houhuan
e441ac82a8
- Cleaned up code in processing.py by removing inline semicolons and improving readability. - Updated upsert_file_relation calls to ensure consistent handling of file relations. - Enhanced query_file_relations in db_schema.py to support filtering by file existence. - Improved API error handling in index.ts with user-friendly messages for 401 and 403 errors. - Added online/offline status tracking in Layout.vue. - Implemented debounced search functionality across multiple views to optimize performance. - Introduced loading skeletons in Dashboard.vue for better user experience during data fetching. - Enhanced file preview cleanup logic in Images.vue, Orders.vue, and Tables.vue to prevent memory leaks. - Updated global styles to include new loading and notification animations.
708 lines
28 KiB
Python
708 lines
28 KiB
Python
"""Processing endpoints: OCR, Excel conversion, merge, and full pipeline."""
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import asyncio
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import logging
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import os
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import sys
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import threading
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import traceback
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from pathlib import Path
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from typing import Optional, List
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from fastapi import APIRouter, HTTPException, Depends, Request
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from pydantic import BaseModel
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from ..auth.dependencies import get_current_user
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from ..services.service_wrapper import ServiceWrapper
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from ..services.db_schema import upsert_file_relation
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router = APIRouter(prefix="/api/processing", tags=["processing"])
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_wrapper = ServiceWrapper(max_workers=3)
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# ── Thread-safe log capture ──
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_tlocal = threading.local()
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class TaskLogHandler(logging.Handler):
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"""Capture all log records during task execution and forward to tm.add_log()"""
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def emit(self, record: logging.LogRecord):
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ctx = getattr(_tlocal, 'ctx', None)
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if ctx:
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tm = ctx.get('tm')
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task_id = ctx.get('task_id')
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if tm and task_id:
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msg = self.format(record)
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if any(skip in msg for skip in ['DEBUG:', 'urllib3', 'charset_normalizer']):
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return
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tm.add_log(task_id, msg)
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_log_handler = TaskLogHandler()
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_log_handler.setLevel(logging.DEBUG)
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_log_handler.setFormatter(logging.Formatter('%(message)s'))
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_root_logger = logging.getLogger()
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_configured = False
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def _setup_log_capture():
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global _configured
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if not _configured:
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_root_logger.addHandler(_log_handler)
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_configured = True
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def _start_log_capture(tm, task_id: str):
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_setup_log_capture()
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_root_logger.setLevel(logging.DEBUG)
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_tlocal.ctx = {'tm': tm, 'task_id': task_id}
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def _stop_log_capture():
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_tlocal.ctx = None
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def _add_result_file(name: str):
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files = getattr(_tlocal, 'result_files', None)
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if files is not None:
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files.append(name)
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def _wrap_with_capture(tm, task_id, func):
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"""Wrap a do_work function with log capture setup/teardown."""
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def wrapped():
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_start_log_capture(tm, task_id)
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_tlocal.result_files = []
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try:
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return func()
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finally:
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_stop_log_capture()
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return wrapped
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_project_root = Path(__file__).resolve().parent.parent.parent.parent
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_input_dir = _project_root / "data" / "input"
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_output_dir = _project_root / "data" / "output"
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_result_dir = _project_root / "data" / "result"
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class PipelineRequest(BaseModel):
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files: Optional[List[str]] = None
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supplier: Optional[str] = None
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class SingleFileRequest(BaseModel):
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filename: str
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class MergeBatchRequest(BaseModel):
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filenames: List[str]
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class TaskResponse(BaseModel):
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task_id: str
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status: str
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message: str
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def _get_task_manager(request: Request):
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return request.state.task_manager
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def _list_input_files(filter_ext: Optional[List[str]] = None) -> List[Path]:
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if not _input_dir.is_dir():
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return []
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files = []
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for f in sorted(_input_dir.iterdir()):
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if f.is_file():
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if filter_ext is None or f.suffix.lower() in filter_ext:
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files.append(f)
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return files
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def _list_files_in(directory: Path, filter_ext: List[str] = None) -> List[Path]:
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if not directory.is_dir():
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return []
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files = []
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for f in sorted(directory.iterdir()):
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if f.is_file():
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if filter_ext is None or f.suffix.lower() in filter_ext:
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files.append(f)
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return files
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def _run_background(coro):
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"""Schedule a coroutine as a background task."""
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asyncio.ensure_future(coro)
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def _run_background_with_log(coro, tm, task_id: str):
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"""Schedule a coroutine with log capture during execution."""
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async def _wrapped():
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_start_log_capture(tm, task_id)
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try:
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await coro
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finally:
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_stop_log_capture()
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asyncio.ensure_future(_wrapped())
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def _get_product_db():
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from app.core.db.product_db import ProductDatabase
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return ProductDatabase(
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str(_project_root / 'data' / 'product_cache.db'),
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str(_project_root / 'templates' / '商品资料.xlsx')
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)
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def _learn_products_from_excel(excel_path: Path, tm, task_id, source: str = 'ocr'):
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"""从处理后的Excel文件学习商品数据到记忆库"""
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try:
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from app.core.utils.file_utils import smart_read_excel
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df = smart_read_excel(str(excel_path))
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if df is None or df.empty:
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return
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except Exception:
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return
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from app.core.handlers.column_mapper import ColumnMapper
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barcode_col = ColumnMapper.find_column(list(df.columns), 'barcode')
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if not barcode_col:
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return
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name_col = ColumnMapper.find_column(list(df.columns), 'name')
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spec_col = ColumnMapper.find_column(list(df.columns), 'specification')
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unit_col = ColumnMapper.find_column(list(df.columns), 'unit')
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price_col = ColumnMapper.find_column(list(df.columns), 'unit_price') or ColumnMapper.find_column(list(df.columns), 'price')
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db = _get_product_db()
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barcodes = [str(r.get(barcode_col, '')).strip() for _, r in df.iterrows() if str(r.get(barcode_col, '')).strip()]
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memory = db.load_batch(barcodes)
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learned = 0
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for _, row in df.iterrows():
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barcode = str(row.get(barcode_col, '')).strip()
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if not barcode or barcode == 'nan':
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continue
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price = 0.0
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if price_col:
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try:
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p = row.get(price_col)
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if p is not None and str(p).strip() not in ('', 'nan', 'None'):
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price = float(p)
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except (ValueError, TypeError):
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pass
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product = {
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'barcode': barcode,
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'name': str(row.get(name_col, '')).strip() if name_col else '',
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'specification': str(row.get(spec_col, '')).strip() if spec_col else '',
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'unit': str(row.get(unit_col, '')).strip() if unit_col else '',
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'price': price,
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}
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# 1. 记忆辅助补全
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filled, fill_log = db.fill_from_memory(barcode, product, memory)
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if fill_log:
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tm.add_log(task_id, f" {fill_log}")
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# 2. 价格预警
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warn = db.price_warning(barcode, price, memory)
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if warn:
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tm.add_log(task_id, f" {warn}")
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# 3. 学习
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log = db.learn_from_product(filled, source=source, memory=memory, add_log=None)
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if log:
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tm.add_log(task_id, f" {log}")
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learned += 1
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if learned:
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tm.add_log(task_id, f"[记忆库] 从 {excel_path.name} 学习了 {learned} 条商品数据")
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# ---------------------------------------------------------------------------
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# Batch endpoints
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# ---------------------------------------------------------------------------
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@router.post("/ocr-batch", response_model=TaskResponse)
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async def ocr_batch(
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request: Request,
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current_user: dict = Depends(get_current_user),
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):
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"""Run OCR on all images in input/."""
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tm = _get_task_manager(request)
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task = tm.create_task("批量OCR识别")
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image_exts = {'.jpg', '.jpeg', '.png', '.bmp', '.tiff', '.tif'}
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files = _list_input_files(filter_ext=list(image_exts))
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if not files:
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raise HTTPException(400, "input/ 目录中没有图片文件")
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async def _bg():
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def do_work():
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from app.services.ocr_service import OCRService
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svc = OCRService()
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total = len(files)
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for i, f in enumerate(files):
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# Skip check
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out_stem = f.stem
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# OCR output could be .xlsx or .xls
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out_xlsx = _output_dir / f"{out_stem}.xlsx"
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out_xls = _output_dir / f"{out_stem}.xls"
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if out_xlsx.exists() or out_xls.exists():
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out_name = out_xlsx.name if out_xlsx.exists() else out_xls.name
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tm.add_log(task.id, f"[跳过] {f.name} 已OCR过 → {out_name}")
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upsert_file_relation(input_image=f.name, output_excel=out_name, status='ocr_done')
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continue
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tm.update_progress(task.id, int((i / total) * 100), f"正在识别: {f.name}")
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tm.add_log(task.id, f"[OCR] 处理 {f.name}")
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try:
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svc.process_image(str(f))
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# Find the output file
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for ext in ['.xlsx', '.xls']:
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candidate = _output_dir / f"{out_stem}{ext}"
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if candidate.exists():
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upsert_file_relation(input_image=f.name, output_excel=candidate.name, status='ocr_done')
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_add_result_file(candidate.name)
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break
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tm.add_log(task.id, f"[OCR] 完成: {f.name}")
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# Learn products into memory from OCR output
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out_file = _output_dir / f"{out_stem}.xlsx"
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if not out_file.exists():
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out_file = _output_dir / f"{out_stem}.xls"
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if out_file.exists():
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_learn_products_from_excel(out_file, tm, task.id, source='ocr')
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except Exception as e:
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tm.add_log(task.id, f"[OCR] 失败: {f.name} - {e}")
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result_files = list(getattr(_tlocal, 'result_files', []))
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tm.set_completed(task.id, result_files=result_files, message=f"OCR完成，共处理 {total} 个文件")
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await _wrapper.run_sync(_wrap_with_capture(tm, task.id, do_work))
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_run_background(_bg())
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return TaskResponse(task_id=task.id, status="accepted", message="OCR任务已创建")
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@router.post("/excel", response_model=TaskResponse)
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async def process_excel(
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request: Request,
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body: PipelineRequest = PipelineRequest(),
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current_user: dict = Depends(get_current_user),
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):
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"""Convert OCR output Excel files to standardized purchase orders."""
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tm = _get_task_manager(request)
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task = tm.create_task("Excel标准化处理")
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excel_exts = {'.xls', '.xlsx'}
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if body.files:
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files = [_output_dir / f for f in body.files if (_output_dir / f).is_file()]
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else:
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files = _list_files_in(_output_dir, filter_ext=list(excel_exts))
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if not files:
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raise HTTPException(400, "output/ 目录中没有Excel文件")
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async def _bg():
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def do_work():
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from app.services.order_service import OrderService
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svc = OrderService()
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total = len(files)
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for i, f in enumerate(files):
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# Skip check
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result_name = f"采购单_{f.stem}.xls"
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result_path = _result_dir / result_name
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if result_path.exists():
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tm.add_log(task.id, f"[跳过] {f.name} 已处理过 → {result_name}")
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upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done')
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_add_result_file(result_name)
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continue
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tm.update_progress(task.id, int((i / total) * 100), f"正在处理: {f.name}")
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tm.add_log(task.id, f"[Excel] 处理 {f.name}")
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try:
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svc.process_excel(str(f))
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# Find result file
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if result_path.exists():
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upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done')
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_add_result_file(result_name)
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tm.add_log(task.id, f"[Excel] 完成: {f.name}")
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# Learn products into memory from purchase order result
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if result_path.exists():
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_learn_products_from_excel(result_path, tm, task.id, source='ocr')
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except Exception as e:
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tm.add_log(task.id, f"[Excel] 失败: {f.name} - {e}")
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result_files = list(getattr(_tlocal, 'result_files', []))
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tm.set_completed(task.id, result_files=result_files, message=f"Excel处理完成，共 {total} 个文件")
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await _wrapper.run_sync(_wrap_with_capture(tm, task.id, do_work))
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_run_background(_bg())
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return TaskResponse(task_id=task.id, status="accepted", message="Excel处理任务已创建")
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@router.post("/merge", response_model=TaskResponse)
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async def merge_orders(
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request: Request,
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body: MergeBatchRequest = MergeBatchRequest(filenames=[]),
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current_user: dict = Depends(get_current_user),
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):
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"""Merge selected purchase order files into one PosPal template."""
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tm = _get_task_manager(request)
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task = tm.create_task("合并采购单")
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# If specific files provided, use them; otherwise merge all
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if body.filenames:
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file_paths = [_result_dir / f for f in body.filenames if (_result_dir / f).is_file()]
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else:
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file_paths = list(_result_dir.glob("采购单_*.xls"))
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if not file_paths:
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raise HTTPException(400, "没有找到可合并的采购单文件")
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async def _bg():
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def do_work():
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from app.core.excel.merger import PurchaseOrderMerger
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tm.update_progress(task.id, 20, "正在合并采购单...")
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tm.add_log(task.id, f"[合并] 合并 {len(file_paths)} 个文件")
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try:
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from app.config.settings import ConfigManager
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merger = PurchaseOrderMerger(ConfigManager())
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result = merger.process([str(f) for f in file_paths])
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if result:
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merged_name = Path(result).name
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upsert_file_relation(result_purchase=merged_name, status='merged')
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tm.add_log(task.id, f"[合并] 完成: {merged_name}")
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tm.set_completed(task.id, result_files=[merged_name], message="合并完成")
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else:
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tm.set_failed(task.id, "合并返回空结果")
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except Exception as e:
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tm.add_log(task.id, f"[合并] 失败: {e}")
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tm.set_failed(task.id, str(e))
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await _wrapper.run_sync(_wrap_with_capture(tm, task.id, do_work))
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_run_background(_bg())
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return TaskResponse(task_id=task.id, status="accepted", message="合并任务已创建")
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@router.post("/pipeline", response_model=TaskResponse)
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async def full_pipeline(
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request: Request,
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body: PipelineRequest = PipelineRequest(),
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current_user: dict = Depends(get_current_user),
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):
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"""Run the full pipeline: OCR -> Excel -> Result (NO merge)."""
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tm = _get_task_manager(request)
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task = tm.create_task("一键全流程处理")
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async def _bg():
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def do_work():
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try:
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# Step 1: OCR
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tm.update_progress(task.id, 0, "步骤 1/2: OCR识别")
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tm.add_log(task.id, "[Pipeline] 开始OCR识别")
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from app.services.ocr_service import OCRService
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ocr_svc = OCRService()
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image_exts = {'.jpg', '.jpeg', '.png', '.bmp', '.tiff', '.tif'}
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images = _list_input_files(filter_ext=list(image_exts))
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for i, f in enumerate(images):
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pct = int((i / max(len(images), 1)) * 40)
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# Skip check
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out_stem = f.stem
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out_xlsx = _output_dir / f"{out_stem}.xlsx"
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out_xls = _output_dir / f"{out_stem}.xls"
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if out_xlsx.exists() or out_xls.exists():
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out_name = out_xlsx.name if out_xlsx.exists() else out_xls.name
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tm.add_log(task.id, f"[跳过] {f.name} 已OCR过 → {out_name}")
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upsert_file_relation(input_image=f.name, output_excel=out_name, status='ocr_done')
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tm.update_progress(task.id, pct, f"跳过: {f.name}")
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continue
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tm.update_progress(task.id, pct, f"OCR: {f.name}")
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try:
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ocr_svc.process_image(str(f))
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for ext in ['.xlsx', '.xls']:
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candidate = _output_dir / f"{out_stem}{ext}"
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if candidate.exists():
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upsert_file_relation(input_image=f.name, output_excel=candidate.name, status='ocr_done')
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_add_result_file(candidate.name)
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break
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tm.add_log(task.id, f"[OCR] 完成: {f.name}")
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out_file = _output_dir / f"{out_stem}.xlsx"
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if not out_file.exists():
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out_file = _output_dir / f"{out_stem}.xls"
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if out_file.exists():
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_learn_products_from_excel(out_file, tm, task.id, source='ocr')
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except Exception as e:
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tm.add_log(task.id, f"[OCR] 失败: {f.name} - {e}")
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# Step 2: Excel conversion
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tm.update_progress(task.id, 45, "步骤 2/2: Excel标准化")
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tm.add_log(task.id, "[Pipeline] 开始Excel处理")
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from app.services.order_service import OrderService
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|
order_svc = OrderService()
|
|
|
|
excel_files = list(_output_dir.glob("*.xls")) + list(_output_dir.glob("*.xlsx"))
|
|
for i, f in enumerate(excel_files):
|
|
pct = 45 + int((i / max(len(excel_files), 1)) * 55)
|
|
|
|
# Skip check
|
|
result_name = f"采购单_{f.stem}.xls"
|
|
result_path = _result_dir / result_name
|
|
if result_path.exists():
|
|
tm.add_log(task.id, f"[跳过] {f.name} 已处理过 → {result_name}")
|
|
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done')
|
|
_add_result_file(result_name)
|
|
tm.update_progress(task.id, pct, f"跳过: {f.name}")
|
|
continue
|
|
|
|
tm.update_progress(task.id, pct, f"Excel: {f.name}")
|
|
try:
|
|
order_svc.process_excel(str(f))
|
|
if result_path.exists():
|
|
upsert_file_relation(output_excel=f.name, result_purchase=result_name, status='done')
|
|
_add_result_file(result_name)
|
|
tm.add_log(task.id, f"[Excel] 完成: {f.name}")
|
|
if result_path.exists():
|
|
_learn_products_from_excel(result_path, tm, task.id, source='ocr')
|
|
except Exception as e:
|
|
tm.add_log(task.id, f"[Excel] 失败: {f.name} - {e}")
|
|
|
|
result_files = list(getattr(_tlocal, 'result_files', []))
|
|
tm.set_completed(task.id, result_files=result_files, message="全流程处理完成（不含合并）")
|
|
except Exception as e:
|
|
tb = traceback.format_exc()
|
|
tm.add_log(task.id, f"[错误] {tb}")
|
|
tm.set_failed(task.id, str(e))
|
|
|
|
await _wrapper.run_sync(_wrap_with_capture(tm, task.id, do_work))
|
|
|
|
_run_background(_bg())
|
|
return TaskResponse(task_id=task.id, status="accepted", message="全流程任务已创建")
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Single-file endpoints
|
|
# ---------------------------------------------------------------------------
|
|
|
|
@router.post("/ocr-single", response_model=TaskResponse)
|
|
async def ocr_single(
|
|
request: Request,
|
|
body: SingleFileRequest,
|
|
current_user: dict = Depends(get_current_user),
|
|
):
|
|
"""OCR a single image file."""
|
|
tm = _get_task_manager(request)
|
|
task = tm.create_task(f"OCR: {body.filename}")
|
|
|
|
file_path = _input_dir / body.filename
|
|
if not file_path.is_file():
|
|
raise HTTPException(404, f"文件不存在: {body.filename}")
|
|
|
|
async def _bg():
|
|
def do_work():
|
|
from app.services.ocr_service import OCRService
|
|
svc = OCRService()
|
|
tm.update_progress(task.id, 10, f"正在识别: {body.filename}")
|
|
tm.add_log(task.id, f"[OCR] 处理 {body.filename}")
|
|
try:
|
|
svc.process_image(str(file_path))
|
|
# Find output
|
|
stem = file_path.stem
|
|
for ext in ['.xlsx', '.xls']:
|
|
candidate = _output_dir / f"{stem}{ext}"
|
|
if candidate.exists():
|
|
upsert_file_relation(input_image=body.filename, output_excel=candidate.name, status='ocr_done')
|
|
_add_result_file(candidate.name)
|
|
break
|
|
tm.add_log(task.id, f"[OCR] 完成: {body.filename}")
|
|
result_files = list(getattr(_tlocal, 'result_files', []))
|
|
tm.set_completed(task.id, result_files=result_files, message=f"OCR完成: {body.filename}")
|
|
except Exception as e:
|
|
tm.add_log(task.id, f"[OCR] 失败: {e}")
|
|
tm.set_failed(task.id, str(e))
|
|
|
|
await _wrapper.run_sync(_wrap_with_capture(tm, task.id, do_work))
|
|
|
|
_run_background(_bg())
|
|
return TaskResponse(task_id=task.id, status="accepted", message=f"OCR任务已创建: {body.filename}")
|
|
|
|
|
|
@router.post("/excel-single", response_model=TaskResponse)
|
|
async def excel_single(
|
|
request: Request,
|
|
body: SingleFileRequest,
|
|
current_user: dict = Depends(get_current_user),
|
|
):
|
|
"""Process a single Excel file to purchase order."""
|
|
tm = _get_task_manager(request)
|
|
task = tm.create_task(f"Excel处理: {body.filename}")
|
|
|
|
file_path = _output_dir / body.filename
|
|
if not file_path.is_file():
|
|
raise HTTPException(404, f"文件不存在: {body.filename}")
|
|
|
|
async def _bg():
|
|
def do_work():
|
|
from app.services.order_service import OrderService
|
|
svc = OrderService()
|
|
tm.update_progress(task.id, 10, f"正在处理: {body.filename}")
|
|
tm.add_log(task.id, f"[Excel] 处理 {body.filename}")
|
|
try:
|
|
svc.process_excel(str(file_path))
|
|
result_name = f"采购单_{file_path.stem}.xls"
|
|
if (_result_dir / result_name).exists():
|
|
upsert_file_relation(output_excel=body.filename, result_purchase=result_name, status='done')
|
|
tm.add_log(task.id, f"[Excel] 完成: {body.filename}")
|
|
result_files = list(getattr(_tlocal, 'result_files', []))
|
|
tm.set_completed(task.id, result_files=result_files, message=f"Excel处理完成: {body.filename}")
|
|
except Exception as e:
|
|
tm.add_log(task.id, f"[Excel] 失败: {e}")
|
|
tm.set_failed(task.id, str(e))
|
|
|
|
await _wrapper.run_sync(_wrap_with_capture(tm, task.id, do_work))
|
|
|
|
_run_background(_bg())
|
|
return TaskResponse(task_id=task.id, status="accepted", message=f"Excel处理任务已创建: {body.filename}")
|
|
|
|
|
|
@router.post("/pipeline-single", response_model=TaskResponse)
|
|
async def pipeline_single(
|
|
request: Request,
|
|
body: SingleFileRequest,
|
|
current_user: dict = Depends(get_current_user),
|
|
):
|
|
"""Full pipeline for a single image: OCR -> Excel -> Result (no merge)."""
|
|
tm = _get_task_manager(request)
|
|
task = tm.create_task(f"全流程: {body.filename}")
|
|
|
|
file_path = _input_dir / body.filename
|
|
if not file_path.is_file():
|
|
raise HTTPException(404, f"文件不存在: {body.filename}")
|
|
|
|
async def _bg():
|
|
def do_work():
|
|
try:
|
|
stem = file_path.stem
|
|
|
|
# Step 1: OCR
|
|
tm.update_progress(task.id, 10, "步骤 1/2: OCR识别")
|
|
tm.add_log(task.id, f"[Pipeline] OCR: {body.filename}")
|
|
from app.services.ocr_service import OCRService
|
|
ocr_svc = OCRService()
|
|
|
|
out_xlsx = _output_dir / f"{stem}.xlsx"
|
|
out_xls = _output_dir / f"{stem}.xls"
|
|
if out_xlsx.exists() or out_xls.exists():
|
|
out_name = out_xlsx.name if out_xlsx.exists() else out_xls.name
|
|
tm.add_log(task.id, f"[跳过] 已OCR过 → {out_name}")
|
|
upsert_file_relation(input_image=body.filename, output_excel=out_name, status='ocr_done')
|
|
_add_result_file(out_name)
|
|
else:
|
|
ocr_svc.process_image(str(file_path))
|
|
for ext in ['.xlsx', '.xls']:
|
|
candidate = _output_dir / f"{stem}{ext}"
|
|
if candidate.exists():
|
|
upsert_file_relation(input_image=body.filename, output_excel=candidate.name, status='ocr_done')
|
|
_add_result_file(candidate.name)
|
|
break
|
|
tm.add_log(task.id, f"[OCR] 完成")
|
|
|
|
# Step 2: Excel
|
|
tm.update_progress(task.id, 50, "步骤 2/2: Excel处理")
|
|
tm.add_log(task.id, f"[Pipeline] Excel处理")
|
|
from app.services.order_service import OrderService
|
|
order_svc = OrderService()
|
|
|
|
result_name = f"采购单_{stem}.xls"
|
|
result_path = _result_dir / result_name
|
|
if result_path.exists():
|
|
tm.add_log(task.id, f"[跳过] 已处理过 → {result_name}")
|
|
upsert_file_relation(output_excel=f"{stem}.xlsx", result_purchase=result_name, status='done')
|
|
else:
|
|
# Find the output excel
|
|
excel_file = out_xlsx if out_xlsx.exists() else (out_xls if out_xls.exists() else None)
|
|
if excel_file:
|
|
order_svc.process_excel(str(excel_file))
|
|
if result_path.exists():
|
|
upsert_file_relation(output_excel=excel_file.name, result_purchase=result_name, status='done')
|
|
tm.add_log(task.id, f"[Excel] 完成")
|
|
else:
|
|
tm.add_log(task.id, f"[错误] OCR未生成Excel文件")
|
|
|
|
result_files = list(getattr(_tlocal, 'result_files', []))
|
|
tm.set_completed(task.id, result_files=result_files, message=f"全流程完成: {body.filename}")
|
|
except Exception as e:
|
|
tb = traceback.format_exc()
|
|
tm.add_log(task.id, f"[错误] {tb}")
|
|
tm.set_failed(task.id, str(e))
|
|
|
|
await _wrapper.run_sync(_wrap_with_capture(tm, task.id, do_work))
|
|
|
|
_run_background(_bg())
|
|
return TaskResponse(task_id=task.id, status="accepted", message=f"全流程任务已创建: {body.filename}")
|
|
|
|
|
|
@router.post("/merge-batch", response_model=TaskResponse)
|
|
async def merge_batch(
|
|
request: Request,
|
|
body: MergeBatchRequest,
|
|
current_user: dict = Depends(get_current_user),
|
|
):
|
|
"""Merge selected purchase order files into one PosPal template."""
|
|
tm = _get_task_manager(request)
|
|
task = tm.create_task("批量合并采购单")
|
|
|
|
file_paths = [_result_dir / f for f in body.filenames if (_result_dir / f).is_file()]
|
|
if not file_paths:
|
|
raise HTTPException(400, "没有找到可合并的采购单文件")
|
|
|
|
async def _bg():
|
|
def do_work():
|
|
from app.core.excel.merger import PurchaseOrderMerger
|
|
tm.update_progress(task.id, 20, f"正在合并 {len(file_paths)} 个采购单...")
|
|
tm.add_log(task.id, f"[合并] 合并文件: {', '.join(f.name for f in file_paths)}")
|
|
try:
|
|
from app.config.settings import ConfigManager
|
|
merger = PurchaseOrderMerger(ConfigManager())
|
|
result = merger.process([str(f) for f in file_paths])
|
|
if result:
|
|
merged_name = Path(result).name
|
|
upsert_file_relation(result_purchase=merged_name, status='merged')
|
|
tm.add_log(task.id, f"[合并] 完成: {merged_name}")
|
|
tm.set_completed(task.id, result_files=[merged_name], message="批量合并完成")
|
|
else:
|
|
tm.set_failed(task.id, "合并返回空结果")
|
|
except Exception as e:
|
|
tm.add_log(task.id, f"[合并] 失败: {e}")
|
|
tm.set_failed(task.id, str(e))
|
|
|
|
await _wrapper.run_sync(_wrap_with_capture(tm, task.id, do_work))
|
|
|
|
_run_background(_bg())
|
|
return TaskResponse(task_id=task.id, status="accepted", message="批量合并任务已创建")
|
|
|
|
|
|
# ---------------------------------------------------------------------------
|
|
# Status endpoint
|
|
# ---------------------------------------------------------------------------
|
|
|
|
@router.get("/status/{task_id}")
|
|
async def get_task_status(
|
|
task_id: str,
|
|
request: Request,
|
|
current_user: dict = Depends(get_current_user),
|
|
):
|
|
tm = _get_task_manager(request)
|
|
task = tm.get_task(task_id)
|
|
if not task:
|
|
raise HTTPException(404, "任务不存在")
|
|
return task.to_dict()
|