爆改了数据可视化
This commit is contained in:
@@ -17,9 +17,8 @@ class ElasticConfig(AppConfig):
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return
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# 延迟导入，避免循环导入或过早加载
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from .es_connect import create_index_with_mapping, start_daily_analytics_scheduler
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from .es_connect import create_index_with_mapping
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try:
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create_index_with_mapping()
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start_daily_analytics_scheduler()
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except Exception as e:
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print(f"❌ ES 初始化失败: {e}")
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@@ -9,8 +9,8 @@ from .documents import AchievementDocument, UserDocument, GlobalDocument
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from .indexes import ACHIEVEMENT_INDEX_NAME, USER_INDEX_NAME, GLOBAL_INDEX_NAME
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import hashlib
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import time
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from datetime import datetime, timezone, timedelta
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import threading
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from datetime import datetime, timezone
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import json
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# 使用环境变量配置ES连接，默认为本机
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_ES_URL = os.environ.get('ELASTICSEARCH_URL', 'http://localhost:9200')
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@@ -309,67 +309,193 @@ def search_by_any_field(keyword):
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print(f"模糊搜索失败: {str(e)}")
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return []
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ANALYTICS_CACHE = {"data": None, "ts": 0}
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def _compute_hist(range_gte: str, interval: str, fmt: str):
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from elasticsearch_dsl import Search
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s = AchievementDocument.search()
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s = s.filter('range', time={'gte': range_gte, 'lte': 'now'})
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s = s.extra(size=0)
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s.aggs.bucket('b', 'date_histogram', field='time', calendar_interval=interval, format=fmt, min_doc_count=0)
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resp = s.execute()
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buckets = getattr(resp.aggs, 'b').buckets
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return [{"label": b.key_as_string, "count": b.doc_count} for b in buckets]
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def _compute_type_counts(range_gte: str, types: list):
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counts = []
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def _type_filters_from_list(limit: int = None):
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try:
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types = get_type_list()
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except Exception:
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types = ['软著', '专利', '奖状']
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if isinstance(limit, int) and limit > 0:
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types = types[:limit]
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filters = {}
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for t in types:
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s = AchievementDocument.search()
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s = s.filter('range', time={'gte': range_gte, 'lte': 'now'})
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s = s.query('match_phrase', data=str(t))
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total = s.count()
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counts.append({"type": str(t), "count": int(total)})
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return counts
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key = str(t)
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# 精确匹配键与值之间的关系，避免其它字段中的同名值造成误匹配
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pattern = f'*"数据类型": "{key}"*'
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filters[key] = {"wildcard": {"data.keyword": {"value": pattern}}}
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return filters
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def compute_analytics():
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types = get_type_list()
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days = _compute_hist('now-10d/d', 'day', 'yyyy-MM-dd')
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weeks = _compute_hist('now-10w/w', 'week', 'yyyy-ww')
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months = _compute_hist('now-10M/M', 'month', 'yyyy-MM')
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pie_1m = _compute_type_counts('now-1M/M', types)
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pie_12m = _compute_type_counts('now-12M/M', types)
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return {
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"last_10_days": days[-10:],
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"last_10_weeks": weeks[-10:],
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"last_10_months": months[-10:],
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"type_pie_1m": pie_1m,
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"type_pie_12m": pie_12m,
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}
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def analytics_trend(gte: str = None, lte: str = None, interval: str = "day"):
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try:
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search = AchievementDocument.search()
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body = {
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"size": 0,
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"aggs": {
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"trend": {
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"date_histogram": {
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"field": "time",
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"calendar_interval": interval,
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"min_doc_count": 0
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}
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}
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}
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}
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if gte or lte:
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rng = {}
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if gte:
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rng["gte"] = gte
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if lte:
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rng["lte"] = lte
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body["query"] = {"range": {"time": rng}}
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search = search.update_from_dict(body)
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resp = search.execute()
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buckets = resp.aggregations.trend.buckets if hasattr(resp, 'aggregations') else []
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return [{"key_as_string": b.key_as_string, "key": b.key, "doc_count": b.doc_count} for b in buckets]
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except Exception as e:
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print(f"分析趋势失败: {str(e)}")
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return []
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def get_analytics_overview(force: bool = False):
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now_ts = time.time()
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if force or ANALYTICS_CACHE["data"] is None or (now_ts - ANALYTICS_CACHE["ts"]) > 3600:
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ANALYTICS_CACHE["data"] = compute_analytics()
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ANALYTICS_CACHE["ts"] = now_ts
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return ANALYTICS_CACHE["data"]
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def analytics_types(gte: str = None, lte: str = None, size: int = 10):
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try:
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filters = _type_filters_from_list(limit=size)
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body = {
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"size": 0,
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"aggs": {
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"by_type": {
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"filters": {
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"filters": filters
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}
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}
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}
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}
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if gte or lte:
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rng = {}
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if gte:
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rng["gte"] = gte
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if lte:
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rng["lte"] = lte
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body["query"] = {"range": {"time": rng}}
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resp = es.search(index=DATA_INDEX_NAME, body=body)
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buckets = resp.get("aggregations", {}).get("by_type", {}).get("buckets", {})
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out = []
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for k, v in buckets.items():
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try:
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out.append({"key": k, "doc_count": int(v.get("doc_count", 0))})
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except Exception:
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out.append({"key": str(k), "doc_count": 0})
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return out
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except Exception as e:
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print(f"分析类型占比失败: {str(e)}")
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return []
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def _seconds_until_hour(h: int):
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now = datetime.now()
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tgt = now.replace(hour=h, minute=0, second=0, microsecond=0)
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if tgt <= now:
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tgt = tgt + timedelta(days=1)
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return max(0, int((tgt - now).total_seconds()))
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def analytics_types_trend(gte: str = None, lte: str = None, interval: str = "week", size: int = 8):
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try:
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filters = _type_filters_from_list(limit=size)
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body = {
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"size": 0,
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"aggs": {
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"by_interval": {
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"date_histogram": {
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"field": "time",
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"calendar_interval": interval,
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"min_doc_count": 0
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},
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"aggs": {
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"by_type": {
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"filters": {"filters": filters}
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}
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}
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}
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}
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}
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if gte or lte:
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rng = {}
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if gte:
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rng["gte"] = gte
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if lte:
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rng["lte"] = lte
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body["query"] = {"range": {"time": rng}}
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resp = es.search(index=DATA_INDEX_NAME, body=body)
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by_interval = resp.get("aggregations", {}).get("by_interval", {}).get("buckets", [])
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out = []
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for ib in by_interval:
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t_buckets = ib.get("by_type", {}).get("buckets", {})
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types_arr = []
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for k, v in t_buckets.items():
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types_arr.append({"key": k, "doc_count": int(v.get("doc_count", 0))})
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out.append({
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"key_as_string": ib.get("key_as_string"),
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"key": ib.get("key"),
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"doc_count": ib.get("doc_count", 0),
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"types": types_arr
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})
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return out
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except Exception as e:
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print(f"分析类型变化失败: {str(e)}")
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return []
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def start_daily_analytics_scheduler():
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def _run_and_reschedule():
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try:
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get_analytics_overview(force=True)
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except Exception as e:
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print(f"分析任务失败: {e}")
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finally:
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threading.Timer(24 * 3600, _run_and_reschedule).start()
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delay = _seconds_until_hour(3)
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threading.Timer(delay, _run_and_reschedule).start()
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def analytics_recent(limit: int = 10, gte: str = None, lte: str = None):
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try:
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def _extract_type(s: str):
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if not s:
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return ""
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try:
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obj = json.loads(s)
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if isinstance(obj, dict):
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v = obj.get("数据类型")
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if isinstance(v, str) and v:
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return v
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except Exception:
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pass
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try:
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m = re.search(r'"数据类型"\s*:\s*"([^"]+)"', s)
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if m:
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return m.group(1)
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except Exception:
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pass
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return ""
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search = AchievementDocument.search()
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body = {
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"size": max(1, min(limit, 100)),
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"sort": [{"time": {"order": "desc"}}]
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}
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if gte or lte:
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rng = {}
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if gte:
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rng["gte"] = gte
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if lte:
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rng["lte"] = lte
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body["query"] = {"range": {"time": rng}}
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search = search.update_from_dict(body)
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resp = search.execute()
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results = []
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for hit in resp:
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w = getattr(hit, 'writer_id', '')
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uname = None
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try:
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uname_lookup = get_user_by_id(w)
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uname = (uname_lookup or {}).get("username")
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except Exception:
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uname = None
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if not uname:
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try:
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uname_lookup = get_user_by_id(int(w))
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uname = (uname_lookup or {}).get("username")
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except Exception:
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uname = None
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tval = _extract_type(getattr(hit, 'data', ''))
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results.append({
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"_id": hit.meta.id,
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"writer_id": w,
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"username": uname or "",
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"type": tval or "",
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"time": getattr(hit, 'time', None)
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})
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return results
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except Exception as e:
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print(f"获取最近活动失败: {str(e)}")
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return []
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def write_user_data(user_data):
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"""
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@@ -1,5 +1,5 @@
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INDEX_NAME = "wordsearch266666"
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INDEX_NAME = "wordsearch2666661"
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USER_NAME = "users11111"
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ACHIEVEMENT_INDEX_NAME = INDEX_NAME
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USER_INDEX_NAME = USER_NAME
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GLOBAL_INDEX_NAME = "global11111"
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GLOBAL_INDEX_NAME = "global11111111211"
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@@ -17,7 +17,6 @@ urlpatterns = [
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path('search/', views.search, name='search'),
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path('fuzzy-search/', views.fuzzy_search, name='fuzzy_search'),
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path('all-data/', views.get_all_data, name='get_all_data'),
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path('analytics/overview/', views.analytics_overview, name='analytics_overview'),
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# 用户管理
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path('users/', views.get_users, name='get_users'),
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@@ -33,4 +32,10 @@ urlpatterns = [
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# 管理页面
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path('manage/', views.manage_page, name='manage_page'),
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path('user_manage/', views.user_manage, name='user_manage'),
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# 分析接口
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path('analytics/trend/', views.analytics_trend_view, name='analytics_trend'),
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path('analytics/types/', views.analytics_types_view, name='analytics_types'),
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path('analytics/types_trend/', views.analytics_types_trend_view, name='analytics_types_trend'),
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path('analytics/recent/', views.analytics_recent_view, name='analytics_recent'),
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]
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@@ -14,6 +14,12 @@ from django.views.decorators.csrf import ensure_csrf_cookie
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from django.views.decorators.csrf import csrf_exempt, ensure_csrf_cookie, csrf_protect
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from .es_connect import *
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from .es_connect import update_user_by_id as es_update_user_by_id, delete_user_by_id as es_delete_user_by_id
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from .es_connect import (
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analytics_trend as es_analytics_trend,
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analytics_types as es_analytics_types,
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analytics_types_trend as es_analytics_types_trend,
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analytics_recent as es_analytics_recent,
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)
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from PIL import Image
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@@ -80,16 +86,6 @@ def get_all_data(request):
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except Exception as e:
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return JsonResponse({"status": "error", "message": str(e)}, status=500)
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@require_http_methods(["GET"])
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def analytics_overview(request):
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try:
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force = request.GET.get("force") == "1"
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data = get_analytics_overview(force=force)
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return JsonResponse({"status": "success", "data": data})
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except Exception as e:
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return JsonResponse({"status": "error", "message": str(e)}, status=500)
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@require_http_methods(["DELETE"])
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@csrf_exempt
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def delete_data(request, doc_id):
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@@ -159,7 +155,11 @@ def update_data(request, doc_id):
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if isinstance(v, dict):
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updated["data"] = json.dumps(v, ensure_ascii=False)
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else:
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updated["data"] = str(v)
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try:
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obj = json.loads(str(v))
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updated["data"] = json.dumps(obj, ensure_ascii=False)
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except Exception:
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updated["data"] = str(v)
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success = update_by_id(doc_id, updated)
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if success:
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@@ -511,6 +511,67 @@ def manage_page(request):
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context = {"items": results, "user_id": user_id_qs or session_user_id}
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return render(request, "elastic/manage.html", context)
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@require_http_methods(["GET"])
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def analytics_trend_view(request):
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try:
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gte = request.GET.get("from")
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lte = request.GET.get("to")
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interval = request.GET.get("interval", "day")
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data = es_analytics_trend(gte=gte, lte=lte, interval=interval)
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return JsonResponse({"status": "success", "data": data})
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except Exception as e:
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return JsonResponse({"status": "error", "message": str(e)}, status=500)
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@require_http_methods(["GET"])
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def analytics_types_view(request):
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try:
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gte = request.GET.get("from")
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lte = request.GET.get("to")
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size = request.GET.get("size")
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try:
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size_int = int(size) if size is not None else 10
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except Exception:
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size_int = 10
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data = es_analytics_types(gte=gte, lte=lte, size=size_int)
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return JsonResponse({"status": "success", "data": data})
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except Exception as e:
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return JsonResponse({"status": "error", "message": str(e)}, status=500)
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@require_http_methods(["GET"])
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def analytics_types_trend_view(request):
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try:
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gte = request.GET.get("from")
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lte = request.GET.get("to")
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interval = request.GET.get("interval", "week")
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size = request.GET.get("size")
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try:
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size_int = int(size) if size is not None else 8
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except Exception:
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size_int = 8
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data = es_analytics_types_trend(gte=gte, lte=lte, interval=interval, size=size_int)
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return JsonResponse({"status": "success", "data": data})
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except Exception as e:
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return JsonResponse({"status": "error", "message": str(e)}, status=500)
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@require_http_methods(["GET"])
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def analytics_recent_view(request):
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try:
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limit = request.GET.get("limit")
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gte = request.GET.get("from")
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lte = request.GET.get("to")
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try:
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limit_int = int(limit) if limit is not None else 10
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except Exception:
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limit_int = 10
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data = es_analytics_recent(limit=limit_int, gte=gte, lte=lte)
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return JsonResponse({"status": "success", "data": data})
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except Exception as e:
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return JsonResponse({"status": "error", "message": str(e)}, status=500)
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@require_http_methods(["GET"])
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@ensure_csrf_cookie
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def user_manage(request):
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@@ -3,6 +3,7 @@
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<head>
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<meta charset="UTF-8" />
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<title>数据管理系统</title>
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<script src="https://cdn.jsdelivr.net/npm/echarts@5/dist/echarts.min.js"></script>
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<style>
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body {
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margin: 0;
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@@ -154,42 +155,31 @@
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<div class="main-content">
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<div class="card">
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<div class="header">
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<h2>数据概览</h2>
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<div style="display:flex; gap:8px; align-items:center;">
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<span class="badge">用户：{{ user_id }}</span>
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{% if is_admin %}
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<button id="triggerAnalyze" class="btn btn-primary">手动开始分析</button>
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{% endif %}
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</div>
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</div>
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<div class="grid-3">
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<div>
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||||
<div class="legend"><span class="dot" style="background:#4f46e5;"></span><span class="muted">最近十天录入</span></div>
|
||||
<canvas id="chartDays" height="140"></canvas>
|
||||
</div>
|
||||
<div>
|
||||
<div class="legend"><span class="dot" style="background:#16a34a;"></span><span class="muted">最近十周录入</span></div>
|
||||
<canvas id="chartWeeks" height="140"></canvas>
|
||||
</div>
|
||||
<div>
|
||||
<div class="legend"><span class="dot" style="background:#ea580c;"></span><span class="muted">最近十个月录入</span></div>
|
||||
<canvas id="chartMonths" height="140"></canvas>
|
||||
</div>
|
||||
<h2>主页</h2>
|
||||
<span class="badge">用户：{{ user_id }}</span>
|
||||
</div>
|
||||
<div class="muted">数据可视化概览：录入量变化、类型占比、类型变化、最近活动</div>
|
||||
</div>
|
||||
<div class="grid" style="margin-top:16px;">
|
||||
<div class="card">
|
||||
<div class="header"><h2>近1个月成果类型</h2></div>
|
||||
<canvas id="pie1m" height="200"></canvas>
|
||||
<div class="header"><h3>录入量变化（近90天）</h3></div>
|
||||
<div id="chartTrend" style="width:100%;height:320px;"></div>
|
||||
</div>
|
||||
<div class="card">
|
||||
<div class="header"><h2>近12个月成果类型</h2></div>
|
||||
<canvas id="pie12m" height="200"></canvas>
|
||||
<div class="header"><h3>类型占比（近30天）</h3></div>
|
||||
<div id="chartTypes" style="width:100%;height:320px;"></div>
|
||||
</div>
|
||||
<div class="card">
|
||||
<div class="header"><h3>类型变化（近180天，按周）</h3></div>
|
||||
<div id="chartTypesTrend" style="width:100%;height:320px;"></div>
|
||||
</div>
|
||||
<div class="card">
|
||||
<div class="header"><h3>最近活动（近7天）</h3></div>
|
||||
<ul id="recentList" style="list-style:none;padding:0;margin:0;"></ul>
|
||||
</div>
|
||||
</div>
|
||||
</div>
|
||||
|
||||
<script src="https://cdn.jsdelivr.net/npm/chart.js"></script>
|
||||
<script>
|
||||
// 获取CSRF令牌的函数
|
||||
function getCookie(name) {
|
||||
@@ -256,88 +246,101 @@
|
||||
}
|
||||
});
|
||||
|
||||
async function loadAnalytics() {
|
||||
const resp = await fetch('/elastic/analytics/overview/');
|
||||
const d = await resp.json();
|
||||
if (!resp.ok || d.status !== 'success') return;
|
||||
const data = d.data || {};
|
||||
renderLine('chartDays', data.last_10_days || [], '#4f46e5');
|
||||
renderLine('chartWeeks', data.last_10_weeks || [], '#16a34a');
|
||||
renderLine('chartMonths', data.last_10_months || [], '#ea580c');
|
||||
renderPie('pie1m', data.type_pie_1m || []);
|
||||
renderPie('pie12m', data.type_pie_12m || []);
|
||||
}
|
||||
|
||||
const btn = document.getElementById('triggerAnalyze');
|
||||
if (btn) {
|
||||
btn.addEventListener('click', async () => {
|
||||
btn.disabled = true;
|
||||
btn.textContent = '分析中…';
|
||||
try {
|
||||
const resp = await fetch('/elastic/analytics/overview/?force=1');
|
||||
const d = await resp.json();
|
||||
if (!resp.ok || d.status !== 'success') throw new Error('分析失败');
|
||||
window.location.reload();
|
||||
} catch (e) {
|
||||
btn.textContent = '重试';
|
||||
btn.disabled = false;
|
||||
}
|
||||
function fetchJSON(url){ return fetch(url, {credentials:'same-origin'}).then(r=>r.json()); }
|
||||
function qs(params){ const u = new URLSearchParams(params); return u.toString(); }
|
||||
|
||||
const trendChart = echarts.init(document.getElementById('chartTrend'));
|
||||
const typesChart = echarts.init(document.getElementById('chartTypes'));
|
||||
const typesTrendChart = echarts.init(document.getElementById('chartTypesTrend'));
|
||||
|
||||
async function loadTrend(){
|
||||
const url = '/elastic/analytics/trend/?' + qs({ from:'now-90d', to:'now', interval:'day' });
|
||||
const res = await fetchJSON(url);
|
||||
if(res.status!=='success') return;
|
||||
const buckets = res.data || [];
|
||||
const x = buckets.map(b=>b.key_as_string||'');
|
||||
const y = buckets.map(b=>b.doc_count||0);
|
||||
trendChart.setOption({
|
||||
tooltip:{trigger:'axis'},
|
||||
xAxis:{type:'category', data:x},
|
||||
yAxis:{type:'value'},
|
||||
series:[{ type:'line', areaStyle:{}, data:y, smooth:true, color:'#4f46e5' }]
|
||||
});
|
||||
}
|
||||
|
||||
function hexWithAlpha(hex, alphaHex) {
|
||||
if (!hex || !hex.startsWith('#')) return hex;
|
||||
if (hex.length === 7) return hex + alphaHex;
|
||||
return hex;
|
||||
}
|
||||
function renderLine(id, items, color) {
|
||||
const ctx = document.getElementById(id);
|
||||
const labels = items.map(x => x.label);
|
||||
const values = items.map(x => x.count);
|
||||
new Chart(ctx, {
|
||||
type: 'line',
|
||||
data: {
|
||||
labels,
|
||||
datasets: [{
|
||||
data: values,
|
||||
borderColor: color,
|
||||
backgroundColor: hexWithAlpha(color, '26'),
|
||||
tension: 0.25,
|
||||
fill: true,
|
||||
pointRadius: 3,
|
||||
}]
|
||||
},
|
||||
options: {
|
||||
responsive: true,
|
||||
plugins: { legend: { display: false } },
|
||||
animation: { duration: 800, easing: 'easeOutQuart' },
|
||||
scales: {
|
||||
x: { grid: { display: false } },
|
||||
y: { grid: { color: 'rgba(31,35,40,0.06)' }, beginAtZero: true }
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
function renderPie(id, items) {
|
||||
const ctx = document.getElementById(id);
|
||||
const labels = items.map(x => x.type);
|
||||
const values = items.map(x => x.count);
|
||||
const colors = ['#2563eb','#22c55e','#f59e0b','#ef4444','#a855f7','#06b6d4','#84cc16','#ec4899','#475569','#d946ef'];
|
||||
new Chart(ctx, {
|
||||
type: 'doughnut',
|
||||
data: {
|
||||
labels,
|
||||
datasets: [{ data: values, backgroundColor: colors.slice(0, labels.length) }]
|
||||
},
|
||||
options: {
|
||||
responsive: true,
|
||||
animation: { duration: 900, easing: 'easeOutQuart' },
|
||||
plugins: { legend: { position: 'bottom' } }
|
||||
}
|
||||
async function loadTypes(){
|
||||
const url = '/elastic/analytics/types/?' + qs({ from:'now-30d', to:'now', size:10 });
|
||||
const res = await fetchJSON(url);
|
||||
if(res.status!=='success') return;
|
||||
const buckets = res.data || [];
|
||||
const data = buckets.map(b=>({ name: String(b.key||'未知'), value: b.doc_count||0 }));
|
||||
typesChart.setOption({
|
||||
tooltip:{trigger:'item'},
|
||||
legend:{type:'scroll'},
|
||||
series:[{ type:'pie', radius:['40%','70%'], data }]
|
||||
});
|
||||
}
|
||||
|
||||
loadAnalytics();
|
||||
async function loadTypesTrend(){
|
||||
const url = '/elastic/analytics/types_trend/?' + qs({ from:'now-180d', to:'now', interval:'week', size:6 });
|
||||
const res = await fetchJSON(url);
|
||||
if(res.status!=='success') return;
|
||||
const rows = res.data || [];
|
||||
const x = rows.map(r=>r.key_as_string||'');
|
||||
const typeSet = new Set();
|
||||
rows.forEach(r=> (r.types||[]).forEach(t=> typeSet.add(String(t.key||'未知'))));
|
||||
const types = Array.from(typeSet);
|
||||
const series = types.map(tp=>({
|
||||
name: tp,
|
||||
type:'line',
|
||||
smooth:true,
|
||||
data: rows.map(r=>{
|
||||
const b = (r.types||[]).find(x=>String(x.key||'')===tp);
|
||||
return b? b.doc_count||0 : 0;
|
||||
})
|
||||
}));
|
||||
typesTrendChart.setOption({
|
||||
tooltip:{trigger:'axis'},
|
||||
legend:{type:'scroll'},
|
||||
xAxis:{type:'category', data:x},
|
||||
yAxis:{type:'value'},
|
||||
series
|
||||
});
|
||||
}
|
||||
|
||||
function formatTime(t){
|
||||
try{
|
||||
const d = new Date(t);
|
||||
if(String(d) !== 'Invalid Date'){
|
||||
const pad = n=> String(n).padStart(2,'0');
|
||||
return `${d.getFullYear()}-${pad(d.getMonth()+1)}-${pad(d.getDate())} ${pad(d.getHours())}:${pad(d.getMinutes())}`;
|
||||
}
|
||||
}catch(e){}
|
||||
return t||'';
|
||||
}
|
||||
|
||||
async function loadRecent(){
|
||||
const listEl = document.getElementById('recentList');
|
||||
const url = '/elastic/analytics/recent/?' + qs({ from:'now-7d', to:'now', limit:10 });
|
||||
const res = await fetchJSON(url);
|
||||
if(res.status!=='success') return;
|
||||
const items = res.data || [];
|
||||
listEl.innerHTML = '';
|
||||
items.forEach(it=>{
|
||||
const li = document.createElement('li');
|
||||
const t = formatTime(it.time);
|
||||
const u = it.username || '';
|
||||
const ty = it.type || '未知';
|
||||
li.textContent = `${t}，${u}，${ty}`;
|
||||
listEl.appendChild(li);
|
||||
});
|
||||
}
|
||||
|
||||
loadTrend();
|
||||
loadTypes();
|
||||
loadTypesTrend();
|
||||
loadRecent();
|
||||
</script>
|
||||
</body>
|
||||
</html>
|
||||
Reference in New Issue
Block a user