From cc68634df488a5b67b2bb79ff65d7d1c14e882c5 Mon Sep 17 00:00:00 2001
From: Dorae <86833913+Toperlock@users.noreply.github.com>
Date: Wed, 6 Dec 2023 00:09:36 +0800
Subject: [PATCH] Update main.py

---
 main.py | 49 ++++++++++++++++++++++++++++++-------------------
 1 file changed, 30 insertions(+), 19 deletions(-)

diff --git a/main.py b/main.py
index 29ed2aa..fcd20c3 100644
--- a/main.py
+++ b/main.py
@@ -6,12 +6,10 @@ import json
 def read_csv_and_append(link):
     return pd.read_csv(link, header=None, names=['pattern', 'address', 'other'], on_bad_lines='warn')
 
-def parse_list_file(list_links, output_directory):
-    with open(list_links, 'r') as file:
-        list_links = file.read().splitlines()
+def parse_list_file(link, output_directory):
     with concurrent.futures.ThreadPoolExecutor() as executor:
         # 使用executor.map并行处理链接
-        results = list(executor.map(read_csv_and_append, list_links))
+        results = list(executor.map(read_csv_and_append, [link]))
         # 拼接为一个DataFrame
         df = pd.concat(results, ignore_index=True)
 
@@ -19,8 +17,10 @@ def parse_list_file(list_links, output_directory):
     df = df[~df['pattern'].str.contains('#')].reset_index(drop=True)
 
     # 映射字典
-    map_dict = {'DOMAIN-SUFFIX': 'domain_suffix', 'HOST-SUFFIX': 'domain_suffix', 'DOMAIN': 'domain', 'HOST': 'domain', 'DOMAIN-KEYWORD': 'domain_keyword',
-                'IP-CIDR': 'ip_cidr', 'IP-CIDR6': 'ip_cidr', 'SRC-IP-CIDR': 'source_ip_cidr', 'GEOIP': 'geoip', 'DST-PORT': 'port',
+    map_dict = {'DOMAIN-SUFFIX': 'domain_suffix', 'HOST-SUFFIX': 'domain_suffix', 'DOMAIN': 'domain', 'HOST': 'domain', 'host': 'domain',
+                'DOMAIN-KEYWORD':'domain_keyword', 'HOST-KEYWORD': 'domain_keyword', 'host-keyword': 'domain_keyword', 'IP-CIDR': 'ip_cidr',
+                'ip-cidr': 'ip_cidr', 'IP-CIDR6': 'ip_cidr', 
+                'IP6-CIDR': 'ip_cidr','SRC-IP-CIDR': 'source_ip_cidr', 'GEOIP': 'geoip', 'DST-PORT': 'port',
                 'SRC-PORT': 'source_port', "URL-REGEX": "domain_regex"}
 
     # 删除不在字典中的pattern
@@ -31,22 +31,33 @@ def parse_list_file(list_links, output_directory):
     # 替换pattern为字典中的值
     df['pattern'] = df['pattern'].replace(map_dict)
 
-    # 使用 groupby 分组并转化为字典
-    result_dict = df.groupby('pattern')['address'].apply(list).to_dict()
-
     # 创建自定义文件夹
     os.makedirs(output_directory, exist_ok=True)
 
-    file_names = []  # 存储生成的文件名
-    for link in list_links:
-        # 使用 output_directory 拼接完整路径
-        file_name = os.path.join(output_directory, os.path.basename(link).split('.')[0] + '.json')
-        file_names.append(file_name)
-        with open(file_name, 'w', encoding='utf-8') as output_file:
-            json.dump({"version": 1, "rules": [{"pattern": key, "address": value} for key, value in result_dict.items()]}, output_file, ensure_ascii=False, indent=2)
+    result_rules = {"version": 1, "rules": []}
 
-    return result_dict, file_names
+    for pattern, addresses in df.groupby('pattern')['address'].apply(list).to_dict().items():
+        rule_entry = {pattern: addresses}
+        result_rules["rules"].append(rule_entry)
+
+    # 使用 output_directory 拼接完整路径
+    file_name = os.path.join(output_directory, f"{os.path.basename(link).split('.')[0]}.json")
+    with open(file_name, 'w', encoding='utf-8') as output_file:
+        json.dump(result_rules, output_file, ensure_ascii=False, indent=2)
+
+    return file_name
+
+# 读取 links.txt 中的每个链接并生成对应的 JSON 文件
+with open("../links.txt", 'r') as links_file:
+    links = links_file.read().splitlines()
 
-list_of_links = "../links.txt"
 output_dir = "./"
-result_rules, file_names = parse_list_file(list_of_links, output_directory=output_dir)
+result_file_names = []
+
+for link in links:
+    result_file_name = parse_list_file(link, output_directory=output_dir)
+    result_file_names.append(result_file_name)
+
+# 打印生成的文件名
+# for file_name in result_file_names:
+    # print(file_name)