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"""
PRA Analysis Web App
上傳 HLA Fusion XLS → 自動分析 PRA Class I / II → 產生報告
"""
import io
import os
import re
import sys
import tempfile
from pathlib import Path
from collections import OrderedDict
from datetime import datetime
from flask import Flask, render_template, request, send_file, jsonify, redirect, url_for, session as flask_session
from PRA import NC_BEAD, PC_BEAD, _parse_allele_list
app = Flask(__name__)
app.config['MAX_CONTENT_LENGTH'] = 16 * 1024 * 1024 # 16MB
app.secret_key = 'pra-analysis-2025'
DEFAULT_USERS = {'NEPH': 'NEPH12345', 'okokyytt@gmail.com': '1234'}
ADMIN_USER = 'okokyytt@gmail.com'
import db as _db
_db.seed_default_users(DEFAULT_USERS, admin_user=ADMIN_USER)
def login_required(f):
from functools import wraps
@wraps(f)
def decorated(*args, **kwargs):
if not flask_session.get('logged_in'):
return redirect(url_for('login'))
return f(*args, **kwargs)
return decorated
# ============================================================
# 分析邏輯
# ============================================================
def build_qc_comment(nc_raw, pc_raw, beads_detail):
"""
QC 檢查 → 自動產生 Comment。
nc_raw: 病人樣本的 NC bead (001) Raw 值
pc_raw: NC 樣本的 PC bead (002) Raw 值(plate-level)
beads_detail: list of bead dicts, each with 'bead' and 'count'
"""
lines = []
# NC background check
if nc_raw > 1500:
lines.append('Uninterpretable due to high background bindings, please repeat')
elif nc_raw > 500:
lines.append('High background bindings')
# PC signal check (must be > 500)
if pc_raw <= 500:
lines.append('Low PC signal, please repeat')
# PC/NC ratio check
if nc_raw > 0 and pc_raw > 0:
ratio = pc_raw / nc_raw
if ratio < 2:
lines.append('Uninterpretable, please repeat')
# Bead count check
low_beads = [(b['bead'], b['count']) for b in beads_detail
if b.get('count', 0) > 0 and b['count'] < 80]
if low_beads:
lines.append('Low HLA Beads count, please repeat')
return '\n'.join(lines)
def clean_sero(sero_str):
"""清理 sero 字串: 'A2, , B46, , Bw6, , Cw1,' → 'A2, B46, Cw1'"""
if not sero_str:
return ''
skip = {'Bw4', 'Bw6', ''}
parts = [s.strip() for s in sero_str.split(',')]
parts = [s for s in parts if s not in skip]
return ', '.join(parts)
def clean_allele(allele_str):
"""清理 allele 字串:
- 移除 =alias (DPB1*04:01=DPB1*105:01 → DPB1*04:01)
- 移除 /276N, /163N null allele 後綴
- 移除 dash (-) 條目
- 移除空條目
"""
if not allele_str:
return ''
parts = [a.strip() for a in allele_str.split(',')]
cleaned = [p for p in parts if p and p != '-']
return ', '.join(cleaned)
def calculate_pra(bead_results, threshold='X6'):
threshold_rxn = int(threshold[1:])
total = len(bead_results)
positive = sum(1 for r in bead_results.values() if r['rxn'] >= threshold_rxn)
pra = round(positive / total * 100) if total > 0 else 0
return pra, positive, total
def get_confident_alleles(bead_results, bead_hla_map, threshold=0.8):
"""
篩選 confident alleles:80% Rule + Gray Zone(PRA1/PRA2 通用)
Step 1: 有 X2/X1 → 硬性排除
Step 2: 只有 X4 → 80% rule(X6X8/total ≥ 80% 才列入)
Step 3: 全部 X6/X8 → 直接列入
"""
def _clean(ag):
ag = ag.split('/')[0]
ag = ag.split('=')[0]
return ag
# 收集每個 allele 在不同 Rxn 層級的 bead
allele_beads = {} # allele -> {'x6x8': set, 'x4': set, 'x2x1': set}
for bid, r in bead_results.items():
hla = bead_hla_map.get(bid, {})
alleles = {_clean(a) for a in _parse_allele_list(hla.get('allele', ''))}
for ag in alleles:
if ag not in allele_beads:
allele_beads[ag] = {'x6x8': set(), 'x4': set(), 'x2x1': set()}
if r['rxn'] >= 6:
allele_beads[ag]['x6x8'].add(bid)
elif r['rxn'] >= 4:
allele_beads[ag]['x4'].add(bid)
else:
allele_beads[ag]['x2x1'].add(bid)
# 建 allele→sero 對照
a2s = _build_allele_to_sero(bead_hla_map)
confident = set()
decisions = [] # 每個 allele 的判定過程
for ag, levels in allele_beads.items():
n68 = len(levels['x6x8'])
n4 = len(levels['x4'])
n21 = len(levels['x2x1'])
sero = a2s.get(ag, '')
# 必須有 X6/X8
if not levels['x6x8']:
continue
# Step 1: 有 X2/X1 → 硬性排除
if levels['x2x1']:
decisions.append({'allele': ag, 'sero': sero, 'x6x8': n68, 'x4': n4, 'x2x1': n21, 'decision': 'Excluded (X2/X1)'})
continue
# Step 2: 只有 X4 → 80% rule
if levels['x4']:
total = n68 + n4
ratio = n68 / total
if ratio >= threshold:
confident.add(ag)
decisions.append({'allele': ag, 'sero': sero, 'x6x8': n68, 'x4': n4, 'x2x1': n21, 'decision': 'Assign'})
else:
decisions.append({'allele': ag, 'sero': sero, 'x6x8': n68, 'x4': n4, 'x2x1': n21, 'decision': f'Excluded (<80%: {ratio*100:.1f}%)'})
else:
# 全部都是 X6/X8,直接列入
confident.add(ag)
decisions.append({'allele': ag, 'sero': sero, 'x6x8': n68, 'x4': n4, 'x2x1': n21, 'decision': 'Assign'})
decisions.sort(key=lambda d: d['allele'])
return confident, decisions
def _build_allele_to_sero(bead_hla_map):
"""從 bead map 建立 allele→sero 對照"""
mapping = {}
for bid, hla in bead_hla_map.items():
sero_parts = [s.strip() for s in hla.get('sero', '').split(',')]
allele_parts = [a.strip() for a in hla.get('allele', '').split(',')]
skip = {'Bw4', 'Bw6', ''}
sero_by_locus = {}
for s in sero_parts:
if s in skip:
continue
# 判斷 locus
if s.startswith('A'):
sero_by_locus.setdefault('A', []).append(s)
elif s.startswith('B'):
sero_by_locus.setdefault('B', []).append(s)
elif s.startswith('Cw') or s.startswith('C'):
sero_by_locus.setdefault('C', []).append(s)
elif s.startswith('DR'):
sero_by_locus.setdefault('DR', []).append(s)
elif s.startswith('DQ'):
sero_by_locus.setdefault('DQ', []).append(s)
elif s.startswith('DP'):
sero_by_locus.setdefault('DP', []).append(s)
allele_by_locus = {}
for a in allele_parts:
if not a or a == '-':
continue
if a.startswith('A'):
allele_by_locus.setdefault('A', []).append(a)
elif a.startswith('B'):
allele_by_locus.setdefault('B', []).append(a)
elif a.startswith('C'):
allele_by_locus.setdefault('C', []).append(a)
elif a.startswith('DRB'):
allele_by_locus.setdefault('DR', []).append(a)
elif a.startswith('DQB'):
allele_by_locus.setdefault('DQ', []).append(a) # DQ sero = DQB1 only
elif a.startswith('DPB'):
allele_by_locus.setdefault('DP', []).append(a) # DP sero = DPB1 only
# DQA1/DPA1 不建 sero mapping(用 allele 格式顯示)
for locus in sero_by_locus:
seros = sero_by_locus[locus]
alleles = allele_by_locus.get(locus, [])
for i, ag in enumerate(alleles):
if i < len(seros):
# 同時建立原始和清理後的 mapping
mapping[ag] = seros[i]
clean_ag = ag.split('/')[0].split('=')[0]
if clean_ag != ag:
mapping[clean_ag] = seros[i]
return mapping
def build_sero_mfi_stats(beads_detail, confident_alleles, bead_hla_map):
"""
計算每個 confident sero 的 Max/Mean Normal MFI。
回傳 list of dict: [{sero, alleles, max_mfi, mean_mfi, count, beads}, ...]
按 max_mfi 降序排列。
"""
a2s = _build_allele_to_sero(bead_hla_map)
skip_sero = {'Bw4', 'Bw6', ''}
# 找出 confident sero set, DQA1/DQB1/DPA1/DPB1 用 allele 本身當 key
conf_seros = set()
sero_alleles = {} # sero -> set of confident alleles
for ag in confident_alleles:
prefix = ag.split('*')[0] if '*' in ag else ''
if prefix in ('DQA1', 'DQB1', 'DPA1', 'DPB1'):
# 用 allele 本身當 key
conf_seros.add(ag)
sero_alleles[ag] = {ag}
else:
sero = a2s.get(ag)
if sero and sero not in skip_sero:
conf_seros.add(sero)
sero_alleles.setdefault(sero, set()).add(ag)
# 收集每個 confident sero/allele 在正陽性 bead 上的 Normal 值
sero_normals = {}
sero_beads = {}
for b in beads_detail:
if b['rxn'] < 6:
continue
hla = bead_hla_map.get(b['bead'], {})
# Sero level
sero_parts = [s.strip() for s in hla.get('sero', '').split(',')]
for s in sero_parts:
if s in skip_sero:
continue
if s in conf_seros:
sero_normals.setdefault(s, []).append(b['normal'])
sero_beads.setdefault(s, []).append(b['bead'])
# Allele level (DQA1/DQB1/DPA1/DPB1)
for ag in _parse_allele_list(hla.get('allele', '')):
if ag in conf_seros:
sero_normals.setdefault(ag, []).append(b['normal'])
sero_beads.setdefault(ag, []).append(b['bead'])
# 組裝結果
stats = []
for sero in conf_seros:
normals = sero_normals.get(sero, [])
if not normals:
continue
alleles_str = ', '.join(sorted(sero_alleles.get(sero, set())))
stats.append({
'sero': sero,
'alleles': alleles_str,
'max_mfi': round(max(normals), 1),
'mean_mfi': round(sum(normals) / len(normals), 1),
'count': len(normals),
'beads': ', '.join(sero_beads.get(sero, [])),
})
# 排序: 按 locus 分組, 再按 max_mfi 降序
def sort_key(x):
s = x['sero']
if s.startswith('A'):
locus = 0
elif s.startswith('B'):
locus = 1
elif s.startswith('Cw') or s.startswith('C'):
locus = 2
elif s.startswith('DR'):
locus = 0
elif s.startswith('DQ'):
locus = 1
elif s.startswith('DP'):
locus = 2
else:
locus = 9
return (locus, -x['max_mfi'])
stats.sort(key=sort_key)
return stats
def generate_specificity(confident_alleles, bead_hla_map):
"""
將 confident alleles 轉為 Specificity 字串。
Class I: A11(A*11:02) A23 B7 Cw1
Class II: DR1 DR4 DQ5 DQ7 DQA1(*05:01 *03:03) DQB1(*03:01) DP2 DPA1(*01:03) DPB1(*04:01)
"""
if not confident_alleles:
return '(-)'
a2s = _build_allele_to_sero(bead_hla_map)
# 統計每個 sero group 在整個 bead panel 上有哪些 allele
all_alleles_per_sero = {}
for bid, hla in bead_hla_map.items():
for ag in _parse_allele_list(hla.get('allele', '')):
sero = a2s.get(ag)
if sero:
all_alleles_per_sero.setdefault(sero, set()).add(ag)
# 清理 allele 名稱(移除 /276N, =DPB1*105:01 等後綴)
def clean_allele(ag):
ag = ag.split('/')[0] # remove /276N
ag = ag.split('=')[0] # remove =DPB1*105:01
return ag
# 分組:
# DQA1/DPA1 (alpha chain, 無 sero) → allele 格式
# DQB1/DPB1 (beta chain, 有 sero) → 回歸 sero 對照
# 其他 → sero 對照
sero_groups = {}
allele_groups = {'DQA1': set(), 'DPA1': set()}
for ag in confident_alleles:
ag_clean = clean_allele(ag)
prefix = ag_clean.split('*')[0] if '*' in ag_clean else ''
if prefix in allele_groups:
# DQA1/DPA1 → allele 格式
allele_groups[prefix].add(ag_clean)
else:
# DQB1/DPB1 和其他 → sero 對照
sero = a2s.get(ag)
if not sero:
sero = a2s.get(ag_clean)
if sero:
sero_groups.setdefault(sero, set()).add(ag_clean)
# 排序: 按 locus 再按數字
import re as _re
def sort_key(s):
if s.startswith('A'):
locus = 0
elif s.startswith('B'):
locus = 1
elif s.startswith('Cw'):
locus = 2
elif s.startswith('DR'):
locus = 0
elif s.startswith('DQ'):
locus = 1
elif s.startswith('DP'):
locus = 2
else:
locus = 9
# 提取數字排序
m = _re.search(r'(\d+)', s)
num = int(m.group(1)) if m else 0
return (locus, num, s)
parts = []
# 分 DR/DQ sero, DQA1, DP sero, DPA1 四段輸出
dr_parts = []
dq_parts = []
dp_parts = []
other_parts = []
for sero in sorted(sero_groups.keys(), key=sort_key):
conf = sero_groups[sero]
alleles_str = ' '.join(f'<span style="color:#374151">{a}</span>' for a in sorted(conf))
entry = f'<span style="color:#1E40AF;font-weight:bold">{sero}</span>({alleles_str})'
if sero.startswith('DR'):
dr_parts.append(entry)
elif sero.startswith('DQ'):
dq_parts.append(entry)
elif sero.startswith('DP'):
dp_parts.append(entry)
else:
other_parts.append(entry)
# 順序: DR → DQ sero → DQA1 → DP sero → DPA1 → 其他(A,B,Cw)
parts.extend(other_parts) # A, B, Cw (Class I)
parts.extend(dr_parts)
parts.extend(dq_parts)
for ag in sorted(allele_groups['DQA1']):
parts.append(f'<span style="color:#374151">{ag}</span>')
parts.extend(dp_parts)
for ag in sorted(allele_groups['DPA1']):
parts.append(f'<span style="color:#374151">{ag}</span>')
return ' '.join(parts)
def parse_xls_file(raw_bytes):
"""
解析 HLA Fusion XLS 報告。
可能包含一個病人或 NC 報告。
回傳 dict: {sample_name, pra_class, date, beads_detail, ...}
"""
import xlrd
wb = xlrd.open_workbook(file_contents=raw_bytes)
sh = wb.sheet_by_index(0)
# 讀取 metadata
sample_name = str(sh.cell_value(0, 0)).strip()
if not sample_name:
# Row 1 可能有 PATIENT: xxx
if sh.nrows > 1:
r1 = str(sh.cell_value(1, 0)).strip()
if r1.startswith('PATIENT'):
sample_name = str(sh.cell_value(1, 1)).strip() if sh.ncols > 1 else r1
session = ''
date_val = ''
catalog = ''
# 掃描 header rows 找 TEST DATE / SESSION / CATALOG(直到找到 date_val 為止)
# TEST DATE label 和值的欄位位置依 XLS 版本不同,可能在 col 34/38 等
import re as _re
max_header_rows = min(sh.nrows, 15)
for r in range(max_header_rows):
if date_val and session and catalog:
break
row = [str(sh.cell_value(r, c)).strip() for c in range(sh.ncols)]
for i, v in enumerate(row):
if not session and v in ('SESSION :', 'SESSION:'):
for j in range(i + 1, len(row)):
if row[j]:
session = row[j]; break
if not date_val and v in ('TEST DATE :', 'TEST DATE:'):
for j in range(i + 1, len(row)):
if row[j] and '/' in row[j]:
date_val = row[j]; break
if not catalog and v in ('CATALOG :', 'CATALOG:'):
for j in range(i + 1, len(row)):
if row[j]:
catalog = row[j]; break
# 仍然沒抓到 TEST DATE → 從 SESSION 撈第一組 8 位數日期
if not date_val and session:
m = _re.search(r'\b(\d{8})\b', session)
if m:
digits = m.group(1)
date_val = f'{digits[:4]}/{digits[4:6]}/{digits[6:8]}'
# 最後 fallback:掃整張表任何含 'YYYY/M/D' 或 'YYYY-M-D' 的 cell
if not date_val:
date_re = _re.compile(r'\b(20\d{2})[/-](\d{1,2})[/-](\d{1,2})\b')
for r in range(min(sh.nrows, 20)):
for c in range(sh.ncols):
m = date_re.search(str(sh.cell_value(r, c)))
if m:
date_val = f'{m.group(1)}/{int(m.group(2))}/{int(m.group(3))}'
break
if date_val:
break
# 偵測 PRA class
pra_class = 'PRA1'
if 'LS2PRA' in catalog.upper() or 'PRA2' in catalog.upper():
pra_class = 'PRA2'
elif 'PRA2' in session.upper():
pra_class = 'PRA2'
# 讀取 bead 資料 (col 0=BeadID, 3=Raw, 11=NS_Raw, 15=Normal, 20=Ratio, 22=Rxn, 26=Count, 29=Sero, 35=Allele)
beads_detail = []
nc_raw = 0
pc_raw = 0
for r in range(9, sh.nrows):
bid = str(sh.cell_value(r, 0)).strip()
if not bid or bid == 'BeadID':
continue
# 整數 bead ID → 補零到 3 位
try:
bid_int = int(float(bid))
bid = f'{bid_int:03d}'
except (ValueError, TypeError):
continue
raw_val = sh.cell_value(r, 3) if sh.ncols > 3 else 0
ns_raw = sh.cell_value(r, 11) if sh.ncols > 11 else 0
normal = sh.cell_value(r, 15) if sh.ncols > 15 else 0
ratio = sh.cell_value(r, 20) if sh.ncols > 20 else 0
rxn_val = sh.cell_value(r, 22) if sh.ncols > 22 else ''
count_val = sh.cell_value(r, 26) if sh.ncols > 26 else 0
sero_raw = str(sh.cell_value(r, 29)).strip() if sh.ncols > 29 else ''
sero = clean_sero(sero_raw)
allele = str(sh.cell_value(r, 35)).strip() if sh.ncols > 35 else ''
# 處理數值
try:
raw_val = float(raw_val) if raw_val != '' else 0
except (ValueError, TypeError):
raw_val = 0
try:
ns_raw = float(ns_raw) if ns_raw != '' else 0
except (ValueError, TypeError):
ns_raw = 0
try:
normal = float(normal) if normal != '' else 0
except (ValueError, TypeError):
normal = 0
try:
ratio = float(ratio) if ratio != '' else 0
except (ValueError, TypeError):
ratio = 0
try:
count_val = int(float(count_val)) if count_val != '' else 0
except (ValueError, TypeError):
count_val = 0
# Rxn: 可能是數字 1/2/4/6/8 或 'NC'/'PC'
rxn_str = str(rxn_val).strip()
if rxn_str in ('NC', 'nc'):
nc_raw = raw_val
continue
elif rxn_str in ('PC', 'pc'):
pc_raw = raw_val
continue
try:
rxn_int = int(float(rxn_val))
except (ValueError, TypeError):
continue
# 跳過沒有 sero/allele 的 bead(非 HLA bead)
if not sero and not allele:
continue
beads_detail.append({
'bead': bid, 'rxn': rxn_int,
'raw': round(raw_val, 1), 'ns_raw': round(ns_raw, 1),
'normal': round(normal, 2), 'ratio': round(ratio, 2),
'count': count_val,
'sero': sero,
'allele': clean_allele(allele),
})
if not beads_detail:
return None # 沒有有效的 HLA bead 資料
# 計算 PRA%
total = len(beads_detail)
pra_all = {}
for t in ['X2', 'X4', 'X6', 'X8']:
t_rxn = int(t[1:])
pos = sum(1 for b in beads_detail if b['rxn'] >= t_rxn)
pra_all[t] = round(pos / total * 100) if total > 0 else 0
pra6 = pra_all['X6']
overall = 'Positive' if pra6 > 0 else 'Negative'
# Confident alleles — XLS 路徑:用 XLS 自帶的 allele 建 bead map(lot 可能不同)
br_dict = OrderedDict()
xls_bead_map = {}
for b in beads_detail:
br_dict[b['bead']] = {'rxn': b['rxn']}
xls_bead_map[b['bead']] = {'sero': b['sero'], 'allele': b['allele']}
confident, allele_decisions = get_confident_alleles(br_dict, xls_bead_map)
# Mark beads that contain confident alleles
for b in beads_detail:
bead_alleles = {a.strip().split('=')[0].split('/')[0] for a in b['allele'].split(',') if a.strip() and a.strip() != '-'}
b['is_confident'] = bool(bead_alleles & confident)
sero_mfi = build_sero_mfi_stats(beads_detail, confident, xls_bead_map) if overall == 'Positive' else []
pc_nc_ratio = round(pc_raw / nc_raw, 1) if nc_raw > 0 else 0
qc_comment = build_qc_comment(nc_raw, pc_raw, beads_detail)
return {
'name': sample_name,
'overall': overall,
'pra': pra6,
'pra_all': pra_all,
'beads': beads_detail,
'confident_alleles': sorted(confident),
'allele_decisions': allele_decisions,
'specificity': generate_specificity(confident, xls_bead_map) if overall == 'Positive' else '(-)',
'sero_mfi': sero_mfi,
'comment': qc_comment,
'qc': {
'nc_raw': round(nc_raw, 1),
'pc_raw': round(pc_raw, 1),
'pc_nc_ratio': pc_nc_ratio,
'nc_count': 0,
'pc_count': 0,
'low_beads': [{'bead': b['bead'], 'count': b['count']} for b in beads_detail if b.get('count', 0) > 0 and b['count'] < 80],
},
'_pra_class': pra_class,
'_date': date_val,
'_batch': session,
'_nc_raw': nc_raw,
'_pc_raw': pc_raw,
}
def full_analyze_xls(raw_bytes_list, filenames):
"""解析一個或多個 XLS 檔,回傳與 full_analyze 相同格式的結果"""
patients = []
pra_class = 'PRA1'
date_val = ''
batch = ''
nc_signal = 0
pc_signal = 0
errors = []
for raw_bytes, fname in zip(raw_bytes_list, filenames):
try:
pt = parse_xls_file(raw_bytes)
except Exception as e:
errors.append(f'{fname}: {type(e).__name__}: {e}')
continue
if pt is None:
errors.append(f'{fname}: 無 bead 資料 (可能非 HLA Fusion 報告)')
continue
# 若 sample name 為空,用檔名
if not pt.get('name'):
pt['name'] = Path(fname).stem
pra_class = pt.pop('_pra_class', 'PRA1')
if pt['_date']:
date_val = pt.pop('_date')
else:
pt.pop('_date')
if pt['_batch']:
batch = pt.pop('_batch')
else:
pt.pop('_batch')
nc_signal = pt.pop('_nc_raw', 0) or nc_signal
pc_signal = pt.pop('_pc_raw', 0) or pc_signal
patients.append(pt)
if not patients:
err_detail = '; '.join(errors) if errors else '無 bead 資料'
fnames = ', '.join(filenames)
return None, f'無法從 XLS 中讀取病人資料 [{fnames}] ({err_detail})'
return {
'pra_class': pra_class,
'class_label': 'PRA Class I' if pra_class == 'PRA1' else 'PRA Class II',
'date': date_val,
'batch': batch,
'nc_name': 'NC',
'pc_signal': round(pc_signal, 0),
'nc_signal': round(nc_signal, 0),
'patients': patients,
'filename': ', '.join(filenames),
}, None
# ============================================================
# Flask Routes
# ============================================================
@app.route('/login', methods=['GET', 'POST'])
def login():
if request.method == 'POST':
username = request.form.get('username', '').strip()
password = request.form.get('password', '')
import db
if db.check_user(username, password):
flask_session['logged_in'] = True
flask_session['username'] = username
flask_session['role'] = db.get_user_role(username)
flask_session['display_name'] = db.get_user_display_name(username)
return redirect(url_for('dashboard'))
# 自動註冊模式:帳號不存在就自動建立(臨時開放)
ok, msg = db.register_user(username, password, username)
if ok:
flask_session['logged_in'] = True
flask_session['username'] = username
flask_session['role'] = db.get_user_role(username)
flask_session['display_name'] = db.get_user_display_name(username)
return redirect(url_for('dashboard'))
return render_template('login.html', error='帳號或密碼錯誤')
return render_template('login.html')
@app.route('/register', methods=['GET', 'POST'])
def register():
if request.method == 'POST':
display_name = request.form.get('display_name', '').strip()
username = request.form.get('username', '').strip()
password = request.form.get('password', '')
password2 = request.form.get('password2', '')
if not display_name:
return render_template('register.html', error='請輸入姓名')
if not username:
return render_template('register.html', error='請輸入帳號')
if not password or len(password) < 4:
return render_template('register.html', error='密碼至少 4 碼')
if password != password2:
return render_template('register.html', error='兩次密碼不一致')
import db
ok, msg = db.register_user(username, password, display_name)
if ok:
return render_template('login.html', success='註冊成功,請登入')
return render_template('register.html', error=msg)
return render_template('register.html')
@app.route('/logout')
def logout():
flask_session.clear()
return redirect(url_for('login'))
@app.route('/')
@login_required
def dashboard():
return render_template('dashboard.html',
username=flask_session.get('username', ''),
is_admin=flask_session.get('role') == 'admin')
@app.route('/new')
@login_required
def index():
return render_template('index.html')
@app.route('/batch_upload', methods=['GET', 'POST'])
@login_required
def batch_upload():
"""批次上傳 XLS,從檔名抓病歷號與姓名,直接存入 DB。"""
if request.method == 'GET':
return render_template('batch.html')
import db
files = request.files.getlist('file')
charts = request.form.getlist('chart')
names = request.form.getlist('name')
mode = request.form.get('mode', 'new') # 'new' | 'overwrite' | 'skip'
results = []
ok_n = err_n = dup_n = 0
submitted_by = flask_session.get('display_name', flask_session.get('username', ''))
for idx, f in enumerate(files):
fname = f.filename or f'file{idx}'
chart = (charts[idx] if idx < len(charts) else '').strip()
name = (names[idx] if idx < len(names) else '').strip()
if not chart:
results.append({'file': fname, 'status': 'error', 'msg': '缺病歷號'})
err_n += 1
continue
try:
raw = f.read()
pt = parse_xls_file(raw)
except Exception:
results.append({'file': fname, 'status': 'error', 'msg': '解析失敗'})
err_n += 1
continue
if pt is None:
results.append({'file': fname, 'status': 'error', 'msg': '解析失敗(無 bead 資料)'})
err_n += 1
continue
pra_tag = pt.pop('_pra_class', 'PRA1')
pra_class = 'PRA Class I' if pra_tag == 'PRA1' else 'PRA Class II'
date_val = pt.pop('_date', '') or ''
if not date_val:
results.append({'file': fname, 'status': 'error', 'msg': '抓不到報告日期'})
err_n += 1
continue
patient_id = db.get_or_create_patient(name or fname, chart)
# 原始檔案先存 uploads/(同名直接覆寫,只留最新)
upload_dir = db.get_upload_dir()
orig_name = Path(fname).name.replace('/', '_').replace('\\', '_') or f'file_{idx}.xls'
save_path = upload_dir / orig_name
try:
save_path.write_bytes(raw)
saved_filename = save_path.name
db.push_upload_to_repo(save_path, saved_filename)
except Exception:
saved_filename = fname
# 重複偵測(依使用者模式處理 DB report,不影響已存的檔案)
existing = db.find_active_duplicate(patient_id, date_val, pra_class)
save_mode = 'overwrite'
if existing and mode == 'skip':
results.append({'file': fname, 'status': 'skipped', 'msg': f'檔案已保留;active report_id={existing}'})
dup_n += 1
continue
if existing and mode == 'new':
save_mode = 'new'
# strip HTML from specificity(generate_specificity 回傳帶色 span,DB 要存純文字)
import re as _re
spec_plain = _re.sub(r'<[^>]*>', '', pt.get('specificity', '')).strip()
spec_plain = _re.sub(r'\s+', ' ', spec_plain)
rid = db.save_report(
patient_id, date_val, pra_class,
pt.get('pra', 0), pt.get('overall', ''),
spec_plain, pt.get('comment', ''),
pt.get('sero_mfi', []),
'submitted', submitted_by, saved_filename, mode=save_mode
)
status = 'duplicate' if existing else 'ok'
if existing:
dup_n += 1
results.append({'file': fname, 'status': 'duplicate', 'msg': f'mode={mode}, report_id={rid}'})
else:
ok_n += 1
results.append({'file': fname, 'status': 'ok', 'msg': f'report_id={rid}'})
return jsonify({
'results': results,
'summary': {'ok': ok_n, 'err': err_n, 'dup': dup_n, 'total': len(files)},
})
@app.route('/analyze', methods=['POST'])
@login_required
def analyze():
files = request.files.getlist('file')
if not files or not files[0].filename:
return render_template('index.html', error='請選擇檔案')
# 收集所有結果,按 PRA class 分組
all_patients = {'PRA1': [], 'PRA2': []}
meta = {'PRA1': {}, 'PRA2': {}}
errors = []
for f in files:
raw_bytes = f.read()
fname = f.filename or 'unknown'
ext = Path(fname).suffix.lower()
is_xls = ext in ('.xls', '.xlsx') or (
len(raw_bytes) > 8 and raw_bytes[:8] == b'\xd0\xcf\x11\xe0\xa1\xb1\x1a\xe1')
if is_xls:
try:
pt = parse_xls_file(raw_bytes)
except Exception as e:
errors.append(f'{fname}: {e}')
continue
if pt is None:
errors.append(f'{fname}: 無 bead 資料')
continue
if not pt.get('name'):
pt['name'] = Path(fname).stem
pc = pt.pop('_pra_class', 'PRA1')
date_val = pt.pop('_date', '')
batch = pt.pop('_batch', '')
nc_raw = pt.pop('_nc_raw', 0)
pc_raw = pt.pop('_pc_raw', 0)
# 保存原始檔案
import db as _dbmod
import xlrd as _xlrd
upload_dir = _dbmod.get_upload_dir()
patient_name = request.form.get('patient_name', '').strip()
chart_no = request.form.get('patient_id', '').strip()
class_tag = 'PRA1' if pc == 'PRA1' else 'PRA2'
# 從 XLS row 0 抓 EL 編號 (如 EL20022_27996823)
el_part = ''
try:
_wb = _xlrd.open_workbook(file_contents=raw_bytes)
_sh = _wb.sheet_by_index(0)
_r0 = str(_sh.cell_value(0, 0)).strip()
if not _r0:
_r0 = str(_sh.cell_value(0, 1)).strip()
if 'EL' in _r0.upper():
el_part = _r0.split('_')[0] # EL20022
except Exception:
pass
# 保留原始檔名,同名直接覆寫(只留最新一筆)
orig = Path(fname).name.replace('/', '_').replace('\\', '_') or f'{patient_name}_{class_tag}{ext}'
save_path = upload_dir / orig
save_path.write_bytes(raw_bytes)
safe_name = save_path.name
import db as _dbmod2
_dbmod2.push_upload_to_repo(save_path, safe_name)
pt['_upload_file'] = safe_name
all_patients[pc].append(pt)
if date_val:
meta[pc]['date'] = date_val
if batch:
meta[pc]['batch'] = batch
meta[pc]['nc_signal'] = nc_raw
meta[pc]['pc_signal'] = pc_raw
else:
errors.append(f'{fname}: 不支援的檔案格式(僅支援 .xls)')
continue
# 組裝兩邊結果
def build_result(pc):
pts = all_patients[pc]
if not pts:
return None
m = meta.get(pc, {})
return {
'pra_class': pc,
'class_label': 'PRA Class I' if pc == 'PRA1' else 'PRA Class II',
'date': m.get('date', ''),
'batch': m.get('batch', ''),
'nc_name': m.get('nc_name', 'NC'),
'pc_signal': round(m.get('pc_signal', 0)),
'nc_signal': round(m.get('nc_signal', 0)),
'patients': pts,
}
result_pra1 = build_result('PRA1')
result_pra2 = build_result('PRA2')
if not result_pra1 and not result_pra2:
err_msg = '; '.join(errors) if errors else '無法辨識檔案格式'
return render_template('index.html', error=err_msg)
patient_name = request.form.get('patient_name', '').strip()
patient_id = request.form.get('patient_id', '').strip()
# 從 DB 帶入已存的 Donor HLA
donor_hla = ''
if patient_id:
import db
donor_hla = db.get_donor_hla(patient_id)
return render_template('index.html',
result_pra1=result_pra1,
result_pra2=result_pra2,
patient_name=patient_name,
patient_id=patient_id,
donor_hla=donor_hla,
errors=errors if errors else None)
@app.route('/export_docx', methods=['POST'])
@login_required
def export_docx():
"""匯出 DOCX 報告"""
from docx import Document
from docx.shared import Pt, Cm
from docx.enum.text import WD_ALIGN_PARAGRAPH
doc = Document()
style = doc.styles['Normal']
style.font.name = 'Calibri'
style.font.size = Pt(11)
data = request.json
pra_class_label = data.get('class_label', 'PRA Class I')
date_str = data.get('date', '')
pra_tag = 'PRA1' if 'I' in pra_class_label else 'PRA2'
# 標題
p = doc.add_paragraph(f'{date_str} {pra_tag}')
p.runs[0].bold = True
p.runs[0].font.size = Pt(14)
for pt in data.get('patients', []):
doc.add_paragraph('')
p = doc.add_paragraph(pt['name'])
p.runs[0].bold = True
doc.add_paragraph(pra_class_label)
doc.add_paragraph(f'Overall: {pt["overall"]}')
doc.add_paragraph(f'%SA (or %PRA): {pt["pra"]}')
doc.add_paragraph('Specificity:')
spec = pt.get('specificity', '').strip()
if not spec or spec == '':
spec = '(-)' if pt['overall'] == 'Negative' else '(-)'
doc.add_paragraph(spec)
doc.add_paragraph('COMMENT:')
buf = io.BytesIO()
doc.save(buf)
buf.seek(0)
filename = f'{date_str.replace("/", "")}_{pra_tag}_report.docx'
return send_file(buf, as_attachment=True, download_name=filename,
mimetype='application/vnd.openxmlformats-officedocument.wordprocessingml.document')
@app.route('/save', methods=['POST'])
@login_required
def save():
"""儲存分析結果到資料庫。
mode: 'auto' (default) 偵測到重複回 {duplicate:[...]} 不寫入;
'overwrite' 覆寫 active 重複;'new' 強制 INSERT 新列。"""
import db
data = request.json
patient_name = data.get('patient_name', '').strip()
chart_no = data.get('chart_no', '').strip()
if not chart_no:
return jsonify({'error': '請輸入病歷號'}), 400
patient_id = db.get_or_create_patient(patient_name, chart_no)
is_submitted = data.get('submitted', False)
status = 'submitted' if is_submitted else 'draft'
mode = data.get('mode', 'auto')
reports = data.get('reports', [])
# auto 模式:先偵測 active 重複
if mode == 'auto':
dups = []
for r in reports:
rid = db.find_active_duplicate(patient_id, r.get('report_date', ''), r.get('pra_class', ''))
if rid:
dups.append({'report_id': rid,
'pra_class': r.get('pra_class', ''),
'report_date': r.get('report_date', '')})
if dups:
return jsonify({'ok': False, 'duplicate': dups})
save_mode = 'new' if mode == 'new' else 'overwrite'
saved = []
for r in reports:
submitted_by = flask_session.get('display_name', flask_session.get('username', ''))
rid = db.save_report(patient_id, r.get('report_date', ''), r.get('pra_class', ''),
r.get('pra_percent', 0), r.get('overall', ''),
r.get('specificity', ''), r.get('comment', ''),
r.get('sero_mfi', []), status, submitted_by,
r.get('upload_file', ''), mode=save_mode)
saved.append({'report_id': rid, 'pra_class': r.get('pra_class', '')})
return jsonify({'ok': True, 'patient_id': patient_id, 'saved': saved})
def format_donor_hla(s):
"""Donor HLA JSON → 緊湊字串,例 'A:2,24 B:7,46 DRB1*:04:01,07:01 ...'"""
if not s:
return ''
import json as _json
try:
obj = _json.loads(s)
except Exception:
return ''
parts = []
for locus in ['A', 'B', 'Cw', 'DR', 'DQ', 'DP']:
vs = [obj.get(f'donor-{locus}-{n}') for n in ('1', '2')]
vs = [v for v in vs if v]
if vs:
parts.append(f'{locus}:{",".join(vs)}')
for locus in ['A', 'B', 'C', 'DRB1', 'DQB1', 'DQA1', 'DPB1', 'DPA1']:
vs = [obj.get(f'donor-dna-{locus}-{n}') for n in ('1', '2')]
vs = [v for v in vs if v]
if vs:
parts.append(f'{locus}*:{",".join(vs)}')
return ' '.join(parts)
@app.route('/history')
@login_required
def history():
"""顯示所有報告紀錄"""
import db
reports = db.get_all_reports()
for r in reports:
r['donor_hla_fmt'] = format_donor_hla(r.get('donor_hla'))
# DB stats
conn = db.get_conn()
db_stats = {
'patients': conn.execute('SELECT COUNT(*) as c FROM patients').fetchone()['c'],
'reports': conn.execute('SELECT COUNT(*) as c FROM reports WHERE COALESCE(is_deleted,0)=0').fetchone()['c'],
'users': conn.execute('SELECT COUNT(*) as c FROM users').fetchone()['c'],
}
conn.close()
return render_template('history.html', reports=reports, db_stats=db_stats,
is_admin=flask_session.get('role') == 'admin')
@app.route('/history/<chart_no>')
@login_required
def patient_history(chart_no):
"""顯示單一病人的報告歷史 + MFI 比較"""
import db
patient, reports = db.get_patient_reports(chart_no)
if not patient:
return render_template('history.html', reports=db.get_all_reports(),
error=f'找不到病歷號 {chart_no}')
# MFI comparison (Class I and Class II) — 已以 allele 為主 key 展開
dates1, antigens1, pra1, labels1 = db.get_mfi_comparison(chart_no, 'PRA Class I')
dates2, antigens2, pra2, labels2 = db.get_mfi_comparison(chart_no, 'PRA Class II')
all_labels = {**labels1, **labels2}
for r in reports:
r['chart_label'] = all_labels.get(r['id'], r['report_date'])
class Comp:
def __init__(self, dates, antigens, pra_by_date):
self.dates = dates
self.antigens = antigens
self.pra_by_date = pra_by_date
comp1 = Comp(dates1, antigens1, pra1) if dates1 else None
comp2 = Comp(dates2, antigens2, pra2) if dates2 else None
donor_hla = db.get_donor_hla(chart_no)
return render_template('patient.html', patient=patient, reports=reports,
comparison_class1=comp1, comparison_class2=comp2,
donor_hla=donor_hla)
@app.route('/cloud_sync', methods=['POST'])
@login_required
def cloud_sync():
if flask_session.get('role') != 'admin':
return jsonify({'error': '無權限'}), 403
try:
import sync as sync_module
import importlib
importlib.reload(sync_module)
local_info = sync_module.get_db_info(sync_module.LOCAL_DB)
# 下載雲端 DB
cloud_path = sync_module.download_cloud_db()
cloud_info = sync_module.get_db_info(cloud_path) if cloud_path else {'patients': 0, 'reports': 0, 'users': 0}
result = {
'ok': True,
'before': {
'local': f"{local_info['patients']} 病患 / {local_info['reports']} 報告",
'cloud': f"{cloud_info['patients']} 病患 / {cloud_info['reports']} 報告",
}
}
# Append-only merge: 以雲端為底,合併 Local 新增/更新
if cloud_path:
import tempfile
merged_path = Path(tempfile.gettempdir()) / 'pra_data_merged.db'
sync_module.merge_local_into_cloud(str(sync_module.LOCAL_DB), cloud_path, str(merged_path))
sync_module.upload_db(merged_path)
merged_info = sync_module.get_db_info(merged_path)
else:
# 雲端無 DB,直接上傳
sync_module.upload_db(sync_module.LOCAL_DB)
merged_info = local_info
# 同時推 backup 到 repo
import db as _dbmod
_dbmod.push_backups_to_repo()
result['status'] = 'synced'
result['message'] = f'Append-only merge 完成'
result['after'] = f"{merged_info['patients']} 病患 / {merged_info['reports']} 報告 / {merged_info['users']} 使用者"
return jsonify(result)
except Exception as e:
return jsonify({'error': str(e)})
@app.route('/update_report', methods=['POST'])
@login_required
def update_report():
import db
data = request.json
report_id = data.get('report_id')
specificity = data.get('specificity', '')
comment = data.get('comment', '')
if not report_id:
return jsonify({'error': 'missing report_id'}), 400
conn = db.get_conn()
db.backup_db()
conn.execute("""UPDATE reports SET specificity=?, comment=?,
updated_at=datetime('now','localtime') WHERE id=?""",
(specificity, comment, report_id))
conn.commit()
conn.close()
db.schedule_auto_push()
return jsonify({'ok': True})
@app.route('/delete_report/<int:report_id>', methods=['POST'])
@login_required
def delete_report_route(report_id):
import db
db.delete_report(report_id)
return jsonify({'ok': True})
@app.route('/admin')
@login_required
def admin():
if flask_session.get('role') != 'admin':
return redirect(url_for('dashboard'))
import db
users = db.get_all_users()
storage = db.get_storage_stats()
uploads = db.list_uploads()
return render_template('admin.html', users=users, storage=storage, uploads=uploads,
username=flask_session.get('username', ''))
@app.route('/admin/delete_upload', methods=['POST'])
@login_required
def admin_delete_upload():
if flask_session.get('role') != 'admin':
return jsonify({'error': '無權限'}), 403
import db
filename = (request.json or {}).get('filename', '')
if not filename:
return jsonify({'error': '缺檔名'}), 400
ok = db.delete_upload(filename)
return jsonify({'ok': ok})
@app.route('/admin/delete_user/<int:user_id>', methods=['POST'])
@login_required
def admin_delete_user(user_id):
if flask_session.get('role') != 'admin':
return jsonify({'error': '無權限'}), 403
import db
db.delete_user(user_id)
return jsonify({'ok': True})
@app.route('/admin/update_user/<int:user_id>', methods=['POST'])
@login_required
def admin_update_user(user_id):
if flask_session.get('role') != 'admin':
return jsonify({'error': '無權限'}), 403
import db
data = request.json
db.update_user(user_id, data.get('display_name'), data.get('username'),
data.get('password'), data.get('role'))
return jsonify({'ok': True})
@app.route('/save_donor_hla', methods=['POST'])
@login_required
def save_donor_hla_route():
import db
data = request.json
chart_no = data.get('chart_no', '')
donor_hla = data.get('donor_hla', '')
if not chart_no:
return jsonify({'error': 'missing chart_no'}), 400
db.save_donor_hla(chart_no, donor_hla)
return jsonify({'ok': True})
@app.route('/get_donor_hla/<chart_no>')
@login_required
def get_donor_hla_route(chart_no):
import db
donor_hla = db.get_donor_hla(chart_no)
return jsonify({'donor_hla': donor_hla})
@app.route('/analysis')
@login_required
def analysis():
"""統計分析頁面 — 選擇病人查看 MFI 趨勢"""
import db
patients = db.get_all_patients()
chart_no = request.args.get('chart_no', '')
patient = None
reports = []
comp1 = None
comp2 = None
if chart_no:
patient, reports = db.get_patient_reports(chart_no)
if patient:
dates1, antigens1, pra1, labels1 = db.get_mfi_comparison(chart_no, 'PRA Class I')
dates2, antigens2, pra2, labels2 = db.get_mfi_comparison(chart_no, 'PRA Class II')
# 新版 get_mfi_comparison 已以 allele 為主 key 展開,antigen 已是 sero(或無 sero 時 = allele)
all_labels = {**labels1, **labels2}
for r in reports:
r['chart_label'] = all_labels.get(r['id'], r['report_date'])
class Comp:
def __init__(self, dates, antigens, pra_by_date):
self.dates = dates
self.antigens = antigens
self.pra_by_date = pra_by_date
comp1 = Comp(dates1, antigens1, pra1) if dates1 else None
comp2 = Comp(dates2, antigens2, pra2) if dates2 else None
donor_hla = ''
if chart_no:
donor_hla = db.get_donor_hla(chart_no)
return render_template('analysis.html', patients=patients, chart_no=chart_no,
patient=patient, reports=reports,
comparison_class1=comp1, comparison_class2=comp2,
donor_hla=donor_hla)
@app.route('/download_upload/<path:filename>')
@login_required
def download_upload(filename):
"""下載上傳的原始檔案"""
import db
upload_dir = db.get_upload_dir()
fpath = upload_dir / filename
if not fpath.exists():
return 'File not found', 404
return send_file(str(fpath), as_attachment=True, download_name=filename)
@app.route('/admin/download_all_uploads')
@login_required
def download_all_uploads():
"""一鍵下載所有上傳檔案 (ZIP)。
?source=PRA / DSA:只下載該類,檔案放在 zip 根目錄。
無 source(預設):下載全部,依分類放入 PRA/ 與 DSA/ 子資料夾。
"""
if flask_session.get('role') != 'admin':
return 'Forbidden', 403
import db, zipfile
source = (request.args.get('source') or '').upper()
uploads = db.list_uploads()
name_to_source = {u['name']: u['source'] for u in uploads}
if source in ('PRA', 'DSA'):
wanted = {n for n, s in name_to_source.items() if s == source}
else:
wanted = set(name_to_source)
upload_dir = db.get_upload_dir()
files = [f for f in (list(upload_dir.glob('*.xls')) + list(upload_dir.glob('*.xlsx')) + list(upload_dir.glob('*.csv')))
if f.name in wanted]
if not files:
return 'No files', 404
buf = io.BytesIO()
with zipfile.ZipFile(buf, 'w', zipfile.ZIP_DEFLATED) as zf:
for f in files:
if source in ('PRA', 'DSA'):
arcname = f.name
else:
arcname = f"{name_to_source.get(f.name, 'PRA')}/{f.name}"
zf.write(str(f), arcname)
buf.seek(0)
from datetime import datetime
tag = f'_{source.lower()}' if source in ('PRA', 'DSA') else ''
fname = f'uploads{tag}_{datetime.now().strftime("%Y%m%d_%H%M%S")}.zip'
return send_file(buf, as_attachment=True, download_name=fname,
mimetype='application/zip')
@app.route('/admin/cleanup_uploads', methods=['POST'])
@login_required
def cleanup_uploads():
"""清理 N 個月前的上傳檔案"""
if flask_session.get('role') != 'admin':
return jsonify({'error': '無權限'}), 403
import db
from datetime import datetime, timedelta
months = request.json.get('months', 6)
cutoff = datetime.now() - timedelta(days=months * 30)
upload_dir = db.get_upload_dir()
files = list(upload_dir.glob('*.xls')) + list(upload_dir.glob('*.xlsx')) + list(upload_dir.glob('*.csv'))
deleted = 0
for f in files:
mtime = datetime.fromtimestamp(f.stat().st_mtime)
if mtime < cutoff:
f.unlink()
deleted += 1
return jsonify({'ok': True, 'deleted': deleted})
# ============================================================
# DSA Routes (Single-Antigen / Donor-Specific Antibody)
# Mirror of PRA flow but reads SA xls and uses Strong/Weak cutoffs.
# ============================================================
import dsa as _dsa
def _dsa_class_label(tag):
return 'DSA Class I' if tag == 'DSA1' else 'DSA Class II'
def _build_dsa_result(pc, all_patients, meta):
pts = all_patients[pc]
if not pts:
return None
m = meta.get(pc, {})
return {
'pra_class': pc,
'class_label': _dsa_class_label(pc),
'date': m.get('date', ''),
'batch': m.get('batch', ''),
'nc_name': m.get('nc_name', 'NC'),
'pc_signal': round(m.get('pc_signal', 0)),
'nc_signal': round(m.get('nc_signal', 0)),
'patients': pts,
}
@app.route('/dsa/new')
@login_required
def dsa_index():
return render_template('dsa_index.html')
@app.route('/dsa/analyze', methods=['POST'])
@login_required
def dsa_analyze():
files = request.files.getlist('file')
if not files or not files[0].filename:
return render_template('dsa_index.html', error='請選擇檔案')
import db as _dbmod
all_patients = {'DSA1': [], 'DSA2': []}
meta = {'DSA1': {}, 'DSA2': {}}
errors = []
for f in files:
raw = f.read()
fname = f.filename or 'unknown'
ext = Path(fname).suffix.lower()
is_xls = ext in ('.xls', '.xlsx') or (
len(raw) > 8 and raw[:8] == b'\xd0\xcf\x11\xe0\xa1\xb1\x1a\xe1')
if not is_xls:
errors.append(f'{fname}: 僅支援 .xls')
continue
try:
pt = _dsa.parse_xls_file(raw)
except Exception as e:
errors.append(f'{fname}: {e}')
continue
if pt is None:
errors.append(f'{fname}: 無 bead 資料')
continue
if not pt.get('name'):
pt['name'] = Path(fname).stem
pc = pt.pop('_pra_class', 'DSA1')
date_val = pt.pop('_date', '')
batch = pt.pop('_batch', '')
nc_raw = pt.pop('_nc_raw', 0)
pc_raw = pt.pop('_pc_raw', 0)
upload_dir = _dbmod.get_upload_dir()
orig = Path(fname).name.replace('/', '_').replace('\\', '_') or f'dsa_{pc}{ext}'
save_path = upload_dir / orig
try:
save_path.write_bytes(raw)
_dbmod.push_upload_to_repo(save_path, save_path.name)
pt['_upload_file'] = save_path.name
except Exception:
pt['_upload_file'] = fname
all_patients[pc].append(pt)
if date_val: meta[pc]['date'] = date_val
if batch: meta[pc]['batch'] = batch
meta[pc]['nc_signal'] = nc_raw
meta[pc]['pc_signal'] = pc_raw
result_dsa1 = _build_dsa_result('DSA1', all_patients, meta)
result_dsa2 = _build_dsa_result('DSA2', all_patients, meta)
if not result_dsa1 and not result_dsa2:
err_msg = '; '.join(errors) if errors else '無法辨識檔案格式'
return render_template('dsa_index.html', error=err_msg)
patient_name = request.form.get('patient_name', '').strip()
patient_id = request.form.get('patient_id', '').strip()
donor_hla = ''
if patient_id:
donor_hla = _dbmod.get_donor_hla(patient_id)
return render_template('dsa_index.html',
result_dsa1=result_dsa1, result_dsa2=result_dsa2,
patient_name=patient_name, patient_id=patient_id,
donor_hla=donor_hla,
errors=errors if errors else None)
@app.route('/dsa/save', methods=['POST'])
@login_required
def dsa_save():
import db as _dbmod
data = request.json
patient_name = data.get('patient_name', '').strip()
chart_no = data.get('chart_no', '').strip()
if not chart_no:
return jsonify({'error': '請輸入病歷號'}), 400
patient_id = _dbmod.get_or_create_patient(patient_name, chart_no)
is_submitted = data.get('submitted', False)
status = 'submitted' if is_submitted else 'draft'
mode = data.get('mode', 'auto')
reports = data.get('reports', [])
if mode == 'auto':
dups = []
for r in reports:
rid = _dbmod.find_active_duplicate_dsa(
patient_id, r.get('report_date', ''), r.get('dsa_class', ''))
if rid:
dups.append({'report_id': rid,
'dsa_class': r.get('dsa_class', ''),
'report_date': r.get('report_date', '')})
if dups:
return jsonify({'ok': False, 'duplicate': dups})
save_mode = 'new' if mode == 'new' else 'overwrite'
saved = []
for r in reports:
submitted_by = flask_session.get('display_name', flask_session.get('username', ''))
rid = _dbmod.save_dsa_report(
patient_id, r.get('report_date', ''), r.get('dsa_class', ''),
r.get('pct_sa', 0), r.get('overall', ''),
r.get('specificity', ''), r.get('comment', ''),
r.get('sero_mfi', []), status, submitted_by,
r.get('upload_file', ''), mode=save_mode)
saved.append({'report_id': rid, 'dsa_class': r.get('dsa_class', '')})
return jsonify({'ok': True, 'patient_id': patient_id, 'saved': saved})
@app.route('/dsa/batch_upload', methods=['GET', 'POST'])
@login_required
def dsa_batch_upload():
if request.method == 'GET':
return render_template('dsa_batch.html')
import db as _dbmod
files = request.files.getlist('file')
charts = request.form.getlist('chart')
names = request.form.getlist('name')
mode = request.form.get('mode', 'new')
results = []
ok_n = err_n = dup_n = 0
submitted_by = flask_session.get('display_name', flask_session.get('username', ''))
for idx, f in enumerate(files):
fname = f.filename or f'file{idx}'
chart = (charts[idx] if idx < len(charts) else '').strip()
name = (names[idx] if idx < len(names) else '').strip()
if not chart:
results.append({'file': fname, 'status': 'error', 'msg': '缺病歷號'})
err_n += 1
continue
try:
raw = f.read()
pt = _dsa.parse_xls_file(raw)
except Exception:
results.append({'file': fname, 'status': 'error', 'msg': '解析失敗'})
err_n += 1
continue
if pt is None:
results.append({'file': fname, 'status': 'error', 'msg': '無 bead 資料'})
err_n += 1
continue
dsa_tag = pt.pop('_pra_class', 'DSA1')
dsa_class = _dsa_class_label(dsa_tag)
date_val = pt.pop('_date', '') or ''
if not date_val:
results.append({'file': fname, 'status': 'error', 'msg': '抓不到報告日期'})
err_n += 1
continue
patient_id = _dbmod.get_or_create_patient(name or fname, chart)
upload_dir = _dbmod.get_upload_dir()
orig_name = Path(fname).name.replace('/', '_').replace('\\', '_') or f'file_{idx}.xls'
save_path = upload_dir / orig_name
try:
save_path.write_bytes(raw)
saved_filename = save_path.name
_dbmod.push_upload_to_repo(save_path, saved_filename)
except Exception:
saved_filename = fname
existing = _dbmod.find_active_duplicate_dsa(patient_id, date_val, dsa_class)
save_mode = 'overwrite'
if existing and mode == 'skip':
results.append({'file': fname, 'status': 'skipped',
'msg': f'檔案已保留;active report_id={existing}'})
dup_n += 1
continue
if existing and mode == 'new':
save_mode = 'new'
import re as _re
spec_plain = _re.sub(r'<[^>]*>', '', pt.get('specificity', '')).strip()
spec_plain = _re.sub(r'\s+', ' ', spec_plain)
rid = _dbmod.save_dsa_report(
patient_id, date_val, dsa_class,
pt.get('pra', 0), pt.get('overall', ''),
spec_plain, pt.get('comment', ''),
pt.get('sero_mfi', []),
'submitted', submitted_by, saved_filename, mode=save_mode)
if existing:
dup_n += 1
results.append({'file': fname, 'status': 'duplicate',
'msg': f'mode={mode}, report_id={rid}'})
else:
ok_n += 1
results.append({'file': fname, 'status': 'ok', 'msg': f'report_id={rid}'})
return jsonify({'results': results,
'summary': {'ok': ok_n, 'err': err_n, 'dup': dup_n, 'total': len(files)}})
@app.route('/dsa/history')
@login_required
def dsa_history():
import db as _dbmod
reports = _dbmod.get_all_dsa_reports(limit=500)
for r in reports:
r['donor_hla_fmt'] = format_donor_hla(r.get('donor_hla', ''))
db_stats = {'patients': len(_dbmod.get_all_dsa_patients()), 'reports': len(reports)}
is_admin = flask_session.get('role') == 'admin'
return render_template('dsa_history.html', reports=reports, db_stats=db_stats, is_admin=is_admin)
@app.route('/dsa/history/<chart_no>')
@login_required
def dsa_patient_history(chart_no):
import db as _dbmod
patient, reports = _dbmod.get_dsa_patient_reports(chart_no)
if not patient:
return redirect(url_for('dsa_history'))
dates1, antigens1, pra1, labels1 = _dbmod.get_dsa_mfi_comparison(chart_no, 'DSA Class I')
dates2, antigens2, pra2, labels2 = _dbmod.get_dsa_mfi_comparison(chart_no, 'DSA Class II')
all_labels = {**labels1, **labels2}
for r in reports:
r['chart_label'] = all_labels.get(r['id'], r['report_date'])
class Comp:
def __init__(self, dates, antigens, pra_by_date):
self.dates = dates
self.antigens = antigens
self.pra_by_date = pra_by_date
comp1 = Comp(dates1, antigens1, pra1) if dates1 else None
comp2 = Comp(dates2, antigens2, pra2) if dates2 else None
donor_hla = _dbmod.get_donor_hla(chart_no)
return render_template('dsa_patient.html', patient=patient, reports=reports,
comparison_class1=comp1, comparison_class2=comp2,
donor_hla=donor_hla)
@app.route('/dsa/analysis')
@login_required
def dsa_analysis():
import db as _dbmod
patients = _dbmod.get_all_dsa_patients()
chart_no = request.args.get('chart_no', '')
patient = None
reports = []
comp1 = None
comp2 = None
if chart_no:
patient, reports = _dbmod.get_dsa_patient_reports(chart_no)
if patient:
dates1, antigens1, pra1, labels1 = _dbmod.get_dsa_mfi_comparison(chart_no, 'DSA Class I')
dates2, antigens2, pra2, labels2 = _dbmod.get_dsa_mfi_comparison(chart_no, 'DSA Class II')
all_labels = {**labels1, **labels2}
for r in reports:
r['chart_label'] = all_labels.get(r['id'], r['report_date'])
class Comp:
def __init__(self, dates, antigens, pra_by_date):
self.dates = dates
self.antigens = antigens
self.pra_by_date = pra_by_date
comp1 = Comp(dates1, antigens1, pra1) if dates1 else None
comp2 = Comp(dates2, antigens2, pra2) if dates2 else None
donor_hla = _dbmod.get_donor_hla(chart_no) if chart_no else ''
return render_template('dsa_analysis.html', patients=patients, chart_no=chart_no,
patient=patient, reports=reports,
comparison_class1=comp1, comparison_class2=comp2,
donor_hla=donor_hla)
@app.route('/dsa/update_report', methods=['POST'])
@login_required
def dsa_update_report():
import db as _dbmod
data = request.json
rid = int(data.get('report_id', 0))
if not rid:
return jsonify({'error': 'missing report_id'}), 400
spec = data.get('specificity', '')
comment = data.get('comment', '')
conn = _dbmod.get_conn()
conn.execute("""UPDATE dsa_reports SET specificity=?, comment=?,
updated_at=datetime('now','localtime') WHERE id=?""",
(spec, comment, rid))
conn.commit()
conn.close()
_dbmod.schedule_auto_push()
return jsonify({'ok': True})
@app.route('/dsa/delete_report/<int:report_id>', methods=['POST'])
@login_required
def dsa_delete_report_route(report_id):
import db as _dbmod
_dbmod.delete_dsa_report(report_id)
return jsonify({'ok': True})
# ============================================================
# Combined (PRA + DSA) Analysis Route
# ============================================================
@app.route('/combined')
@login_required
def combined_analysis():
"""Combined PRA + DSA trend on one page (per patient)."""
import db as _dbmod
patients = _dbmod.get_patients_with_both()
chart_no = request.args.get('chart_no', '')
patient = None
reports = []
comp1 = comp1_alleles = None
comp2 = comp2_alleles = None
donor_hla = ''
if chart_no:
# Resolve patient
conn = _dbmod.get_conn()
row = conn.execute('SELECT * FROM patients WHERE chart_no=?', (chart_no,)).fetchone()
conn.close()
if row:
patient = dict(row)
reports = _dbmod.get_combined_reports(chart_no)
d1, ag1 = _dbmod.get_combined_mfi(chart_no, 'I')
d2, ag2 = _dbmod.get_combined_mfi(chart_no, 'II')
class Comp:
def __init__(self, dates, antigens):
self.dates = dates
self.antigens = antigens
comp1 = Comp(d1, ag1) if d1 else None
comp2 = Comp(d2, ag2) if d2 else None
donor_hla = _dbmod.get_donor_hla(chart_no)
return render_template('combined_analysis.html',
patients=patients, chart_no=chart_no,
patient=patient, reports=reports,
comparison_class1=comp1, comparison_class2=comp2,
donor_hla=donor_hla)
if __name__ == '__main__':
print('PRA / DSA Analysis Web App')
print('http://127.0.0.1:5000')
app.run(debug=True, port=5000)
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