fix: rewrite projects/ and demos with new data api

demo/magic_pdf_parse_main.py

-import os
-import json
-import copy
-
-from loguru import logger
-
-from magic_pdf.libs.draw_bbox import draw_layout_bbox, draw_span_bbox
-from magic_pdf.pipe.UNIPipe import UNIPipe
-from magic_pdf.pipe.OCRPipe import OCRPipe
-from magic_pdf.pipe.TXTPipe import TXTPipe
-from magic_pdf.rw.DiskReaderWriter import DiskReaderWriter
-
-
-# todo: 设备类型选择 （？）
-
-def json_md_dump(
-        pipe,
-        md_writer,
-        pdf_name,
-        content_list,
-        md_content,
-        orig_model_list,
-):
-    # 写入模型结果到 model.json
-
-    md_writer.write(
-        content=json.dumps(orig_model_list, ensure_ascii=False, indent=4),
-        path=f"{pdf_name}_model.json"
-    )
-
-    # 写入中间结果到 middle.json
-    md_writer.write(
-        content=json.dumps(pipe.pdf_mid_data, ensure_ascii=False, indent=4),
-        path=f"{pdf_name}_middle.json"
-    )
-
-    # text文本结果写入到 conent_list.json
-    md_writer.write(
-        content=json.dumps(content_list, ensure_ascii=False, indent=4),
-        path=f"{pdf_name}_content_list.json"
-    )
-
-    # 写入结果到 .md 文件中
-    md_writer.write(
-        content=md_content,
-        path=f"{pdf_name}.md"
-    )
-
-
-# 可视化
-def draw_visualization_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name):
-    # 画布局框，附带排序结果
-    draw_layout_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
-    # 画 span 框
-    draw_span_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
-
-
-def pdf_parse_main(
-        pdf_path: str,
-        parse_method: str = 'auto',
-        model_json_path: str = None,
-        is_json_md_dump: bool = True,
-        is_draw_visualization_bbox: bool = True,
-        output_dir: str = None
-):
-    """
-    执行从 pdf 转换到 json、md 的过程，输出 md 和 json 文件到 pdf 文件所在的目录
-
-    :param pdf_path: .pdf 文件的路径，可以是相对路径，也可以是绝对路径
-    :param parse_method: 解析方法， 共 auto、ocr、txt 三种，默认 auto，如果效果不好，可以尝试 ocr
-    :param model_json_path: 已经存在的模型数据文件，如果为空则使用内置模型，pdf 和 model_json 务必对应
-    :param is_json_md_dump: 是否将解析后的数据写入到 .json 和 .md 文件中，默认 True，会将不同阶段的数据写入到不同的 .json 文件中（共3个.json文件），md内容会保存到 .md 文件中
-    :param output_dir: 输出结果的目录地址，会生成一个以 pdf 文件名命名的文件夹并保存所有结果
-    """
-    try:
-        pdf_name = os.path.basename(pdf_path).split(".")[0]
-        pdf_path_parent = os.path.dirname(pdf_path)
-
-        if output_dir:
-            output_path = os.path.join(output_dir, pdf_name)
-        else:
-            output_path = os.path.join(pdf_path_parent, pdf_name)
-
-        output_image_path = os.path.join(output_path, 'images')
-
-        # 获取图片的父路径，为的是以相对路径保存到 .md 和 conent_list.json 文件中
-        image_path_parent = os.path.basename(output_image_path)
-
-        pdf_bytes = open(pdf_path, "rb").read()  # 读取 pdf 文件的二进制数据
-
-        orig_model_list = []
-
-        if model_json_path:
-            # 读取已经被模型解析后的pdf文件的 json 原始数据，list 类型
-            model_json = json.loads(open(model_json_path, "r", encoding="utf-8").read())
-            orig_model_list = copy.deepcopy(model_json)
-        else:
-            model_json = []
-
-        # 执行解析步骤
-        # image_writer = DiskReaderWriter(output_image_path)
-        image_writer, md_writer = DiskReaderWriter(output_image_path), DiskReaderWriter(output_path)
-
-        # 选择解析方式
-        # jso_useful_key = {"_pdf_type": "", "model_list": model_json}
-        # pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
-        if parse_method == "auto":
-            jso_useful_key = {"_pdf_type": "", "model_list": model_json}
-            pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
-        elif parse_method == "txt":
-            pipe = TXTPipe(pdf_bytes, model_json, image_writer)
-        elif parse_method == "ocr":
-            pipe = OCRPipe(pdf_bytes, model_json, image_writer)
-        else:
-            logger.error("unknown parse method, only auto, ocr, txt allowed")
-            exit(1)
-
-        # 执行分类
-        pipe.pipe_classify()
-
-        # 如果没有传入模型数据，则使用内置模型解析
-        if len(model_json) == 0:
-            pipe.pipe_analyze()  # 解析
-            orig_model_list = copy.deepcopy(pipe.model_list)
-
-        # 执行解析
-        pipe.pipe_parse()
-
-        # 保存 text 和 md 格式的结果
-        content_list = pipe.pipe_mk_uni_format(image_path_parent, drop_mode="none")
-        md_content = pipe.pipe_mk_markdown(image_path_parent, drop_mode="none")
-
-        if is_json_md_dump:
-            json_md_dump(pipe, md_writer, pdf_name, content_list, md_content, orig_model_list)
-
-        if is_draw_visualization_bbox:
-            draw_visualization_bbox(pipe.pdf_mid_data['pdf_info'], pdf_bytes, output_path, pdf_name)
-
-    except Exception as e:
-        logger.exception(e)
-
-
-# 测试
-if __name__ == '__main__':
-    pdf_path = r"D:\project\20240617magicpdf\Magic-PDF\demo\demo1.pdf"
-    pdf_parse_main(pdf_path)
+import copy
+import json
+import os
+
+from loguru import logger
+
+from magic_pdf.data.data_reader_writer import FileBasedDataWriter
+from magic_pdf.libs.draw_bbox import draw_layout_bbox, draw_span_bbox
+from magic_pdf.pipe.OCRPipe import OCRPipe
+from magic_pdf.pipe.TXTPipe import TXTPipe
+from magic_pdf.pipe.UNIPipe import UNIPipe
+
+# todo: 设备类型选择 （？）
+
+
+def json_md_dump(
+        pipe,
+        md_writer,
+        pdf_name,
+        content_list,
+        md_content,
+        orig_model_list,
+):
+    # 写入模型结果到 model.json
+
+    md_writer.write_string(
+        f'{pdf_name}_model.json',
+        json.dumps(orig_model_list, ensure_ascii=False, indent=4)
+    )
+
+    # 写入中间结果到 middle.json
+    md_writer.write_string(
+        f'{pdf_name}_middle.json',
+        json.dumps(pipe.pdf_mid_data, ensure_ascii=False, indent=4)
+    )
+
+    # text文本结果写入到 conent_list.json
+    md_writer.write_string(
+        f'{pdf_name}_content_list.json',
+        json.dumps(content_list, ensure_ascii=False, indent=4)
+    )
+
+    # 写入结果到 .md 文件中
+    md_writer.write_string(
+        f'{pdf_name}.md',
+        md_content,
+    )
+
+
+# 可视化
+def draw_visualization_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name):
+    # 画布局框，附带排序结果
+    draw_layout_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
+    # 画 span 框
+    draw_span_bbox(pdf_info, pdf_bytes, local_md_dir, pdf_file_name)
+
+
+def pdf_parse_main(
+        pdf_path: str,
+        parse_method: str = 'auto',
+        model_json_path: str = None,
+        is_json_md_dump: bool = True,
+        is_draw_visualization_bbox: bool = True,
+        output_dir: str = None
+):
+    """执行从 pdf 转换到 json、md 的过程，输出 md 和 json 文件到 pdf 文件所在的目录.
+
+    :param pdf_path: .pdf 文件的路径，可以是相对路径，也可以是绝对路径
+    :param parse_method: 解析方法， 共 auto、ocr、txt 三种，默认 auto，如果效果不好，可以尝试 ocr
+    :param model_json_path: 已经存在的模型数据文件，如果为空则使用内置模型，pdf 和 model_json 务必对应
+    :param is_json_md_dump: 是否将解析后的数据写入到 .json 和 .md 文件中，默认 True，会将不同阶段的数据写入到不同的 .json 文件中（共3个.json文件），md内容会保存到 .md 文件中
+    :param output_dir: 输出结果的目录地址，会生成一个以 pdf 文件名命名的文件夹并保存所有结果
+    """
+    try:
+        pdf_name = os.path.basename(pdf_path).split('.')[0]
+        pdf_path_parent = os.path.dirname(pdf_path)
+
+        if output_dir:
+            output_path = os.path.join(output_dir, pdf_name)
+        else:
+            output_path = os.path.join(pdf_path_parent, pdf_name)
+
+        output_image_path = os.path.join(output_path, 'images')
+
+        # 获取图片的父路径，为的是以相对路径保存到 .md 和 conent_list.json 文件中
+        image_path_parent = os.path.basename(output_image_path)
+
+        pdf_bytes = open(pdf_path, 'rb').read()  # 读取 pdf 文件的二进制数据
+
+        orig_model_list = []
+
+        if model_json_path:
+            # 读取已经被模型解析后的pdf文件的 json 原始数据，list 类型
+            model_json = json.loads(open(model_json_path, 'r', encoding='utf-8').read())
+            orig_model_list = copy.deepcopy(model_json)
+        else:
+            model_json = []
+
+        # 执行解析步骤
+        # image_writer = DiskReaderWriter(output_image_path)
+        image_writer, md_writer = FileBasedDataWriter(output_image_path), FileBasedDataWriter(output_path)
+
+        # 选择解析方式
+        # jso_useful_key = {"_pdf_type": "", "model_list": model_json}
+        # pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
+        if parse_method == 'auto':
+            jso_useful_key = {'_pdf_type': '', 'model_list': model_json}
+            pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
+        elif parse_method == 'txt':
+            pipe = TXTPipe(pdf_bytes, model_json, image_writer)
+        elif parse_method == 'ocr':
+            pipe = OCRPipe(pdf_bytes, model_json, image_writer)
+        else:
+            logger.error('unknown parse method, only auto, ocr, txt allowed')
+            exit(1)
+
+        # 执行分类
+        pipe.pipe_classify()
+
+        # 如果没有传入模型数据，则使用内置模型解析
+        if len(model_json) == 0:
+            pipe.pipe_analyze()  # 解析
+            orig_model_list = copy.deepcopy(pipe.model_list)
+
+        # 执行解析
+        pipe.pipe_parse()
+
+        # 保存 text 和 md 格式的结果
+        content_list = pipe.pipe_mk_uni_format(image_path_parent, drop_mode='none')
+        md_content = pipe.pipe_mk_markdown(image_path_parent, drop_mode='none')
+
+        if is_json_md_dump:
+            json_md_dump(pipe, md_writer, pdf_name, content_list, md_content, orig_model_list)
+
+        if is_draw_visualization_bbox:
+            draw_visualization_bbox(pipe.pdf_mid_data['pdf_info'], pdf_bytes, output_path, pdf_name)
+
+    except Exception as e:
+        logger.exception(e)
+
+
+# 测试
+if __name__ == '__main__':
+    pdf_path = r'D:\project\20240617magicpdf\Magic-PDF\demo\demo1.pdf'
+    pdf_parse_main(pdf_path)

magic_pdf/data/data_reader_writer/filebase.py

@@ -55,5 +55,8 @@ class FileBasedDataWriter(DataWriter):
         if not os.path.isabs(fn_path) and len(self._parent_dir) > 0:
             fn_path = os.path.join(self._parent_dir, path)
 
+        if not os.path.exists(os.path.dirname(fn_path)):
+            os.makedirs(os.path.dirname(fn_path), exist_ok=True)
+
         with open(fn_path, 'wb') as f:
             f.write(data)

magic_pdf/model/types.py

+
+import os
+
+from magic_pdf.data.data_reader_writer import FileBasedDataWriter
+from magic_pdf.data.dataset import Dataset
+
+
+class InferenceResult:
+    def __init__(self, inference_results: list, dataset: Dataset):
+        self._infer_res = inference_results
+        self._dataset = dataset
+
+    def draw_model(self, writer: FileBasedDataWriter, dump_file_path: str):
+        dir_name = os.path.dirname(dump_file_path)
+        if dir_name not in ('', '.', '..'):
+            os.makedirs(dir_name, exist_ok=True)
+
+    def get_infer_res(self):
+        return self._infer_res

projects/web_api/app.py

@@ -3,75 +3,79 @@ import json
 import os
 from tempfile import NamedTemporaryFile
 
-import magic_pdf.model as model_config
 import uvicorn
-from fastapi import FastAPI, File, UploadFile, Form
+from fastapi import FastAPI, File, UploadFile
 from fastapi.responses import JSONResponse
 from loguru import logger
+
+import magic_pdf.model as model_config
+from magic_pdf.data.data_reader_writer import FileBasedDataWriter
 from magic_pdf.pipe.OCRPipe import OCRPipe
 from magic_pdf.pipe.TXTPipe import TXTPipe
 from magic_pdf.pipe.UNIPipe import UNIPipe
-from magic_pdf.rw.DiskReaderWriter import DiskReaderWriter
 
 model_config.__use_inside_model__ = True
 
 app = FastAPI()
 
+
 def json_md_dump(
-        pipe,
-        md_writer,
-        pdf_name,
-        content_list,
-        md_content,
+    pipe,
+    md_writer,
+    pdf_name,
+    content_list,
+    md_content,
 ):
     # Write model results to model.json
     orig_model_list = copy.deepcopy(pipe.model_list)
-    md_writer.write(
-        content=json.dumps(orig_model_list, ensure_ascii=False, indent=4),
-        path=f"{pdf_name}_model.json"
+    md_writer.write_string(
+        f'{pdf_name}_model.json',
+        json.dumps(orig_model_list, ensure_ascii=False, indent=4),
     )
 
     # Write intermediate results to middle.json
-    md_writer.write(
-        content=json.dumps(pipe.pdf_mid_data, ensure_ascii=False, indent=4),
-        path=f"{pdf_name}_middle.json"
+    md_writer.write_string(
+        f'{pdf_name}_middle.json',
+        json.dumps(pipe.pdf_mid_data, ensure_ascii=False, indent=4),
     )
 
     # Write text content results to content_list.json
-    md_writer.write(
-        content=json.dumps(content_list, ensure_ascii=False, indent=4),
-        path=f"{pdf_name}_content_list.json"
+    md_writer.write_string(
+        f'{pdf_name}_content_list.json',
+        json.dumps(content_list, ensure_ascii=False, indent=4),
     )
 
     # Write results to .md file
-    md_writer.write(
-        content=md_content,
-        path=f"{pdf_name}.md"
+    md_writer.write_string(
+        f'{pdf_name}.md',
+        md_content,
     )
 
-@app.post("/pdf_parse", tags=["projects"], summary="Parse PDF file")
+
+@app.post('/pdf_parse', tags=['projects'], summary='Parse PDF file')
 async def pdf_parse_main(
-        pdf_file: UploadFile = File(...),
-        parse_method: str = 'auto',
-        model_json_path: str = None,
-        is_json_md_dump: bool = True,
-        output_dir: str = "output"
+    pdf_file: UploadFile = File(...),
+    parse_method: str = 'auto',
+    model_json_path: str = None,
+    is_json_md_dump: bool = True,
+    output_dir: str = 'output',
 ):
-    """
-    Execute the process of converting PDF to JSON and MD, outputting MD and JSON files to the specified directory
+    """Execute the process of converting PDF to JSON and MD, outputting MD and
+    JSON files to the specified directory.
+
     :param pdf_file: The PDF file to be parsed
     :param parse_method: Parsing method, can be auto, ocr, or txt. Default is auto. If results are not satisfactory, try ocr
     :param model_json_path: Path to existing model data file. If empty, use built-in model. PDF and model_json must correspond
-    :param is_json_md_dump: Whether to write parsed data to .json and .md files. Default is True. Different stages of data will be written to different .json files (3 in total), md content will be saved to .md file
+    :param is_json_md_dump: Whether to write parsed data to .json and .md files. Default is True. Different stages of data will be written to different .json files (3 in total), md content will be saved to .md file  # noqa E501
     :param output_dir: Output directory for results. A folder named after the PDF file will be created to store all results
     """
     try:
         # Create a temporary file to store the uploaded PDF
-        with NamedTemporaryFile(delete=False, suffix=".pdf") as temp_pdf:
+        with NamedTemporaryFile(delete=False, suffix='.pdf') as temp_pdf:
             temp_pdf.write(await pdf_file.read())
             temp_pdf_path = temp_pdf.name
 
-        pdf_name = os.path.basename(pdf_file.filename).split(".")[0]
+        pdf_name = os.path.basename(pdf_file.filename).split('.')[0]
 
         if output_dir:
             output_path = os.path.join(output_dir, pdf_name)
@@ -83,28 +87,32 @@ async def pdf_parse_main(
         # Get parent path of images for relative path in .md and content_list.json
         image_path_parent = os.path.basename(output_image_path)
 
-        pdf_bytes = open(temp_pdf_path, "rb").read()  # Read binary data of PDF file
+        pdf_bytes = open(temp_pdf_path, 'rb').read()  # Read binary data of PDF file
 
         if model_json_path:
             # Read original JSON data of PDF file parsed by model, list type
-            model_json = json.loads(open(model_json_path, "r", encoding="utf-8").read())
+            model_json = json.loads(open(model_json_path, 'r', encoding='utf-8').read())
         else:
             model_json = []
 
         # Execute parsing steps
-        image_writer, md_writer = DiskReaderWriter(output_image_path), DiskReaderWriter(output_path)
+        image_writer, md_writer = FileBasedDataWriter(
+            output_image_path
+        ), FileBasedDataWriter(output_path)
 
         # Choose parsing method
-        if parse_method == "auto":
-            jso_useful_key = {"_pdf_type": "", "model_list": model_json}
+        if parse_method == 'auto':
+            jso_useful_key = {'_pdf_type': '', 'model_list': model_json}
             pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer)
-        elif parse_method == "txt":
+        elif parse_method == 'txt':
             pipe = TXTPipe(pdf_bytes, model_json, image_writer)
-        elif parse_method == "ocr":
+        elif parse_method == 'ocr':
             pipe = OCRPipe(pdf_bytes, model_json, image_writer)
         else:
-            logger.error("Unknown parse method, only auto, ocr, txt allowed")
-            return JSONResponse(content={"error": "Invalid parse method"}, status_code=400)
+            logger.error('Unknown parse method, only auto, ocr, txt allowed')
+            return JSONResponse(
+                content={'error': 'Invalid parse method'}, status_code=400
+            )
 
         # Execute classification
         pipe.pipe_classify()
@@ -114,28 +122,36 @@ async def pdf_parse_main(
             if model_config.__use_inside_model__:
                 pipe.pipe_analyze()  # Parse
             else:
-                logger.error("Need model list input")
-                return JSONResponse(content={"error": "Model list input required"}, status_code=400)
+                logger.error('Need model list input')
+                return JSONResponse(
+                    content={'error': 'Model list input required'}, status_code=400
+                )
 
         # Execute parsing
         pipe.pipe_parse()
 
         # Save results in text and md format
-        content_list = pipe.pipe_mk_uni_format(image_path_parent, drop_mode="none")
-        md_content = pipe.pipe_mk_markdown(image_path_parent, drop_mode="none")
+        content_list = pipe.pipe_mk_uni_format(image_path_parent, drop_mode='none')
+        md_content = pipe.pipe_mk_markdown(image_path_parent, drop_mode='none')
 
         if is_json_md_dump:
             json_md_dump(pipe, md_writer, pdf_name, content_list, md_content)
-        data = {"layout": copy.deepcopy(pipe.model_list), "info": pipe.pdf_mid_data, "content_list": content_list,'md_content':md_content}
+        data = {
+            'layout': copy.deepcopy(pipe.model_list),
+            'info': pipe.pdf_mid_data,
+            'content_list': content_list,
+            'md_content': md_content,
+        }
         return JSONResponse(data, status_code=200)
 
     except Exception as e:
         logger.exception(e)
-        return JSONResponse(content={"error": str(e)}, status_code=500)
+        return JSONResponse(content={'error': str(e)}, status_code=500)
     finally:
         # Clean up the temporary file
         if 'temp_pdf_path' in locals():
             os.unlink(temp_pdf_path)
 
-# if __name__ == '__main__':
-#     uvicorn.run(app, host="0.0.0.0", port=8888)
+
+if __name__ == '__main__':
\ No newline at end of file
+    uvicorn.run(app, host='0.0.0.0', port=8888)

projects/web_demo/web_demo/api/analysis/pdf_ext.py

 import json
-import re
 import os
 import shutil
 import traceback
 from pathlib import Path
+
+from common.error_types import ApiException
+from common.mk_markdown.mk_markdown import \
+    ocr_mk_mm_markdown_with_para_and_pagination
 from flask import current_app, url_for
-from magic_pdf.rw.DiskReaderWriter import DiskReaderWriter
-from magic_pdf.pipe.UNIPipe import UNIPipe
+from loguru import logger
+
 import magic_pdf.model as model_config
+from magic_pdf.data.data_reader_writer import FileBasedDataWriter
 from magic_pdf.libs.json_compressor import JsonCompressor
-from common.mk_markdown.mk_markdown import ocr_mk_mm_markdown_with_para_and_pagination
+from magic_pdf.pipe.UNIPipe import UNIPipe
+
+from ..extensions import app, db
 from .ext import find_file
-from ..extentions import app, db
 from .models import AnalysisPdf, AnalysisTask
-from common.error_types import ApiException
-from loguru import logger
 
 model_config.__use_inside_model__ = True
 
@@ -22,51 +25,51 @@ model_config.__use_inside_model__ = True
 def analysis_pdf(image_url_prefix, image_dir, pdf_bytes, is_ocr=False):
     try:
         model_json = []  # model_json传空list使用内置模型解析
-        logger.info(f"is_ocr: {is_ocr}")
+        logger.info(f'is_ocr: {is_ocr}')
         if not is_ocr:
-            jso_useful_key = {"_pdf_type": "", "model_list": model_json}
-            image_writer = DiskReaderWriter(image_dir)
+            jso_useful_key = {'_pdf_type': '', 'model_list': model_json}
+            image_writer = FileBasedDataWriter(image_dir)
             pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer, is_debug=True)
             pipe.pipe_classify()
         else:
-            jso_useful_key = {"_pdf_type": "ocr", "model_list": model_json}
-            image_writer = DiskReaderWriter(image_dir)
+            jso_useful_key = {'_pdf_type': 'ocr', 'model_list': model_json}
+            image_writer = FileBasedDataWriter(image_dir)
             pipe = UNIPipe(pdf_bytes, jso_useful_key, image_writer, is_debug=True)
         """如果没有传入有效的模型数据，则使用内置model解析"""
         if len(model_json) == 0:
             if model_config.__use_inside_model__:
                 pipe.pipe_analyze()
             else:
-                logger.error("need model list input")
+                logger.error('need model list input')
                 exit(1)
         pipe.pipe_parse()
         pdf_mid_data = JsonCompressor.decompress_json(pipe.get_compress_pdf_mid_data())
-        pdf_info_list = pdf_mid_data["pdf_info"]
+        pdf_info_list = pdf_mid_data['pdf_info']
         md_content = json.dumps(ocr_mk_mm_markdown_with_para_and_pagination(pdf_info_list, image_url_prefix),
                                 ensure_ascii=False)
         bbox_info = get_bbox_info(pdf_info_list)
         return md_content, bbox_info
-    except Exception as e:
+    except Exception as e:  # noqa: F841
         logger.error(traceback.format_exc())
 
 
 def get_bbox_info(data):
     bbox_info = []
     for page in data:
-        preproc_blocks = page.get("preproc_blocks", [])
-        discarded_blocks = page.get("discarded_blocks", [])
+        preproc_blocks = page.get('preproc_blocks', [])
+        discarded_blocks = page.get('discarded_blocks', [])
         bbox_info.append({
-            "preproc_blocks": preproc_blocks,
-            "page_idx": page.get("page_idx"),
-            "page_size": page.get("page_size"),
-            "discarded_blocks": discarded_blocks,
+            'preproc_blocks': preproc_blocks,
+            'page_idx': page.get('page_idx'),
+            'page_size': page.get('page_size'),
+            'discarded_blocks': discarded_blocks,
         })
     return bbox_info
 
 
 def analysis_pdf_task(pdf_dir, image_dir, pdf_path, is_ocr, analysis_pdf_id):
-    """
-    解析pdf
+    """解析pdf.
+
     :param pdf_dir:  pdf解析目录
     :param image_dir:  图片目录
     :param pdf_path:  pdf路径
@@ -75,8 +78,8 @@ def analysis_pdf_task(pdf_dir, image_dir, pdf_path, is_ocr, analysis_pdf_id):
     :return:
     """
     try:
-        logger.info(f"start task: {pdf_path}")
-        logger.info(f"image_dir: {image_dir}")
+        logger.info(f'start task: {pdf_path}')
+        logger.info(f'image_dir: {image_dir}')
         if not Path(image_dir).exists():
             Path(image_dir).mkdir(parents=True, exist_ok=True)
         else:
@@ -96,26 +99,26 @@ def analysis_pdf_task(pdf_dir, image_dir, pdf_path, is_ocr, analysis_pdf_id):
         # ############ markdown #############
         pdf_name = Path(pdf_path).name
 
-        full_md_content = ""
+        full_md_content = ''
         for item in json.loads(md_content):
-            full_md_content += item["md_content"] + "\n"
+            full_md_content += item['md_content'] + '\n'
 
-        full_md_name = "full.md"
-        with open(f"{pdf_dir}/{full_md_name}", "w", encoding="utf-8") as file:
+        full_md_name = 'full.md'
+        with open(f'{pdf_dir}/{full_md_name}', 'w', encoding='utf-8') as file:
             file.write(full_md_content)
         with app.app_context():
             full_md_link = url_for('analysis.mdview', filename=full_md_name, as_attachment=False)
-            full_md_link = f"{full_md_link}&pdf={pdf_name}"
+            full_md_link = f'{full_md_link}&pdf={pdf_name}'
 
         md_link_list = []
         with app.app_context():
             for n, md in enumerate(json.loads(md_content)):
-                md_content = md["md_content"]
+                md_content = md['md_content']
                 md_name = f"{md.get('page_no', n)}.md"
-                with open(f"{pdf_dir}/{md_name}", "w", encoding="utf-8") as file:
+                with open(f'{pdf_dir}/{md_name}', 'w', encoding='utf-8') as file:
                     file.write(md_content)
                 md_url = url_for('analysis.mdview', filename=md_name, as_attachment=False)
-                md_link_list.append(f"{md_url}&pdf={pdf_name}")
+                md_link_list.append(f'{md_url}&pdf={pdf_name}')
 
         with app.app_context():
             with db.auto_commit():
@@ -129,8 +132,8 @@ def analysis_pdf_task(pdf_dir, image_dir, pdf_path, is_ocr, analysis_pdf_id):
                 analysis_task_object = AnalysisTask.query.filter_by(analysis_pdf_id=analysis_pdf_id).first()
                 analysis_task_object.status = 1
                 db.session.add(analysis_task_object)
-        logger.info(f"finished!")
-    except Exception as e:
+        logger.info('finished!')
+    except Exception as e:  # noqa: F841
         logger.error(traceback.format_exc())
         with app.app_context():
             with db.auto_commit():
@@ -141,7 +144,7 @@ def analysis_pdf_task(pdf_dir, image_dir, pdf_path, is_ocr, analysis_pdf_id):
                 analysis_task_object = AnalysisTask.query.filter_by(analysis_pdf_id=analysis_pdf_id).first()
                 analysis_task_object.status = 1
                 db.session.add(analysis_task_object)
-        raise ApiException(code=500, msg="PDF parsing failed", msgZH="pdf解析失败")
+        raise ApiException(code=500, msg='PDF parsing failed', msgZH='pdf解析失败')
     finally:
         # 执行pending
         with app.app_context():
@@ -149,12 +152,12 @@ def analysis_pdf_task(pdf_dir, image_dir, pdf_path, is_ocr, analysis_pdf_id):
                 AnalysisTask.update_date.asc()).first()
             if analysis_task_object:
                 pdf_upload_folder = current_app.config['PDF_UPLOAD_FOLDER']
-                upload_dir = f"{current_app.static_folder}/{pdf_upload_folder}"
+                upload_dir = f'{current_app.static_folder}/{pdf_upload_folder}'
                 file_path = find_file(analysis_task_object.file_key, upload_dir)
                 file_stem = Path(file_path).stem
                 pdf_analysis_folder = current_app.config['PDF_ANALYSIS_FOLDER']
-                pdf_dir = f"{current_app.static_folder}/{pdf_analysis_folder}/{file_stem}"
-                image_dir = f"{pdf_dir}/images"
+                pdf_dir = f'{current_app.static_folder}/{pdf_analysis_folder}/{file_stem}'
+                image_dir = f'{pdf_dir}/images'
                 with db.auto_commit():
                     analysis_pdf_object = AnalysisPdf.query.filter_by(id=analysis_task_object.analysis_pdf_id).first()
                     analysis_pdf_object.status = 0
@@ -164,4 +167,4 @@ def analysis_pdf_task(pdf_dir, image_dir, pdf_path, is_ocr, analysis_pdf_id):
                     db.session.add(analysis_task_object)
                 analysis_pdf_task(pdf_dir, image_dir, file_path, analysis_task_object.is_ocr, analysis_task_object.analysis_pdf_id)
             else:
-                logger.info(f"all task finished!")
+                logger.info('all task finished!')

projects/web_demo/web_demo/api/extentions.py → projects/web_demo/web_demo/api/extensions.py

+from contextlib import contextmanager
+
+from common.error_types import ApiException
 from flask import Flask, jsonify
-from flask_restful import Api as _Api
 from flask_cors import CORS
-from flask_sqlalchemy import SQLAlchemy as _SQLAlchemy
-from flask_migrate import Migrate
-from contextlib import contextmanager
 from flask_jwt_extended import JWTManager
 from flask_marshmallow import Marshmallow
-from common.error_types import ApiException
-from werkzeug.exceptions import HTTPException
+from flask_migrate import Migrate
+from flask_restful import Api as _Api
+from flask_sqlalchemy import SQLAlchemy as _SQLAlchemy
 from loguru import logger
+from werkzeug.exceptions import HTTPException
 
 
 class Api(_Api):
@@ -21,23 +22,23 @@ class Api(_Api):
         elif isinstance(e, HTTPException):
             code = e.code
             msg = e.description
-            msgZH = "服务异常，详细信息请查看日志"
+            msgZH = '服务异常，详细信息请查看日志'
             error_code = e.code
         else:
             code = 500
             msg = str(e)
             error_code = 500
-            msgZH = "服务异常，详细信息请查看日志"
+            msgZH = '服务异常，详细信息请查看日志'
 
         # 使用 loguru 记录异常信息
-        logger.opt(exception=e).error(f"An error occurred: {msg}")
+        logger.opt(exception=e).error(f'An error occurred: {msg}')
 
         return jsonify({
-            "error": "Internal Server Error" if code == 500 else e.name,
-            "msg": msg,
-            "msgZH": msgZH,
-            "code": code,
-            "error_code": error_code
+            'error': 'Internal Server Error' if code == 500 else e.name,
+            'msg': msg,
+            'msgZH': msgZH,
+            'code': code,
+            'error_code': error_code
         }), code
 
 
@@ -59,4 +60,4 @@ db = SQLAlchemy()
 migrate = Migrate()
 jwt = JWTManager()
 ma = Marshmallow()
-folder = app.config.get("REACT_APP_DIST")
+folder = app.config.get('REACT_APP_DIST')