init

requirements.txt

@@ -0,0 +1 @@
+pandas

stat.py

@@ -0,0 +1,103 @@
+import sys
+import getopt
+import pandas as pd
+import re
+
+
+def trim_space(s):
+    return s.replace(' ', '').replace(',', '').replace('，', '')
+
+def remove_at(s, i):
+    return s[0:i] + s[i+1:]
+
+def main(argv):
+    mode = '0'
+    parameter = '3323'
+    mode = '1'
+    parameter = 'bai vvv vv vvv,012 000 00 000;bai tou er xin,012 010 10 001'
+    try:
+        opts, args = getopt.getopt(argv, "hm:p:", ["mode=", "parameter="])
+    except getopt.GetoptError:
+        print('test.py -m <mode> -p <parameter>')
+        sys.exit(2)
+    for opt, arg in opts:
+        if opt == '-h':
+            print('test.py -i <mode> -o <parameter>')
+            sys.exit()
+        elif opt in ("-m", "--mode"):
+            mode = arg
+        elif opt in ("-p", "--parameter"):
+            parameter = arg
+    df = pd.read_json('idiom.json')
+    if mode == '0':
+        df['pinyin_rt'] = df.apply(lambda x: ''.join(map(lambda y: str(len(y)), re.split('[ ,，]',x['pinyin_r']))), axis=1)
+        groups = df.groupby(by='pinyin_rt')
+        group = groups.get_group(parameter).copy()
+        group['pinyin_c'] = group.apply(lambda x: len(set(trim_space(x['pinyin_r']))), axis=1)
+        print(df.loc[group['pinyin_c'].idxmax()])
+    elif mode == '1':
+        parameter_rst = parameter.split(';', 1)
+        if len(parameter_rst) > 1:
+            parameter_rst = parameter_rst[1]
+        else:
+            parameter_rst = ''
+        parameter = parameter.split(';')[0]
+
+        hits = parameter.split(',')[1]
+        parameter = trim_space(parameter.split(',')[0])
+ 
+        count = ''.join([str(len(x)) for x in hits.split()])
+        df['pinyin_rt'] = df.apply(lambda x: ''.join(map(lambda y: str(len(y)), re.split('[ ,，]',x['pinyin_r']))), axis=1)
+        groups = df.groupby(by='pinyin_rt')
+        group = groups.get_group(count).copy()
+
+        while(True):
+            group = filter_group_mode1(parameter, group, hits)
+            if(len(group) > 1 and len(parameter_rst) > 0):
+                parameter = parameter_rst.split(';')[0]
+                parameter_rst = parameter_rst.split(';', 1)
+                if len(parameter_rst) > 1:
+                    parameter_rst = parameter_rst[1]
+                else:
+                    parameter_rst = ''
+                hits = parameter.split(',')[1]
+                parameter = trim_space(parameter.split(',')[0])
+            elif len(group) < 0:
+                print('未找到匹配项')
+                return
+            else:
+                break
+        group['pinyin_c'] = group.apply(lambda x: len(set(trim_space(x['pinyin_r']))), axis=1)
+        print(df.loc[group['pinyin_c'].idxmax()])
+
+def filter_group_mode1(parameter, group, hits):
+    for i in range(len(parameter)):
+        key0 = 'pinyin0_%d' % i
+        key1 = 'pinyin1_%d' % i
+        key2 = 'pinyin2_%d' % i
+        group[key0] = group.apply(lambda x: ''.join(set(trim_space(x['pinyin_r']))), axis=1)
+        group[key1] = group.apply(lambda x: ''.join(set(remove_at(trim_space(x['pinyin_r']), i))), axis=1)
+        group[key2] = group.apply(lambda x: trim_space(x['pinyin_r'])[i], axis=1)
+    includes = set()
+    for i, hit in enumerate(list(trim_space(hits))):
+        if hit == '2':
+            includes.add(parameter[i])
+    for i, hit in enumerate(list(trim_space(hits))):
+        key0 = 'pinyin0_%d' % i
+        key1 = 'pinyin1_%d' % i
+        key2 = 'pinyin2_%d' % i
+        target = parameter[i]
+        if hit == '0' and target not in includes:
+            group = group[~group[key0].str.contains(target)]
+        elif hit == '1':
+            group = group[(group[key2] != target) & (group[key1].str.contains(target))]
+            includes.add(target)
+        elif hit == '2':
+            group = group[group[key2] == target]
+        if len(group) == 1:
+            break
+    return group
+
+if __name__ == '__main__':
+    main(sys.argv[1:])
+