. of transpositions between s1 and s2
+ flagged_1 = [] # positions in s1 which are matches to some character in s2
+ flagged_2 = [] # positions in s2 which are matches to some character in s1
+
+ # Iterate through sequences, check for matches and compute transpositions.
+ for i in range(len_s1): # Iterate through each character.
+ upperbound = min(i + match_bound, len_s2 - 1)
+ lowerbound = max(0, i - match_bound)
+ for j in range(lowerbound, upperbound + 1):
+ if s1[i] == s2[j] and j not in flagged_2:
+ matches += 1
+ flagged_1.append(i)
+ flagged_2.append(j)
+ break
+ flagged_2.sort()
+ for i, j in zip(flagged_1, flagged_2):
+ if s1[i] != s2[j]:
+ transpositions += 1
+
+ if matches == 0:
+ return 0
+ else:
+ matches = float(matches) # Added to nltk's implementation. int division and float division are qualitatively different in python 2 (unlike python 3, where nltk is implemented), and the float division is the intended behaviour.
+ return (
+ 1 / 3.0 # Changed from nltk's 3 to 3.0, for the same reason as the last change.
+ * (
+ matches / len_s1
+ + matches / len_s2
+ + (matches - int(transpositions / 2)) / matches
+ )
+ )
+
+
+
+_jaro_best_match_cache = {}
+
+
+def jaro_set_similarity(query_set, target1, target2):
+ """Finds approximate similarity between word set query_set and target word strings target1 and target2.
+ each word in query_set is compared against all of target1's and target2's words to find the best match.
+ the similarity is then the average of each of those best similarity numbers.
+ these results are cached by target1 for each word of query_set, and as such, for each value of target1 there should only be a single value of target2."""
+
+
+ best_similarity_1 = {}
+ best_similarity_2 = {}
+ for query_word in query_set:
+ if (query_word, target1) not in _jaro_best_match_cache:
+ t1_word_set = set(target1.lower().split())
+ curr_best_1 = 0
+ for target_word in t1_word_set:
+ curr_best_1 = max(curr_best_1, jaro_similarity(query_word, target_word))
+ best_similarity_1[query_word] = curr_best_1
+
+ t2_word_set = set(target2.lower().split())
+ curr_best_2 = 0
+ for target_word in t2_word_set:
+ curr_best_2 = max(curr_best_2, jaro_similarity(query_word, target_word))
+ best_similarity_2[query_word] = curr_best_2
+
+ _jaro_best_match_cache[(query_word, target1)] = (curr_best_1, curr_best_2)
+ else:
+ sim1, sim2 = _jaro_best_match_cache[(query_word, target1)]
+ best_similarity_1[query_word] = sim1
+ best_similarity_2[query_word] = sim2
+
+ n_values = len(query_set)
+ return (sum(best_similarity_1[query_word] for query_word in query_set) / n_values,
+ sum(best_similarity_2[query_word] for query_word in query_set) / n_values)
+
+
+
+def jaro_split_compare(query, modlist):
+ """Compare the modlist to the query using jaro similarity on each word.
+ :returns dict from modname to similarity tuple, which contains the similarity of query to modname, then the similarity of query to mod description.
+ """
+ comps = {}
+ query_words = set(query.lower().split())
+
+ for _, name, _, desc, _ in modlist:
+ comps[name] = jaro_set_similarity(query_words, name, desc)
+
+ return comps
+
+def jaro_author_compare(author_query, modlist):
+ comps = {}
+ author_query = author_query.lower()
+
+ for _, name, author, _, _ in modlist:
+ comps[name] = jaro_similarity(author_query, author.lower())
+
+ return comps
+
+
+def sort_best(query, modlist, author_query="", return_score=False):
+ """Sort mods by best match to query"""
+ if query.strip():
+ similarities = jaro_split_compare(query, modlist)
+ else:
+ similarities = {name: (0.0, 0.0) for _, name, _, _, _ in modlist}
+ if author_query.strip():
+ author_similarities = jaro_author_compare(author_query, modlist)
+ else:
+ author_similarities = {name: 0.0 for name in similarities.iterkeys()}
+ similarities = {name: scores + (author_similarities[name],) for name, scores in similarities.iteritems()} # Much easier to deal with if it's a single iterable
+
+ # Sort by best match, with bias to strong modname matches and strong authorname matches
+ # This bias is useful as the description normally takes the stronger value, unless the mod name is searched specifically.
+ # Max gave me better results than sum, so I used it.
+ comp_func = lambda e: (max(e[1][:2]) + (int(e[1][0] > 0.9) * e[1][0]) + (int(e[1][2] > 0.7) * e[1][2]))
+ mod_order = list(sorted(similarities.items(), key=comp_func, reverse=True))
+
+ if comp_func(mod_order[0]) <= 0.3: # All bad matches, don't reorder
+ print "No good matches. reordering suppressed"
+ mod_order = list((name, 0.0) for _, name, _, _, _ in modlist)
+
+ mods_by_name = {mod[1]: mod for mod in modlist}
+
+ if return_score:
+ return [(mods_by_name[name], score) for name, score in mod_order]
+ else:
+ return [mods_by_name[name] for name, _ in mod_order]
+
+
+def clear_cache():
+ _jaro_best_match_cache.clear()
+ jaro_similarity.clear_cache()
\ No newline at end of file