From 6802a4f89d1431913ce3218f4db9bbe2748115e5 Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Tue, 22 Sep 2015 14:23:55 -0400
Subject: [PATCH 01/12] fix README conflict

Former-commit-id: 5b918e7bb069a9068a5416228dcf5e49b7dd69ac
---
 README.md | 17 +++++------------
 1 file changed, 5 insertions(+), 12 deletions(-)

diff --git a/README.md b/README.md
index 3aa0043..b8c8dbb 100644
--- a/README.md
+++ b/README.md
@@ -232,20 +232,14 @@ sources:
 
 - Wikipedia, the free encyclopedia (http://www.wikipedia.org)
 
-<<<<<<< HEAD
 It contains data from various SUBTLEX word lists: SUBTLEX-US, SUBTLEX-UK,
-SUBTLEX-CH, SUBTLEX-DE, and SUBTLEX-NL, created by Marc Brysbaert et al. (see citations below) and
-available at http://crr.ugent.be/programs-data/subtitle-frequencies.
-=======
-It contains data from various SUBTLEX word lists: SUBTLEX-US, SUBTLEX-UK, and
-SUBTLEX-CH, created by Marc Brysbaert et al. and available at
+SUBTLEX-CH, SUBTLEX-DE, and SUBTLEX-NL, created by Marc Brysbaert et al.
+(see citations below) and available at
 http://crr.ugent.be/programs-data/subtitle-frequencies.
->>>>>>> greek-and-turkish
 
-I (Robyn Speer) have
-obtained permission by e-mail from Marc Brysbaert to distribute these wordlists
-in wordfreq, to be used for any purpose, not just for academic use, under these
-conditions:
+I (Robyn Speer) have obtained permission by e-mail from Marc Brysbaert to
+distribute these wordlists in wordfreq, to be used for any purpose, not just
+for academic use, under these conditions:
 
 - Wordfreq and code derived from it must credit the SUBTLEX authors.
 - It must remain clear that SUBTLEX is freely available data.
@@ -297,4 +291,3 @@ Twitter; it does not display or republish any Twitter content.
   SUBTLEX-UK: A new and improved word frequency database for British English.
   The Quarterly Journal of Experimental Psychology, 67(6), 1176-1190.
   http://www.tandfonline.com/doi/pdf/10.1080/17470218.2013.850521
-

From fe8a6b51e718084d9b4bda0c6f83231e4af58f60 Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Tue, 22 Sep 2015 15:31:27 -0400
Subject: [PATCH 02/12] document what this file is for

Former-commit-id: 06f8b299712a5952c5847ece8b13c1a18fcc2ed0
---
 scripts/make_chinese_mapping.py | 13 +++++++++++++
 1 file changed, 13 insertions(+)

diff --git a/scripts/make_chinese_mapping.py b/scripts/make_chinese_mapping.py
index 19b7826..9855e18 100644
--- a/scripts/make_chinese_mapping.py
+++ b/scripts/make_chinese_mapping.py
@@ -1,3 +1,16 @@
+"""
+Generate a Python file, _chinese_mapping.py, that maps Traditional Chinese
+characters to their Simplified Chinese equivalents.
+
+This is meant to be a normalization of text, somewhat like case-folding -- not
+an actual translator, a task for which this method would be unsuitable. We
+store word frequencies using Simplified Chinese characters so that, in the large
+number of cases where a Traditional Chinese word has an obvious Simplified Chinese
+mapping, we can get a frequency for it that's the same in Simplified and Traditional
+Chinese.
+
+Generating this mapping requires the external Chinese conversion tool OpenCC.
+"""
 import unicodedata
 import itertools
 import os

From db30d09947f86ed734385d8de08f2fd3ce7f5c2b Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Tue, 22 Sep 2015 16:31:50 -0400
Subject: [PATCH 03/12] load the Chinese character mapping from a .msgpack.gz
 file

Former-commit-id: 6cf4210187430c822297ce921775db6d983c22ab
---
 scripts/make_chinese_mapping.py           |   24 +-
 wordfreq/__init__.py                      |    9 +-
 wordfreq/_chinese_mapping.py              | 3275 ---------------------
 wordfreq/chinese.py                       |   11 +-
 wordfreq/data/_chinese_mapping.msgpack.gz |  Bin 0 -> 16831 bytes
 5 files changed, 25 insertions(+), 3294 deletions(-)
 delete mode 100644 wordfreq/_chinese_mapping.py
 create mode 100644 wordfreq/data/_chinese_mapping.msgpack.gz

diff --git a/scripts/make_chinese_mapping.py b/scripts/make_chinese_mapping.py
index 9855e18..4a17d4f 100644
--- a/scripts/make_chinese_mapping.py
+++ b/scripts/make_chinese_mapping.py
@@ -1,20 +1,21 @@
 """
-Generate a Python file, _chinese_mapping.py, that maps Traditional Chinese
-characters to their Simplified Chinese equivalents.
+Generate a msgpack file, _chinese_mapping.msgpack.gz, that maps Traditional
+Chinese characters to their Simplified Chinese equivalents.
 
 This is meant to be a normalization of text, somewhat like case-folding -- not
 an actual translator, a task for which this method would be unsuitable. We
-store word frequencies using Simplified Chinese characters so that, in the large
-number of cases where a Traditional Chinese word has an obvious Simplified Chinese
-mapping, we can get a frequency for it that's the same in Simplified and Traditional
-Chinese.
+store word frequencies using Simplified Chinese characters so that, in the
+large number of cases where a Traditional Chinese word has an obvious
+Simplified Chinese mapping, we can get a frequency for it that's the same in
+Simplified and Traditional Chinese.
 
 Generating this mapping requires the external Chinese conversion tool OpenCC.
 """
 import unicodedata
 import itertools
 import os
-import pprint
+import msgpack
+import gzip
 
 
 def make_hanzi_table(filename):
@@ -25,7 +26,7 @@ def make_hanzi_table(filename):
                 print('%5X\t%s' % (codept, char), file=out)
 
 
-def make_hanzi_converter(table_in, python_out):
+def make_hanzi_converter(table_in, msgpack_out):
     table = {}
     with open(table_in, encoding='utf-8') as infile:
         for line in infile:
@@ -34,15 +35,14 @@ def make_hanzi_converter(table_in, python_out):
             assert len(char) == 1
             if chr(codept) != char:
                 table[codept] = char
-    with open(python_out, 'w', encoding='utf-8') as outfile:
-        print('SIMPLIFIED_MAP = ', end='', file=outfile)
-        pprint.pprint(table, stream=outfile)
+    with gzip.open(msgpack_out, 'wb') as outfile:
+        msgpack.dump(table, outfile, encoding='utf-8')
 
 
 def build():
     make_hanzi_table('/tmp/han_in.txt')
     os.system('opencc -c zht2zhs.ini < /tmp/han_in.txt > /tmp/han_out.txt')
-    make_hanzi_converter('/tmp/han_out.txt', '_chinese_mapping.py')
+    make_hanzi_converter('/tmp/han_out.txt', '_chinese_mapping.msgpack.gz')
 
 
 if __name__ == '__main__':
diff --git a/wordfreq/__init__.py b/wordfreq/__init__.py
index d5b95a2..4790282 100644
--- a/wordfreq/__init__.py
+++ b/wordfreq/__init__.py
@@ -85,10 +85,11 @@ def available_languages(wordlist='combined'):
     """
     available = {}
     for path in DATA_PATH.glob('*.msgpack.gz'):
-        list_name = path.name.split('.')[0]
-        name, lang = list_name.split('_')
-        if name == wordlist:
-            available[lang] = str(path)
+        if not path.name.startswith('_'):
+            list_name = path.name.split('.')[0]
+            name, lang = list_name.split('_')
+            if name == wordlist:
+                available[lang] = str(path)
     return available
 
 
diff --git a/wordfreq/_chinese_mapping.py b/wordfreq/_chinese_mapping.py
deleted file mode 100644
index 2efac17..0000000
--- a/wordfreq/_chinese_mapping.py
+++ /dev/null
@@ -1,3275 +0,0 @@
-SIMPLIFIED_MAP = {13423: '㑔',
- 13427: '㑇',
- 13459: '𠉂',
- 13544: '刾',
- 13810: '𠵾',
- 13850: '㘎',
- 14084: '㚯',
- 14095: '㛣',
- 14114: '𡞱',
- 14135: '𡝠',
- 14238: '𪨊',
- 14351: '㟆',
- 14493: '𢋈',
- 14702: '㤘',
- 14734: '𢛯',
- 14940: '㨫',
- 14963: '㧐',
- 15871: '𤈷',
- 16015: '𤠋',
- 16359: '𤽯',
- 16441: '𥅴',
- 16490: '𥇢',
- 16507: '䀥',
- 16985: '𥬀',
- 17004: '𫂈',
- 17010: '𥮜',
- 17069: '𥺅',
- 17079: '䌶',
- 17113: '䌺',
- 17114: '䌻',
- 17147: '䌾',
- 17151: '𦈓',
- 17160: '𦈖',
- 17163: '𦈘',
- 17174: '𦈜',
- 17181: '𦈟',
- 17183: '𦈞',
- 17189: '𦈠',
- 17200: '𦈙',
- 17779: '𦰴',
- 17919: '𧉞',
- 18017: '䙌',
- 18176: '䜧',
- 18299: '𧹕',
- 18300: '䞍',
- 18312: '𧹑',
- 18600: '𨑹',
- 18759: '䦂',
- 18793: '𨱖',
- 18801: '䥾',
- 18840: '𨸄',
- 18843: '䦶',
- 18847: '䦷',
- 18867: '𨷿',
- 18914: '𨸟',
- 19087: '𩏼',
- 19095: '𩐀',
- 19096: '𩏿',
- 19188: '𩖗',
- 19224: '𩙮',
- 19229: '𩙯',
- 19230: '𩙧',
- 19264: '𩠇',
- 19267: '𩠈',
- 19327: '𩧭',
- 19357: '𩧰',
- 19358: '𩨁',
- 19360: '𩧿',
- 19371: '𩨇',
- 19379: '𩨏',
- 19390: '𩧪',
- 19392: '䯅',
- 19518: '鲃',
- 19545: '𩾈',
- 19564: '𩾊',
- 19568: '𩾋',
- 19575: '䲣',
- 19581: '䲝',
- 19585: '鳚',
- 19606: '𩾂',
- 19632: '𪉂',
- 19721: '鹮',
- 19756: '𪎈',
- 19764: '𪎋',
- 19999: '丢',
- 20006: '并',
- 20094: '干',
- 20098: '乱',
- 20121: '亘',
- 20126: '亚',
- 20295: '伫',
- 20296: '布',
- 20308: '占',
- 20341: '并',
- 20358: '来',
- 20374: '仑',
- 20406: '侣',
- 20407: '局',
- 20417: '俣',
- 20418: '系',
- 20436: '伣',
- 20448: '侠',
- 20453: '伡',
- 20460: '私',
- 20480: '伥',
- 20486: '俩',
- 20488: '俫',
- 20489: '仓',
- 20491: '个',
- 20497: '们',
- 20502: '幸',
- 20523: '伦',
- 20530: '㑈',
- 20553: '伟',
- 20561: '㐽',
- 20596: '侧',
- 20597: '侦',
- 20605: '伪',
- 20625: '杰',
- 20630: '伧',
- 20632: '伞',
- 20633: '备',
- 20642: '家',
- 20653: '佣',
- 20655: '偬',
- 20659: '传',
- 20660: '伛',
- 20661: '债',
- 20663: '伤',
- 20670: '倾',
- 20674: '偻',
- 20677: '仅',
- 20681: '佥',
- 20689: '侨',
- 20693: '仆',
- 20702: '伪',
- 20709: '侥',
- 20712: '偾',
- 20721: '雇',
- 20729: '价',
- 20736: '仪',
- 20737: '俊',
- 20738: '侬',
- 20740: '亿',
- 20744: '侩',
- 20745: '俭',
- 20752: '傧',
- 20756: '俦',
- 20757: '侪',
- 20760: '尽',
- 20767: '偿',
- 20771: '𠆲',
- 20778: '优',
- 20786: '储',
- 20791: '俪',
- 20792: '㑩',
- 20794: '傩',
- 20795: '傥',
- 20796: '俨',
- 20807: '凶',
- 20812: '兑',
- 20818: '儿',
- 20823: '兖',
- 20839: '内',
- 20841: '两',
- 20874: '册',
- 20906: '幂',
- 20936: '净',
- 20941: '冻',
- 20953: '𪞝',
- 20956: '凛',
- 20977: '凯',
- 21029: '别',
- 21034: '删',
- 21060: '刭',
- 21063: '则',
- 21067: '克',
- 21070: '刹',
- 21079: '刬',
- 21083: '刚',
- 21085: '剥',
- 21102: '剐',
- 21108: '剀',
- 21109: '创',
- 21111: '铲',
- 21118: '𠛅',
- 21123: '划',
- 21127: '剧',
- 21129: '刘',
- 21130: '刽',
- 21132: '刿',
- 21133: '剑',
- 21135: '㓥',
- 21137: '剂',
- 21146: '㔉',
- 21185: '劲',
- 21205: '动',
- 21209: '务',
- 21211: '勋',
- 21213: '胜',
- 21214: '劳',
- 21218: '势',
- 21225: '勚',
- 21233: '劢',
- 21235: '勋',
- 21237: '励',
- 21240: '劝',
- 21243: '匀',
- 21293: '匦',
- 21295: '汇',
- 21297: '匮',
- 21312: '区',
- 21332: '协',
- 21369: '恤',
- 21371: '却',
- 21373: '即',
- 21401: '厍',
- 21408: '厕',
- 21412: '历',
- 21421: '厌',
- 21426: '厉',
- 21428: '厣',
- 21443: '参',
- 21444: '叁',
- 21474: '丛',
- 21522: '咤',
- 21555: '吴',
- 21558: '呐',
- 21570: '吕',
- 21692: '呙',
- 21729: '员',
- 21743: '𠯟',
- 21764: '呗',
- 21786: '吣',
- 21816: '念',
- 21839: '问',
- 21843: '启',
- 21854: '哑',
- 21855: '启',
- 21858: '唡',
- 21902: '㖞',
- 21914: '唤',
- 21930: '丧',
- 21931: '吃',
- 21932: '乔',
- 21934: '单',
- 21938: '哟',
- 21958: '呛',
- 21959: '啬',
- 21962: '唝',
- 21966: '吗',
- 21978: '呜',
- 21993: '唢',
- 22000: '𠮶',
- 22006: '哔',
- 22009: '𪡏',
- 22022: '叹',
- 22029: '喽',
- 22035: '啯',
- 22036: '呕',
- 22038: '啧',
- 22039: '尝',
- 22044: '唛',
- 22057: '哗',
- 22062: '唠',
- 22063: '啸',
- 22064: '叽',
- 22069: '哓',
- 22072: '呒',
- 22077: '啴',
- 22081: '恶',
- 22085: '𠯠',
- 22099: '嘘',
- 22106: '㖊',
- 22109: '咝',
- 22112: '哒',
- 22117: '哝',
- 22118: '哕',
- 22127: '嗳',
- 22130: '哙',
- 22132: '喷',
- 22136: '吨',
- 22137: '当',
- 22144: '咛',
- 22151: '吓',
- 22156: '哜',
- 22160: '尝',
- 22165: '噜',
- 22169: '啮',
- 22181: '咽',
- 22182: '呖',
- 22184: '咙',
- 22190: '向',
- 22194: '亸',
- 22195: '喾',
- 22196: '严',
- 22198: '嘤',
- 22208: '啭',
- 22209: '嗫',
- 22210: '嚣',
- 22213: '冁',
- 22216: '呓',
- 22217: '啰',
- 22220: '苏',
- 22225: '嘱',
- 22250: '囱',
- 22279: '囵',
- 22283: '国',
- 22285: '围',
- 22290: '园',
- 22291: '圆',
- 22294: '图',
- 22296: '团',
- 22302: '𪢮',
- 22453: '埯',
- 22497: '垭',
- 22512: '采',
- 22519: '执',
- 22533: '坚',
- 22538: '垩',
- 22550: '垴',
- 22557: '埚',
- 22575: '尧',
- 22577: '报',
- 22580: '场',
- 22602: '块',
- 22603: '茔',
- 22607: '垲',
- 22610: '埘',
- 22615: '涂',
- 22618: '冢',
- 22626: '坞',
- 22628: '埙',
- 22645: '尘',
- 22649: '堑',
- 22666: '垫',
- 22684: '坠',
- 22702: '堕',
- 22704: '坛',
- 22707: '坟',
- 22710: '垯',
- 22715: '墙',
- 22718: '垦',
- 22727: '坛',
- 22728: '𡒄',
- 22731: '垱',
- 22739: '压',
- 22744: '垒',
- 22745: '圹',
- 22746: '垆',
- 22748: '坛',
- 22750: '坏',
- 22751: '垄',
- 22752: '垅',
- 22754: '坜',
- 22761: '坝',
- 22767: '壮',
- 22778: '壶',
- 22780: '壸',
- 22781: '寿',
- 22816: '够',
- 22818: '梦',
- 22821: '伙',
- 22846: '夹',
- 22864: '奂',
- 22887: '奥',
- 22889: '奁',
- 22890: '夺',
- 22892: '奖',
- 22894: '奋',
- 22908: '姹',
- 22941: '妆',
- 22989: '姗',
- 23014: '奸',
- 23067: '娱',
- 23105: '娄',
- 23142: '妇',
- 23149: '娅',
- 23207: '娲',
- 23215: '妫',
- 23216: '㛀',
- 23228: '媪',
- 23229: '妈',
- 23243: '袅',
- 23255: '妪',
- 23285: '妩',
- 23291: '娴',
- 23295: '婳',
- 23296: '妫',
- 23299: '媭',
- 23304: '娆',
- 23307: '婵',
- 23308: '娇',
- 23321: '嫱',
- 23329: '嫒',
- 23338: '嫔',
- 23344: '婴',
- 23352: '婶',
- 23363: '娘',
- 23371: '㛤',
- 23372: '娈',
- 23403: '孙',
- 23416: '学',
- 23423: '孪',
- 23470: '宫',
- 23488: '采',
- 23522: '寝',
- 23526: '实',
- 23527: '宁',
- 23529: '审',
- 23531: '写',
- 23532: '宽',
- 23541: '宠',
- 23542: '宝',
- 23559: '将',
- 23560: '专',
- 23563: '寻',
- 23565: '对',
- 23566: '导',
- 23607: '尴',
- 23622: '届',
- 23629: '尸',
- 23635: '屃',
- 23644: '屉',
- 23650: '屡',
- 23652: '层',
- 23656: '屦',
- 23657: '𪨗',
- 23660: '属',
- 23713: '冈',
- 23791: '峰',
- 23796: '岘',
- 23798: '岛',
- 23805: '峡',
- 23821: '崃',
- 23825: '昆',
- 23831: '岗',
- 23833: '仑',
- 23842: '峥',
- 23852: '岽',
- 23888: '岚',
- 23895: '岁',
- 23932: '𡶴',
- 23937: '嵝',
- 23940: '崭',
- 23943: '岖',
- 23956: '嵚',
- 23959: '崂',
- 23968: '峤',
- 23970: '峣',
- 23975: '峄',
- 23982: '崄',
- 23988: '岙',
- 23992: '嵘',
- 23994: '岭',
- 23996: '屿',
- 23997: '岳',
- 24011: '岿',
- 24018: '峦',
- 24020: '巅',
- 24022: '岩',
- 24048: '巯',
- 24057: '卺',
- 24101: '帅',
- 24107: '师',
- 24115: '帐',
- 24118: '带',
- 24128: '帧',
- 24131: '帏',
- 24151: '帼',
- 24152: '帻',
- 24159: '帜',
- 24163: '币',
- 24171: '帮',
- 24172: '帱',
- 24185: '干',
- 24190: '几',
- 24235: '库',
- 24257: '厕',
- 24258: '厢',
- 24260: '厩',
- 24264: '厦',
- 24277: '荫',
- 24282: '厨',
- 24285: '厮',
- 24287: '庙',
- 24288: '厂',
- 24289: '庑',
- 24290: '废',
- 24291: '广',
- 24297: '廪',
- 24300: '庐',
- 24307: '厅',
- 24338: '弑',
- 24340: '吊',
- 24371: '弪',
- 24373: '张',
- 24375: '强',
- 24390: '别',
- 24392: '弹',
- 24396: '弥',
- 24398: '弯',
- 24404: '录',
- 24409: '汇',
- 24414: '彝',
- 24416: '彟',
- 24421: '彦',
- 24427: '雕',
- 24434: '彨',
- 24447: '佛',
- 24460: '后',
- 24465: '径',
- 24478: '从',
- 24480: '徕',
- 24489: '复',
- 24501: '征',
- 24505: '彻',
- 24646: '恒',
- 24677: '耻',
- 24709: '悦',
- 24734: '悮',
- 24757: '怅',
- 24758: '闷',
- 24765: '凄',
- 24801: '恶',
- 24817: '恼',
- 24818: '恽',
- 24827: '恻',
- 24859: '爱',
- 24860: '惬',
- 24872: '悫',
- 24884: '怆',
- 24887: '恺',
- 24894: '忾',
- 24900: '栗',
- 24907: '态',
- 24909: '愠',
- 24920: '惨',
- 24922: '惭',
- 24927: '恸',
- 24931: '惯',
- 24932: '悫',
- 24938: '怄',
- 24939: '怂',
- 24942: '虑',
- 24947: '悭',
- 24950: '庆',
- 24956: '戚',
- 24958: '欲',
- 24962: '忧',
- 24970: '惫',
- 24976: '怜',
- 24977: '凭',
- 24978: '愦',
- 24986: '惮',
- 24996: '愤',
- 25003: '悯',
- 25006: '怃',
- 25010: '宪',
- 25014: '忆',
- 25024: '𢙓',
- 25031: '恳',
- 25033: '应',
- 25036: '怿',
- 25037: '懔',
- 25054: '蒙',
- 25055: '怼',
- 25059: '懑',
- 25064: '恹',
- 25074: '惩',
- 25078: '懒',
- 25079: '怀',
- 25080: '悬',
- 25082: '忏',
- 25084: '惧',
- 25086: '慑',
- 25088: '恋',
- 25095: '戆',
- 25108: '戋',
- 25127: '戗',
- 25129: '戬',
- 25136: '战',
- 25137: '戯',
- 25138: '戏',
- 25142: '户',
- 25291: '抛',
- 25385: '捝',
- 25393: '挲',
- 25406: '挟',
- 25448: '舍',
- 25451: '扪',
- 25457: '挨',
- 25458: '卷',
- 25475: '扫',
- 25476: '抡',
- 25478: '㧏',
- 25495: '挜',
- 25497: '挣',
- 25499: '挂',
- 25505: '采',
- 25536: '拣',
- 25562: '扬',
- 25563: '换',
- 25582: '挥',
- 25613: '损',
- 25622: '摇',
- 25623: '捣',
- 25653: '揾',
- 25654: '抢',
- 25675: '𢫬',
- 25681: '掴',
- 25692: '掼',
- 25695: '搂',
- 25711: '挚',
- 25715: '抠',
- 25718: '抟',
- 25722: '折',
- 25723: '掺',
- 25736: '捞',
- 25743: '挦',
- 25744: '撑',
- 25747: '挠',
- 25757: '㧑',
- 25759: '挢',
- 25763: '掸',
- 25765: '拨',
- 25771: '抚',
- 25778: '扑',
- 25779: '揿',
- 25787: '挞',
- 25790: '挝',
- 25791: '捡',
- 25793: '拥',
- 25796: '掳',
- 25799: '择',
- 25802: '击',
- 25803: '挡',
- 25811: '㧟',
- 25812: '担',
- 25818: '据',
- 25824: '挤',
- 25825: '抬',
- 25827: '捣',
- 25836: '拟',
- 25839: '摈',
- 25840: '拧',
- 25841: '搁',
- 25842: '掷',
- 25844: '扩',
- 25847: '撷',
- 25850: '摆',
- 25851: '擞',
- 25852: '撸',
- 25853: '㧰',
- 25854: '扰',
- 25860: '摅',
- 25862: '撵',
- 25871: '拢',
- 25876: '拦',
- 25878: '撄',
- 25881: '搀',
- 25883: '撺',
- 25884: '携',
- 25885: '摄',
- 25890: '攒',
- 25891: '挛',
- 25892: '摊',
- 25898: '搅',
- 25900: '揽',
- 25934: '教',
- 25943: '败',
- 25944: '叙',
- 25973: '敌',
- 25976: '数',
- 25986: '敛',
- 25987: '毙',
- 25989: '𢽾',
- 25990: '敩',
- 26005: '斓',
- 26028: '斩',
- 26039: '断',
- 26044: '于',
- 26050: '旗',
- 26083: '既',
- 26119: '升',
- 26178: '时',
- 26185: '晋',
- 26205: '昼',
- 26248: '晕',
- 26249: '晖',
- 26264: '旸',
- 26274: '畅',
- 26283: '暂',
- 26308: '晔',
- 26310: '历',
- 26311: '昙',
- 26313: '晓',
- 26319: '向',
- 26326: '暧',
- 26336: '旷',
- 26341: '𣆐',
- 26344: '昽',
- 26348: '晒',
- 26360: '书',
- 26371: '会',
- 26405: '𦛨',
- 26407: '胧',
- 26414: '术',
- 26481: '东',
- 26484: '锨',
- 26548: '拐',
- 26613: '栅',
- 26618: '拐',
- 26619: '查',
- 26751: '杆',
- 26772: '栀',
- 26776: '枧',
- 26781: '条',
- 26783: '枭',
- 26802: '棁',
- 26820: '弃',
- 26826: '棋',
- 26838: '枨',
- 26839: '枣',
- 26847: '栋',
- 26849: '㭎',
- 26855: '栈',
- 26866: '栖',
- 26870: '梾',
- 26895: '桠',
- 26930: '㭏',
- 26954: '杨',
- 26963: '枫',
- 26984: '桢',
- 26989: '业',
- 26997: '极',
- 27032: '矩',
- 27046: '干',
- 27050: '杩',
- 27054: '荣',
- 27058: '榅',
- 27071: '桤',
- 27083: '构',
- 27085: '枪',
- 27091: '杠',
- 27108: '梿',
- 27111: '椠',
- 27112: '椁',
- 27123: '桨',
- 27126: '椢',
- 27132: '椝',
- 27137: '桩',
- 27138: '乐',
- 27141: '枞',
- 27153: '梁',
- 27155: '楼',
- 27161: '标',
- 27166: '枢',
- 27170: '㭤',
- 27171: '样',
- 27179: '㭴',
- 27187: '桪',
- 27192: '朴',
- 27193: '树',
- 27194: '桦',
- 27199: '椫',
- 27208: '桡',
- 27211: '桥',
- 27231: '机',
- 27234: '椭',
- 27243: '横',
- 27265: '檩',
- 27273: '柽',
- 27284: '档',
- 27292: '桧',
- 27295: '槚',
- 27298: '检',
- 27299: '樯',
- 27309: '𣘴',
- 27310: '梼',
- 27311: '台',
- 27315: '槟',
- 27320: '柠',
- 27323: '槛',
- 27331: '柜',
- 27347: '橹',
- 27354: '榈',
- 27355: '栉',
- 27357: '椟',
- 27358: '橼',
- 27359: '栎',
- 27365: '橱',
- 27367: '槠',
- 27368: '栌',
- 27370: '枥',
- 27371: '橥',
- 27372: '榇',
- 27377: '蘖',
- 27379: '栊',
- 27384: '榉',
- 27387: '樱',
- 27396: '栏',
- 27397: '榉',
- 27402: '权',
- 27405: '𣐤',
- 27407: '椤',
- 27410: '栾',
- 27411: '𣗋',
- 27414: '榄',
- 27422: '棂',
- 27453: '钦',
- 27470: '叹',
- 27472: '欧',
- 27487: '欤',
- 27489: '欢',
- 27506: '岁',
- 27511: '历',
- 27512: '归',
- 27519: '殁',
- 27544: '残',
- 27550: '殒',
- 27556: '殇',
- 27560: '㱮',
- 27563: '殚',
- 27565: '僵',
- 27566: '殓',
- 27567: '殡',
- 27568: '㱩',
- 27570: '歼',
- 27578: '杀',
- 27579: '壳',
- 27580: '壳',
- 27584: '毁',
- 27590: '殴',
- 27647: '毵',
- 27650: '牦',
- 27656: '毡',
- 27660: '氇',
- 27683: '气',
- 27691: '氢',
- 27692: '氩',
- 27699: '氲',
- 27710: '泛',
- 27726: '泛',
- 27737: '污',
- 27770: '决',
- 27794: '没',
- 27798: '冲',
- 27841: '况',
- 27869: '溯',
- 27945: '泄',
- 27958: '汹',
- 28025: '浃',
- 28039: '泾',
- 28092: '凉',
- 28114: '凄',
- 28122: '泪',
- 28133: '渌',
- 28136: '净',
- 28137: '凌',
- 28138: '沦',
- 28149: '渊',
- 28150: '涞',
- 28154: '浅',
- 28185: '涣',
- 28187: '减',
- 28194: '沨',
- 28198: '涡',
- 28204: '测',
- 28222: '浑',
- 28234: '凑',
- 28254: '浈',
- 28263: '涌',
- 28271: '汤',
- 28296: '沩',
- 28310: '准',
- 28317: '沟',
- 28331: '温',
- 28334: '浉',
- 28339: '涢',
- 28348: '湿',
- 28356: '沧',
- 28357: '灭',
- 28364: '涤',
- 28366: '荥',
- 28377: '汇',
- 28396: '沪',
- 28399: '滞',
- 28402: '渗',
- 28407: '卤',
- 28408: '浒',
- 28411: '浐',
- 28414: '滚',
- 28415: '满',
- 28417: '渔',
- 28426: '溇',
- 28442: '沤',
- 28450: '汉',
- 28451: '涟',
- 28460: '渍',
- 28466: '涨',
- 28469: '溆',
- 28472: '渐',
- 28479: '浆',
- 28481: '颍',
- 28497: '泼',
- 28500: '洁',
- 28505: '沩',
- 28507: '潜',
- 28516: '润',
- 28527: '浔',
- 28528: '溃',
- 28535: '滗',
- 28543: '涠',
- 28544: '涩',
- 28549: '𣶩',
- 28550: '浇',
- 28551: '涝',
- 28560: '沄',
- 28567: '涧',
- 28576: '渑',
- 28580: '泽',
- 28582: '滪',
- 28585: '泶',
- 28590: '浍',
- 28593: '淀',
- 28606: '㳠',
- 28609: '浊',
- 28611: '浓',
- 28612: '㳡',
- 28614: '𣸣',
- 28629: '湿',
- 28632: '泞',
- 28635: '蒙',
- 28636: '浕',
- 28639: '济',
- 28644: '涛',
- 28647: '㳔',
- 28651: '滥',
- 28656: '潍',
- 28657: '滨',
- 28666: '溅',
- 28668: '泺',
- 28670: '滤',
- 28674: '澛',
- 28675: '𣽷',
- 28677: '滢',
- 28678: '渎',
- 28679: '㲿',
- 28681: '泻',
- 28683: '沈',
- 28687: '浏',
- 28693: '濒',
- 28696: '泸',
- 28701: '沥',
- 28703: '潇',
- 28704: '潆',
- 28710: '潴',
- 28711: '泷',
- 28712: '濑',
- 28720: '弥',
- 28722: '潋',
- 28734: '澜',
- 28739: '沣',
- 28740: '滠',
- 28753: '洒',
- 28757: '漓',
- 28760: '滩',
- 28761: '𣺼',
- 28765: '灏',
- 28768: '漤',
- 28769: '㳕',
- 28771: '湾',
- 28772: '滦',
- 28775: '滟',
- 28777: '滟',
- 28797: '灾',
- 28858: '为',
- 28879: '乌',
- 28916: '烃',
- 28961: '无',
- 29001: '炼',
- 29010: '炜',
- 29017: '烟',
- 29026: '茕',
- 29029: '焕',
- 29033: '烦',
- 29036: '炀',
- 29041: '㶽',
- 29061: '煴',
- 29065: '𤈶',
- 29068: '𤇄',
- 29074: '荧',
- 29075: '𤆡',
- 29079: '炝',
- 29089: '𤋏',
- 29105: '热',
- 29106: '颎',
- 29118: '炽',
- 29121: '烨',
- 29128: '灯',
- 29129: '炖',
- 29138: '烧',
- 29145: '烫',
- 29148: '焖',
- 29151: '营',
- 29158: '灿',
- 29164: '毁',
- 29165: '烛',
- 29172: '烩',
- 29174: '㶶',
- 29179: '熏',
- 29180: '烬',
- 29182: '焘',
- 29188: '𤇃',
- 29197: '烁',
- 29200: '炉',
- 29211: '烂',
- 29229: '争',
- 29234: '为',
- 29242: '爷',
- 29246: '尔',
- 29248: '床',
- 29254: '墙',
- 29272: '牍',
- 29309: '牵',
- 29334: '荦',
- 29346: '犊',
- 29351: '牺',
- 29376: '状',
- 29433: '狭',
- 29437: '狈',
- 29465: '狰',
- 29494: '犹',
- 29499: '狲',
- 29505: '犸',
- 29507: '呆',
- 29508: '狱',
- 29509: '狮',
- 29518: '奖',
- 29544: '独',
- 29546: '狯',
- 29547: '猃',
- 29550: '狝',
- 29552: '狞',
- 29553: '㺍',
- 29554: '获',
- 29557: '猎',
- 29559: '犷',
- 29560: '兽',
- 29562: '獭',
- 29563: '献',
- 29564: '猕',
- 29568: '猡',
- 29569: '𤞤',
- 29694: '现',
- 29745: '雕',
- 29754: '珐',
- 29759: '珲',
- 29771: '玮',
- 29778: '玚',
- 29795: '琐',
- 29796: '瑶',
- 29801: '莹',
- 29802: '玛',
- 29810: '玱',
- 29821: '𪻐',
- 29833: '琏',
- 29857: '琎',
- 29859: '玑',
- 29862: '瑷',
- 29867: '珰',
- 29871: '㻅',
- 29872: '环',
- 29885: '玺',
- 29898: '琼',
- 29903: '珑',
- 29908: '璎',
- 29909: '𤦀',
- 29914: '瓒',
- 29964: '瓯',
- 29973: '瓮',
- 29986: '产',
- 29987: '产',
- 29990: '苏',
- 29999: '宁',
- 30045: '亩',
- 30050: '毕',
- 30059: '画',
- 30064: '异',
- 30069: '画',
- 30070: '当',
- 30087: '畴',
- 30090: '叠',
- 30169: '痉',
- 30176: '酸',
- 30206: '疴',
- 30210: '痖',
- 30219: '疯',
- 30221: '疡',
- 30227: '痪',
- 30238: '瘗',
- 30241: '疮',
- 30247: '疟',
- 30254: '瘆',
- 30258: '疭',
- 30266: '瘘',
- 30267: '瘘',
- 30274: '疗',
- 30278: '痨',
- 30279: '痫',
- 30281: '瘅',
- 30290: '愈',
- 30296: '疠',
- 30303: '瘪',
- 30305: '痴',
- 30306: '痒',
- 30308: '疖',
- 30309: '症',
- 30311: '疬',
- 30313: '癞',
- 30316: '癣',
- 30317: '瘿',
- 30318: '瘾',
- 30320: '痈',
- 30321: '瘫',
- 30322: '癫',
- 30332: '发',
- 30337: '皂',
- 30362: '皑',
- 30367: '𤾀',
- 30384: '疱',
- 30392: '皲',
- 30394: '皱',
- 30403: '杯',
- 30428: '盗',
- 30430: '盏',
- 30433: '尽',
- 30435: '监',
- 30436: '盘',
- 30439: '卢',
- 30442: '荡',
- 30494: '真',
- 30501: '眦',
- 30526: '众',
- 30541: '𪾢',
- 30543: '困',
- 30556: '睁',
- 30558: '睐',
- 30570: '睾',
- 30616: '眍',
- 30620: '䁖',
- 30622: '瞒',
- 30628: '𥆧',
- 30646: '瞆',
- 30652: '睑',
- 30663: '蒙',
- 30675: '眬',
- 30682: '瞩',
- 30703: '矫',
- 30787: '朱',
- 30812: '硁',
- 30820: '硖',
- 30824: '砗',
- 30831: '砚',
- 30869: '埼',
- 30873: '𥐻',
- 30889: '硕',
- 30893: '砀',
- 30904: '砜',
- 30906: '确',
- 30908: '码',
- 30909: '䂵',
- 30929: '硙',
- 30938: '砖',
- 30944: '硵',
- 30947: '碜',
- 30951: '碛',
- 30959: '矶',
- 30973: '硗',
- 30980: '硚',
- 30982: '硷',
- 30990: '础',
- 30994: '𥐟',
- 31001: '碍',
- 31014: '矿',
- 31018: '砺',
- 31019: '砾',
- 31020: '矾',
- 31025: '砻',
- 31061: '秘',
- 31103: '禄',
- 31117: '祸',
- 31118: '祯',
- 31125: '祎',
- 31137: '祃',
- 31142: '御',
- 31146: '禅',
- 31150: '礼',
- 31152: '祢',
- 31153: '祷',
- 31167: '秃',
- 31176: '籼',
- 31237: '税',
- 31240: '秆',
- 31247: '䅉',
- 31260: '棱',
- 31263: '禀',
- 31278: '种',
- 31281: '称',
- 31296: '谷',
- 31308: '稣',
- 31309: '积',
- 31310: '颖',
- 31328: '秾',
- 31329: '穑',
- 31330: '秽',
- 31337: '稳',
- 31339: '获',
- 31341: '稆',
- 31401: '窝',
- 31402: '洼',
- 31406: '穷',
- 31407: '窑',
- 31413: '窎',
- 31414: '窭',
- 31418: '窥',
- 31428: '窜',
- 31429: '窍',
- 31431: '窦',
- 31432: '灶',
- 31434: '窃',
- 31466: '竖',
- 31478: '竞',
- 31558: '笔',
- 31565: '笋',
- 31591: '笕',
- 31604: '䇲',
- 31623: '个',
- 31627: '笺',
- 31631: '筝',
- 31680: '节',
- 31684: '范',
- 31689: '筑',
- 31691: '箧',
- 31700: '筼',
- 31704: '𥬠',
- 31716: '笃',
- 31721: '筛',
- 31731: '筚',
- 31744: '箦',
- 31757: '篓',
- 31761: '蓑',
- 31774: '箪',
- 31777: '简',
- 31779: '篑',
- 31787: '箫',
- 31801: '筜',
- 31805: '签',
- 31806: '帘',
- 31811: '篮',
- 31819: '𥬞',
- 31820: '筹',
- 31828: '䉤',
- 31833: '箓',
- 31835: '篯',
- 31836: '箨',
- 31839: '籁',
- 31840: '笼',
- 31844: '签',
- 31849: '笾',
- 31850: '簖',
- 31852: '篱',
- 31854: '箩',
- 31858: '吁',
- 31925: '粤',
- 31965: '糁',
- 31966: '粪',
- 31975: '粮',
- 31984: '团',
- 31986: '粝',
- 31988: '籴',
- 31990: '粜',
- 31993: '纟',
- 31998: '纠',
- 32000: '纪',
- 32002: '纣',
- 32004: '约',
- 32005: '红',
- 32006: '纡',
- 32007: '纥',
- 32008: '纨',
- 32009: '纫',
- 32011: '纹',
- 32013: '纳',
- 32016: '纽',
- 32019: '纾',
- 32020: '纯',
- 32021: '纰',
- 32022: '纼',
- 32023: '纱',
- 32024: '纮',
- 32025: '纸',
- 32026: '级',
- 32027: '纷',
- 32028: '纭',
- 32029: '纴',
- 32033: '纺',
- 32044: '䌷',
- 32046: '扎',
- 32048: '细',
- 32049: '绂',
- 32050: '绁',
- 32051: '绅',
- 32053: '纻',
- 32057: '绍',
- 32058: '绀',
- 32060: '绋',
- 32063: '绐',
- 32064: '绌',
- 32066: '终',
- 32067: '弦',
- 32068: '组',
- 32069: '䌹',
- 32070: '绊',
- 32078: '绗',
- 32080: '结',
- 32085: '绝',
- 32091: '绦',
- 32093: '绔',
- 32094: '绞',
- 32097: '络',
- 32098: '绚',
- 32102: '给',
- 32104: '绒',
- 32112: '绖',
- 32113: '统',
- 32114: '丝',
- 32115: '绛',
- 32118: '绝',
- 32121: '绢',
- 32122: '𫄨',
- 32128: '𦈌',
- 32129: '绑',
- 32131: '绡',
- 32134: '绠',
- 32135: '𦈋',
- 32136: '绨',
- 32137: '绣',
- 32140: '绤',
- 32143: '绥',
- 32144: '䌼',
- 32145: '捆',
- 32147: '经',
- 32156: '综',
- 32158: '缍',
- 32160: '绿',
- 32162: '绸',
- 32163: '绻',
- 32171: '线',
- 32172: '绶',
- 32173: '维',
- 32175: '绹',
- 32176: '绾',
- 32177: '纲',
- 32178: '网',
- 32179: '绷',
- 32180: '缀',
- 32181: '彩',
- 32184: '纶',
- 32185: '绺',
- 32186: '绮',
- 32187: '绽',
- 32189: '绰',
- 32190: '绫',
- 32191: '绵',
- 32196: '绲',
- 32199: '缁',
- 32202: '紧',
- 32203: '绯',
- 32205: '𦈏',
- 32209: '绿',
- 32210: '绪',
- 32211: '绬',
- 32212: '绱',
- 32215: '缃',
- 32216: '缄',
- 32217: '缂',
- 32218: '线',
- 32221: '缉',
- 32222: '缎',
- 32224: '缔',
- 32225: '缗',
- 32227: '缘',
- 32230: '缌',
- 32232: '编',
- 32233: '缓',
- 32236: '缅',
- 32239: '纬',
- 32240: '𦈕',
- 32241: '缑',
- 32242: '缈',
- 32244: '练',
- 32246: '缏',
- 32247: '𦈉',
- 32248: '𦈑',
- 32249: '缇',
- 32251: '致',
- 32264: '萦',
- 32265: '缙',
- 32266: '缢',
- 32267: '缒',
- 32270: '𦈔',
- 32272: '绉',
- 32273: '缣',
- 32277: '缊',
- 32279: '缞',
- 32283: '缚',
- 32285: '缜',
- 32286: '缟',
- 32287: '缛',
- 32291: '县',
- 32295: '绦',
- 32299: '缝',
- 32300: '𦈚',
- 32301: '缡',
- 32302: '缩',
- 32305: '纵',
- 32306: '缧',
- 32307: '䌸',
- 32308: '纤',
- 32309: '缦',
- 32310: '絷',
- 32311: '缕',
- 32313: '缥',
- 32314: '𦈐',
- 32317: '总',
- 32318: '绩',
- 32323: '绷',
- 32325: '缫',
- 32326: '缪',
- 32335: '𦈝',
- 32336: '穗',
- 32338: '缯',
- 32339: '𦈛',
- 32340: '织',
- 32341: '缮',
- 32346: '缭',
- 32350: '绕',
- 32351: '𦈎',
- 32353: '绣',
- 32354: '缋',
- 32361: '绳',
- 32362: '绘',
- 32363: '系',
- 32365: '茧',
- 32366: '缰',
- 32367: '缳',
- 32368: '缲',
- 32371: '缴',
- 32376: '䍁',
- 32377: '绎',
- 32379: '𦈡',
- 32380: '继',
- 32381: '缤',
- 32382: '缱',
- 32383: '䍀',
- 32385: '𫄸',
- 32391: '颣',
- 32392: '缬',
- 32394: '纩',
- 32396: '续',
- 32397: '累',
- 32399: '缠',
- 32403: '缨',
- 32404: '才',
- 32406: '纤',
- 32408: '缵',
- 32412: '缆',
- 32573: '钵',
- 32584: '坛',
- 32588: '罂',
- 32590: '坛',
- 32624: '罚',
- 32629: '骂',
- 32631: '罢',
- 32645: '罗',
- 32646: '罴',
- 32648: '羁',
- 32651: '芈',
- 32675: '群',
- 32677: '羟',
- 32680: '羡',
- 32681: '义',
- 32694: '膻',
- 32722: '习',
- 32748: '翚',
- 32761: '翘',
- 32765: '翙',
- 32812: '耧',
- 32814: '耢',
- 32854: '圣',
- 32862: '闻',
- 32879: '联',
- 32880: '聪',
- 32882: '声',
- 32883: '耸',
- 32885: '聩',
- 32886: '聂',
- 32887: '职',
- 32889: '聍',
- 32893: '听',
- 32894: '聋',
- 32901: '肃',
- 33029: '胁',
- 33032: '脉',
- 33051: '胫',
- 33059: '唇',
- 33061: '𣍰',
- 33065: '修',
- 33067: '脱',
- 33081: '胀',
- 33102: '肾',
- 33110: '胨',
- 33121: '脶',
- 33126: '脑',
- 33130: '𣍯',
- 33131: '肿',
- 33139: '脚',
- 33144: '肠',
- 33155: '腽',
- 33173: '腘',
- 33178: '肤',
- 33184: '胶',
- 33186: '𦝼',
- 33193: '腻',
- 33213: '胆',
- 33214: '脍',
- 33215: '脓',
- 33225: '脸',
- 33229: '脐',
- 33231: '膑',
- 33239: '𣎑',
- 33240: '腊',
- 33242: '胪',
- 33247: '脏',
- 33248: '脔',
- 33250: '臜',
- 33253: '卧',
- 33256: '临',
- 33274: '台',
- 33287: '与',
- 33288: '兴',
- 33289: '举',
- 33290: '旧',
- 33304: '馆',
- 33369: '舱',
- 33380: '舣',
- 33382: '舰',
- 33387: '舻',
- 33393: '艰',
- 33399: '艳',
- 33467: '刍',
- 33511: '苎',
- 33586: '兹',
- 33610: '荆',
- 33674: '庄',
- 33686: '茎',
- 33698: '荚',
- 33703: '苋',
- 33775: '华',
- 33780: '庵',
- 33784: '烟',
- 33799: '苌',
- 33802: '莱',
- 33836: '万',
- 33844: '荝',
- 33845: '莴',
- 33865: '叶',
- 33874: '荭',
- 33892: '荮',
- 33894: '苇',
- 33903: '药',
- 33911: '荤',
- 33936: '搜',
- 33939: '莼',
- 33940: '莳',
- 33950: '莅',
- 33980: '苍',
- 33984: '荪',
- 33990: '席',
- 33995: '盖',
- 34030: '莲',
- 34031: '苁',
- 34036: '莼',
- 34045: '荜',
- 34068: '卜',
- 34072: '参',
- 34078: '蒌',
- 34083: '蒋',
- 34085: '葱',
- 34086: '茑',
- 34093: '荫',
- 34113: '荨',
- 34118: '蒇',
- 34126: '荞',
- 34130: '荬',
- 34131: '芸',
- 34133: '莸',
- 34136: '荛',
- 34146: '蒉',
- 34153: '荡',
- 34154: '芜',
- 34157: '萧',
- 34167: '蓣',
- 34176: '蕰',
- 34184: '荟',
- 34186: '蓟',
- 34188: '芗',
- 34193: '姜',
- 34196: '蔷',
- 34200: '荙',
- 34207: '莶',
- 34214: '荐',
- 34217: '萨',
- 34227: '䓕',
- 34228: '苧',
- 34233: '苔',
- 34234: '荠',
- 34253: '蓝',
- 34254: '荩',
- 34269: '艺',
- 34277: '药',
- 34282: '薮',
- 34292: '蕴',
- 34294: '苈',
- 34297: '蔼',
- 34298: '蔺',
- 34308: '蕲',
- 34310: '芦',
- 34311: '苏',
- 34314: '蕴',
- 34315: '苹',
- 34330: '藓',
- 34334: '蔹',
- 34338: '茏',
- 34349: '兰',
- 34362: '蓠',
- 34367: '萝',
- 34374: '蔂',
- 34389: '处',
- 34395: '虚',
- 34396: '虏',
- 34399: '号',
- 34407: '亏',
- 34415: '虬',
- 34554: '蛱',
- 34555: '蜕',
- 34566: '蚬',
- 34645: '蚀',
- 34655: '猬',
- 34662: '虾',
- 34680: '蜗',
- 34692: '蛳',
- 34718: '蚂',
- 34722: '萤',
- 34734: '䗖',
- 34747: '蝼',
- 34751: '螀',
- 34756: '蛰',
- 34760: '蝈',
- 34766: '螨',
- 34787: '虮',
- 34796: '蝉',
- 34799: '蛲',
- 34802: '虫',
- 34806: '蛏',
- 34811: '蚁',
- 34817: '蚃',
- 34821: '蝇',
- 34822: '虿',
- 34829: '蝎',
- 34832: '蛴',
- 34833: '蝾',
- 34847: '蜡',
- 34851: '蛎',
- 34856: '蟏',
- 34865: '蛊',
- 34870: '蚕',
- 34875: '蛮',
- 34886: '众',
- 34890: '蔑',
- 34899: '术',
- 34901: '同',
- 34906: '胡',
- 34907: '卫',
- 34909: '冲',
- 34974: '衮',
- 35018: '袅',
- 35023: '里',
- 35036: '补',
- 35037: '装',
- 35041: '里',
- 35069: '制',
- 35079: '复',
- 35084: '裈',
- 35096: '袆',
- 35122: '裤',
- 35123: '裢',
- 35128: '褛',
- 35131: '亵',
- 35136: '𫌀',
- 35142: '幞',
- 35143: '裥',
- 35145: '裥',
- 35151: '袯',
- 35158: '袄',
- 35165: '裣',
- 35168: '裆',
- 35172: '褴',
- 35178: '袜',
- 35180: '摆',
- 35183: '衬',
- 35186: '袭',
- 35188: '襕',
- 35208: '核',
- 35211: '见',
- 35214: '觃',
- 35215: '规',
- 35219: '觅',
- 35222: '视',
- 35224: '觇',
- 35233: '觋',
- 35237: '觍',
- 35238: '觎',
- 35242: '亲',
- 35244: '觊',
- 35247: '觏',
- 35250: '觐',
- 35255: '觑',
- 35258: '觉',
- 35260: '𫌨',
- 35261: '览',
- 35263: '觌',
- 35264: '观',
- 35316: '觞',
- 35318: '觯',
- 35320: '触',
- 35329: '讠',
- 35330: '订',
- 35331: '讣',
- 35336: '计',
- 35338: '讯',
- 35340: '讧',
- 35342: '讨',
- 35344: '讦',
- 35345: '𫍙',
- 35346: '讱',
- 35347: '训',
- 35349: '讪',
- 35350: '讫',
- 35351: '托',
- 35352: '记',
- 35355: '讹',
- 35357: '讶',
- 35359: '讼',
- 35362: '䜣',
- 35363: '诀',
- 35365: '讷',
- 35369: '讻',
- 35370: '访',
- 35373: '设',
- 35377: '许',
- 35380: '诉',
- 35382: '诃',
- 35386: '诊',
- 35387: '注',
- 35392: '𧮪',
- 35393: '诂',
- 35398: '诋',
- 35406: '讵',
- 35408: '诈',
- 35409: '𫍟',
- 35410: '诒',
- 35412: '诏',
- 35413: '评',
- 35414: '诐',
- 35415: '诇',
- 35416: '诎',
- 35419: '诅',
- 35422: '词',
- 35424: '咏',
- 35425: '诩',
- 35426: '询',
- 35427: '诣',
- 35430: '试',
- 35433: '诗',
- 35435: '诧',
- 35436: '诟',
- 35437: '诡',
- 35438: '诠',
- 35440: '诘',
- 35441: '话',
- 35442: '该',
- 35443: '详',
- 35445: '诜',
- 35452: '诙',
- 35455: '诖',
- 35460: '诔',
- 35461: '诛',
- 35462: '诓',
- 35463: '夸',
- 35468: '志',
- 35469: '认',
- 35473: '诳',
- 35474: '诶',
- 35477: '诞',
- 35480: '诱',
- 35482: '诮',
- 35486: '语',
- 35488: '诚',
- 35489: '诫',
- 35491: '诬',
- 35492: '误',
- 35493: '诰',
- 35494: '诵',
- 35496: '诲',
- 35498: '说',
- 35500: '说',
- 35504: '谁',
- 35506: '课',
- 35510: '谇',
- 35513: '诽',
- 35516: '谊',
- 35518: '訚',
- 35519: '调',
- 35522: '谄',
- 35524: '谆',
- 35527: '谈',
- 35529: '诿',
- 35531: '请',
- 35533: '诤',
- 35535: '诹',
- 35537: '诼',
- 35538: '谅',
- 35542: '论',
- 35543: '谂',
- 35547: '谀',
- 35548: '谍',
- 35549: '谞',
- 35550: '谝',
- 35553: '谥',
- 35554: '诨',
- 35556: '谔',
- 35558: '谛',
- 35559: '谐',
- 35563: '谏',
- 35565: '谕',
- 35566: '咨',
- 35568: '𫍰',
- 35569: '讳',
- 35571: '谙',
- 35574: '谌',
- 35575: '讽',
- 35576: '诸',
- 35578: '谚',
- 35580: '谖',
- 35582: '诺',
- 35584: '谋',
- 35585: '谒',
- 35586: '谓',
- 35588: '誊',
- 35589: '诌',
- 35594: '谎',
- 35598: '谜',
- 35599: '𫍲',
- 35600: '谧',
- 35604: '谑',
- 35606: '谡',
- 35607: '谤',
- 35609: '谦',
- 35610: '谥',
- 35611: '讲',
- 35613: '谢',
- 35616: '谣',
- 35617: '谣',
- 35624: '谟',
- 35627: '谪',
- 35628: '谬',
- 35629: '谫',
- 35635: '讴',
- 35641: '谨',
- 35646: '谩',
- 35649: '哗',
- 35653: '䜧',
- 35657: '证',
- 35658: '𫍢',
- 35662: '谲',
- 35663: '讥',
- 35670: '谮',
- 35672: '识',
- 35673: '谯',
- 35674: '谭',
- 35676: '谱',
- 35679: '噪',
- 35691: '谵',
- 35693: '毁',
- 35695: '译',
- 35696: '议',
- 35700: '谴',
- 35703: '护',
- 35704: '诪',
- 35709: '誉',
- 35710: '谫',
- 35712: '读',
- 35722: '变',
- 35723: '詟',
- 35724: '䜩',
- 35726: '雠',
- 35730: '谗',
- 35731: '让',
- 35733: '谰',
- 35734: '谶',
- 35738: '赞',
- 35740: '谠',
- 35742: '谳',
- 35912: '岂',
- 35918: '竖',
- 35920: '丰',
- 35924: '艳',
- 35948: '猪',
- 35958: '豮',
- 35987: '猫',
- 35993: '䝙',
- 35997: '贝',
- 35998: '贞',
- 35999: '贠',
- 36000: '负',
- 36001: '财',
- 36002: '贡',
- 36007: '贫',
- 36008: '货',
- 36009: '贩',
- 36010: '贪',
- 36011: '贯',
- 36012: '责',
- 36015: '贮',
- 36016: '贳',
- 36018: '赀',
- 36019: '贰',
- 36020: '贵',
- 36022: '贬',
- 36023: '买',
- 36024: '贷',
- 36026: '贶',
- 36027: '费',
- 36028: '贴',
- 36029: '贻',
- 36031: '贸',
- 36032: '贺',
- 36033: '贲',
- 36034: '赂',
- 36035: '赁',
- 36036: '贿',
- 36037: '赅',
- 36039: '资',
- 36040: '贾',
- 36042: '贼',
- 36049: '赈',
- 36050: '赊',
- 36051: '宾',
- 36053: '赇',
- 36057: '赒',
- 36058: '赉',
- 36060: '赐',
- 36062: '赏',
- 36063: '𧹖',
- 36064: '赔',
- 36065: '赓',
- 36066: '贤',
- 36067: '卖',
- 36068: '贱',
- 36070: '赋',
- 36071: '赕',
- 36074: '质',
- 36075: '赍',
- 36076: '账',
- 36077: '赌',
- 36080: '䞐',
- 36084: '赖',
- 36085: '赗',
- 36090: '赚',
- 36091: '赙',
- 36092: '购',
- 36093: '赛',
- 36094: '赜',
- 36099: '𧹗',
- 36100: '贽',
- 36101: '赘',
- 36103: '赟',
- 36104: '赠',
- 36106: '赞',
- 36107: '赝',
- 36109: '赡',
- 36111: '赢',
- 36112: '赆',
- 36115: '赃',
- 36116: '赑',
- 36118: '赎',
- 36119: '赝',
- 36123: '赣',
- 36124: '赃',
- 36204: '赪',
- 36245: '赶',
- 36249: '赵',
- 36264: '趋',
- 36274: '趱',
- 36321: '迹',
- 36368: '践',
- 36400: '逾',
- 36404: '踊',
- 36428: '跄',
- 36437: '跸',
- 36447: '迹',
- 36451: '蹒',
- 36452: '踪',
- 36474: '跷',
- 36475: '𫏋',
- 36482: '跶',
- 36489: '趸',
- 36490: '踌',
- 36491: '跻',
- 36493: '跃',
- 36494: '䟢',
- 36497: '踯',
- 36498: '跞',
- 36499: '踬',
- 36501: '蹰',
- 36506: '跹',
- 36509: '𨅬',
- 36513: '蹑',
- 36517: '蹿',
- 36518: '躜',
- 36522: '躏',
- 36544: '躯',
- 36553: '𨉗',
- 36554: '车',
- 36555: '轧',
- 36556: '轨',
- 36557: '军',
- 36559: '𫐄',
- 36561: '轪',
- 36562: '轩',
- 36564: '轫',
- 36567: '𨐅',
- 36571: '轭',
- 36575: '软',
- 36580: '轷',
- 36584: '𫐉',
- 36587: '轸',
- 36594: '轱',
- 36600: '轴',
- 36601: '轵',
- 36602: '轺',
- 36603: '轲',
- 36604: '轶',
- 36606: '轼',
- 36611: '较',
- 36612: '𨐈',
- 36613: '辂',
- 36615: '辁',
- 36616: '辀',
- 36617: '载',
- 36618: '轾',
- 36626: '辄',
- 36627: '挽',
- 36628: '辅',
- 36629: '轻',
- 36631: '𫐐',
- 36635: '辆',
- 36636: '辎',
- 36637: '辉',
- 36638: '辋',
- 36639: '辍',
- 36645: '辊',
- 36646: '辇',
- 36649: '辈',
- 36650: '轮',
- 36652: '辌',
- 36654: '𫐓',
- 36655: '辑',
- 36659: '辏',
- 36664: '输',
- 36667: '辐',
- 36670: '辗',
- 36671: '舆',
- 36672: '辒',
- 36674: '毂',
- 36676: '辖',
- 36677: '辕',
- 36678: '辘',
- 36681: '转',
- 36685: '辙',
- 36686: '轿',
- 36692: '辚',
- 36703: '轰',
- 36705: '辔',
- 36706: '轹',
- 36707: '𫐆',
- 36708: '轳',
- 36774: '办',
- 36781: '辞',
- 36782: '辫',
- 36783: '辩',
- 36786: '农',
- 36852: '回',
- 36885: '迳',
- 36889: '这',
- 36899: '连',
- 36913: '周',
- 36914: '进',
- 36938: '游',
- 36939: '运',
- 36942: '过',
- 36948: '达',
- 36949: '违',
- 36953: '遥',
- 36956: '逊',
- 36958: '递',
- 36960: '远',
- 36961: '溯',
- 36969: '适',
- 36978: '迟',
- 36983: '迁',
- 36984: '选',
- 36986: '遗',
- 36988: '辽',
- 36993: '迈',
- 36996: '还',
- 36999: '迩',
- 37002: '边',
- 37007: '逻',
- 37008: '逦',
- 37087: '郏',
- 37109: '邮',
- 37126: '郓',
- 37129: '乡',
- 37138: '邹',
- 37140: '邬',
- 37142: '郧',
- 37159: '邓',
- 37165: '郑',
- 37168: '邻',
- 37170: '郸',
- 37172: '邺',
- 37174: '郐',
- 37178: '邝',
- 37191: '酂',
- 37192: '郦',
- 37251: '腌',
- 37270: '酝',
- 37276: '丑',
- 37278: '酝',
- 37283: '糖',
- 37291: '医',
- 37292: '酱',
- 37297: '酦',
- 37312: '酿',
- 37313: '衅',
- 37315: '酾',
- 37317: '酽',
- 37323: '释',
- 37328: '厘',
- 37330: '钅',
- 37331: '钆',
- 37332: '钇',
- 37333: '钌',
- 37335: '钊',
- 37336: '钉',
- 37337: '钋',
- 37341: '针',
- 37347: '钓',
- 37348: '钐',
- 37350: '扣',
- 37351: '钏',
- 37353: '钒',
- 37363: '𨰿',
- 37365: '钗',
- 37367: '钍',
- 37369: '钕',
- 37370: '钎',
- 37374: '䥺',
- 37376: '钯',
- 37377: '钫',
- 37379: '钘',
- 37380: '钭',
- 37383: '𫓧',
- 37384: '钚',
- 37385: '钠',
- 37387: '𨱂',
- 37389: '钝',
- 37390: '钩',
- 37392: '钤',
- 37393: '钣',
- 37394: '钑',
- 37396: '钞',
- 37397: '钮',
- 37406: '钧',
- 37408: '𨱁',
- 37411: '钙',
- 37413: '钬',
- 37414: '钛',
- 37415: '钪',
- 37422: '铌',
- 37423: '𨱄',
- 37424: '铈',
- 37426: '𨱃',
- 37427: '钶',
- 37428: '铃',
- 37431: '钴',
- 37432: '钹',
- 37433: '铍',
- 37434: '钰',
- 37437: '钸',
- 37438: '铀',
- 37439: '钿',
- 37440: '钾',
- 37441: '𨱅',
- 37445: '巨',
- 37448: '铊',
- 37449: '铉',
- 37451: '铇',
- 37453: '铋',
- 37457: '铂',
- 37461: '钷',
- 37463: '钳',
- 37466: '铆',
- 37467: '铅',
- 37470: '钺',
- 37474: '钵',
- 37476: '钩',
- 37478: '钲',
- 37484: '钼',
- 37485: '钽',
- 37494: '铏',
- 37496: '铰',
- 37498: '铒',
- 37499: '铬',
- 37503: '铪',
- 37504: '银',
- 37507: '铳',
- 37509: '铜',
- 37517: '铚',
- 37521: '铣',
- 37523: '铨',
- 37526: '铢',
- 37528: '铭',
- 37530: '铫',
- 37531: '铦',
- 37532: '衔',
- 37536: '铑',
- 37539: '铷',
- 37541: '铱',
- 37542: '铟',
- 37544: '铵',
- 37545: '铥',
- 37546: '铕',
- 37547: '铯',
- 37548: '铐',
- 37553: '铞',
- 37555: '锐',
- 37558: '𨱇',
- 37559: '销',
- 37561: '锈',
- 37563: '锑',
- 37564: '锉',
- 37569: '铝',
- 37571: '锒',
- 37573: '锌',
- 37575: '钡',
- 37577: '𨱈',
- 37580: '铤',
- 37583: '铗',
- 37586: '锋',
- 37593: '铻',
- 37597: '锊',
- 37599: '锓',
- 37603: '铘',
- 37604: '锄',
- 37605: '锃',
- 37606: '锔',
- 37608: '锇',
- 37609: '铓',
- 37610: '铺',
- 37613: '锐',
- 37614: '铖',
- 37615: '锆',
- 37616: '锂',
- 37617: '铽',
- 37622: '锍',
- 37624: '锯',
- 37628: '钢',
- 37633: '锞',
- 37634: '𨱋',
- 37636: '录',
- 37638: '锖',
- 37639: '锫',
- 37640: '锩',
- 37647: '铔',
- 37648: '锥',
- 37650: '锕',
- 37653: '锟',
- 37656: '锤',
- 37657: '锱',
- 37658: '铮',
- 37659: '锛',
- 37663: '锬',
- 37664: '锭',
- 37665: '锜',
- 37666: '钱',
- 37670: '锦',
- 37672: '锚',
- 37673: '锠',
- 37675: '锡',
- 37678: '锢',
- 37679: '错',
- 37682: '录',
- 37683: '锰',
- 37686: '表',
- 37688: '铼',
- 37696: '锝',
- 37697: '锨',
- 37699: '锪',
- 37700: '𨱉',
- 37702: '钔',
- 37703: '锴',
- 37704: '锳',
- 37706: '炼',
- 37707: '锅',
- 37709: '镀',
- 37716: '锷',
- 37720: '铡',
- 37722: '钖',
- 37723: '锻',
- 37728: '锽',
- 37732: '锸',
- 37733: '锲',
- 37737: '锘',
- 37740: '锹',
- 37742: '𨱎',
- 37744: '锾',
- 37749: '键',
- 37750: '锶',
- 37754: '锗',
- 37756: '针',
- 37758: '钟',
- 37762: '镁',
- 37764: '锿',
- 37767: '镅',
- 37770: '镑',
- 37772: '镰',
- 37780: '镕',
- 37782: '锁',
- 37784: '镉',
- 37786: '锤',
- 37787: '镈',
- 37789: '𨱏',
- 37793: '镃',
- 37794: '钨',
- 37795: '蓥',
- 37798: '镏',
- 37799: '铠',
- 37801: '铩',
- 37802: '锼',
- 37804: '镐',
- 37805: '鎮',
- 37806: '镇',
- 37807: '𨱍',
- 37808: '镒',
- 37810: '镋',
- 37811: '镍',
- 37813: '镓',
- 37815: '𨰾',
- 37816: '镌',
- 37823: '镎',
- 37827: '镞',
- 37830: '𨱌',
- 37831: '镟',
- 37832: '链',
- 37833: '𨱒',
- 37836: '镆',
- 37837: '镙',
- 37840: '镠',
- 37841: '镝',
- 37847: '铿',
- 37848: '锵',
- 37850: '戚',
- 37852: '镗',
- 37853: '镘',
- 37854: '镛',
- 37855: '铲',
- 37857: '镜',
- 37858: '镖',
- 37860: '镂',
- 37862: '𫓩',
- 37864: '錾',
- 37872: '镚',
- 37877: '铧',
- 37879: '镤',
- 37881: '镪',
- 37882: '䥽',
- 37885: '锈',
- 37891: '铙',
- 37892: '𨱑',
- 37899: '铴',
- 37901: '𫔎',
- 37902: '𨱓',
- 37903: '𨱔',
- 37904: '镣',
- 37906: '铹',
- 37907: '镦',
- 37908: '镡',
- 37912: '钟',
- 37913: '镫',
- 37917: '镢',
- 37920: '镨',
- 37925: '䦅',
- 37926: '锎',
- 37927: '锏',
- 37928: '镄',
- 37931: '镌',
- 37934: '镰',
- 37935: '䦃',
- 37938: '镯',
- 37939: '镭',
- 37941: '铁',
- 37942: '镮',
- 37944: '铎',
- 37946: '铛',
- 37951: '镱',
- 37956: '铸',
- 37962: '镬',
- 37964: '镔',
- 37969: '鉴',
- 37970: '鉴',
- 37972: '镲',
- 37973: '锧',
- 37982: '镴',
- 37984: '铄',
- 37987: '镳',
- 37989: '镥',
- 37997: '镧',
- 38000: '钥',
- 38001: '镵',
- 38002: '镶',
- 38007: '镊',
- 38009: '镩',
- 38012: '锣',
- 38013: '钻',
- 38014: '銮',
- 38015: '凿',
- 38017: '镢',
- 38239: '旋',
- 38263: '长',
- 38272: '门',
- 38274: '闩',
- 38275: '闪',
- 38278: '闫',
- 38280: '闬',
- 38281: '闭',
- 38283: '开',
- 38284: '闶',
- 38285: '𨸂',
- 38286: '闳',
- 38287: '闰',
- 38288: '𨸃',
- 38289: '闲',
- 38290: '闲',
- 38291: '间',
- 38292: '闵',
- 38296: '闸',
- 38305: '阂',
- 38307: '阁',
- 38308: '合',
- 38309: '阀',
- 38312: '闺',
- 38313: '闽',
- 38315: '阃',
- 38316: '阆',
- 38317: '闾',
- 38321: '阅',
- 38322: '阅',
- 38326: '阊',
- 38329: '阉',
- 38331: '阎',
- 38332: '阏',
- 38333: '阍',
- 38334: '阈',
- 38335: '阌',
- 38339: '阒',
- 38342: '板',
- 38343: '暗',
- 38344: '闱',
- 38346: '阔',
- 38347: '阕',
- 38348: '阑',
- 38349: '阇',
- 38352: '阗',
- 38354: '阘',
- 38355: '闿',
- 38356: '阖',
- 38357: '阙',
- 38358: '闯',
- 38364: '关',
- 38366: '阚',
- 38368: '阓',
- 38369: '阐',
- 38370: '辟',
- 38372: '阛',
- 38373: '闼',
- 38488: '陉',
- 38493: '陕',
- 38494: '升',
- 38499: '阵',
- 38512: '阴',
- 38515: '陈',
- 38520: '陆',
- 38525: '阳',
- 38537: '陧',
- 38538: '队',
- 38542: '阶',
- 38549: '陨',
- 38555: '际',
- 38568: '随',
- 38570: '险',
- 38577: '隐',
- 38580: '陇',
- 38584: '隶',
- 38587: '只',
- 38603: '隽',
- 38614: '虽',
- 38617: '双',
- 38619: '雏',
- 38620: '杂',
- 38622: '鸡',
- 38626: '离',
- 38627: '难',
- 38642: '云',
- 38651: '电',
- 38690: '霡',
- 38695: '雾',
- 38717: '霁',
- 38722: '雳',
- 38724: '霭',
- 38728: '灵',
- 38729: '叆',
- 38746: '靓',
- 38748: '静',
- 38758: '腼',
- 38760: '靥',
- 38784: '鼗',
- 38799: '巩',
- 38813: '绱',
- 38822: '秋',
- 38845: '鞒',
- 38849: '缰',
- 38851: '鞑',
- 38854: '千',
- 38857: '鞯',
- 38859: '韦',
- 38860: '韧',
- 38861: '韨',
- 38867: '韩',
- 38873: '韪',
- 38876: '韬',
- 38877: '鞲',
- 38878: '韫',
- 38907: '韵',
- 38911: '响',
- 38913: '页',
- 38914: '顶',
- 38915: '顷',
- 38917: '项',
- 38918: '顺',
- 38919: '顸',
- 38920: '须',
- 38922: '顼',
- 38924: '颂',
- 38926: '颀',
- 38927: '颃',
- 38928: '预',
- 38929: '顽',
- 38930: '颁',
- 38931: '顿',
- 38935: '颇',
- 38936: '领',
- 38940: '颌',
- 38945: '颉',
- 38948: '颐',
- 38950: '颏',
- 38957: '头',
- 38958: '颒',
- 38960: '颊',
- 38962: '颋',
- 38964: '颕',
- 38967: '颔',
- 38968: '颈',
- 38969: '颓',
- 38971: '频',
- 38973: '颓',
- 38979: '𩖖',
- 38982: '颗',
- 38988: '题',
- 38989: '额',
- 38990: '颚',
- 38991: '颜',
- 38994: '颙',
- 38995: '颛',
- 38996: '颜',
- 39000: '愿',
- 39001: '颡',
- 39003: '颠',
- 39006: '类',
- 39010: '颟',
- 39013: '颢',
- 39015: '顾',
- 39019: '颤',
- 39020: '颥',
- 39023: '显',
- 39024: '颦',
- 39025: '颅',
- 39027: '颞',
- 39028: '颧',
- 39080: '风',
- 39085: '飐',
- 39086: '飑',
- 39087: '飒',
- 39088: '𩙥',
- 39089: '台',
- 39091: '刮',
- 39094: '飓',
- 39095: '𩙪',
- 39096: '飔',
- 39098: '飏',
- 39099: '飖',
- 39100: '飕',
- 39102: '𩙫',
- 39104: '飗',
- 39108: '飘',
- 39110: '飙',
- 39112: '飚',
- 39131: '飞',
- 39136: '饣',
- 39138: '饥',
- 39139: '饤',
- 39141: '饦',
- 39145: '饨',
- 39146: '饪',
- 39147: '饫',
- 39149: '饬',
- 39151: '饭',
- 39153: '飧',
- 39154: '饮',
- 39156: '饴',
- 39164: '饲',
- 39165: '饱',
- 39166: '饰',
- 39167: '饳',
- 39171: '饺',
- 39172: '饸',
- 39173: '饼',
- 39177: '饷',
- 39178: '养',
- 39180: '饵',
- 39182: '饹',
- 39183: '饻',
- 39185: '饽',
- 39186: '馁',
- 39187: '饿',
- 39188: '𫗦',
- 39189: '馂',
- 39190: '饾',
- 39191: '𫗧',
- 39192: '余',
- 39194: '肴',
- 39195: '馄',
- 39196: '馃',
- 39198: '饯',
- 39201: '馅',
- 39206: '𫗠',
- 39208: '馆',
- 39213: '𫗮',
- 39217: '糇',
- 39219: '饧',
- 39221: '喂',
- 39222: '馉',
- 39223: '馇',
- 39224: '𩠌',
- 39226: '馎',
- 39228: '饩',
- 39230: '馏',
- 39231: '馊',
- 39233: '馌',
- 39235: '馍',
- 39237: '馒',
- 39240: '馐',
- 39241: '馑',
- 39242: '馓',
- 39243: '馈',
- 39244: '馔',
- 39249: '饥',
- 39250: '饶',
- 39255: '飨',
- 39256: '𫗴',
- 39260: '餍',
- 39262: '馋',
- 39266: '馕',
- 39340: '马',
- 39341: '驭',
- 39342: '冯',
- 39345: '驮',
- 39347: '驰',
- 39348: '驯',
- 39353: '驲',
- 39361: '驳',
- 39363: '𫘝',
- 39374: '𩧨',
- 39376: '驻',
- 39377: '驽',
- 39378: '驹',
- 39380: '驵',
- 39381: '驾',
- 39384: '骀',
- 39385: '驸',
- 39386: '𩧫',
- 39387: '驶',
- 39389: '驼',
- 39391: '驷',
- 39393: '骂',
- 39394: '骈',
- 39399: '𩧲',
- 39401: '𩧴',
- 39405: '骇',
- 39408: '骃',
- 39409: '骆',
- 39414: '𩧺',
- 39416: '骎',
- 39419: '𫘣',
- 39423: '骏',
- 39425: '骋',
- 39426: '骍',
- 39427: '𫘤',
- 39429: '骓',
- 39436: '骔',
- 39437: '骒',
- 39438: '骑',
- 39439: '骐',
- 39444: '𩨀',
- 39446: '骛',
- 39449: '骗',
- 39450: '𩨊',
- 39453: '𩨃',
- 39455: '𩨈',
- 39456: '𫘨',
- 39460: '骙',
- 39463: '䯄',
- 39466: '𩨄',
- 39467: '骞',
- 39469: '骘',
- 39470: '骝',
- 39472: '腾',
- 39478: '驺',
- 39479: '骚',
- 39480: '骟',
- 39486: '骡',
- 39488: '蓦',
- 39489: '骜',
- 39490: '骖',
- 39491: '骠',
- 39492: '骢',
- 39493: '驱',
- 39498: '骅',
- 39499: '𩧯',
- 39500: '骕',
- 39501: '骁',
- 39503: '骣',
- 39509: '骄',
- 39511: '验',
- 39514: '惊',
- 39515: '驿',
- 39519: '骤',
- 39522: '驴',
- 39524: '骧',
- 39525: '骥',
- 39526: '骦',
- 39530: '骊',
- 39531: '骉',
- 39599: '肮',
- 39631: '髅',
- 39634: '脏',
- 39636: '体',
- 39637: '髌',
- 39638: '髋',
- 39662: '发',
- 39686: '松',
- 39693: '胡',
- 39706: '须',
- 39714: '鬓',
- 39717: '斗',
- 39719: '闹',
- 39720: '哄',
- 39721: '阋',
- 39726: '阄',
- 39729: '郁',
- 39737: '鬶',
- 39758: '魉',
- 39768: '魇',
- 39770: '鱼',
- 39771: '鱽',
- 39775: '𫚉',
- 39778: '鱾',
- 39781: '𩽹',
- 39784: '鲀',
- 39791: '鲁',
- 39796: '鲂',
- 39799: '鱿',
- 39802: '鲄',
- 39809: '鲅',
- 39811: '鲆',
- 39812: '𫚒',
- 39818: '鲌',
- 39819: '鲉',
- 39821: '鲏',
- 39822: '鲇',
- 39824: '鲐',
- 39825: '鲍',
- 39826: '鲋',
- 39827: '鲊',
- 39829: '𩾀',
- 39834: '鲒',
- 39836: '鲘',
- 39837: '鲞',
- 39838: '鲕',
- 39839: '𩽾',
- 39843: '䲟',
- 39846: '鲖',
- 39850: '鲔',
- 39851: '鲛',
- 39853: '鲑',
- 39854: '鲜',
- 39856: '𫚔',
- 39859: '鲓',
- 39862: '鲪',
- 39864: '𩾃',
- 39866: '鲝',
- 39872: '鲧',
- 39873: '鲠',
- 39876: '𩾁',
- 39878: '𫚙',
- 39879: '鲩',
- 39881: '鲤',
- 39882: '鲨',
- 39890: '鲬',
- 39892: '鲻',
- 39893: '鲯',
- 39894: '鲭',
- 39895: '鲞',
- 39899: '鲷',
- 39901: '鲴',
- 39905: '鲱',
- 39906: '鲵',
- 39908: '鲲',
- 39911: '鲳',
- 39912: '鲸',
- 39914: '鲮',
- 39915: '鲰',
- 39920: '鲶',
- 39921: '𩾇',
- 39924: '鲺',
- 39926: '𩽼',
- 39927: '鳀',
- 39933: '鲫',
- 39935: '鳊',
- 39937: '鳈',
- 39938: '鲗',
- 39939: '鳂',
- 39942: '䲠',
- 39944: '鲽',
- 39945: '鳇',
- 39948: '䲡',
- 39949: '鳅',
- 39951: '鲾',
- 39952: '鳄',
- 39954: '鳆',
- 39955: '鳃',
- 39964: '鳒',
- 39967: '鳑',
- 39968: '鳋',
- 39971: '鲥',
- 39972: '𫚕',
- 39973: '鳏',
- 39975: '䲢',
- 39976: '鳎',
- 39977: '鳐',
- 39981: '鳍',
- 39982: '鳁',
- 39985: '鲢',
- 39986: '鳌',
- 39987: '鳓',
- 39989: '鳘',
- 39991: '鲦',
- 39993: '鲣',
- 39994: '鲹',
- 39995: '鳗',
- 39996: '鳛',
- 39998: '鳔',
- 40002: '鳉',
- 40005: '鳙',
- 40007: '𩾌',
- 40008: '鳕',
- 40009: '鳖',
- 40018: '鳟',
- 40020: '鳝',
- 40022: '鳜',
- 40023: '鳞',
- 40024: '鲟',
- 40029: '鲼',
- 40031: '鲎',
- 40032: '鲙',
- 40035: '鳣',
- 40036: '鳡',
- 40039: '鳢',
- 40040: '鲿',
- 40045: '鲚',
- 40046: '𫚈',
- 40047: '鳠',
- 40055: '鳄',
- 40056: '鲈',
- 40058: '鲡',
- 40165: '鸟',
- 40167: '凫',
- 40169: '鸠',
- 40172: '凫',
- 40178: '鸤',
- 40179: '凤',
- 40180: '鸣',
- 40182: '鸢',
- 40183: '𫛛',
- 40188: '𪉃',
- 40190: '䴓',
- 40195: '𫛞',
- 40198: '鸩',
- 40199: '鸨',
- 40201: '鸦',
- 40210: '鸰',
- 40213: '鸵',
- 40215: '𫁡',
- 40219: '鸳',
- 40220: '𪉈',
- 40221: '鸲',
- 40222: '鸮',
- 40223: '鸱',
- 40227: '鸪',
- 40230: '鸯',
- 40232: '鸭',
- 40239: '鸸',
- 40240: '鸹',
- 40242: '𪉆',
- 40244: '鸻',
- 40247: '䴕',
- 40251: '鸿',
- 40255: '鸽',
- 40257: '䴔',
- 40258: '鸺',
- 40259: '鸼',
- 40272: '鹀',
- 40273: '鹃',
- 40274: '鹆',
- 40275: '鹁',
- 40282: '𪉍',
- 40284: '鹈',
- 40285: '鹅',
- 40288: '鹄',
- 40289: '鹉',
- 40298: '鹌',
- 40300: '鹏',
- 40302: '鹐',
- 40303: '鹎',
- 40304: '雕',
- 40306: '鹊',
- 40311: '鹓',
- 40318: '鹍',
- 40324: '䴖',
- 40327: '鸫',
- 40329: '鹑',
- 40330: '鹒',
- 40338: '𫛶',
- 40339: '鹋',
- 40342: '鹙',
- 40343: '𫛸',
- 40344: '鹕',
- 40346: '鹗',
- 40353: '鹖',
- 40357: '鹛',
- 40361: '鹜',
- 40362: '䴗',
- 40364: '鸧',
- 40367: '莺',
- 40370: '鹟',
- 40372: '鹤',
- 40377: '鹠',
- 40378: '鹡',
- 40379: '鹘',
- 40380: '鹣',
- 40383: '鹚',
- 40384: '鹚',
- 40385: '鹢',
- 40386: '鹞',
- 40388: '鸡',
- 40392: '䴘',
- 40394: '鹝',
- 40403: '鹧',
- 40404: '𪉑',
- 40406: '鹥',
- 40407: '鸥',
- 40409: '鸷',
- 40410: '鹨',
- 40421: '鸶',
- 40422: '鹪',
- 40424: '𪉊',
- 40427: '鹔',
- 40431: '鹩',
- 40434: '鹫',
- 40435: '鹇',
- 40440: '鹬',
- 40441: '鹰',
- 40442: '鹭',
- 40445: '鸴',
- 40447: '䴙',
- 40450: '㶉',
- 40455: '鹯',
- 40459: '𫛢',
- 40460: '鹱',
- 40463: '鹲',
- 40469: '鸬',
- 40472: '鹴',
- 40474: '鹦',
- 40475: '鹳',
- 40477: '鹂',
- 40478: '鸾',
- 40565: '卤',
- 40569: '咸',
- 40570: '鹾',
- 40572: '碱',
- 40573: '盐',
- 40599: '丽',
- 40613: '麦',
- 40616: '𪎊',
- 40617: '麸',
- 40618: '面',
- 40619: '面',
- 40623: '曲',
- 40626: '𪎉',
- 40627: '𪎌',
- 40628: '曲',
- 40629: '面',
- 40636: '么',
- 40637: '么',
- 40643: '黄',
- 40652: '黉',
- 40670: '点',
- 40680: '党',
- 40690: '黪',
- 40692: '霉',
- 40694: '黡',
- 40695: '黩',
- 40701: '黾',
- 40703: '鼋',
- 40713: '鼍',
- 40725: '冬',
- 40756: '鼹',
- 40775: '齄',
- 40778: '齐',
- 40779: '斋',
- 40782: '赍',
- 40783: '齑',
- 40786: '齿',
- 40788: '龀',
- 40789: '龁',
- 40791: '龂',
- 40793: '龅',
- 40796: '龇',
- 40799: '龃',
- 40800: '龆',
- 40801: '龄',
- 40803: '出',
- 40806: '龈',
- 40807: '啮',
- 40810: '龊',
- 40812: '龉',
- 40818: '龋',
- 40822: '腭',
- 40823: '龌',
- 40845: '龙',
- 40846: '厐',
- 40848: '庞',
- 40849: '䶮',
- 40852: '龚',
- 40853: '龛',
- 40860: '龟',
- 40877: '𩨎',
- 40879: '𨱆',
- 131877: '𠆿',
- 132066: '𠉗',
- 132998: '𠛆',
- 133134: '𠚳',
- 135444: '𠴢',
- 135459: '𠵸',
- 135503: '𠲥',
- 136301: '𡋗',
- 136446: '𡋀',
- 137141: '㛟',
- 137273: '㛿',
- 137347: '㛠',
- 138121: '𡭜',
- 138147: '𡭬',
- 138965: '岁',
- 139185: '㟜',
- 141530: '𢘝',
- 141549: '𢘞',
- 142763: '𢫞',
- 142830: '𢫊',
- 142975: '𢬦',
- 144974: '㭣',
- 145237: '𣘷',
- 145339: '𣘓',
- 145458: '𣑶',
- 146420: '𣭤',
- 147383: '㳢',
- 147401: '𣶫',
- 147555: '𣺽',
- 148622: '𤊀',
- 150202: '㻘',
- 150249: '㻏',
- 150776: '𤳄',
- 151083: '𤶧',
- 152323: '𥅘',
- 152933: '𥐰',
- 152965: '𥐯',
- 153762: '䅪',
- 154128: '𥧂',
- 154947: '𥱔',
- 154954: '𥭉',
- 155168: '𥮋',
- 155453: '𥹥',
- 155478: '𥺇',
- 155594: '𦈈',
- 155781: '𦈒',
- 155844: '𦈗',
- 157832: '𣍨',
- 157902: '𦟗',
- 158361: '䑽',
- 158397: '𦨩',
- 161061: '𧒭',
- 161559: '䘞',
- 161589: '䙊',
- 161630: '䘛',
- 162215: '𫍟',
- 162393: '䜥',
- 163039: '𧳕',
- 163187: '䞌',
- 163220: '𧹓',
- 163239: '䞎',
- 164131: '𨀱',
- 164173: '𨁴',
- 164289: '𧿈',
- 164318: '𨅫',
- 164362: '𨂺',
- 164364: '𨄄',
- 164528: '䢀',
- 164536: '䢁',
- 164539: '𨐆',
- 164578: '䢂',
- 164782: '𨐉',
- 164832: '𨐇',
- 164837: '𨐊',
- 166203: '𨤰',
- 166235: '𨱀',
- 166315: '䦀',
- 166364: '䦁',
- 166385: '𨱊',
- 166610: '𨱐',
- 166786: '𨱕',
- 166853: '䥿',
- 167121: '𨸁',
- 167125: '𨸀',
- 167191: '𨸅',
- 167273: '𨸆',
- 167288: '𨸇',
- 167296: '𨸉',
- 167311: '𨸊',
- 167342: '𨸌',
- 167346: '𨸋',
- 167410: '𨸎',
- 167759: '𨸘',
- 168866: '𩏾',
- 168938: '𩏽',
- 169187: '𩖕',
- 169408: '𩙦',
- 169441: '𩙧',
- 169472: '𩙩',
- 169501: '𩙭',
- 169529: '𩙨',
- 169530: '𩙬',
- 169544: '𩙰',
- 169627: '𩟿',
- 169637: '𩠀',
- 169653: '𩠁',
- 169670: '𩠂',
- 169705: '𩠃',
- 169735: '𩠉',
- 169766: '𩠆',
- 169781: '𩠊',
- 169812: '𩠋',
- 169860: '𩠎',
- 169894: '𩠏',
- 169903: '䭪',
- 169936: '𩠅',
- 170036: '𩠠',
- 170106: '𩧦',
- 170145: '𩧬',
- 170164: '𩧵',
- 170168: '𩧳',
- 170174: '𩧮',
- 170191: '𩧶',
- 170193: '䯃',
- 170229: '𩧻',
- 170234: '𩧼',
- 170250: '𩧩',
- 170265: '𩨆',
- 170290: '𩨉',
- 170296: '𩨅',
- 170308: '𩨋',
- 170311: '𩨍',
- 170313: '𩧱',
- 170321: '𩨌',
- 170438: '𩨐',
- 170841: '𩬣',
- 170995: '𩯒',
- 171008: '𩬤',
- 171236: '𩲒',
- 171369: '𩽺',
- 171385: '𩽻',
- 171416: '䲞',
- 171440: '𩽿',
- 171441: '𩽽',
- 171504: '𩾄',
- 171523: '𩾅',
- 171558: '𩾆',
- 171847: '𩾎',
- 172010: '𪉄',
- 172070: '𪉅',
- 172094: '𪉋',
- 172104: '𪉉',
- 172118: '𪉌',
- 172166: '𪉎',
- 172237: '𪉐',
- 172239: '𪉏',
- 172294: '𪉔',
- 172309: '𪉒',
- 172531: '𪉕',
- 172799: '𪎍',
- 173365: '𪔭',
- 173568: '𪚏',
- 173615: '𪚐'}
diff --git a/wordfreq/chinese.py b/wordfreq/chinese.py
index 63cc84e..03a1ca3 100644
--- a/wordfreq/chinese.py
+++ b/wordfreq/chinese.py
@@ -1,14 +1,19 @@
 from pkg_resources import resource_filename
-from wordfreq._chinese_mapping import SIMPLIFIED_MAP
 import jieba
-
+import msgpack
+import gzip
 
 jieba_tokenizer = None
+simplified_map = None
 DICT_FILENAME = resource_filename('wordfreq', 'data/jieba_zh.txt')
+SIMP_MAP_FILENAME = resource_filename('wordfreq', 'data/_chinese_mapping.msgpack.gz')
 
 
 def simplify_chinese(text):
-    return text.translate(SIMPLIFIED_MAP).casefold()
+    global simplified_map
+    if simplified_map is None:
+        simplified_map = msgpack.load(gzip.open(SIMP_MAP_FILENAME), encoding='utf-8')
+    return text.translate(simplified_map).casefold()
 
 
 def jieba_tokenize(text):
diff --git a/wordfreq/data/_chinese_mapping.msgpack.gz b/wordfreq/data/_chinese_mapping.msgpack.gz
new file mode 100644
index 0000000000000000000000000000000000000000..d1313854a74ec9d7a1e8cbcd2b70e6ad7e1deb4c
GIT binary patch
literal 16831
zcmV)CK*GNtiwFphxB*rI|6^!rZe??2Uu|J<aA|I5E^TvXaA9L>041DvVB}TR{uK*Y
zu%cjBc(GRm5&Ve=D#9XcVV5l12%BBlY{}MaO*WHcl1$0;$@EFN>21<`0mbg4uU&Z+
zk<Fx7S4AvXexE!1b#m|bmUGWN=Q+=r`A(jE<+qg?Gi%fB+EZlm{)8ULnS5uT4!_ha
zPx-$4f=gQ7-F~sx<y6%N&1zMbsy>Wp)8Uty<<VK)dQ<zw4(FIQ?=ty7&W^stj`ryA
zE6nmpgC6{XS$2eM{}*k)OPe1u`ADm(wwQd{sA{KKi_P-**4^zF&CI+W+{5ZDTgtNa
zZK^6WtB#1O4kLP1b=2g|kgAR`W=d5j=<HEdIigxsClOv%okle3*0W}*szX&3Xw|Q(
zN;*9Xyuqw4j_N_DS+4H1D%Dw)e0nfT$DlIPSfND^j+^BwryiU@vq?QTZ}RoE+VO3Z
zA6Zmph9Rv?eem)2i=7QI{@QUnnhr<oa<a<><d#{@wd=uObMguL-9Ko**gYK3gMXr9
zP7nSW!9kxx%*yc+vs&X|RO?Ia?1&tfnblgCvae{r*q3Uv58hxOgyj2yS)K1u@mtJF
z!?23qYL;vI<+uiG*2{4%)@vM6@q0N*pB(QqON)bYe1N5fb@)27JnvEIFU@j$vx=|h
zcy%g$(k%DPsrW{;n33Zqw5U??EhfLXpyJP&<(8O=*D=ze;xC!y+7>zPF{{-J+UzqI
znzC|iVM4cxi_ik`0AfJNTg_^?Q^mVjb4re4cArr3Zl2{-T=KkTd+7|SxRj-9RlFZj
zt>QywH9_Ywh772<+~jBK<T%BCEh;`|mK%~Pt~AU2BPy;&!7e#!%&K!<#cr1Fll%8(
zbttOh0E?wn9OS}SC4|<Uazq&!S8<Y&gBUa1)_$?azaU2o`cKF~vonJk+8N!h(m$Ei
zc#|AGOqx}3ANrvAAnVqsc*NufdsX@uY~xn(1d5>KJj);!I8~z@i-@p_A8o(bmI$+(
z<FWROU5gDW{yG*JRq;1DSw!(NvmD3D-(lTFIq;U+fE?d5t93z@{@pBhy5#sN_vs7D
z@iR1W%kc!;^s4wtvl>dM_*YDvljA8S;xA8|)q0M7!7SG^A#d`HT{^tMERTg$yvn}Q
zD#qh#daNt`#kvxvdX~XF{u>K%>+D(Gui}4lB)^LP#o#U#|Hmvlg9>aWWHNf_1uW!I
zw9l-?Ypknpu?u<i(52i?ovJT0c`%^*WoBt=LDere%dsv-RlgF)udUTXS1^k3+iKPv
z9jd;{taa9D|BErCU;AHDIPjfuhE6f`Jq(TMq4y#B6&+zerylw!t+*cg7$T>KaOVcU
z9{L1gQv2B~Q=`Cx=$Tfa*euWFblX;9vcF3EUyaMRtM&%7>O;K}v)W)(jSDsmsd_(R
zR<|7>&Z-+!eZ;J~hIHFeW)8B@KC^~r?tdfN)oRNglMiQ<`4-Wi(dMt2d@!ZWUpM(^
zzit~~#*9<z-iBu-ECN;!nWeTWt$Vxe=+bSIX31-Dpn8gahpJ~yzM)Z@zeVI?*>9U=
zcS@<N&02q0xBZ;4GrH{wghj>br<qc%>J_u<@#%1dS#d1rw&!??_^*Yaux`K1$|l|Z
z3M=Ef{f$<pb^F__Y*v+%K&sL0*V<-_c4OMcjBfv^Z6>rEqk2bFa~(H0t#g-~m0Vc6
zZ=thUC!R8E&MBn^&Duy>HFufS#yahO1iLkAH=*n5)$SvV?AC68xp7jvYv}CL?pn^&
zs@-+wLYH4PZoIx$HBDyK>(lNS6Vlq9Kp5>#A*!{z)vVRmtEP<|lB((Av>s)Ch_$U7
z#X2!0uCn`4v+Oa-{K)!VQ2Xy8TTSZ_&OH^=?kCu~U%UU0(^=H4c?yRL)brPio^HR`
z;<8X(lec|t?fwJ1cBtl$DD6|tGw3(2n!lTsnr22NUe0!1J*vGFHN2{QInFbzlFM1R
zStU3`uwErs(lQEv#H>XU+IuMr)vNY{xIf~0PLWZ`4Q3gjDZx$MZQ2he_T!0nqVt4G
z)`1Xx{n~Q5$v4fbglNS-Yd11+01ZBTp2z*2D%no|oJyD*s8%iR+c>CN+}C5z6`!(t
zj;fXv*_c!L>&;56S0&}_*Q{EyVPm^W&d`dh<SYx#sH6d{vpPh)kK2^|IbZw5c6XIZ
z{Mdu-0MJlSC1F}Es*P~&QI%x4#Gq=kw45qw=9x9`gHG!{A(a?bo>EB%SJSN$5YwGh
z$q0ABLZet<QK{p&Pqj*BnVMDY9O^f!WPuh&T12B()jo>0=>8b1bg1NU*5q7-+0=ka
zz)nw(N(h(wS(Okj-d1@?4ml?L5aqa(A29^waDhe(@-5%99^zNYQw+ukBw}~JN-h-c
ztmJnL#z24IKqIRCBkDL*a*@t1m5`wWv~Vfkq{5#ttF0XB8BT)&fMsY>CI7?$K(F&=
zd61ESWoSyZ|3?3`O2AAoBz=on8;xiW02g#>4>T$?u024J$67A>>*rx%51{DjRQZR^
zO1w^c@T*X*oLAu=)!OqW^r+IFx6nDGJ*4^o;%%(QkhhZryxMcMS&oFX=NgWf(w_g}
znOn|l&1!I1&UX`PLG5`z^HAV}T*JJaA411I6zI4C>qG|R{45>aN_n^*mz-Z<*?Kw2
z^0<i8x?;bao6M?vN=}jhm%QhGvpUuxXA#d*O6Gu-K{+2{o=d4mS*1(PeLQQGvy^#h
zIS-oEK$kv$3||=<)1DJ%IqH=Y*9;r&IYnzo&MLEt*i%i5a{wT@g!bTFZSxD-Q%7%)
zoDHnnET@}^2rrAr<Rs5`u?KD%nbe-BS#Ao;8E0fd&Sn&z(5|~peh!5@=?ut8Ru6P5
zv0}q!M0@&~!P=u{DIAq^3_s}7ewg4OR-NP-7Mi9rBIgYATeN4+EY0||=gVX_wkK_q
z5}e=VS&!0($Rf!Gtos(zezA1`)BTcs!lmJKu{JsLg&55&18Kc-{>H2}VY+8H`k0*0
zvP*+1{%BTanD-CPGbiUi5i`ovo3*JveIBUqa%EY*^95X9(yw)WoT9s4buVU(5t}Jy
zEw<IE?xk3#Q*{=+{Hl9-VT-y~(3)0xky&YKQN=|YyHVA>*{sIGs>7io(+b}TmSt3T
zHNNB5j(-4Y?7wOw$*sB%ksgM$WrxX!GD?kd*<l4q_tUMayBSNgsO~eEH>16`ao`En
z;ZBii?Y+}1Cp@a#Z1U~3s^;chqpI5m-Ak%&JHoHMJ77a|s-u4JPwETBW+~xS-NV=#
z^?|lTzk*koH3-VON6k{sslA|BBC5SEM3eT$*^e9rAMaUksOd0_VN845%u3WL$6Me{
zecB5wC973_)T|`>l=>#xw`(sblZa?9DC4WsUQi|ul7ExVu=akBvLUD~rx4v3_qErM
zLdK`G_a`jWrM=(^rNLg(iKz={FDxrQue|_EBBab8x#J$~{X53#RO&};Hmf?WGc~Nb
z=gew4s??9^%;}C7n5A@=9)6KonoFvli%a(FVVkB?-Fo;vsNSWFi`9Y(UT4;7ru6WK
z&2l=Y^oIbLM)ZnY;M7el_%sWSEAwXt_o<$6O;#zjMCXWtH)Fhv>UWtHZ@=ov9*G5|
zR(Lk5hmVl4(s~$#j@WZvb(6V}TGX~RsBWw30oim+cbvufrlY#!oLR~?swryL62Qi9
zSz$=^wH$1esh3hqwWR8FM}r+5v}yZNo3>r5Cv{-`dXjsfo&HZ=huMM?3f=*`pnuRT
z#hU0(K~8&eAw4_>Fb3%O)H4hmXjlELS%st5!>+Scs(+jvhm?Aj(ew0vgNF^OCl0gr
z2#zli2aYlRYU;52GvNY99@LH>nEYs`>VL<0myT>SE7fV$1OKTJHFcXcf~x+{jO^3H
ze}$PkRZm=|{CfDGRvkS|xz^mFh8J>}8Z}V0W$M+yoh264a5*hoDPQ&~jF22v!)us2
zriRzjzo3S9V8>Q9TtlZ%4evFp&3<i%GYr+K;bU~V)j+CAM%6?eo?zKe(Mdh}cdoNv
z4PU@NVrqbXMS|K6WynpdX$p-e)Uc`G5Dmmvz^jG_@EJDRM(p;ffncp0(WwEmf)$SJ
zgWgaNmD)lvr$@+N844FjaP=aZKhj|PyY)zfvsdX6qAJ^^M>33JL2j^hP>+!Ovjh5K
zHx>>~Tc&iK1tFInA>SK^9F*m?Nfp6w+Y(B@11AmYk;lQ{8a?tYhIs5o-^IV1InMW>
zd|sum!Hqif2!WMl_n#sRqu%=j2_T+P!!Otws{^LSsYfV$T0Cm_bz$lwE3_=+zW4Wb
za8{3ywp*I?2*phsR{u9NdqM|3V3vp4R0=P|7hPDry-}`LvR;Gsk&|0nwBtu6Kk1a~
zDzn;Fr>0+U=4!dFV@SJPA4jyQ=}B<7RjyB()%KKJp8}o6<+>Hn_g2aE1(To7%5?`r
zJLI~vAoktGGTlnw$oV?ux|g-#Xcx>%DkvAlb6c&_H}TBq)D#z#mTL#|j9e5lrcN%%
zUi+B#J%Wa9x^tiX1ffYT@@gAH4-`1azJo+>QZ7KUwO@A<%N+}H9c9RXT*u97M^yVr
zxmo+^LerWJh8mUsrjVf1&u|_#14>(_<nox+E{9w`M2%d2M6Fz51Xh8zccBl7wX0rt
zrp!_&Wpfg@Y1f_2v?k?h<(WsW4g|I(+jjZ1ub1=Nn$y+CAdJ*cw_E!L*`JLe50nP3
z5kx?Dj&i)oMY$$vVjl8s7k4#h&D$*(HFj5nT!ep@S1zbxSGCg5a)36)N4exd?SmC&
zYqd{^UY(l5pbj0l$1IPgtOmb81BdQ>+LoBj+P8#%ENUO_)83+efOosKkn2y@#%M@^
z59@Q0oV&8xhcmUe$@O<yol4(_PiM3b*4Lhq8!Q-Xk^2%vo7^u#7?o1bX0vi%MypkB
z^6y|yZv1VqOYT=8y5$BP20K;yTJ&(p{W@C1Dt*0K?wFJN4YYdYej}n!cW<>>twC;F
zb8twd(888_xyfpS({jHJF`?48vmx69GJ|s}z1my=GE1R_Et7J?2L~q=90qASwSBwE
z54+@kKb?yz{Qx7!<c1awF31fI4Nj@_;~bvtDPeMq1eJ0%D*YrNGp5p;STiU$=|1O{
z`%_rATcw}D6n%0N3SCxjIAyL{ZnA&QqtY+3TB}OeAv)xSS`LoOy`E<rX#=+lsdK|L
z0e$y<2*2E<u3W9$1V}C*H-t0Cc_ExRpU#z-l>sz`J-`CoI}wd4r8Y{>$o(M1gz3d}
z_Q(w<&9x~&2rs7OCgtU#azjmXF_luccBAM4TI>!(&2deK5ZvTpL|pD82(Fh%%Aq!>
zmg`hz5im~5eS%h6+X=|t?wH)?XeQ)7k7!b<!z}l*JvlKKk(;_Z$M$uIu-x?^&y=<w
z;0|yPugNbmy%CeN>n^|jP>RbBGIUh#5Q2*Zid&7`QCeBu6=MuFftx_g4dbt+39}TO
zmzz+`4XQNFU_1<@&JCy(r0zo57Fr16GuNlmHXyi4rBrO)xMVw>2!b{@BsW2u<8HbU
zBXaj5aE<<gC><a*z^O_H@mD-72T^0jkXapa=*TzBii2ec<lKTvsrabJPQKl&q%rOU
zL+a)DCTRiJnj(Q>V>oqg9{ul{F&AdzDy1y!!b+5dLvDMldGbRyMqDtf-RMr#57o&1
zWkjt?zrq@6xuF2$PWRUlcoOU97UljnVp2C=4gby#%l$o?1j+XiSoQ}Db*l7-X1RyX
zpI~;J=BIR4tCX^_lV$#o7WO6M3^mG4#u?(Co<w9+Y7>u7?qAcwBc5hW!gz^RM5TGw
zWWQxvDV2gMT`ejFRa(6Elxv*QuhQQTq#Y{#En^Wd#m;&Ke_+-^c=8|cU6#9O0|LYT
z3FUBtzp!3HcRgbn9-aaj8S={gHy(27z)@~WZdm0|Ql(InZZ!B8ttPqu!?PKAUO>wu
z4;VERk_U_$3d=*a(Cd~5_LB3;12_%&wEuGMH_$E*=roj;=haq^5qUtVAu6KRagqh?
ze?5a@tak;yL3zNZA<FP85$#%cl`Uxp<#`j$PI=y3Fq6l^6zc#}B;ftPl&O~IowSTR
z?|NRqg@&4S<QHb8wn?53(CU@vgNS~40H&cnc}T#6md-hz1fQLB+(du39KXV={M!F%
zY{-_k&}p+x>;{|X+*)_5mG$y`*5t!6t-IYe8|3+XfpUAu(K&}aciE%1$pbPCp(#mv
zutWRTo8^ASfI&l?$%0RvJX>ky<bh!g4ah_3GBhj?HA|vb`-_>-rr<KwKWBnc4UH@N
z1`-sfI7mUuPUPquW&>ab2jy5LagS;LQIj9x8L67;c>l>lA+n#EW1b7E;HF&iR2Gb|
z?!2v8*_UEDXFnJ8RNG_~)!j`tL10!lK^d2aMBdXZkC#*S$m26>sTO&FlcAVA<nuu~
zfs>&jc}VL+_Cv|cu;tP7+7II!<bHvZ@vJ;)9=B*+#_r2#U}b1j>soAcQTy8&Td)1y
z=ECrx_ETLACbfUS<ZH&YACwpjYkv;Ws{KO@>Ct`&;=r8Njat6QrOm(%s<a=XXhyYv
zt{~Pe*u}BtqXmnFDdZvx_NZTl*Rbc;Sa3`?`QUn~oE-mr9)*63VtyU@4-OPp!?)l*
zPVN6MD~#*FC1%CdsRNhMYSn>P!UOA7MlPEQDD-07W<c4u0P3T<d&pL~)jB}dB%)*6
z%~~d*>PxvLpALMG&K?~gGvXtee=uXn*4r=V2C8Rt;1<g=bZ*?NP*i%q$dy*hdyiS^
zYf|WPcFD-Qo`r_wy{}OH9@uJ@hg+3>8w*t{^csdR?*P?VukJo<uhS!Mxmm@scb_y%
z5X1v#Ao6HgK`W!X9dMAO4m?KZxRM_>YrPpA2$|)PR(ZoL)29PX1?KN1LvRjn#;lH^
z1$Q`>mA4tuA}^_7tXW=C!&sZV)MjH$??Uv+OBNXGlD7xZBQMEdtXJMXL{46E!kCd4
z{x&u!FG*l*R9?`3yh`3tTAXtXF)lCYKh`hrBy}*IQ?w@Kh1!ix$V){xHZ3opKQ<;W
z1aE9sUZ8$#N?r)w*o?f7AvgoTKaN4af^f(S@Q*FZ`&C*_dBOkjT6w7e#}?$}^2g@n
z1@Olk<OT4@-SYmBN|t9ord2QR&k-ScpFp^@xgX6U@&fqd0Uh{d;hO_5fIse6=vuA?
z<)5O(5O9AyEHAh}#$8>YylRpc_#YdV7u+A`##Rtfd7;;1-SXm=<BjrCYmRlw`+Hhm
zc`s5w2jqoVjx+tQ2>YS*-G6Vt*gncJ0Q2#ryw4%HG{AgpK;D1TO34eRkEa>z{jue+
zRcd^Zt+Hck1klIk)d--E$JKZ#qFIe_&+!(0>1BA>pc-FZi0H;wATnyCR2^?s<Es&E
zY6RoQ>(uyqM2#B3_VJ(^!S->V8n1kQ0w_Li)cDrIkn|;#EHNE?A5LGZFMW`>@ipk^
zbvXD8>NSp7^*s90_4a{B2S0(YbI-rB+S(d_*QeVrc1(9Dvjg3n3f+vEZ8SC70%xjD
z=@pZ&?^7e}Y`j;YTg+Ox%0512AJ^;PX|p_Tzkh11vK=mkZe@W59jr$m3l@!j+wWE*
zC^tT##sp$qnJdA02dBodCu|Y=p+5WhdsgW`1Jd?0iN--Y&#Oi}d16>6vt}h5(z$2M
z%J7&D0#Nl}@kz7nZdYg>O4aM!vjluv>A%^pX;V7*gTmLu>C3RsybeMsMtjwW-z-k+
zAPj-ELmQY_t%IwKtkS_XgjWY41|#;n=nwtDs$?0^+kae03kUzoEVm9)fJ|g{@SmI<
zgWb=0N9E(*CdXAxQfe61A<BXYqas$!WOUCvxQsR(x|)T%723w8PGw%oL3?!Q-HdEi
z=2BYSIs~%ey1tK^wW<aA;QZ{D!E2^EbqH7+x1Zu%Ic_ebnsw+d)D6maHyhWg;&QVx
zgBq~)$tfM$$=C+@b`?&0miTp7%eULCPKV^9j-Be&p@-R+Y9Bxxb?Q(VZeh*-qHEhP
zw$v@kcZP)~<vWWp{T|&@NkI+P+7vo2Uo{UWbckAYq(?p%H#8-mn{~bNk?<yG<%360
z*2w2GOU-TaL8GT~@{#u@v+|MmNW?xo0vtL7G}hOt;!PZ2O80<}GjaJydXv*i{2nZ=
zmoH<9M!)XK@-QhM5IG%GhEy@dk>ShJC=6eoNh|YKn>aW+7&+tDAu^%0GAR&z$$;=v
zBRT{pp0FSMcYefvbQ@6S9rSZ+b7tADgt@?-LyvR1E*<(Rbb3I(Z=!-LCLfqK-zgu|
zcD_r#?;yJ66X>4OA^XX5hkW0|W`SDyz`gli?Y!OOr~LB$h*qC`KeZnUWALA2a83rr
zoo98Z(>(S8z~(Xfs$IY(ADA`IWx`EIxUfH(<ynmPXF7)!`=MED=3svV`P$`!ea?@`
z_YVZu18&XF$OmrCkH`mZ%}>Y&V9n3z5Se(kRb?;4E)n^ukQZv?f3a1nL4H6B>f#5q
z798>eS_@V3zl@3V@&j7)3yMEw);f&*l*kLU@>3#vc?L`^IOV5Oo}ZQ9#&#f}vNxl5
zyZpe_LY@4;)q+ocxaWdP{<kAM@>3!&G%AC?Pfe?g0HGQ#Bj-;v%TJ}e;Fka0h<f?o
zhd@Ir<@rIy|A-a?^219Pyvkf>@0=|@Y&Q<e{}H-_D!Yz#y5)ziF8Eb;1KETzpQOc*
zPay*GLsA!F@_&Y?<=L&YLMr>LS!-*Q|29|(#`qkaP4a&p5tW}ZdLgcR?=VYqeYzKJ
zF@^cyuJir!e~D)a`Jt}!iwZRo=1G-p0C(o(hiNR(y3Z_+IaIc_5IAMq%<_C%exh`K
zNPa5i1+Iijd45{{-S#Z#M6}M^Pjj1YvW&i4@e3T?Mylf)F0E=<WrQvnvFtGCtI@qD
z2-FFcfsC^;Wj=#p=T&wdOSGu03SlXE)6I6ReubLQu}x)ltN;-MvL`ai+{T<4l?BkT
zR+-yr&FS7IvowoIV+`q1D9OA&m9^kRbizGHae_{hcV|`BLu*3*0Zx;Ze-P0pKjdVA
z0}q?!Njz$VaN*p~n0zX$dne4&g3-N`l;Kq>TQC<!QS~uYa_inNo0ZX7l~H7p?aLnL
z8NT~93ZE%v{D@01D*JIEYRi7czHI-0g%>i)e!+~W%BT`aocBJ(7A>k+Z&qf*swXaz
zT*4A(N$K7^tFY(_Yhy*q!PySo`#ZDJ#gL0!P@~HJL?^&q!>LDA2JX)|RrW9T!%Y9-
zS-aN1fK@tl_!6_ckkVnefFY0%zl4WvTK`hBwAiD=mzoPBi&}pftv;=P85Rv|{VT`~
zy*m7A6!mNUYw7IQ;WwD&#gNv&k-MDI;j7qbN&!l_#e@#OjeB9Icc5Cm4!;vor@%El
z%c}XF0?9c{P5})LzlV7!@m>}SYW)Y$uu~N~ut7wJKU(-6F7Ppv4|Z$)b>>2_K}9b&
z`7C;pXcp2sd^;N%9sV3=Xi=sZdf?LfJ6WY!fxEbQR9eTj0R`B0v0m#pm<xe<1+1$t
z=<sH<JQvpCBBrzER{Jj5oId$#bD<f1;qz5)9Yz_4UxA&pLOT2)Gum~yn45^|@NTY^
zWlEUesl#Ne*=8NyR}g`tY}l-#f17*`gC6I0yR`lUqEmsBJaZ^;iZxvdoH1*Tm;&d}
zX<qB$>vO#dI2h8PKrJG!Ks};I0n*pPv;uzS%_<N;bZUK&vS>)_@%}k>h$FIEpD_9M
zdSxhwQc<mMgU?QA{eW4TH(H-Fc}Kt2k211F>&Fl&tsgh}su`_^ciZ#LSZb#A3v@1M
z{g;_w>&KHj%~G7P)K;@jt^X#=am(L>5PP-$`y7pH`Z3SyY=wB*R*17|zR#?I(CeRk
z{#d^<Yc==~4!zJ}zaqPWR8A?e9(v<or$3=D9s`4_sZrpsX03Wq>;J)$liGm$&h~1<
z3vo@iHeA9A{o3$ivhAXR5S5y+b~sEP^0@);C6YJby^90d@EVh^?o#k|EH<qTSJ2t1
z4R2sbuYzx69$4{nqGnbbt}^+dd1Y$N(pZx=yaSaMb>v-UIo6^L_Pac)qu_g3Caewb
z=QwfgsE2elDfl6l2`cnUichzKWQuB5yN-Rk6}+C-jDnwFNI)BIWP1+rNu0SyMc12r
zdPW;=W+eK43elkr|BoTv%JxxCwrRs1FpmiZzsU4X9l6u2RL^O{-6rp}H0!nZq7{+0
zVWY{{E^5R5^f&3qR{Kthj)2nMsE+KR%8hEn!vLC78}@Ot?K(o`SY4$fN6du@P8=q1
zJlY5q^dwofB4U|$SV8;3oL5JjX2m(CBQ8pgh6!zOvl1CCW;yJXj(F*=ueDc>?~P=2
z1P0aEr6Xbb>sl2Az?~T#iLqlwp&+I<3Z_vbsN}2RP5}k8&kt#3hR3g<0a2-gafa}`
zHuQop)e82RymwZ?eufU~$S_A7(2)_+pif5@SbJW<M|sALJ;pN({}oyb3Vs#AD&HvZ
z=Of=_Bp3E=vsRB2Sx&^7|7-HTxI%yD`f@t*1E%9Ike5)Mf<HpkEBIrCSHYhmxZ$56
zT-xw+a(XtSqI<!l5pDPdTci}k3qlP#0$mDpC`c*{VaX*#Ku4AV6Wn!$7Ux_;*f(k_
zx~TCu#_tNBVI28A3Z%5*Pb`;H@Gqp$Ax>puqDMhuA{5h+XSq1s;%~GX75oPxs^C8n
zEc2XMsq^c|znIXk;D5|g$BaTR;8{+g7b5x;dJ!V7qc65sSEJCSTxFOzpbiNo6@tu%
zS`>PP{j{iBN1^RC4uxJtZ;y_?1`AR`y_S|yh^PwT`Bxya3PHU?gW9<Z%8}O5w=l0-
zp|{h?+V8Zh*{@78LlzleAJ_08p^ev?d;==In^sC8;w#jvjqj(kMMpnGc(d7u@dQet
zkJu$@6(YdG4GLXnn`r-Wrc5YApoMAONNY@?Pa>ujx{1z49lhDCG)yXFKlYo_(OZb~
zh(ZvL(4vmsYVtE~g+6Onb86$~*m*#q&zt;Yw~l_H@U7%VqOc*M5K$Or=$#0cHm)Pu
zJPLh@7Qu55L+sa^&3D*OV|>~%1sLH~o7rVj8wt&ZejP0`E3QVJDlsdqc=!WMt<%PB
zJWFch4wH9vC`6_SabXW3C_-lmO;#x>7(cWZL5VX*C&oWOYfhnqh<R;1#Poo6%mYcI
z+IXB+l{P}P8n9|P8~L^IBw|D%@=kb2A@WW*q|jLenpL3LxHeYWFXSm1&(ljSU4^h8
z_}%jXTm@RSv4#bi<fK2Xjo_b)P8XeVZ3Gw^P{fN^)W$}h1+~#{E`&R@F-Qw%0BORQ
zwF!vmRQOFq+^|A%ItP?_yzp)5#-zCr;m%WZb}E!MtF7Es3$37zwwV<-7hq^{ogE0K
zcOsf~w2K2^w{BYF3iTi`W-lVD5MUa{`vH$|K%rp--a5+ev?lDu*DEwhvr3_9M1yXB
zhke_HL6{nCD!ye_#=3O$QTCtE#>b$M*b#(@U<(i?f_HwMYiL!-7GcA9=XcnIy8nBK
zm_k2b3{FCk?(WvcpCdTw|ADu3{?e@0V9O`z994)683}9S)3k^Y;3LfS10N9_Kaar0
zml4=x6@lKMNI0y}Zx9^+_s<{d543PFYLG~sLKhL$+6bb!+qCg7&u{xzT3GK{o;7OY
z-)UuZ^dDx$GoX#n0k+uUUmU4TNB>P{gTi1(B&+Zx_JH>DkWDYLFY(6}ezD2VN0s>r
zUfH2Axj53K@TG`8g@Kevk1_z~6wko>a75wP&`AsMh(r|zH6qQ*kc6iu6~2mAyN*$6
zdxjK#GZO|Cri_lHlzD<3x)r7rj`S=1PQ-x1??R*%z8YPJ6$VBkc-DInNrm5sXi@kB
zh*oX-5U1i9XcB4DrjHb=+fC3*FFRaUI71jLi45u3C%ETnWhe=JGYW$x;W-`q6e^8q
z6L{gB(Xr1mWJ<@VoP%`=f6f}krDLCG46A(sWjN;@tTv`Fun`$m_^v|o4zHu-R2bNZ
zR_Pe9(b1$$_faGJ6)s|@R)xWZ5GLHl$XOM=#N;zcWw`vQ356e|b6#NpAu^@#9>j=_
zJ;JtFWFM`#j+N5N>DYd=;;m5_l!#30*daPII(8V5)iDzPOrwrLQhk#;c7l;Ug+YnP
zgpQr$WOSYa-sZLGv{`m=A7{);<A64uMb9xEJI92mHdWB#V3nxbtYcMlw(6Jzq{y}_
zT+IO;3fHpeqQalGFAFK`rZcFp7s2gPxJ7yuj?lvP5QPX6K!Yfj{2YpMpUHwdgh7KS
zE@(ew8TM;a3mKakt@LujHuh(2V^#_IP3?tmM8cp#6pMCYQ9QuHL65?~L4+#+2ciLO
z8epVX;XzvU3g_(FjS3IZ3~3VupwFc+AQ5fUrZHMZ;c;4Fg(q!JUQl?7CJQVgeA@Jt
z!dsY|9!GGDui52z2rNXK75)YaFr$DDA%#JQC`t;EQ22ilDEWOvMqy$ljKv@sk#U8e
zDEyKk{0pAN6oy<xiMS^bDTRMk!1M60X{EL4X*d;~U`4cA;boiCIWj2WUC`;*5vze_
zWlx(tDKHEoL|GL!LEaBTBcd1?svaQ%{|RG&6#f?)jBfuf;Nh|Vm=)iUA`pjgLJ|96
z%y3YVSI`_&<Z||k_!N1S?G7vQYAYj(5a&^&`(DSM?TWmfR;MCxg=nja22H*ts>oFZ
z--(b3qJ4_I4bi3uksa+;+!BREha%USrB0_JHniCUh7j>9LWD<a75PBn3L+maI8@{#
zj4XW8`)B*ftWU>3Rw#fX*YP-~2+<uKP~--*cIduO5V`?HY;?2i&4`pDkb>y2?z_$8
z15s7J!mP}N6!{#_rc^Wm&tsLl7}Brf>#)e6B6rh@D6<}Ds#0WwS#yo)_(q;36~Um<
z5k;T?kuJq&%$h-Q@_Q7U5y#<L9p7zM0s$R|5CkU_A)KQfI=+vvoYryT*oR8w_h^@{
zFQaC_rj&FcY;uIoaUDO(kYQbajA!*KqF&2lVbXlmt;lIak0R&T-RO7)WObI~60C02
zJ`cNGRK!s*_;D9n_;r2QzVnXn9J2R^^;+phz{h<-9q&ZPNgeMqEB+xJ&zTDpfyak<
zmQ&F;+Ap?-YL$iTO)coYIZT_-@p&GCpC`~@P{+xkfjJ%j9`jl4M`i`Gdi=+rMQ4?c
zKVeoNBVjm6B&Pd*&3u6DEQm6wd){q7FS75hQ)A|8bUnpl1F>|@5^ekS#`o=IbD@7k
z{hWOn|BC;hj;BgHKL8VL&}I@;Fs2i)WRILqya6$&&2Q$4jZU#~OOsAq4b$w>iEFH2
zg%j6O0)+;2;@yQeV#D>=$*B_`p^$cH=f_z#pv|8&`NeS^dJCrXtLQ0=@6=AbYN}I@
z{MuX?@TrJ2o=I!-y=E=OmYeLa-E?9HoAhY&PLqezM0ZhOdUWC;$bXcbH}A2LI;0c8
zH|T%ju*uI=>%@uYTjivwu%h;c7Zrt_#kv&*X=6Q#)*yQA3QoI1PSH9#`gEe+tl)6b
z23q}!x)7Ype)Zd;sE5_76a|lC6N)xkLsl#5qdBUmA2Fn8!1mTCO6e9GQ8e_tfXT&J
z73_|UYf}PzY*ZBNj!kKE(&Pc{qCc9v8C04IWGt*oQsZ2oqF{EMEue65hoXRWpg~cX
zTpTsvZm}6f0qfYjHur*OUD{0H7hrcVJ6@;g0M8b*8T4q3Dmq;FrO#%t8U`4hpygH+
z1{ZfJ3UiM86otUW{ff>bP;ddkejs+-zGxAB)Iv<BqENYbNYSsE<qUTHx>-)f6a}+m
z!-{^3XAwoI8RKjTa>uzfkUL(l&EG{iMgrh*1S~HeSCrB*#wwJK@g_wn9pec_VMj6U
z{^w>T=F;XT@W`~Hl#EXM$!Ywb_G|1pMFIABQqiXnTr<EP4=DPySzX|G0DC;8C_ErG
zr_B`Wu$WVDv(}h4U&QqXCv?M~?JLI%s@!DhYf77+#WE3X{s+O|>emTSys7Y(>kI6;
zdsKc2>NIJ~OA9}WDF^PFaw@0bYl4MfY5;D_>rEc)+;RmPTmP)FUwQ>x+VV#FyR_v>
zim8lFzZgA|`ox>f1&qGstte+-qH8MrylFt?Z#OF#sQg{5JgD;bAey!1eTBCy!W8jQ
zkG6c6IW5{kh()Kg<)dgcukz~{IiM{!Ffyzy1Y9trvJ$gA(W!EZI;>s(se;(@Y37Y-
z%V+J+CslqM^J3cad5Z`wD*pn<>{j_52>WA(rY~BxhE#qhbDea2;vT})sC=VYu5Hj3
z;*=#5RJ<M2YJ!v{IPU}ILX%rfJ7`7Kw6pNzo$_5Q(5o#EqF+em#jHQ3@`n&1HSOlU
z##IiqH#Mnz51sYevX_xjl|M{pzsmQSl|)wM2N3Ljki`~N4pWOSXiJ&N6NKduwpfG8
zkI>ntEk~K2P}4D#Ku?Oirb#tX&n4=#<#YiX%FkiBpqeV!eN<bj$h|3*JIqS5T08dx
zPJ;>&8j+y3P`w4hY61}wU21}w#kmx!H!8a(ARs=WErG)Ah6#^oR$HPbpRivjC*EXV
z$zV&uKFWP2S)DB*X$hywn}PI&Ds3+@`Qd79=|F>dZRzCh@U(7P8~`GQ`)wI4yfI%+
z5@{M%6VaRuXv+xjhzE>vILt5x3fPYdo5t<SI1X(g3&-14KE<9RDxX0xb(TYO509b`
z?m~SA@NN0B$tN-ER|skx_^T#gS9q!QYjz<N`vw}}RNrLIkeUeZBx-)AfcIOz&n7JU
z6SJC_*Ur<0Zx)*<+x%WN{U4mdukv4*l@u=hB!bqj3!fb}J#AJxXVpa6mRwNz63^l~
z{cf|;%)PGQGHuGjo!f@B<u@ju8djFFI~7pVpE+|-J1a>gEoyoWuphUuaJ^NvMK`|K
zTuA10|E0_s*Zr?R%<KNk5o5aX)#gIV=<WmdV+XhHhis(=bU#s>E_@Dq(e~Hse!?|n
zzwADFrCEw+b^leg+jRfiL58+L#VDWBtvY$FSxMV3mSgX>JJ;#-$4HN}+IJoC;aABY
z&2q3o33yb8&5|c?FiQ!yZoH9nn`u$#F*r>|u}`y>Lnm)3yn!CO4Rehu28T)yDE39O
z;uu%V{-Ui;C%?q*3vD`iFUr_&^b?=7j%6b<cAr(imYFwhwr>(nDn?b53F{U=?$zSa
z$?aw(!!A1!_Pu}Cr@*E5A;tEZRp*>yk1)DJC*e?;1#P{><lF71GvVLZmnP>GBX!Q%
z7b#-3b|0T&ev_Z<(aAUlXw=EHS#mTfmN6@{!@4nR-`jNSWIKtqu1hhPP?uFL-fCgH
zUw7UC@2u9Lj9DIO*8Srq-<;FQ3A2*5SCF{Vj<RoG-Z*QI64uE%v<fOlQp$!DdyLG8
z;sjZi&adGnH9GnA!k0v`Z_=4l4DW32RE*@)%>E>wX8W^+*#BDPojUnLw5I<12VvT)
z7?pH$uTH{jvOS7XIW+exM&*zlQH%uB+^73-*R1`~U}A$cxK}6th>y~LvG9}1eVfd3
zme$|QvWxAWV-9!rUyz|u%|Wv?F{t<p&06cY;+G&M6sIm|omBiKh-t-NikMOSQpA+v
zmmy{qe>q}K@mHF)wra(}*0w6eUyZ0yoI;_kR`J&|WM1*t(Q+tGz0kU-A{;k6ruda~
z)+<iE&{n7TTM=Fry$wqz6@M2km-T^dmbkL)|IiUooQk2%uQXJ9B%wIve>)3NDzt@E
zM4lOflz)_#TSXr;%kB=vsT0~fieHb2Dt;p(qBsRYTZ7^^A;OA(3K3NN(}mWl+s$%%
zSaIt8wwQ|Ug6$#JnN=_Is0`ZTic{#fWfZ>$fvPaUwzMLj;HEI*Mp|gL36WC#zQVJj
z`$=zDsEAy&sQ6YoDVH7qz1kGtMyo}q@cmXSgzpby*@x(CRuOpH%wp6KZH#;v>n-Ti
zBgAh^@%?nRD}De$@qmHD(>hhgGgP9YXzNs*ilWV_IH{#AtN3w5mx@kcrMQw*@4aXS
z4z}3u9pY!KM_Zh@ss{9FQ4w?!hdD)pXr5Eab7nc5)v1K#p|dJVW0n?ulH$G1)1Y*T
zSsS(g4WX#bEIE4>hxHksPW5mmj1KECTpdNZ!OS@Xmo>x+7-+cg`d$&4A!BKNe9WqW
z6GHq9S2Jm|Itx;kn}|-48d|Y2$<8z>4i7X@otigG)y%N34JP^&f0SO#^EiU5`Whmk
zqOU){8}!d4b?7@>2W0l!oY2N_{CjrO37z^r%QN_gFkg>~e#T=IB}JsCRRq1u;-zE?
zlU30#3hNa;iJ(sS70+sQ>M5q9$kRY+hfZA}DWnyL+jVs6)Cw&WSffQ5{2K(P`Yi&D
ze~;+bDI2fE-JjS2Fa9%~9Q7H5rFZeaS{<?cKVje#O5+QoZ7TW~E#i@iz5}2A4`N91
z{~|_}Ab>k&lz1^>N(th)V@{`EijI>?yo?s&<&f1`B?#b-ah-k@&#IIlfIH|Uay#ag
zz_B_VN)Wjni%MM4ez7mssl*%TtybcV^e!l2U%iNRDRGrqnosETn>cHu5^pxE)niJ$
zg`u@d5Z;|NN>EL9<h1pj1a7kuM0uxETdy|Dxa-zy$u0>c-fdTFQR2OYe-Ci_{kZgu
zPJaNgpwl13NbL9_J7!P`a@lCTf{&TiR;TWxhzqbI)UpZX2*^&C5`=tby$Wfl#jC{4
zG<{0^KlJEP;uczdB|d|2D?v<jGURrI{Z(D!a~4TGN_?IU`>jsGei6{k(Y{DWK#4mM
zK_%`&gq2u_Ad`X-oe{ZL%<51;Ti2U>2fA!1_(TG5=$O#y%_JMh=>6Puw-QD6EU3NR
zthG1lI2_o|+B;c>tpS40sJ1@LG9B8w58=?(Qmi+ltp^GpG;TeF@aXtwm^Y%WaK)}^
zojwn1snzL5v%=+{_91fGM<#6U(dj5HpSEU9-rBd7R*g<W<`!%SpYD48_ZXR@W^LN7
z)4eR@RDxQqr(X#|xo1G92hB=5&IHNpXj1}`*TY?mB8HS0L*$g8Wa}Bx=|zspwL>F%
zaLKQ*c08l>F5uh#PA*}ITX#UGzX9ycX{%5^ro?xxuVWc%upT_|`v^RdQmkiM32LyO
zaV4n1dT@lF0b}?q`LPElf5J}eQ-Ub%nNWfR*)ylauMm@}_@G(x;`3Bsz1#><+S{N*
z;M#aV`#KABaO*OroKl&6Z;M;DKb7hlQ)FY|6QBf%w3nk0pS^WDWZ%F@Dq(+p*hQ56
zonGAPIeS1O7lrQ3h!R9%uU|<LYp+L15^Haxk}tAj+I8k7W~JMwGnZkZIwgt0-iVTy
zBSK1&OM8Pl^J?JKX2Azu1MYTJD|v;r7w3g#*X5KX{(4io8!sNIQSwc+VoJW*j&bXO
zx0rnQu+F^IESq5^ZQ0gcqciW|KC6^`r&Xd`Nz!UBAv?@XPAd6+JE&I4573*{z7ey`
z-Jkg|8lv|{VPOk8L&$XvDM@to%qU58^(K`hq4rw*Zu_r&;j>X?FE`6G^-7{yZ>!GS
zN-#|7fzP55t3w}qo0KHXdRvr)MfSESNsRTNCb87(RC1j)YffkG#zsbGzQmriY{F$C
z3AfiMLNOK{RdO>e7A2T^ZT){{t655SC~5x_jax~wYtN!?-fk{*_bG|r^<w!4S&oxX
z+x1{%YP+s^CCOpET}qN`dpq<1MIESdhH9>xJxb|x>&*VbXX_6f<QPufe9T<v!gUtS
za;tqa>WYK*6RMa>%FMDisRz0kHKH@*z}}3`^qS?dIYkJn=!DJ?KX~Ms9M6J!V2FfU
zrIKS1mKL2ErxUk;YW5E33>nX=GiUO>y?S6Ctr~RZaXQmF^HoHn&U_uwsWbKmI4u1w
zS~Ys$+l4palixFIeTW|vej}0m5%?TdlF;e%D)|$HM-TjzHSK3iO(|?nQFG=ug?HAI
ze<&245sJ<b)xr;{xLWkUUm4t^GtV+4s|TLrh+}#H7D;e#dqLs9MIHIMS*hvMwiluC
zfKo4I-h#GW#>hIAeb6jVHEJ8x4k5hlm2}oCb-Deqs!ef)7yk#f?M)`%H>}i~3nX*f
zyJ&@U?_*|Z(I|DTS#F9c^&Ybpn^x+*@Yh<U-bZEY(YE(9GNKf0FkY)|A7zs<r9NiX
zY8=}3Nm>(1!T9<owC#3wj$5{!GfM-#I{O8)(jU>bbzDTdw%yIs2A##}`aMeFbOSEM
z*fF)BR1q!vPd8Hb7kT|CL<s|OrSP-id8KyQpZ~j58!*d(v{In=Fq8J!ug9l#_F-0x
zDn%VLQl)KF?gI&>%4j)M8^*WhboRJesvlA6Boi04?G!^gl{&+aT9thUSgO;u^K|wq
z<)G84R1Km|sam^nNN4Nqi(U5L54h~VA3y~+&%HY9Ve1*C8fp2J@*(PV)^An@GD-z#
z1(XUR8kGtmICdD}Rw`<1%_^mmG($?I5pkt5h^$gs1m|hC$K#mBEKw_^I_Ygvsu#g+
z^dVA8kvK+z+6Hb7_9-=FwT)=k7fpU{T02@yezaXFINt~dv;WRyp+>10ni*|-v{1jK
z$RHyvI{P?8yhg5P%_@M9`kGw_8-AUKJv#eM&J$GXTeP}$_S<G<5F+(2axNAndyMq!
z?2i~Sr(O53G4lz55uEg=h2xz4nf+%$ElQC+MkbXadyL>f<cpDEZF}0}a~Ykb{_n5R
zHWI~PR@+tzA0DSx88W4_Ypl&tA$KEq@o$0Xgtq;TA@kbN#u4!ra>xj7_$PZrF5oZB
zNGb)%8=28If@`ov+nz;mD}RIGRq0;)H6l8}@J28k31!r+b1&d%ol28eMjI3)`Gq`6
z!}mt3m3}F=(4x{80!uyGei{A{RvNwsPufo4<z|(BB|}<OdWl(@4ru$U=$um;+BdSG
zG<Dl(t<JsHtcHV1!~RC=l!pC{)~K1nWx=U5RBkk+b8kn9UL_%xz3lK#Iz2k~E;_4p
z?i#a_WBUKt`-v)jEf1;M-ow6aN<-{MeM%FxqXC_R*x?epdI~?tP7}PN4yB1&JCfpU
z)T{Kz5o~b-BChQ>QoxMq+)dantu%aYWLjxzxY3x>&^r4goKF{iA$sl>lb?#KnPPE)
zLy&exT{?F=stqblz8Otu`xi`p*sXNo4G(sL*o~qu#BQ`n=hj(=$m$$fXkc2~zr@B<
zN<#-mo3(utGi!A2KC|R%SCU8vZPHtKhEgP>(X7&d1p#qxD<=%=+%`7O=^TaLV7Jmc
zcs8eVyC6Oeog*Xl&uRNZtl6qGnGI(t+DPdYm;1GrkfG`$JnYmtQc^!>D>W-asCa-y
zhm}6aYDt|t#M(Vd11X~|I(HO0?2!BQW_55t>63+vO`l>U6`O^WRynW0yV7!BX_j3U
z4=awDrL0$H4wCljw7nG<rcAcKnQLlNGs$bgqni$y3+)t;@335<LA8Wgiia$Z0o_-V
zeU04LnAIF^@Jr}9r+d<@j95@QXMg`OYCm#LFEJZHN!zc$EpbTOkFWdNb&f)b=t)y3
zO+gOum>f#~uJCJ+?SCYQhIH;?;d8EYe`X|H@-IAV*Y;;j9%R~1@BlaN_i^S~o%@Gb
znQ2z~U-nJy8g2hK^ILW9KlHY!f*_jdRmCL;ql{%`sjMnqOtVuJkh7UKRZuR?w5sA#
zM29M%YBSxccp0Kk6|X=5UYDEv8070igh5;tuc4E0f2~=L*C|8zObw~x^>i+%;tE7g
z6>mV$`9{Q?c3g?VF;!eeYfwAhRCwXJ;?1<WRPh!B#PzL+0ad&WF{X_DK5kHD&i0F@
z@LF}_mG;XVrz!}&nHlZ4nnQLda}C3Kb#EQ{m)5&!<&+`vrUta*gX}r4iVt(^K4m^a
z=aecwYF1|JQ~|x4tyaZ#2!|>@j&Le-Jws+yaRWQdDs!V*8jGre0Gw@91@+2ol`;h2
z)S@c>A1#k6C`M)js<;*5Rpzryh^XQ=S`Dfo`Px^4KS!%p6`zNdPpg6qJZpdSvg0md
zj(l5j4;?Y>pnk%!Gt^JhHOdfr)0lM=0_7;9W;5Dxf8l2`nFs78qYq&=+o=rI)O3SN
zZw3b0Y$u&rWk7;y_JsJ&rd0v)gTg2Gb8~FCmsUc%g496_d4!fN`7--#a+^^G3OLPC
z4j}x>96|(?A<(9MsyNKxCRH3kG^^q$ked;qv@)AgMR`HV4B;^yR>f&rxYZe)t+rb`
z&XJ@ixYJ6WqI#A6ipQ%82cz(U8bqsh)Z$=Ve;qBnw%(4x!VNU>MHd3^CCg8TRN<x7
zt_t${Ebbb>v~#Kmn&n1}7P1aLp^7jM{n`;R`Ed-}#KeSl#Mq-+nK-SeG9>%yn2KeV
z>$$cx6Ido|R_4&Lh1Q}ntqkGFZM5(mgCMV1Vza0nFkg@+)5DOoGL%ANICvkvgMaih
z5+w!@W7+{77{l1`;8}cta&ne1p%$Tbsu(dV^B7^2PGVq;-K$hFZu0Xzs+eNPgleBD
zaHbtIH~<EkWh9{oRfalM%+n&u77)ZLW$5g<GLII1yPtteOt&fXWdsoqo1SGqX!IOz
z^bOPn-KgSwqY6_cMmZ)JH%sKo+8!SLB_85`-!GV=;s*$D<cElURs5*%`SOmRpc9Jz
zltpV)@iPSHgc{EgTTeW13czs=zXKfS@S&#=82i@<taSkqS6L@TCQC2V!Yx)2C<D!y
z3oG+mv}eNaXgO8#Z;Fv2?Eo4lQS?uAVmlCWu0ff<FtT11&!8E)z}@Hks`#5d3)}zQ
zO2z_}bM?ynld;(HIkQ@iU&1=3#`Nj`+Si09mA%AVn6Tw&_C+>bI+eYY(K%IKW>y28
zsstD35~_STqD?!-us}jt>e}gHRldq@6HykHL7`m<OwPJg`C5h=Rf33fZdG21$SQjk
zL&lVa{!g<g7&w<yCEz!gRwbNcu3427v2*sz$er)B|E1BR%4<yCx2T=hlJM<U4O#nL
z2RXm;Jq0kRgk#KQRQW-x1dDx$W~(ZxYv+1Y3F6I+s}jVU>r&;%37RQYUQcJcDnUH3
zs`3+NWqeYVH`0o#65yNbQ02{bwSX!=ZI-KMRe1|r^=Rj<sK7F}7u>dpgr3Q&5_FsE
zRi=X@rBwQmS#BRt<-K-3TCJxTjHz-XV{&ruCUatv`<P#^N+51-P&<LRsX6T|La@^V
zbTZ#!8rtl#%lK4TTtI?KKyA*Wox2(8P;xJxivDnh*-=%(8D`_E++X;4%gzG~;bsoP
zs8RS(;Twy}G6W+*v^lN`44dOBP85FbRe8!RH9AyjG0dkd3}Sjgm1pht81o#xEK|V@
zhE^h2`#dwMROzsAHzhaqbB;0fl<{Z^g3a}-(v79L1q)pqs?n^B;ZY#iT#G8fs=01e
zMo3hRs%$FUNj3()&Z{!cGp-GEnyXV5(~`Ec-S*=Lx3XZ*%#^adg*WbZ_L=-lSlOIe
zPK_u#V#m0Y9ktS{?AY_&<At%=IY@DXvhxM8^RdEPX*<7+;MrHq8Yye%<FvTxZy?z6
zJ9N6_gz-SacmCM^b3N^Rf@j^@`Afv0vV?f`w08aqH4@tS6rI)D`D<E1?WC@NqU^k2
z^3#i2m$jtIq3o*3JCoYEX7a@UPUz1}K-oXD6D<gjkJzJVNOOv3>1<V&Y60)d60ksM
zmNEe+XomFz*}Gmx!VPK{Trc2O^BW*_{mS$c+FiP*nsW|o*T)&st7h^%_1LZ(Xtih;
zM0;*V=RaL|ZMlNzoMGe_3h#C|0fGU2{@-EN=4*BSi-pg@oA06(Q1d#9bC1qLm*=Z>
z{+{Qb-OIC}nn~UBi`sQx;ib&x&9FuL&F!u&_MfKKs~N_;P_12C3vX~Xle{U9cI{+v
zM$Nlu)o9m)w3^jiOsiJSIC%YxcI~0FQ_cAKLW7zgE_``i>N3mC^J*q#FSxa9f8m9(
zW-|AJOXu<I`J{Hijpw^{{zT!!z~*wZ>KxGdlRRtFF1&U=rSnc&F`Xyx&X4Il-n!t>
zd5>9jH)xj^Tl&;YIlYijvyU6$_yMjdtGnX%`^ZH#M|hZ2a}<FYsGJv?wJQt3^Jy0q
z?*bHR8mGs?q|b$Ro$o+2>wGt&Rp)!S8JC&|tVgg_;ax`i-Qzok&4uQ)c99CLLK9}S
z&i<0;Gn3}RD9TTBFsRxLE8Bm8>A%;qL(A<y^G(Yb?Yk1YzGY*U#4th#v*8cesYPx>
yboOh{J!UzY&}UY_{CWFdY@2^$i4}KErddqtJc(j4uJiv!B>q2VgNf-hTmS%eUL@53

literal 0
HcmV?d00001


From 01f9c07c3323843fbc0f1da1a08dc449f488fe00 Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Tue, 22 Sep 2015 16:42:13 -0400
Subject: [PATCH 04/12] remove unnecessary delayed loads in wordfreq.chinese

Former-commit-id: 4a87890afd81d87b3b30df13008d9013391dc446
---
 wordfreq/chinese.py | 14 ++++----------
 1 file changed, 4 insertions(+), 10 deletions(-)

diff --git a/wordfreq/chinese.py b/wordfreq/chinese.py
index 03a1ca3..e7ee371 100644
--- a/wordfreq/chinese.py
+++ b/wordfreq/chinese.py
@@ -3,22 +3,16 @@ import jieba
 import msgpack
 import gzip
 
-jieba_tokenizer = None
-simplified_map = None
 DICT_FILENAME = resource_filename('wordfreq', 'data/jieba_zh.txt')
 SIMP_MAP_FILENAME = resource_filename('wordfreq', 'data/_chinese_mapping.msgpack.gz')
+SIMPLIFIED_MAP = msgpack.load(gzip.open(SIMP_MAP_FILENAME), encoding='utf-8')
+JIEBA_TOKENIZER = jieba.Tokenizer(dictionary=DICT_FILENAME)
 
 
 def simplify_chinese(text):
-    global simplified_map
-    if simplified_map is None:
-        simplified_map = msgpack.load(gzip.open(SIMP_MAP_FILENAME), encoding='utf-8')
-    return text.translate(simplified_map).casefold()
+    return text.translate(SIMPLIFIED_MAP).casefold()
 
 
 def jieba_tokenize(text):
-    global jieba_tokenizer
-    if jieba_tokenizer is None:
-        jieba_tokenizer = jieba.Tokenizer(dictionary=DICT_FILENAME)
-    return jieba_tokenizer.lcut(simplify_chinese(text), HMM=False)
+    return JIEBA_TOKENIZER.lcut(simplify_chinese(text), HMM=False)
 

From 13642d6a4d53d8a00860e7d4bd5b6599c65197cd Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Tue, 22 Sep 2015 16:46:07 -0400
Subject: [PATCH 05/12] replace the literal 10 with the constant
 INFERRED_SPACE_FACTOR

Former-commit-id: 7a3ea2bf796c3f31fdf7d1c441b12b8ec52acf50
---
 wordfreq/__init__.py | 16 +++++++++-------
 1 file changed, 9 insertions(+), 7 deletions(-)

diff --git a/wordfreq/__init__.py b/wordfreq/__init__.py
index 4790282..85e4711 100644
--- a/wordfreq/__init__.py
+++ b/wordfreq/__init__.py
@@ -21,6 +21,14 @@ DATA_PATH = pathlib.Path(resource_filename('wordfreq', 'data'))
 # for the fact that token boundaries were inferred.
 SPACELESS_LANGUAGES = {'zh', 'ja'}
 
+# We'll divide the frequency by 10 for each token boundary that was inferred.
+# (We determined the factor of 10 empirically by looking at words in the
+# Chinese wordlist that weren't common enough to be identified by the
+# tokenizer. These words would get split into multiple tokens, and their
+# inferred frequency would be on average 9.77 times higher than their actual
+# frequency.)
+INFERRED_SPACE_FACTOR = 10.0
+
 # simple_tokenize is imported so that other things can import it from here.
 # Suppress the pyflakes warning.
 simple_tokenize = simple_tokenize
@@ -190,13 +198,7 @@ def _word_frequency(word, lang, wordlist, minimum):
     freq = 1.0 / one_over_result
 
     if lang in SPACELESS_LANGUAGES:
-        # Divide the frequency by 10 for each token boundary that was inferred.
-        # (We determined the factor of 10 empirically by looking at words in
-        # the Chinese wordlist that weren't common enough to be identified by
-        # the tokenizer. These words would get split into multiple tokens, and
-        # their inferred frequency would be on average 9.77 times higher than
-        # their actual frequency.)
-        freq /= 10 ** (len(tokens) - 1)
+        freq /= INFERRED_SPACE_FACTOR ** (len(tokens) - 1)
 
     return max(freq, minimum)
 

From b4628abb388be127426cf79460228d45d426b7de Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Tue, 22 Sep 2015 16:54:39 -0400
Subject: [PATCH 06/12] actually, still delay loading the Jieba tokenizer

Former-commit-id: 48734d1a6031a500c121e762dd2075dd37aaeb68
---
 wordfreq/chinese.py | 8 +++++---
 1 file changed, 5 insertions(+), 3 deletions(-)

diff --git a/wordfreq/chinese.py b/wordfreq/chinese.py
index e7ee371..c07e77e 100644
--- a/wordfreq/chinese.py
+++ b/wordfreq/chinese.py
@@ -6,7 +6,7 @@ import gzip
 DICT_FILENAME = resource_filename('wordfreq', 'data/jieba_zh.txt')
 SIMP_MAP_FILENAME = resource_filename('wordfreq', 'data/_chinese_mapping.msgpack.gz')
 SIMPLIFIED_MAP = msgpack.load(gzip.open(SIMP_MAP_FILENAME), encoding='utf-8')
-JIEBA_TOKENIZER = jieba.Tokenizer(dictionary=DICT_FILENAME)
+jieba_tokenizer = None
 
 
 def simplify_chinese(text):
@@ -14,5 +14,7 @@ def simplify_chinese(text):
 
 
 def jieba_tokenize(text):
-    return JIEBA_TOKENIZER.lcut(simplify_chinese(text), HMM=False)
-
+    global jieba_tokenizer
+    if jieba_tokenizer is None:
+        jieba_tokenizer = jieba.Tokenizer(dictionary=DICT_FILENAME)
+    return jieba_tokenizer.lcut(simplify_chinese(text), HMM=False)

From e6e29a1c03535555d0b18545e1b8a0b759fcb9b4 Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Tue, 22 Sep 2015 17:19:00 -0400
Subject: [PATCH 07/12] Make the jieba_deps comment make sense

Former-commit-id: 7c12f2aca169951f4619deb168b00fe14ff06809
---
 wordfreq_builder/wordfreq_builder/ninja.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

diff --git a/wordfreq_builder/wordfreq_builder/ninja.py b/wordfreq_builder/wordfreq_builder/ninja.py
index 2c94f58..80437ff 100644
--- a/wordfreq_builder/wordfreq_builder/ninja.py
+++ b/wordfreq_builder/wordfreq_builder/ninja.py
@@ -215,7 +215,8 @@ def opensubtitles_deps(dirname_in, languages):
 
 def jieba_deps(dirname_in, languages):
     lines = []
-    # Either subtlex_zh is turned off, or it's just in Chinese
+    # Because there's Chinese-specific handling here, the valid options for
+    # 'languages' are [] and ['zh']. Make sure it's one of those.
     if not languages:
         return lines
     assert languages == ['zh']

From d215f79ea37caf00fb826239f2888f50d71d8698 Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Tue, 22 Sep 2015 17:22:38 -0400
Subject: [PATCH 08/12] describe the use of `lang` in `read_values`

Former-commit-id: f224b8dbbaf4eb30988def5c35c4f8b204e5823e
---
 wordfreq_builder/wordfreq_builder/word_counts.py | 3 +++
 1 file changed, 3 insertions(+)

diff --git a/wordfreq_builder/wordfreq_builder/word_counts.py b/wordfreq_builder/wordfreq_builder/word_counts.py
index 1ba7214..a3bf0ae 100644
--- a/wordfreq_builder/wordfreq_builder/word_counts.py
+++ b/wordfreq_builder/wordfreq_builder/word_counts.py
@@ -42,6 +42,9 @@ def read_values(filename, cutoff=0, lang=None):
 
     If `cutoff` is greater than 0, the csv file must be sorted by value
     in descending order.
+
+    If `lang` is given, it will apply language-specific tokenization to the
+    words that it reads.
     """
     values = defaultdict(float)
     total = 0.

From 6b163e577291c1c5f02daad0a82c33e1c2810eaf Mon Sep 17 00:00:00 2001
From: Andrew Lin <alin@luminoso.com>
Date: Wed, 23 Sep 2015 13:02:40 -0400
Subject: [PATCH 09/12] Revert "Remove the no-longer-existent .txt files from
 the MANIFEST."

This reverts commit 20890901514ce950ba1c0cc8fc91d7a77b28e80e [formerly db41bc790271ec2fe6f12f63a0a1d2f7ffed74fc].


Former-commit-id: bb70bdba58441a398aa14d528f96c02da0dd4480
---
 MANIFEST.in | 1 +
 1 file changed, 1 insertion(+)

diff --git a/MANIFEST.in b/MANIFEST.in
index 4f20a26..012f4ca 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -1,2 +1,3 @@
 recursive-include wordfreq/data *.gz
 include README.md
+recursive-include wordfreq/data *.txt

From 4d00f17477e67ef42f98c6cad0b4ae0a83f06da8 Mon Sep 17 00:00:00 2001
From: Robyn Speer <rspeer@luminoso.com>
Date: Thu, 24 Sep 2015 12:49:45 -0400
Subject: [PATCH 10/12] don't apply the inferred-space penalty to Japanese

Former-commit-id: db5eda605116e5441745cc6712abffea7f59a47b
---
 tests/test_japanese.py |  4 ++--
 wordfreq/__init__.py   | 12 ++++++------
 2 files changed, 8 insertions(+), 8 deletions(-)

diff --git a/tests/test_japanese.py b/tests/test_japanese.py
index af05c2a..9906741 100644
--- a/tests/test_japanese.py
+++ b/tests/test_japanese.py
@@ -14,10 +14,10 @@ def test_combination():
 
     assert_almost_equal(
         word_frequency('おはようおはよう', 'ja'),
-        ohayou_freq / 20
+        ohayou_freq / 2
     )
     assert_almost_equal(
         1.0 / word_frequency('おはようございます', 'ja'),
-        (100.0 / ohayou_freq + 100.0 / gozai_freq + 100.0 / masu_freq)
+        (1.0 / ohayou_freq + 1.0 / gozai_freq + 1.0 / masu_freq)
     )
 
diff --git a/wordfreq/__init__.py b/wordfreq/__init__.py
index 85e4711..e6a4849 100644
--- a/wordfreq/__init__.py
+++ b/wordfreq/__init__.py
@@ -15,11 +15,11 @@ logger = logging.getLogger(__name__)
 CACHE_SIZE = 100000
 DATA_PATH = pathlib.Path(resource_filename('wordfreq', 'data'))
 
-# Chinese and Japanese are written without spaces. This means we have to
-# run language-specific code to infer token boundaries on them, and also
-# that we need to adjust frequencies of multi-token phrases to account
-# for the fact that token boundaries were inferred.
-SPACELESS_LANGUAGES = {'zh', 'ja'}
+# Chinese and Japanese are written without spaces. In Chinese, in particular,
+# we have to infer word boundaries from the frequencies of the words they
+# would create. When this happens, we should adjust the resulting frequency
+# to avoid creating a bias toward improbable word combinations.
+INFERRED_SPACE_LANGUAGES = {'zh'}
 
 # We'll divide the frequency by 10 for each token boundary that was inferred.
 # (We determined the factor of 10 empirically by looking at words in the
@@ -197,7 +197,7 @@ def _word_frequency(word, lang, wordlist, minimum):
 
     freq = 1.0 / one_over_result
 
-    if lang in SPACELESS_LANGUAGES:
+    if lang in INFERRED_SPACE_LANGUAGES:
         freq /= INFERRED_SPACE_FACTOR ** (len(tokens) - 1)
 
     return max(freq, minimum)

From e7d46fb104d9af02da047ce056b2a336b3c57a82 Mon Sep 17 00:00:00 2001
From: Andrew Lin <alin@luminoso.com>
Date: Thu, 24 Sep 2015 13:24:11 -0400
Subject: [PATCH 11/12] Revert a small syntax change introduced by a circular
 series of changes.

Former-commit-id: 09597b7cf33f4c1692f48d08a535bdbc45042cde
---
 tests/test_japanese.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

diff --git a/tests/test_japanese.py b/tests/test_japanese.py
index 9906741..d5a73b3 100644
--- a/tests/test_japanese.py
+++ b/tests/test_japanese.py
@@ -18,6 +18,6 @@ def test_combination():
     )
     assert_almost_equal(
         1.0 / word_frequency('おはようございます', 'ja'),
-        (1.0 / ohayou_freq + 1.0 / gozai_freq + 1.0 / masu_freq)
+        1.0 / ohayou_freq + 1.0 / gozai_freq + 1.0 / masu_freq
     )
 

From e27a75029d08525fb56209ff73a5f898c07feda0 Mon Sep 17 00:00:00 2001
From: Andrew Lin <alin@luminoso.com>
Date: Thu, 24 Sep 2015 13:31:34 -0400
Subject: [PATCH 12/12] Revert "Remove the no-longer-existent .txt files from
 the MANIFEST."

This reverts commit 20890901514ce950ba1c0cc8fc91d7a77b28e80e [formerly db41bc790271ec2fe6f12f63a0a1d2f7ffed74fc].


Former-commit-id: cd0797e1c8081acf96f4ff43b5f8ef76f3e10b7a
---
 MANIFEST.in | 1 +
 1 file changed, 1 insertion(+)

diff --git a/MANIFEST.in b/MANIFEST.in
index 4f20a26..012f4ca 100644
--- a/MANIFEST.in
+++ b/MANIFEST.in
@@ -1,2 +1,3 @@
 recursive-include wordfreq/data *.gz
 include README.md
+recursive-include wordfreq/data *.txt