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fix(pipeline): 探针缺依赖时不 sys.exit，并锁定 jieba/sklearn 依赖

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hub-gif 2026-04-16 17:56:01 +08:00
parent c729d718c4
commit b7c74f942c
2 changed files with 33 additions and 12 deletions
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36
backend/pipeline/demos/chapter8_text_mining_probe.py
View File

@ -30,8 +30,6 @@ from collections import Counter
from pathlib import Path from pathlib import Path
from typing import Any from typing import Any
import numpy as np
BACKEND_ROOT = Path(__file__).resolve().parents[2] BACKEND_ROOT = Path(__file__).resolve().parents[2]
if str(BACKEND_ROOT) not in sys.path: if str(BACKEND_ROOT) not in sys.path:
sys.path.insert(0, str(BACKEND_ROOT)) sys.path.insert(0, str(BACKEND_ROOT))
@ -51,20 +49,25 @@ import jd_keyword_pipeline as kpl # noqa: E402
from pipeline.csv_schema import MERGED_FIELD_TO_CSV_HEADER # noqa: E402 from pipeline.csv_schema import MERGED_FIELD_TO_CSV_HEADER # noqa: E402
from pipeline.llm.generate import _call_llm # noqa: E402 探针专用，不新增 generate 导出 from pipeline.llm.generate import _call_llm # noqa: E402 探针专用，不新增 generate 导出
# 导入失败时**不得** ``sys.exit``：本模块会被 ``runner`` 在 Web 请求中 import，退出会整进程 500。
_PROBE_TEXT_MINING_DEPS_OK = False
_PROBE_TEXT_MINING_IMPORT_ERROR = ""
try: try:
import numpy as np # noqa: WPS433
import jieba # noqa: WPS433 import jieba # noqa: WPS433
from sklearn.decomposition import LatentDirichletAllocation # noqa: WPS433 from sklearn.decomposition import LatentDirichletAllocation # noqa: WPS433
from sklearn.feature_extraction.text import ( # noqa: WPS433 from sklearn.feature_extraction.text import ( # noqa: WPS433
CountVectorizer, CountVectorizer,
TfidfVectorizer, TfidfVectorizer,
) )
_PROBE_TEXT_MINING_DEPS_OK = True
except ImportError as e: except ImportError as e:
print( np = None # type: ignore[assignment]
"缺少依赖，请先安装：pip install jieba scikit-learn numpy\n" jieba = None # type: ignore[assignment]
f"原始错误: {e}", LatentDirichletAllocation = None # type: ignore[assignment]
file=sys.stderr, CountVectorizer = None # type: ignore[assignment]
) TfidfVectorizer = None # type: ignore[assignment]
sys.exit(1) _PROBE_TEXT_MINING_IMPORT_ERROR = str(e)
try: try:
import matplotlib import matplotlib
@ -507,6 +510,15 @@ def _run_probe_text_mining_llm(
return f"> **探针 LLM 解读**调用失败：{e}" return f"> **探针 LLM 解读**调用失败：{e}"
def _ensure_probe_dependencies() -> None:
if not _PROBE_TEXT_MINING_DEPS_OK:
raise ImportError(
"第八章文本挖掘探针依赖未安装，请在 backend 环境下执行："
"pip install jieba scikit-learn numpy wordcloud\n"
f"原始错误: {_PROBE_TEXT_MINING_IMPORT_ERROR}"
)
def build_markdown( def build_markdown(
run_dir: Path, run_dir: Path,
*, *,
@ -520,6 +532,7 @@ def build_markdown(
wordcloud_enabled: bool, wordcloud_enabled: bool,
wordcloud_max: int, wordcloud_max: int,
) -> str: ) -> str:
_ensure_probe_dependencies()
kw, merged, comments = _load_run(run_dir) kw, merged, comments = _load_run(run_dir)
sku_h = MERGED_FIELD_TO_CSV_HEADER["sku_id"] sku_h = MERGED_FIELD_TO_CSV_HEADER["sku_id"]
groups = jcr._consumer_feedback_by_matrix_group( groups = jcr._consumer_feedback_by_matrix_group(
@ -746,6 +759,13 @@ def markdown_embed_body_for_competitor_report(full_probe_md: str) -> str:
def main() -> None: def main() -> None:
if not _PROBE_TEXT_MINING_DEPS_OK:
print(
"缺少依赖，请先安装：pip install jieba scikit-learn numpy wordcloud\n"
f"原始错误: {_PROBE_TEXT_MINING_IMPORT_ERROR}",
file=sys.stderr,
)
sys.exit(1)
ap = argparse.ArgumentParser(description="第八章文本挖掘探针（独立脚本）") ap = argparse.ArgumentParser(description="第八章文本挖掘探针（独立脚本）")
ap.add_argument( ap.add_argument(
"--run-dir", "--run-dir",

9
backend/requirements.txt
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@ -9,7 +9,8 @@ reportlab>=4.0
matplotlib>=3.8 matplotlib>=3.8
playwright>=1.40 playwright>=1.40
# 可选：pipeline.demos.chapter8_text_mining_probe（第八章文本挖掘探针） # 第八章文本挖掘探针（默认写入竞品报告 §8.3 时需安装）
# jieba>=0.42 jieba>=0.42
# scikit-learn>=1.4 scikit-learn>=1.4
# wordcloud>=1.9 numpy>=1.26
wordcloud>=1.9