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行宽 180 下把历史遗留的折行表达式合并，无语义改动。

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
This commit is contained in:
yuetsh
2026-08-05 04:45:26 -06:00
parent db104ac091
commit 3a9ab83ba5
56 changed files with 455 additions and 769 deletions
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147
ai/views/oj.py
View File

@@ -114,16 +114,12 @@ def get_class_user_ids(user):
cache_key = get_cache_key("class_users", user.class_name)
user_ids = cache.get(cache_key)
if user_ids is None:
user_ids = list(
User.objects.filter(class_name=user.class_name).values_list("id", flat=True)
)
user_ids = list(User.objects.filter(class_name=user.class_name).values_list("id", flat=True))
cache.set(cache_key, user_ids, CACHE_TIMEOUT)
return user_ids
def get_user_first_ac_submissions(
user_id, start, end, class_user_ids=None, use_class_scope=False, include_all_time=True
):
def get_user_first_ac_submissions(user_id, start, end, class_user_ids=None, use_class_scope=False, include_all_time=True):
# 用户自己的 AC 记录按时间范围过滤
user_first_ac = list(
Submission.objects.filter(
@@ -151,9 +147,7 @@ def get_user_first_ac_submissions(
if use_class_scope and class_user_ids:
rank_qs = rank_qs.filter(user_id__in=class_user_ids)
ranked_first_ac = list(
rank_qs.values("user_id", "problem_id").annotate(first_ac_time=Min("create_time"))
)
ranked_first_ac = list(rank_qs.values("user_id", "problem_id").annotate(first_ac_time=Min("create_time")))
by_problem = defaultdict(list)
for item in ranked_first_ac:
@@ -241,18 +235,14 @@ class AIDetailDataAPI(APIView):
except User.DoesNotExist:
return self.error("User not found")
cache_key = get_cache_key(
"ai_detail", user.id, user.class_name or "", start, end
)
cache_key = get_cache_key("ai_detail", user.id, user.class_name or "", start, end)
cached_result = cache.get(cache_key)
if cached_result:
return self.success(cached_result)
class_user_ids = get_class_user_ids(user)
use_class_scope = bool(user.class_name) and len(class_user_ids) > 1
user_first_ac, by_problem, problem_ids = get_user_first_ac_submissions(
user.id, start, end, class_user_ids, use_class_scope
)
user_first_ac, by_problem, problem_ids = get_user_first_ac_submissions(user.id, start, end, class_user_ids, use_class_scope)
# 同期排名：只统计时间窗口内解题的人
by_problem_period = defaultdict(list)
@@ -265,9 +255,7 @@ class AIDetailDataAPI(APIView):
)
if use_class_scope and class_user_ids:
period_qs = period_qs.filter(user_id__in=class_user_ids)
for item in period_qs.values("user_id", "problem_id").annotate(
first_ac_time=Min("create_time")
):
for item in period_qs.values("user_id", "problem_id").annotate(first_ac_time=Min("create_time")):
by_problem_period[item["problem_id"]].append(item)
for lst in by_problem_period.values():
lst.sort(key=lambda x: (x["first_ac_time"], x["user_id"]))
@@ -286,15 +274,8 @@ class AIDetailDataAPI(APIView):
}
if user_first_ac:
problems = {
p.id: p
for p in Problem.objects.filter(id__in=problem_ids)
.select_related("contest")
.prefetch_related("tags")
}
solved, contest_ids = self._build_solved_records(
user_first_ac, by_problem, by_problem_period, problems, user.id
)
problems = {p.id: p for p in Problem.objects.filter(id__in=problem_ids).select_related("contest").prefetch_related("tags")}
solved, contest_ids = self._build_solved_records(user_first_ac, by_problem, by_problem_period, problems, user.id)
# 查找 flowchart submissions
flowcharts_query = FlowchartSubmission.objects.filter(
user_id=user,
@@ -336,9 +317,7 @@ class AIDetailDataAPI(APIView):
# 找到最高分和对应的等级
best_score = max(scores) if scores else 0
best_submission = next(
(s for s in submissions if s.ai_score == best_score), submissions[0]
)
best_submission = next((s for s in submissions if s.ai_score == best_score), submissions[0])
best_grade = best_submission.ai_grade or ""
# 计算平均分
@@ -360,9 +339,7 @@ class AIDetailDataAPI(APIView):
flowcharts_data.append(merged_item)
# 按最新提交时间排序
flowcharts_data.sort(
key=lambda x: x["latest_submission_time"] or "", reverse=True
)
flowcharts_data.sort(key=lambda x: x["latest_submission_time"] or "", reverse=True)
result.update(
{
@@ -370,9 +347,7 @@ class AIDetailDataAPI(APIView):
"flowcharts": flowcharts_data,
"grade": calculate_average_grade([s["grade"] for s in solved]),
"tags": self._calculate_top_tags(problems.values()),
"difficulty": self._calculate_difficulty_distribution(
problems.values()
),
"difficulty": self._calculate_difficulty_distribution(problems.values()),
"contest_count": len(set(contest_ids)),
}
)
@@ -428,13 +403,8 @@ class AIDetailDataAPI(APIView):
def _calculate_difficulty_distribution(self, problems):
diff_counter = {"Low": 0, "Mid": 0, "High": 0}
for problem in problems:
diff_counter[
problem.difficulty if problem.difficulty in diff_counter else "Mid"
] += 1
return {
get_difficulty(k): v
for k, v in sorted(diff_counter.items(), key=lambda x: x[1], reverse=True)
}
diff_counter[problem.difficulty if problem.difficulty in diff_counter else "Mid"] += 1
return {get_difficulty(k): v for k, v in sorted(diff_counter.items(), key=lambda x: x[1], reverse=True)}
class AIDurationDataAPI(APIView):
@@ -451,9 +421,7 @@ class AIDurationDataAPI(APIView):
except User.DoesNotExist:
return self.error("User not found")
cache_key = get_cache_key(
"ai_duration", user.id, user.class_name or "", end_iso, duration
)
cache_key = get_cache_key("ai_duration", user.id, user.class_name or "", end_iso, duration)
cached_result = cache.get(cache_key)
if cached_result:
return self.success(cached_result)
@@ -468,9 +436,7 @@ class AIDurationDataAPI(APIView):
start = start + time_config["delta"]
period_end = start + time_config["delta"]
submission_count = Submission.objects.filter(
user_id=user.id, create_time__gte=start, create_time__lte=period_end
).count()
submission_count = Submission.objects.filter(user_id=user.id, create_time__gte=start, create_time__lte=period_end).count()
period_data = {
"unit": time_config["show_unit"],
@@ -502,9 +468,7 @@ class AIDurationDataAPI(APIView):
)
if use_class_scope and class_user_ids:
period_qs = period_qs.filter(user_id__in=class_user_ids)
for row in period_qs.values("user_id", "problem_id").annotate(
first_ac_time=Min("create_time")
):
for row in period_qs.values("user_id", "problem_id").annotate(first_ac_time=Min("create_time")):
by_problem_period[row["problem_id"]].append(row)
for lst in by_problem_period.values():
lst.sort(key=lambda x: (x["first_ac_time"], x["user_id"]))
@@ -558,7 +522,6 @@ class AIDurationDataAPI(APIView):
)
class AILoginSummaryAPI(APIView):
@login_required
def get(self, request):
@@ -574,20 +537,11 @@ class AILoginSummaryAPI(APIView):
)
new_problem_count = problems_qs.count()
submissions_qs = Submission.objects.filter(
user_id=user.id, create_time__gte=start_time, create_time__lte=end_time
)
submissions_qs = Submission.objects.filter(user_id=user.id, create_time__gte=start_time, create_time__lte=end_time)
submission_count = submissions_qs.count()
accepted_count = submissions_qs.filter(result__in=[JudgeStatus.ACCEPTED, JudgeStatus.AST_CHECK_FAILED]).count()
solved_count = (
submissions_qs.filter(result__in=[JudgeStatus.ACCEPTED, JudgeStatus.AST_CHECK_FAILED])
.values("problem_id")
.distinct()
.count()
)
flowchart_submission_count = FlowchartSubmission.objects.filter(
user_id=user.id, create_time__gte=start_time, create_time__lte=end_time
).count()
solved_count = submissions_qs.filter(result__in=[JudgeStatus.ACCEPTED, JudgeStatus.AST_CHECK_FAILED]).values("problem_id").distinct().count()
flowchart_submission_count = FlowchartSubmission.objects.filter(user_id=user.id, create_time__gte=start_time, create_time__lte=end_time).count()
summary = {
"start": datetime2str(start_time),
@@ -614,9 +568,7 @@ class AILoginSummaryAPI(APIView):
start_time = parse_datetime(start_raw) if start_raw else None
if start_time and timezone.is_naive(start_time):
start_time = timezone.make_aware(
start_time, timezone.get_current_timezone()
)
start_time = timezone.make_aware(start_time, timezone.get_current_timezone())
if not start_time:
if user.last_login and user.last_login < end_time:
@@ -637,11 +589,7 @@ class AILoginSummaryAPI(APIView):
except Exception as exc:
return "", str(exc)
system_prompt = (
"你是 OnlineJudge 的学习助教。"
"请根据统计数据给出简短分析(1-2句)，再给出一行结论，"
"结论用“结论：”开头。"
)
system_prompt = "你是 OnlineJudge 的学习助教。请根据统计数据给出简短分析(1-2句)，再给出一行结论，结论用“结论：”开头。"
user_prompt = (
f"时间范围：{summary['start']} 到 {summary['end']}\n"
f"新题目数：{summary['new_problem_count']}\n"
@@ -669,6 +617,7 @@ class AILoginSummaryAPI(APIView):
content = completion.choices[0].message.content or ""
return content.strip(), ""
class AIAnalysisAPI(APIView):
@login_required
def post(self, request):
@@ -697,9 +646,7 @@ class AIAnalysisAPI(APIView):
analysis=full_text,
)
return make_sse_response(
stream_ai_response(client, system_prompt, user_prompt, on_complete)
)
return make_sse_response(stream_ai_response(client, system_prompt, user_prompt, on_complete))
class ClassPKAnalysisAPI(APIView):
@@ -745,24 +692,11 @@ class ClassPKAnalysisAPI(APIView):
class_display = fmt_class(c["class_name"])
lines.append(f"\n### 第{i + 1}名：{class_display}（综合分 {c['composite_score']:.1f}）")
lines.append(f"- 人数：{c['user_count']}")
lines.append(
f"- 总AC数：{c['total_ac']}，总提交数：{c['total_submission']}，AC率：{c['ac_rate']:.1f}%"
)
lines.append(
f"- 平均AC：{c['avg_ac']:.2f}，中位数AC：{c['median_ac']:.2f}"
)
lines.append(
f"- Q1：{c['q1_ac']:.2f}，Q3：{c['q3_ac']:.2f}，"
f"IQR（四分位距）：{c['iqr']:.2f}，标准差：{c['std_dev']:.2f}"
)
lines.append(
f"- 前10%均值：{c['top_10_avg']:.2f}，中间80%均值：{c['middle_80_avg']:.2f}，"
f"后10%均值：{c['bottom_10_avg']:.2f}"
)
lines.append(
f"- 优秀率：{c['excellent_rate']:.1f}%，及格率：{c['pass_rate']:.1f}%，"
f"参与度：{c['active_rate']:.1f}%"
)
lines.append(f"- 总AC数：{c['total_ac']}，总提交数：{c['total_submission']}，AC率：{c['ac_rate']:.1f}%")
lines.append(f"- 平均AC：{c['avg_ac']:.2f}，中位数AC：{c['median_ac']:.2f}")
lines.append(f"- Q1：{c['q1_ac']:.2f}，Q3：{c['q3_ac']:.2f}，IQR（四分位距）：{c['iqr']:.2f}，标准差：{c['std_dev']:.2f}")
lines.append(f"- 前10%均值：{c['top_10_avg']:.2f}，中间80%均值：{c['middle_80_avg']:.2f}，后10%均值：{c['bottom_10_avg']:.2f}")
lines.append(f"- 优秀率：{c['excellent_rate']:.1f}%，及格率：{c['pass_rate']:.1f}%，参与度：{c['active_rate']:.1f}%")
if c.get("recent_total_ac") is not None:
lines.append(
@@ -781,19 +715,15 @@ class ClassPKAnalysisAPI(APIView):
"",
"**2. 参与积极性**：对比参与度和总提交数，谁的班学生更积极主动？",
"",
'**3. 典型学生水平**：重点用中位数AC数对比（而非平均值），'
'分析谁班的"普通学生"更强。若均值明显高于中位数，说明均值被少数强者拉高，需指出。',
'**3. 典型学生水平**：重点用中位数AC数对比（而非平均值），分析谁班的"普通学生"更强。若均值明显高于中位数，说明均值被少数强者拉高，需指出。',
"",
'**4. 班级内部均衡性**：结合标准差、IQR、前10%与后10%差距，'
'判断哪个班是"均衡型"，哪个班是"两极型"。',
'**4. 班级内部均衡性**：结合标准差、IQR、前10%与后10%差距，判断哪个班是"均衡型"，哪个班是"两极型"。',
"",
"**5. 梯队深度对比**：对比各班前10%均值（尖子生天花板）和后10%均值（薄弱学生水平），"
"分析各班在培养尖子生和帮扶后进生上的差异。",
"**5. 梯队深度对比**：对比各班前10%均值（尖子生天花板）和后10%均值（薄弱学生水平），分析各班在培养尖子生和帮扶后进生上的差异。",
"",
'**6. 代码提交质量**：对比AC率，是否有班级存在"凑提交次数但不思考"的问题？',
"",
"**7. 综合结论与建议**：用1句话明确说明胜负；"
"对落后班级给出2~3条具体可操作的改进建议；点出领先班级1条值得借鉴的做法。",
"**7. 综合结论与建议**：用1句话明确说明胜负；对落后班级给出2~3条具体可操作的改进建议；点出领先班级1条值得借鉴的做法。",
"",
"分析对象是班级任课教师，语言专业但不过分学术。",
]
@@ -916,9 +846,7 @@ class AIHintAPI(APIView):
f"学生代码：\n```\n{submission.code[:2000]}\n```"
)
return make_sse_response(
stream_ai_response(client, system_prompt, user_prompt)
)
return make_sse_response(stream_ai_response(client, system_prompt, user_prompt))
class AIHeatmapDataAPI(APIView):
@@ -941,9 +869,7 @@ class AIHeatmapDataAPI(APIView):
# 使用单次查询获取所有数据，按日期分组统计
submission_counts = (
Submission.objects.filter(
user_id=user.id, create_time__gte=start, create_time__lte=end
)
Submission.objects.filter(user_id=user.id, create_time__gte=start, create_time__lte=end)
.annotate(date=TruncDate("create_time"))
.values("date")
.annotate(count=Count("id"))
@@ -961,10 +887,7 @@ class AIHeatmapDataAPI(APIView):
submission_count = submission_dict.get(day_date, 0)
heatmap_data.append(
{
"timestamp": int(
datetime.combine(day_date, datetime.min.time()).timestamp()
* 1000
),
"timestamp": int(datetime.combine(day_date, datetime.min.time()).timestamp() * 1000),
"value": submission_count,
}
)