++

alpha-fetcher-gui/go.mod

@@ -0,0 +1,5 @@
+module alpha-fetcher-gui
+
+go 1.25.1
+
+require fyne.io/fyne/v2 v2.7.3 // indirect

alpha-fetcher-gui/go.sum

@@ -0,0 +1,2 @@
+fyne.io/fyne/v2 v2.7.3 h1:xBT/iYbdnNHONWO38fZMBrVBiJG8rV/Jypmy4tVfRWE=
+fyne.io/fyne/v2 v2.7.3/go.mod h1:gu+dlIcZWSzKZmnrY8Fbnj2Hirabv2ek+AKsfQ2bBlw=

fetch-alphas/wqb-get-alphas-one-week.py

@@ -100,10 +100,7 @@ class AlphaManager:
         except Exception as e:
             self.logger.error(f"标记颜色失败: {e}")
             return False
-    
-    def wechat_check_corr_message(self, message: str):
-        """微信通知（可选功能）"""
-        self.logger.info(f"通知消息: {message}")
+
     
     def _make_request_with_retry(self, url: str, max_retries: int = 3, retry_delay: float = 2.0):
         """

rpc_batch_fetch_dataset/rpc_create_dataset_record.py

@@ -10,7 +10,7 @@ params = {
     'limit': 50,
     'order': '-coverage',
     'region': 'EUR',
-    'universe': 'TOP2500'
+    'universe': 'TOP1200'
 }
 
 need_save = 0
@@ -121,7 +121,7 @@ if client:
 
     if all_results:
         # 输出 coverage 大于 0.5 的数据的 id
-        print("\ncoverage > 0.5 的数据 ID:")
+        print("\ncoverage > 0.5 的数据 ID:\n")
         coverage_ids = []
         for item in all_results:
             if 'coverage' in item and item['coverage'] > 0.5:

test/wqb-fetch-universe/fetch_universe.py

@@ -0,0 +1,65 @@
+# -*- coding: utf-8 -*-
+import httpx
+from httpx import BasicAuth
+
+
+def login():
+    """登录WorldQuant Brain API"""
+    # 从nacos获取账号密码
+    nacos_resp = httpx.get('http://192.168.31.41:30848/nacos/v1/cs/configs?dataId=wq_account&group=quantify')
+    if nacos_resp.status_code != 200:
+        print('获取账号密码失败')
+        return False
+
+    config = nacos_resp.json()
+
+    username = config['user_name']
+    password = config['password']
+
+    print(f"正在登录账户: {username}")
+
+    # 创建客户端并认证
+    client = httpx.Client(auth=BasicAuth(username, password))
+
+    # 发送登录请求
+    response = client.post('https://api.worldquantbrain.com/authentication')
+    print(f"登录状态: {response.status_code}")
+
+    if response.status_code == 201:
+        print("登录成功!")
+        print(response.json())
+        return client
+    else:
+        print(f"登录失败: {response.json()}")
+        client.close()
+        return None
+
+
+def fetch_universe(client):
+    try:
+        response = client.options('https://api.worldquantbrain.com/simulations')
+        print(f"Options请求状态: {response.status_code}")
+        results = response.json()
+    except Exception as e:
+        print(f"Options请求失败: {e}")
+        return {}
+
+    return results
+
+
+# 使用示例
+client = login()
+if client:
+    results = fetch_universe(client)
+    universe_data = (results.get('actions', {})
+                     .get('POST', {})
+                     .get('settings', {})
+                     .get('children', {})
+                     .get('universe', {})
+                     .get('choices', {})
+                     .get('instrumentType', {})
+                     .get('EQUITY', {})
+                     .get('region', {})
+                     )
+    print(universe_data)
+    client.close()

test/wqb-fetch-universe/test.py

@@ -0,0 +1,13 @@
+# -*- coding: utf-8 -*-
+data = {'USA': [{'value': 'TOP3000', 'label': 'TOP3000'}, {'value': 'TOP1000', 'label': 'TOP1000'}, {'value': 'TOP500', 'label': 'TOP500'}, {'value': 'TOP200', 'label': 'TOP200'},
+                {'value': 'ILLIQUID_MINVOL1M', 'label': 'ILLIQUID_MINVOL1M'}, {'value': 'TOPSP500', 'label': 'TOPSP500'}],
+        'GLB': [{'value': 'TOP3000', 'label': 'TOP3000'}, {'value': 'MINVOL1M', 'label': 'MINVOL1M'}, {'value': 'TOPDIV3000', 'label': 'TOPDIV3000'}],
+        'EUR': [{'value': 'TOP2500', 'label': 'TOP2500'}, {'value': 'TOP1200', 'label': 'TOP1200'}, {'value': 'TOP800', 'label': 'TOP800'}, {'value': 'TOP400', 'label': 'TOP400'},
+                {'value': 'ILLIQUID_MINVOL1M', 'label': 'ILLIQUID_MINVOL1M'}, {'value': 'TOPCS1600', 'label': 'TOPCS1600'}],
+        'ASI': [{'value': 'MINVOL1M', 'label': 'MINVOL1M'}, {'value': 'ILLIQUID_MINVOL1M', 'label': 'ILLIQUID_MINVOL1M'}], 'CHN': [{'value': 'TOP2000U', 'label': 'TOP2000U'}],
+        'KOR': [{'value': 'TOP600', 'label': 'TOP600'}], 'TWN': [{'value': 'TOP500', 'label': 'TOP500'}, {'value': 'TOP100', 'label': 'TOP100'}],
+        'IND': [{'value': 'TOP500', 'label': 'TOP500'}]}
+
+result = {k: [item['value'] for item in v] for k, v in data.items()}
+
+print(result)