i18n: translate all Chinese comments, docstrings, and logger messages to English

Comprehensive translation of Chinese text to English across the entire codebase:

- api/: FastAPI server documentation and logger messages
- cache/: Cache abstraction layer comments and docstrings
- database/: Database models and MongoDB store documentation
- media_platform/: All platform crawlers (Bilibili, Douyin, Kuaishou, Tieba, Weibo, Xiaohongshu, Zhihu)
- model/: Data model documentation
- proxy/: Proxy pool and provider documentation
- store/: Data storage layer comments
- tools/: Utility functions and browser automation
- test/: Test file documentation

Preserved: Chinese disclaimer header (lines 10-18) for legal compliance

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>

tools/slider_util.py

@@ -21,7 +21,7 @@
 # -*- coding: utf-8 -*-
 # @Author  : relakkes@gmail.com
 # @Time    : 2023/12/2 12:55
-# @Desc    : 滑块相关的工具包
+# @Desc    : Slider verification utility package
 import os
 from typing import List
 from urllib.parse import urlparse
@@ -38,8 +38,8 @@ class Slide:
     """
     def __init__(self, gap, bg, gap_size=None, bg_size=None, out=None):
         """
-        :param gap: 缺口图片链接或者url
-        :param bg: 带缺口的图片链接或者url
+        :param gap: Gap image path or url
+        :param bg: Background image with gap path or url
         """
         self.img_dir = os.path.join(os.getcwd(), 'temp_image')
         if not os.path.exists(self.img_dir):
@@ -76,13 +76,13 @@ class Slide:
                 cv2.imwrite(img_path, image)
                 return img_path
             else:
-                raise Exception(f"保存{img_type}图片失败")
+                raise Exception(f"Failed to save {img_type} image")
         else:
             return img
 
     @staticmethod
     def clear_white(img):
-        """清除图片的空白区域，这里主要清除滑块的空白"""
+        """Clear whitespace from image, mainly clearing slider whitespace"""
         img = cv2.imread(img)
         rows, cols, channel = img.shape
         min_x = 255
@@ -108,16 +108,16 @@ class Slide:
     def template_match(self, tpl, target):
         th, tw = tpl.shape[:2]
         result = cv2.matchTemplate(target, tpl, cv2.TM_CCOEFF_NORMED)
-        # 寻找矩阵(一维数组当作向量,用Mat定义) 中最小值和最大值的位置
+        # Find min and max value positions in matrix
         min_val, max_val, min_loc, max_loc = cv2.minMaxLoc(result)
         tl = max_loc
         br = (tl[0] + tw, tl[1] + th)
-        # 绘制矩形边框，将匹配区域标注出来
-        # target：目标图像
-        # tl：矩形定点
-        # br：矩形的宽高
-        # (0,0,255)：矩形边框颜色
-        # 1：矩形边框大小
+        # Draw rectangle border to mark the matched area
+        # target: target image
+        # tl: rectangle top-left corner
+        # br: rectangle width and height
+        # (0,0,255): rectangle border color
+        # 1: rectangle border size
         cv2.rectangle(target, tl, br, (0, 0, 255), 2)
         cv2.imwrite(self.out, target)
         return tl[0]
@@ -138,39 +138,39 @@ class Slide:
         slide_pic = cv2.cvtColor(slide, cv2.COLOR_GRAY2RGB)
         back_pic = cv2.cvtColor(back, cv2.COLOR_GRAY2RGB)
         x = self.template_match(slide_pic, back_pic)
-        # 输出横坐标, 即 滑块在图片上的位置
+        # Output x-coordinate, i.e., slider position on image
         return x
 
 
 def get_track_simple(distance) -> List[int]:
-    # 有的检测移动速度的 如果匀速移动会被识别出来，来个简单点的 渐进
-    # distance为传入的总距离
-    # 移动轨迹
+    # Some detection checks movement speed - constant speed will be detected, so use gradual acceleration
+    # distance is the total distance to move
+    # Movement track
     track: List[int] = []
-    # 当前位移
+    # Current displacement
     current = 0
-    # 减速阈值
+    # Deceleration threshold
     mid = distance * 4 / 5
-    # 计算间隔
+    # Time interval
     t = 0.2
-    # 初速度
+    # Initial velocity
     v = 1
 
     while current < distance:
         if current < mid:
-            # 加速度为2
+            # Acceleration = 4
             a = 4
         else:
-            # 加速度为-2
+            # Acceleration = -3
             a = -3
         v0 = v
-        # 当前速度
+        # Current velocity
         v = v0 + a * t  # type: ignore
-        # 移动距离
+        # Movement distance
         move = v0 * t + 1 / 2 * a * t * t
-        # 当前位移
+        # Current displacement
         current += move  # type: ignore
-        # 加入轨迹
+        # Add to track
         track.append(round(move))
     return track