zk
73 lines
2.1 KiB
Python
73 lines
2.1 KiB
Python
"""文件解析工具
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将上传的简历文件（PDF / Word / TXT）转换为纯文本字符串。
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"""
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import io
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import pdfplumber
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from docx import Document
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from app.core.logger import log
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def parse_pdf(content: bytes) -> str:
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"""解析 PDF 文件，提取全部页面文本"""
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text_parts: list[str] = []
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with pdfplumber.open(io.BytesIO(content)) as pdf:
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for page in pdf.pages:
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page_text = page.extract_text()
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if page_text:
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text_parts.append(page_text)
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return "\n".join(text_parts)
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def parse_docx(content: bytes) -> str:
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"""解析 Word (.docx) 文件，提取段落和表格文本"""
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try:
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doc = Document(io.BytesIO(content))
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except Exception:
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raise ValueError("无法解析该 Word 文件，如果是旧版 .doc 格式，请另存为 .docx 后重试")
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text_parts: list[str] = []
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# 段落
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for para in doc.paragraphs:
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text = para.text.strip()
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if text:
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text_parts.append(text)
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# 表格
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for table in doc.tables:
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for row in table.rows:
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row_text = "\t".join(cell.text.strip() for cell in row.cells)
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if row_text.strip():
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text_parts.append(row_text)
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return "\n".join(text_parts)
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def parse_txt(content: bytes) -> str:
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"""解析 TXT 文件，自动检测编码"""
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for encoding in ("utf-8", "gbk", "gb2312", "latin-1"):
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try:
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return content.decode(encoding)
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except (UnicodeDecodeError, LookupError):
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continue
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return content.decode("utf-8", errors="replace")
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def parse_to_text(filename: str, content: bytes) -> str:
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"""根据文件名后缀自动选择解析方法，返回纯文本"""
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suffix = filename[filename.rfind("."):].lower() if "." in filename else ""
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log.info(f"解析文件: {filename}，类型: {suffix}")
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if suffix == ".pdf":
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return parse_pdf(content)
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elif suffix in (".docx", ".doc"):
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return parse_docx(content)
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elif suffix == ".txt":
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return parse_txt(content)
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else:
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raise ValueError(f"不支持的文件类型: {suffix}，支持: .pdf, .docx, .doc, .txt")
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