xhs_factory/services/profile.py
zhoujie b635108b89 refactor: split monolithic main.py into services/ + ui/ modules (improve-maintainability)
- main.py: 4360 → 146 lines (96.6% reduction), entry layer only
- services/: rate_limiter, autostart, persona, connection, profile,
  hotspot, content, engagement, scheduler, queue_ops (10 business modules)
- ui/app.py: all Gradio UI code extracted into build_app(cfg, analytics)
- Fix: with gr.Blocks() indented inside build_app function
- Fix: cfg.all property (not get_all method)
- Fix: STATUS_LABELS, get_persona_keywords, fetch_proactive_notes imports
- Fix: queue_ops module-level set_publish_callback moved into configure()
- Fix: pub_queue.format_*() wrapped as queue_format_table/calendar helpers
- All 14 files syntax-verified, build_app() runtime-verified
- 58/58 tasks complete"
2026-02-24 22:50:56 +08:00

177 lines
6.4 KiB
Python

"""
services/profile.py
小红书账号 Profile 解析与可视化函数
"""
import re
import json
import logging
import matplotlib
import matplotlib.pyplot as plt
from mcp_client import get_mcp_client
_font_candidates = ["Microsoft YaHei", "SimHei", "PingFang SC", "WenQuanYi Micro Hei"]
for _fn in _font_candidates:
try:
matplotlib.font_manager.findfont(_fn, fallback_to_default=False)
plt.rcParams["font.sans-serif"] = [_fn]
break
except Exception:
continue
plt.rcParams["axes.unicode_minus"] = False
logger = logging.getLogger("autobot")
# ==================================================
# Tab 4: 数据看板 (我的账号)
# ==================================================
def _parse_profile_json(text: str):
"""尝试从文本中解析用户 profile JSON"""
if not text:
return None
# 直接 JSON
try:
return json.loads(text)
except (json.JSONDecodeError, TypeError):
pass
# 可能包含 Markdown 代码块
m = re.search(r'```(?:json)?\s*\n([\s\S]+?)\n```', text)
if m:
try:
return json.loads(m.group(1))
except (json.JSONDecodeError, TypeError):
pass
return None
def _parse_count(val) -> float:
"""解析数字字符串, 支持 '1.2万' 格式"""
if isinstance(val, (int, float)):
return float(val)
s = str(val).strip()
if "" in s:
try:
return float(s.replace("", "")) * 10000
except ValueError:
pass
try:
return float(s)
except ValueError:
return 0.0
def fetch_my_profile(user_id, xsec_token, mcp_url):
"""获取我的账号数据, 返回结构化信息 + 可视化图表"""
if not user_id or not xsec_token:
return "❌ 请填写你的用户 ID 和 xsec_token", "", None, None, None
try:
client = get_mcp_client(mcp_url)
result = client.get_user_profile(user_id, xsec_token)
if "error" in result:
return f"{result['error']}", "", None, None, None
raw = result.get("raw", {})
text = result.get("text", "")
# 尝试从 raw 或 text 解析 JSON
data = None
if raw and isinstance(raw, dict):
content_list = raw.get("content", [])
for item in content_list:
if item.get("type") == "text":
data = _parse_profile_json(item.get("text", ""))
if data:
break
if not data:
data = _parse_profile_json(text)
if not data:
return "✅ 数据加载完成 (纯文本)", text, None, None, None
# ---- 提取基本信息 (注意 MCP 对新号可能返回 null) ----
basic = data.get("userBasicInfo") or {}
interactions = data.get("interactions") or []
feeds = data.get("feeds") or []
gender_map = {0: "未知", 1: "", 2: ""}
info_lines = [
f"## 👤 {basic.get('nickname', '未知')}",
f"- **小红书号**: {basic.get('redId', '-')}",
f"- **性别**: {gender_map.get(basic.get('gender', 0), '未知')}",
f"- **IP 属地**: {basic.get('ipLocation', '-')}",
f"- **简介**: {basic.get('desc', '-')}",
"",
"### 📊 核心数据",
]
for inter in interactions:
info_lines.append(f"- **{inter.get('name', '')}**: {inter.get('count', '0')}")
info_lines.append(f"\n### 📝 展示笔记: {len(feeds)}")
profile_md = "\n".join(info_lines)
# ---- 互动数据柱状图 ----
fig_interact = None
if interactions:
inter_data = {i["name"]: _parse_count(i["count"]) for i in interactions}
fig_interact, ax = plt.subplots(figsize=(4, 3), dpi=100)
labels = list(inter_data.keys())
values = list(inter_data.values())
colors = ["#FF6B6B", "#4ECDC4", "#45B7D1"][:len(labels)]
ax.bar(labels, values, color=colors, edgecolor="white", linewidth=0.5)
ax.set_title("账号核心指标", fontsize=12, fontweight="bold")
for i, v in enumerate(values):
display = f"{v/10000:.1f}" if v >= 10000 else str(int(v))
ax.text(i, v + max(values) * 0.02, display, ha="center", fontsize=9)
ax.set_ylabel("")
ax.spines["top"].set_visible(False)
ax.spines["right"].set_visible(False)
fig_interact.tight_layout()
# ---- 笔记点赞分布图 ----
fig_notes = None
if feeds:
titles, likes = [], []
for f in feeds[:15]:
nc = f.get("noteCard") or {}
t = (nc.get("displayTitle", "") or "无标题")[:12]
lk = _parse_count((nc.get("interactInfo") or {}).get("likedCount", "0"))
titles.append(t)
likes.append(lk)
fig_notes, ax2 = plt.subplots(figsize=(7, 3.5), dpi=100)
ax2.barh(range(len(titles)), likes, color="#FF6B6B", edgecolor="white")
ax2.set_yticks(range(len(titles)))
ax2.set_yticklabels(titles, fontsize=8)
ax2.set_title(f"笔记点赞排行 (Top {len(titles)})", fontsize=12, fontweight="bold")
ax2.invert_yaxis()
for i, v in enumerate(likes):
display = f"{v/10000:.1f}" if v >= 10000 else str(int(v))
ax2.text(v + max(likes) * 0.01 if max(likes) > 0 else 0, i, display, va="center", fontsize=8)
ax2.spines["top"].set_visible(False)
ax2.spines["right"].set_visible(False)
fig_notes.tight_layout()
# ---- 笔记详情表格 (Markdown) ----
table_lines = [
"### 📋 笔记数据明细",
"| # | 标题 | 类型 | ❤ 点赞 |",
"|---|------|------|--------|",
]
for i, f in enumerate(feeds):
nc = f.get("noteCard") or {}
t = (nc.get("displayTitle", "") or "无标题")[:25]
tp = "📹 视频" if nc.get("type") == "video" else "📷 图文"
lk = (nc.get("interactInfo") or {}).get("likedCount", "0")
table_lines.append(f"| {i+1} | {t} | {tp} | {lk} |")
notes_table = "\n".join(table_lines)
return "✅ 数据加载完成", profile_md, fig_interact, fig_notes, notes_table
except Exception as e:
logger.error(f"获取我的数据失败: {e}")
return f"{e}", "", None, None, None