摘要：处理大数据集或者生成报告、创建中间文件的时候，很多文件其实根本不需要永久保存。这时候可以用临时目录来解决这个问题。Python 标准库里的 tempfile 模块能创建用完就自动消失的临时文件和目录，省去手动清理的麻烦。
处理大数据集或者生成报告、创建中间文件的时候，很多文件其实根本不需要永久保存。这时候可以用临时目录来解决这个问题。Python 标准库里的 tempfile 模块能创建用完就自动消失的临时文件和目录，省去手动清理的麻烦。
临时目录就是个生命周期很短的文件夹，专门用来存放那些不需要长期保留的数据。用完之后连同里面的内容一起删掉，文件系统保持干净。
Python 的 tempFile 模块提供了一套完整的解决方案，这些临时文件和目录在不需要的时候会自动清理掉。
临时目录在实际开发中有几个明显的好处：
自动清理机制省去了手动删除的步骤，每个临时目录都有唯一标识避免文件名冲突。系统会自动选择安全的存储位置，Unix 系统用 /tmp，Windows 用 %TEMP%。多线程和多进程环境下也能稳定工作，特别适合测试场景和需要中间存储的情况。
需要一个临时空间来存放中间计算结果或临时文件。写单元测试的时候模拟文件操作，完了自动清理。下载或解压的数据不需要长期保存。处理用户上传的文件，在保存最终结果之前需要一个缓冲区。构建自动化流程时，要确保不留下任何痕迹。
import tempfile import os # Create a temporary directorywith tempfile.TemporaryDirectory as temp_dir: print(f"Temporary directory created at: {temp_dir}") # Create a temporary file inside the directoryfile_path = os.path.join(temp_dir, "sample.txt") with open(file_path, "w") as f: f.write("Hello, Temporary World!") # Read back the filewith open(file_path, "r") as f: print(f.read) # At this point, the directory and its contents are deleted automaticallyprint("Temporary directory cleaned up automatically.")输出结果：
Temporary directory created at: /tmp/tmpabcd1234 Hello, Temporary World! Temporary directory cleaned up automatically.关键在于 with 语句块结束时，目录和文件会自动删除，不需要手动调用 os.remove 或 shutil.rmtree。
有时候需要更精细的控制，比如临时目录的生命周期超出单个函数作用域，这时候可以用 tempfile.mkdtemp：
import tempfile import shutil import os # Create a temporary directory manuallytemp_dir = tempfile.mkdtemp print(f"Created temporary directory: {temp_dir}") # Work inside itfile_path = os.path.join(temp_dir, "example.txt") with open(file_path, "w") as f: f.write("Manual cleanup required!") print("Files inside temp dir:", os.listdir(temp_dir)) # Clean up manually when doneshutil.rmtree(temp_dir) print("Temporary directory removed.")这种方式下需要自己负责清理工作，用完记得删除。
tempfile 支持给临时目录添加前缀和后缀，方便调试时识别：
import tempfile # Create with custom prefix and suffixwith tempfile.TemporaryDirectory(prefix="myapp_", suffix="_data") as temp_dir: print(f"Created: {temp_dir}")输出类似这样：
Created: /tmp/myapp_abcd1234_data还可以指定父目录：
with tempfile.TemporaryDirectory(dir="/path/to/parent") as temp_dir: print(temp_dir)当系统默认的临时目录权限不够或者空间不足时，这个功能就派上用场了。
下载大型 ZIP 文件后临时解压处理，处理完就清理掉：
import tempfile import zipfile def extract_and_process(zip_path): with tempfile.TemporaryDirectory as tmp_dir: print(f"Extracting to {tmp_dir}") with zipfile.ZipFile(zip_path, "r") as zip_ref: zip_ref.extractall(tmp_dir) # Process extracted filesfor file in os.listdir(tmp_dir): print("Processing:", file)整个流程结束后，解压的文件夹自动删除，磁盘不会留下任何垃圾文件。
应用程序按需生成报告文件（PDF、csv 之类），不需要永久存储：
import tempfile import csv import os def generate_temp_report(data): with tempfile.TemporaryDirectory as tmp_dir: file_path = os.path.join(tmp_dir, "report.csv") with open(file_path, "w", newline="") as csvfile: writer = csv.writer(csvfile) writer.writerow(["Name", "Age"]) writer.writerows(data) print(f"Report generated at: {file_path}") # Here you can upload it, email it, or read the content directly生成的报告可以直接上传、发邮件或者读取内容，不会在本地留存。
写单元测试时在项目目录下创建很多文件夹显然不是好主意，所以临时目录完美解决这个问题：
import tempfile import unittest import os class TestFileOperations(unittest.TestCase): def test_temp_directory(self): with tempfile.TemporaryDirectory as temp_dir: file_path = os.path.join(temp_dir, "test.txt") with open(file_path, "w") as f: f.write("test data") self.assertTrue(os.path.exists(file_path))每个测试用例都在独立的临时环境中运行，互不干扰，也不需要手动清理。
嵌套临时目录复杂场景下可能需要嵌套的临时目录结构：
import tempfile import os with tempfile.TemporaryDirectory as root_dir: print(f"Root: {root_dir}") sub_dir = tempfile.mkdtemp(dir=root_dir) print(f"Nested: {sub_dir}")多阶段数据处理流程中，每个阶段可以有自己的独立沙箱环境。
始终使用上下文管理器 with tempfile.TemporaryDirectory 来确保自动清理。不要硬编码 /tmp 路径，用 tempfile.gettempdir 获取系统临时目录。如果用了 mkdtemp 就必须手动调用 shutil.rmtree 清理。给临时目录加上有意义的前缀方便调试时快速定位。临时数据随时可能被系统清理，不要在里面存放需要持久化的信息。
几个实用技巧获取系统临时目录路径：
import tempfile print(tempfile.gettempdir)生成唯一文件名（但不创建文件）：
tempfile.mktemp
不过要注意，直接用 mktemp 有安全风险，生产环境建议用 NamedTemporaryFile 或 TemporaryDirectory。
下面这段代码展示了如何在 PDF 处理项目中使用临时目录。整个流程包括 PDF 转图片、图片转 Markdown、最后合并成完整文档：
import os import io import shutil import tempfile from pathlib import Path from typing import Iterable, Optional, Callable, Tuple # Requires: pip install pymupdf pillow import fitz # PyMuPDF from PIL import Imagedef process_pdfs_to_markdown( pdf_paths: Iterable[str | os.PathLike], output_dir: str | os.PathLike, *, page_image_dpi: int = 200, image_format: str = "PNG", llm_page_markdown_fn: Optional[Callable[[Path], str]] = None, ) -> Tuple[list[Path], list[Path]]: """ Convert each input PDF into page images using a temporary workspace, run an LLM on each page image to get Markdown, save one MD per page (still in a temp workspace), then merge the per-PDF Markdown into a single non-temporary Markdown file per PDF in `output_dir`. Non-temp file handling is kept simple (write final merged .md into `output_dir`), while the heavy lifting uses temp directories that auto-clean on success or error. Parameters pdf_paths : Iterable[str | PathLike] Paths to PDF files to process. output_dir : str | PathLike Directory where FINAL merged Markdown files (non-temp) will be written. page_image_dpi : int, optional Rendering resolution for converting PDF pages to images. Higher DPI → sharper (default 200). image_format : str, optional Image format for page renders (e.g., "PNG", "JPEG"). Default "PNG". llm_page_markdown_fn : Callable[[Path], str], optional A callable that takes a Path to a page image and returns Markdown text for that page. If not provided, a placeholder stub will be used. Returns ------- Tuple[list[Path], list[Path]] A tuple (final_markdown_files, per_page_markdown_files_flattened) - final_markdown_files: list of merged Markdown file paths written in output_dir (non-temp) - per_page_markdown_files_flattened: flattened list of all per-page MD files (in temp, ephemeral) (Returned for inspection/logging; these will be deleted when temp dir goes away.) Notes ----- - Uses a single top-level TemporaryDirectory for the whole batch to keep structure neat. - For each PDF, creates `/tmp/...//images` and `/tmp/...//md`. - Each page is rendered to an image file named `page-.`. - Each page's Markdown is saved to `page-.md`. - Finally, merges all page MDs for that PDF into `/.md` (non-temp). - Replace `llm_stub_markdown_from_image` with your actual LLM call (OpenAI, local VLM, etc.). Pseudocode hint for real LLM integration def llm_page_markdown_fn(img_path: Path) -> str: # pseudo: # bytes = img_path.read_bytes # resp = my_llm_client.vision_to_md(image=bytes, system_prompt="Extract content as Markdown.") # return resp.markdown pass """ output_dir = Path(output_dir) output_dir.mkdir(parents=True, exist_ok=True) # --- Local helper: default LLM stub (replace this with your LLM call) --- def llm_stub_markdown_from_image(img_path: Path) -> str: # This is a placeholder. Swap with a real LLM/VLM call to convert the image to Markdown. # You can pass the image bytes and ask the model to produce clean Markdown with headings, tables, lists, etc. return f"# Page extracted (stub)\n\n_Image: {img_path.name}_\n\n> Replace this with real LLM Markdown output." # Choose the LLM function (user-supplied or stub) llm_to_md = llm_page_markdown_fn or llm_stub_markdown_from_image final_markdown_files: list[Path] = per_page_markdown_files_flattened: list[Path] = # Top-level temp root for the entire run with tempfile.TemporaryDirectory(prefix="pdf2img-md_") as temp_root: temp_root = Path(temp_root) for pdf_path in map(Path, pdf_paths): if not pdf_path.exists or pdf_path.suffix.lower != ".pdf": # Skip invalid entries gracefully; alternatively raise ValueError continue pdf_stem = pdf_path.stem pdf_temp_dir = temp_root / pdf_stem images_dir = pdf_temp_dir / "images" md_dir = pdf_temp_dir / "md" images_dir.mkdir(parents=True, exist_ok=True) md_dir.mkdir(parents=True, exist_ok=True) # --- 1) Render pages to images in temp --- # Using PyMuPDF: fast, no external poppler dependency pages_rendered: list[Path] = with fitz.open(pdf_path) as doc: # scale based on DPI (PyMuPDF normally uses zoom factors; convert DPI to zoom) # Base DPI ~72; zoom = target_dpi / 72 zoom = page_image_dpi / 72.0 mat = fitz.Matrix(zoom, zoom) for page_index in range(doc.page_count): page = doc.load_page(page_index) pix = page.get_pixmap(matrix=mat, alpha=False) # no alpha for standard formats img_bytes = pix.tobytes(output=image_format.lower) img_name = f"page-{page_index + 1}.{image_format.lower}" img_path = images_dir / img_name # Save via PIL to ensure consistent headers/metadata if needed with Image.open(io.BytesIO(img_bytes)) as im: im.save(img_path, format=image_format) pages_rendered.append(img_path) # --- 2) For each page image, call LLM to get Markdown; save per-page MD in temp --- page_md_files: list[Path] = for img_path in pages_rendered: md_text = llm_to_md(img_path) #
这段代码的亮点在于所有中间文件（图片、单页 Markdown）都存放在临时目录里，处理完自动清理，只保留最终合并后的文档。整个流程非常干净，不会在磁盘上留下任何垃圾文件。
实际使用时把 llm_stub_markdown_from_image 替换成真正的 LLM 调用（比如 OpenAI 的 Vision API 或者本地视觉模型），就能实现完整的 PDF 文档处理流程。
临时目录在 Python 开发中确实是个实用的工具，文件处理更高效也更安全。不管是处理用户上传、写单元测试还是构建数据流水线，tempfile.TemporaryDirectory 都能让代码更简洁、更可靠。掌握它的用法能省不少麻烦，代码质量也能上个台阶。
Sravanth
来源：deephub