84 lines
3.0 KiB
Python
84 lines
3.0 KiB
Python
from __future__ import annotations
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from io import BytesIO
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from openpyxl import Workbook
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from openpyxl.styles import Alignment, Font, PatternFill, Border, Side
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def build_export(result: dict) -> bytes:
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wb = Workbook()
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thin = Border(
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left=Side(style="thin", color="D9D1C3"),
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right=Side(style="thin", color="D9D1C3"),
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top=Side(style="thin", color="D9D1C3"),
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bottom=Side(style="thin", color="D9D1C3"),
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)
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head = PatternFill("solid", fgColor="12233D")
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head_font = Font(color="F4EFE6", bold=True)
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wrap = Alignment(wrap_text=True, vertical="center")
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first = True
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for g in result["groups"]:
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for t in g["targets"]:
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title = f"{g['group']}-{t['name']}"[:31]
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ws = wb.active if first else wb.create_sheet(title)
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if first:
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ws.title = title
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first = False
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ws.append(
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["班级", "测算人数", "最近一次在线", "滤波期望", "下达指标", "保底下界", "冲刺上界", "相对最近一次"]
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)
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for cell in ws[1]:
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cell.fill = head
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cell.font = head_font
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for row in t["classes"]:
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ws.append(
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[
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row["class_name"],
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row["n"],
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row["current"],
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row["expected"],
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row["assigned"],
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row["floor"],
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row["stretch"],
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row["delta"],
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]
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)
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ws.append([])
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ws.append(["说明：下达指标为预估中位水平，班级应努力超越该人数。保底/冲刺来自模拟分布的约20%/80%分位。"])
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ws = wb.create_sheet("学生明细")
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exams = result["exams"]
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headers = ["学号", "姓名", "班级", "方向", "学籍", "选科"]
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headers += [f"{e}-排名" for e in exams]
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# collect target names
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tcols = []
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for g in result["groups"]:
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for t in g["targets"]:
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tcols.append((g["group"], t["id"], f"{g['group']}-{t['name']}概率"))
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headers += [c[2] for c in tcols]
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headers += ["滤波水平", "预测方差"]
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ws.append(headers)
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for cell in ws[1]:
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cell.fill = head
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cell.font = head_font
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cell.alignment = wrap
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for s in result["students"]:
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row = [s["sid"], s["name"], s["class_name"], s["group"], s.get("status") or "", s.get("subjects") or ""]
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ranks = s.get("ranks") or []
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for i, _e in enumerate(exams):
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row.append(ranks[i] if i < len(ranks) else None)
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for gname, tid, _ in tcols:
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if s["group"] == gname:
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row.append((s.get("probs") or {}).get(tid))
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else:
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row.append(None)
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row.append(s.get("pred_mean"))
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row.append(s.get("pred_var"))
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ws.append(row)
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bio = BytesIO()
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wb.save(bio)
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return bio.getvalue()
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