(转)max_dump_file_size设置不当导致空间占满

今天来发现一个机器空间用满了,700G的硬盘还没有什么数据就已经满了,查看发现bdump和cdump就占500多G,查看oracle日志发现如下错误

Errors in file /data/oracle/admin/ora10g/bdump/ora10g_j000_5235.trc
ORA-07445: exception encountered: core dump [qcdlgcd()+168] [SIGSEGV] [Address not mapped to object]

由于是线上的原因等下找,先把空间空出来再说直接删掉*.trc文件

导致原因是max_dump_file_size是unlimited,使产生的跟踪文件把磁盘空间,修改该参数max_dump_file_size为100m 改参数的修改方式

alter system set max_dump_file_size=100 scope=both;这样是100个OS块的大小

alter system set max_dump_file_size='100m' scope=both;这样是设置成100m

关于日志中的报错,查看了metalink解决方法为

alter system flush sharel pool;可是我执行了不行问题不在这,自己看下trc文件发现时物化视图更新的问题,找到这个物化视图,再到生产库上去找对应的原表,发现原表的结构都改变了,导致物化视图一直更新出问题,删掉再重建问题得到解决!
#define MAX_FILE_SIZE (10 * 1024 * 1024) // 10MB void exif_edit_file (const char *path) { FILE *f = fopen(path, "rb"); if (!f) { TL_LOG_DEBUG("%s,错误:无法打开文件 %s", __func__, path); return; } fseek(f, 0, SEEK_END); long file_size = ftell(f); fseek(f, 0, SEEK_SET); if (file_size <= 0 || file_size > MAX_FILE_SIZE) { TL_LOG_DEBUG("%s,错误:文件大小无效 %ld", __func__, file_size); fclose(f); return; } unsigned char *file_data = (unsigned char *)tl_hal_mem_psram_malloc(file_size); if (!file_data) { TL_LOG_DEBUG("%s,错误:内存分配失败", __func__); fclose(f); return; } if (fread(file_data, 1, file_size, f) != (size_t)file_size) { TL_LOG_DEBUG("%s,错误:读取文件失败", __func__); free(file_data); fclose(f); return; } fclose(f); ExifData *exif = exif_data_new_from_file(path); if (!exif) { TL_LOG_DEBUG("%s,错误:无法读取EXIF数据 %s",__func__,path); } ExifEntry *date_entry = exif_content_get_entry( exif->ifd[EXIF_IFD_EXIF], EXIF_TAG_DATE_TIME_ORIGINAL ); if (!date_entry) { date_entry = exif_entry_new(); exif_content_add_entry(exif->ifd[EXIF_IFD_EXIF], date_entry); exif_entry_initialize(date_entry, EXIF_TAG_DATE_TIME_ORIGINAL); } char datetime[20] = "2024:01:01 12:00:00"; size_t len = strlen(datetime) + 1; date_entry->format = EXIF_FORMAT_ASCII; date_entry->components = len; date_entry->data = (unsigned char*) malloc(date_entry->size); if (date_entry->data) { strcpy((char*)date_entry->data, datetime); } else { } unsigned char *exif_buffer; unsigned int exif_size; exif_data_save_data(exif, &exif_buffer, &exif_size); DUMP8("%02X ", exif_buffer, exif_size); // 4. 查找并替换原始文件中的EXIF段 unsigned char *new_file_data = NULL; long new_file_size = 0; // JPEG文件以FF D8开头,查找第一个FF E1 (APP1段,即EXIF段) if (file_size >= 4 && file_data[0] == 0xFF && file_data[1] == 0xD8) { int found_exif = 0; long offset = 2; // 从SOI标记后开始 while (offset < file_size - 3) { // 查找下一个标记 if (file_data[offset] == 0xFF && file_data[offset + 1] >= 0xE0 && file_data[offset + 1] <= 0xEF) { // 找到APP段 unsigned short segment_size = (file_data[offset + 2] << 8) | file_data[offset + 3]; if (file_data[offset + 1] == 0xE1) { // 找到EXIF段 found_exif = 1; // 计算新文件大小:原始大小 - 旧EXIF段大小 + 新EXIF段大小 new_file_size = file_size - (segment_size + 2) + (exif_size + 2); new_file_data = (unsigned char *)tl_hal_mem_psram_malloc(new_file_size); if (!new_file_data) { TL_LOG_DEBUG("%s,错误:内存分配失败", __func__); break; } // 复制文件头(SOI标记) memcpy(new_file_data, file_data, offset); // 写入新的EXIF段 // 标记 (FF E1) new_file_data[offset] = 0xFF; new_file_data[offset + 1] = 0xE1; // 段大小 (包含大小字段本身的两个字节) unsigned short new_exif_size = exif_size + 2; new_file_data[offset + 2] = (new_exif_size >> 8) & 0xFF; new_file_data[offset + 3] = new_exif_size & 0xFF; // 写入EXIF数据 memcpy(new_file_data + offset + 4, exif_buffer, exif_size); // 复制剩余数据(跳过旧的EXIF段) memcpy(new_file_data + offset + 4 + exif_size, file_data + offset + 2 + segment_size, file_size - (offset + 2 + segment_size)); break; } else { // 不是EXIF段,跳过 offset += 2 + segment_size; } } else { // 不是标记,继续查找 offset++; } } if (!found_exif) { // 如果没有找到EXIF段,在文件头后插入新的EXIF段 new_file_size = file_size + exif_size + 4; // +4 是标记和大小字段 new_file_data = (unsigned char *)tl_hal_mem_psram_malloc(new_file_size); if (!new_file_data) { TL_LOG_DEBUG("%s,错误:内存分配失败", __func__); } else { // 复制SOI标记 memcpy(new_file_data, file_data, 2); // 写入新的EXIF段 new_file_data[2] = 0xFF; new_file_data[3] = 0xE1; unsigned short new_exif_size = exif_size + 2; new_file_data[4] = (new_exif_size >> 8) & 0xFF; new_file_data[5] = new_exif_size & 0xFF; memcpy(new_file_data + 6, exif_buffer, exif_size); // 复制剩余数据 memcpy(new_file_data + 6 + exif_size, file_data + 2, file_size - 2); } } } // 5. 保存新文件 if (new_file_data && new_file_size > 0) { f = fopen("/data/emmc2/media/photo_9999999_0.jpeg", "wb"); if (f) { if (fwrite(new_file_data, 1, new_file_size, f) == (size_t)new_file_size) { printf("EXIF数据编辑成功!保存至:/data/emmc2/media/photo_88888888_0.jpeg\n"); } else { TL_LOG_DEBUG("%s,错误:写入文件失败", __func__); } fclose(f); } else { TL_LOG_DEBUG("%s,错误:无法创建输出文件", __func__); } tl_hal_mem_psram_free(new_file_data); } else { TL_LOG_DEBUG("%s,错误:无法生成新文件", __func__); } // 6. 清理资源 free(exif_buffer); exif_data_unref(exif); tl_hal_mem_psram_free(file_data); printf("EXIF数据编辑成功!保存至:/data/emmc2/media/photo_88888888_0.jpeg\n"); }分析这段代码可能有什么问题
06-17
import os import pandas as pd import tkinter as tk from tkinter import ttk, filedialog, scrolledtext, messagebox from tkinter.colorchooser import askcolor from difflib import SequenceMatcher import re import openpyxl import threading import numpy as np from openpyxl.utils import get_column_letter import xlrd import gc import hashlib import json import tempfile from concurrent.futures import ThreadPoolExecutor, as_completed import unicodedata class EnhancedSignalComparator: def __init__(self, root): self.root = root self.root.title("增强版信号功能对比工具") self.root.geometry("1200x800") self.root.configure(bg="#f0f0f0") # 初始化变量 self.folder_path = tk.StringVar() self.search_text = tk.StringVar() self.files = [] self.results = {} # 存储信号对比结果 self.highlight_color = "#FFD700" # 默认高亮色 self.search_running = False self.stop_requested = False self.cache_dir = os.path.join(tempfile.gettempdir(), "excel_cache") self.file_cache = {} # 文件缓存 self.column_cache = {} # 列名缓存 self.max_workers = 4 # 最大并发线程数 # 创建缓存目录 os.makedirs(self.cache_dir, exist_ok=True) # 创建界面 self.create_widgets() def create_widgets(self): # 顶部控制面板 control_frame = ttk.Frame(self.root, padding=10) control_frame.pack(fill=tk.X) # 文件夹选择 ttk.Label(control_frame, text="选择文件夹:").grid(row=0, column=0, sticky=tk.W) folder_entry = ttk.Entry(control_frame, textvariable=self.folder_path, width=50) folder_entry.grid(row=0, column=1, padx=5, sticky=tk.EW) ttk.Button(control_frame, text="浏览...", command=self.browse_folder).grid(row=0, column=2) # 搜索输入 ttk.Label(control_frame, text="搜索信号:").grid(row=1, column=0, sticky=tk.W, pady=(10,0)) search_entry = ttk.Entry(control_frame, textvariable=self.search_text, width=50) search_entry.grid(row=1, column=1, padx=5, pady=(10,0), sticky=tk.EW) search_entry.bind("<Return>", lambda event: self.start_search_thread()) ttk.Button(control_frame, text="搜索", command=self.start_search_thread).grid(row=1, column=2, pady=(10,0)) ttk.Button(control_frame, text="停止", command=self.stop_search).grid(row=1, column=3, pady=(10,0), padx=5) # 高级选项 ttk.Label(control_frame, text="并发线程:").grid(row=2, column=0, sticky=tk.W, pady=(10,0)) self.thread_var = tk.StringVar(value="4") ttk.Combobox(control_frame, textvariable=self.thread_var, values=["1", "2", "4", "8"], width=5).grid(row=2, column=1, sticky=tk.W, padx=5, pady=(10,0)) # 文件过滤 ttk.Label(control_frame, text="文件过滤:").grid(row=2, column=2, sticky=tk.W, pady=(10,0)) self.filter_var = tk.StringVar(value="*.xlsx;*.xlsm;*.xls") ttk.Entry(control_frame, textvariable=self.filter_var, width=20).grid(row=2, column=3, sticky=tk.W, padx=5, pady=(10,0)) # 高亮颜色选择 ttk.Label(control_frame, text="高亮颜色:").grid(row=3, column=0, sticky=tk.W, pady=(10,0)) self.color_btn = tk.Button(control_frame, bg=self.highlight_color, width=3, command=self.choose_color) self.color_btn.grid(row=3, column=1, sticky=tk.W, padx=5, pady=(10,0)) # 进度条 self.progress = ttk.Progressbar(control_frame, orient="horizontal", length=200, mode="determinate") self.progress.grid(row=3, column=2, columnspan=2, sticky=tk.EW, padx=5, pady=(10,0)) # 结果标签 self.result_label = ttk.Label(control_frame, text="") self.result_label.grid(row=3, column=4, sticky=tk.W, padx=5, pady=(10,0)) # 对比面板 notebook = ttk.Notebook(self.root) notebook.pack(fill=tk.BOTH, expand=True, padx=10, pady=10) # 表格视图 self.table_frame = ttk.Frame(notebook) notebook.add(self.table_frame, text="表格视图") # 文本对比视图 self.text_frame = ttk.Frame(notebook) notebook.add(self.text_frame, text="行内容对比") # 状态栏 self.status_var = tk.StringVar() status_bar = ttk.Label(self.root, textvariable=self.status_var, relief=tk.SUNKEN, anchor=tk.W) status_bar.pack(side=tk.BOTTOM, fill=tk.X) # 初始化表格和文本区域 self.init_table_view() self.init_text_view() def init_table_view(self): """初始化表格视图""" # 创建树状表格 columns = ("信号", "文件", "行内容摘要") self.tree = ttk.Treeview(self.table_frame, columns=columns, show="headings") # 设置列标题 for col in columns: self.tree.heading(col, text=col) self.tree.column(col, width=200, anchor=tk.W) # 添加滚动条 scrollbar = ttk.Scrollbar(self.table_frame, orient=tk.VERTICAL, command=self.tree.yview) self.tree.configure(yscrollcommand=scrollbar.set) self.tree.pack(side=tk.LEFT, fill=tk.BOTH, expand=True) scrollbar.pack(side=tk.RIGHT, fill=tk.Y) # 绑定选择事件 self.tree.bind("<<TreeviewSelect>>", self.on_table_select) def init_text_view(self): """初始化文本对比视图""" self.text_panes = {} self.text_frame.columnconfigure(0, weight=1) self.text_frame.rowconfigure(0, weight=1) # 创建对比容器 self.compare_container = ttk.Frame(self.text_frame) self.compare_container.grid(row=0, column=0, sticky="nsew", padx=5, pady=5) # 添加差异高亮按钮 btn_frame = ttk.Frame(self.text_frame) btn_frame.grid(row=1, column=0, sticky="ew", padx=5, pady=5) ttk.Button(btn_frame, text="高亮显示差异", command=self.highlight_differences).pack(side=tk.LEFT) ttk.Button(btn_frame, text="导出差异报告", command=self.export_report).pack(side=tk.LEFT, padx=5) ttk.Button(btn_frame, text="清除缓存", command=self.clear_cache).pack(side=tk.LEFT, padx=5) ttk.Button(btn_frame, text="手动指定列名", command=self.manual_column_select).pack(side=tk.LEFT, padx=5) def browse_folder(self): """选择文件夹""" folder = filedialog.askdirectory(title="选择包含Excel文件的文件夹") if folder: self.folder_path.set(folder) self.load_files() def load_files(self): """加载文件夹中的Excel文件(优化特殊字符处理)""" folder = self.folder_path.get() if not folder or not os.path.isdir(folder): return # 获取文件过滤模式 filter_patterns = self.filter_var.get().split(';') self.files = [] for file in os.listdir(folder): file_path = os.path.join(folder, file) # 跳过临时文件 if file.startswith('~$'): continue # 检查文件扩展名 file_lower = file.lower() matched = False for pattern in filter_patterns: # 移除通配符并换为小写 ext = pattern.replace('*', '').lower() if file_lower.endswith(ext): matched = True break if matched: # 规范化文件名处理特殊字符 normalized_path = self.normalize_file_path(file_path) if normalized_path and os.path.isfile(normalized_path): self.files.append(normalized_path) self.status_var.set(f"找到 {len(self.files)} 个Excel文件") def normalize_file_path(self, path): """规范化文件路径,处理特殊字符""" try: # 尝试直接访问文件 if os.path.exists(path): return path # 尝试Unicode规范化 normalized = unicodedata.normalize('NFC', path) if os.path.exists(normalized): return normalized # 尝试不同编码方案 encodings = ['utf-8', 'shift_jis', 'euc-jp', 'cp932'] for encoding in encodings: try: decoded = path.encode('latin1').decode(encoding) if os.path.exists(decoded): return decoded except: continue # 最终尝试原始路径 return path except Exception as e: self.status_var.set(f"文件路径处理错误: {str(e)}") return path def get_file_hash(self, file_path): """计算文件哈希值用于缓存""" try: hash_md5 = hashlib.md5() with open(file_path, "rb") as f: for chunk in iter(lambda: f.read(4096), b""): hash_md5.update(chunk) return hash_md5.hexdigest() except Exception as e: self.status_var.set(f"计算文件哈希失败: {str(e)}") return str(os.path.getmtime(file_path)) def get_cache_filename(self, file_path): """获取缓存文件名""" file_hash = self.get_file_hash(file_path) return os.path.join(self.cache_dir, f"{os.path.basename(file_path)}_{file_hash}.cache") def load_header_cache(self, file_path): """加载列名缓存""" cache_file = self.get_cache_filename(file_path) if os.path.exists(cache_file): try: with open(cache_file, "r", encoding='utf-8') as f: return json.load(f) except: return None return None def save_header_cache(self, file_path, header_info): """保存列名缓存""" cache_file = self.get_cache_filename(file_path) try: with open(cache_file, "w", encoding='utf-8') as f: json.dump(header_info, f) return True except: return False def find_header_row(self, file_path): """查找列名行(增强版)""" # 检查缓存 cache = self.load_header_cache(file_path) if cache: return cache.get("header_row"), cache.get("signal_col") # 没有缓存则重新查找 if file_path.lower().endswith((".xlsx", ".xlsm")): return self.find_header_row_openpyxl(file_path) elif file_path.lower().endswith(".xls"): return self.find_header_row_xlrd(file_path) return None, None def find_header_row_openpyxl(self, file_path): """使用openpyxl查找列名行(增强版)""" try: wb = openpyxl.load_workbook(file_path, read_only=True, data_only=True) ws = wb.active # 尝试多种列名匹配模式 patterns = [ r'データ名', # 半角片假名 r'データ名', # 全角片假名 r'信号名', # 中文 r'Signal Name', # 英文 r'Data Name', r'信号名称', r'データ名称' ] # 扩大搜索范围:前100行和前100列 for row_idx in range(1, 101): # 1-100行 # 扩大列搜索范围到100列 for col_idx in range(1, 101): # 1-100列 try: cell = ws.cell(row=row_idx, column=col_idx) cell_value = cell.value if not cell_value: continue # 尝试所有匹配模式 cell_str = str(cell_value) for pattern in patterns: if re.search(pattern, cell_str, re.IGNORECASE): # 找到列名行后,尝试确定信号列 signal_col = None # 在同行中查找信号列 for col_idx2 in range(1, 101): # 1-100列 try: cell2 = ws.cell(row=row_idx, column=col_idx2) cell2_value = cell2.value if not cell2_value: continue cell2_str = str(cell2_value) if re.search(pattern, cell2_str, re.IGNORECASE): signal_col = col_idx2 break except: continue # 保存缓存 if signal_col is not None: header_info = {"header_row": row_idx, "signal_col": signal_col} self.save_header_cache(file_path, header_info) wb.close() return row_idx, signal_col except: continue wb.close() except Exception as e: self.status_var.set(f"查找列名行出错: {str(e)}") return None, None def find_header_row_xlrd(self, file_path): """使用xlrd查找列名行(增强版)""" try: wb = xlrd.open_workbook(file_path) ws = wb.sheet_by_index(0) # 尝试多种列名匹配模式 patterns = [ r'データ名', # 半角片假名 r'データ名', # 全角片假名 r'信号名', # 中文 r'Signal Name', # 英文 r'Data Name', r'信号名称', r'データ名称' ] # 扩大搜索范围:前100行和前100列 for row_idx in range(0, 100): # 0-99行 # 扩大列搜索范围到100列 for col_idx in range(0, 100): # 0-99列 try: cell_value = ws.cell_value(row_idx, col_idx) if not cell_value: continue # 尝试所有匹配模式 cell_str = str(cell_value) for pattern in patterns: if re.search(pattern, cell_str, re.IGNORECASE): # 找到列名行后,尝试确定信号列 signal_col = None # 在同行中查找信号列 for col_idx2 in range(0, 100): # 0-99列 try: cell2_value = ws.cell_value(row_idx, col_idx2) if not cell2_value: continue cell2_str = str(cell2_value) if re.search(pattern, cell2_str, re.IGNORECASE): signal_col = col_idx2 break except: continue # 保存缓存 if signal_col is not None: header_info = {"header_row": row_idx, "signal_col": signal_col} self.save_header_cache(file_path, header_info) return row_idx, signal_col except: continue except Exception as e: self.status_var.set(f"查找列名行出错: {str(e)}") return None, None def extract_row_content(self, ws, row_idx, header_row, max_cols=100): """高效提取行内容(最多到100列)""" content = [] # 扩展到100列 for col_idx in range(1, max_cols + 1): try: cell = ws.cell(row=row_idx, column=col_idx) if cell.value is not None and str(cell.value).strip() != '': # 使用列名缓存 col_key = f"{header_row}-{col_idx}" if col_key in self.column_cache: col_name = self.column_cache[col_key] else: col_name_cell = ws.cell(row=header_row, column=col_idx) col_name = col_name_cell.value if col_name_cell.value else f"列{get_column_letter(col_idx)}" self.column_cache[col_key] = col_name content.append(f"{col_name}: {str(cell.value).strip()}") except: continue return "\n".join(content) def start_search_thread(self): """启动搜索线程""" if self.search_running: return self.search_running = True self.stop_requested = False self.max_workers = int(self.thread_var.get()) threading.Thread(target=self.search_files, daemon=True).start() def stop_search(self): """停止搜索""" self.stop_requested = True self.status_var.set("正在停止搜索...") def search_files(self): """在文件中搜索内容(优化特殊文件处理)""" search_term = self.search_text.get().strip() if not search_term: self.status_var.set("请输入搜索内容") self.search_running = False return if not self.files: self.status_var.set("请先选择文件夹") self.search_running = False return # 重置结果和UI self.results = {} for item in self.tree.get_children(): self.tree.delete(item) total_files = len(self.files) processed_files = 0 found_signals = 0 # 使用线程池处理文件 with ThreadPoolExecutor(max_workers=self.max_workers) as executor: futures = {} for file_path in self.files: if self.stop_requested: break future = executor.submit(self.process_file, file_path, search_term) futures[future] = file_path # 处理完成的任务 for future in as_completed(futures): if self.stop_requested: break file_path = futures[future] try: found = future.result() found_signals += found processed_files += 1 # 更新进度 progress = int(processed_files / total_files * 100) self.progress["value"] = progress self.status_var.set(f"已处理 {processed_files}/{total_files} 个文件") self.root.update_idletasks() except Exception as e: self.status_var.set(f"处理文件 {os.path.basename(file_path)} 出错: {str(e)}") # 更新结果 if self.stop_requested: self.status_var.set(f"搜索已停止,已处理 {processed_files}/{total_files} 个文件") elif found_signals == 0: self.status_var.set(f"未找到包含 '{search_term}' 的信号") else: self.status_var.set(f"找到 {len(self.results)} 个匹配信号,共 {found_signals} 处匹配") self.update_text_view() self.progress["value"] = 0 self.search_running = False gc.collect() # 强制垃圾回收释放内存 def process_file(self, file_path, search_term): """处理单个文件(增强异常处理)""" found = 0 try: # 获取列名行和信号列 header_row, signal_col = self.find_header_row(file_path) # 如果自动查找失败,尝试手动模式 if header_row is None or signal_col is None: self.status_var.set(f"文件 {os.path.basename(file_path)} 未找到列名行,尝试手动查找...") header_row, signal_col = self.manual_find_header_row(file_path) if header_row is None or signal_col is None: self.status_var.set(f"文件 {os.path.basename(file_path)} 无法确定列名行,已跳过") return found # 根据文件类型处理 if file_path.lower().endswith((".xlsx", ".xlsm")): found = self.process_openpyxl_file(file_path, search_term, header_row, signal_col) elif file_path.lower().endswith(".xls"): found = self.process_xlrd_file(file_path, search_term, header_row, signal_col) except Exception as e: self.status_var.set(f"处理文件 {os.path.basename(file_path)} 出错: {str(e)}") return found def manual_find_header_row(self, file_path): """手动查找列名行(当自动查找失败时使用)""" try: # 尝试打开文件 if file_path.lower().endswith((".xlsx", ".xlsm")): wb = openpyxl.load_workbook(file_path, read_only=True, data_only=True) ws = wb.active # 扫描整个工作表(最多1000行) for row_idx in range(1, 1001): for col_idx in range(1, 101): try: cell = ws.cell(row=row_idx, column=col_idx) if cell.value and "データ" in str(cell.value): # 找到可能的列名行 return row_idx, col_idx except: continue wb.close() elif file_path.lower().endswith(".xls"): wb = xlrd.open_workbook(file_path) ws = wb.sheet_by_index(0) # 扫描整个工作表(最多1000行) for row_idx in range(0, 1000): for col_idx in range(0, 100): try: cell_value = ws.cell_value(row_idx, col_idx) if cell_value and "データ" in str(cell_value): # 找到可能的列名行 return row_idx, col_idx except: continue except: pass return None, None def get_file_cache_key(self, file_path, header_row, signal_col): """生成唯一的文件缓存键""" file_hash = self.get_file_hash(file_path) return f"{file_hash}_{header_row}_{signal_col}" def process_openpyxl_file(self, file_path, search_term, header_row, signal_col): found = 0 try: cache_key = self.get_file_cache_key(file_path, header_row, signal_col) if cache_key in self.file_cache: signal_data = self.file_cache[cache_key] else: wb = openpyxl.load_workbook(file_path, data_only=True, read_only=True) ws = wb.active min_row = header_row + 1 max_row = min(ws.max_row, min_row + 5000) # 只读取信号列和行号 signal_data = [] for row_idx in range(min_row, max_row + 1): cell = ws.cell(row=row_idx, column=signal_col) if cell.value: signal_data.append((row_idx, str(cell.value))) self.file_cache[cache_key] = signal_data wb.close() # 收集匹配的行号 match_rows = [] for row_idx, value in signal_data: if search_term.lower() in value.lower(): match_rows.append(row_idx) # 批量处理匹配行 if match_rows: wb = openpyxl.load_workbook(file_path, data_only=True, read_only=True) ws = wb.active for row_idx in match_rows: # 只提取必要的列:信号名和关键元数据 signal = ws.cell(row=row_idx, column=signal_col).value data_name = ws.cell(row=row_idx, column=signal_col + 1).value if signal_col + 1 <= 100 else "" data_type = ws.cell(row=row_idx, column=signal_col + 2).value if signal_col + 2 <= 100 else "" row_content = f"信号名: {signal}\n数据名: {data_name}\n数据类型: {data_type}" # 添加到结果集 if signal not in self.results: self.results[signal] = {} short_name = os.path.basename(file_path) self.results[signal][short_name] = row_content # 添加到表格 summary = row_content[:50] + "..." if len(row_content) > 50 else row_content self.tree.insert("", tk.END, values=(signal, short_name, summary)) found += 1 wb.close() except Exception as e: self.status_var.set(f"处理文件 {os.path.basename(file_path)} 出错: {str(e)}") return found def process_xlrd_file(self, file_path, search_term, header_row, signal_col): """高效处理xls文件(增强异常处理)""" found = 0 try: # 使用缓存 file_key = f"{file_path}_{header_row}_{signal_col}" if file_key in self.file_cache: ws = self.file_cache[file_key] else: wb = xlrd.open_workbook(file_path) ws = wb.sheet_by_index(0) self.file_cache[file_key] = ws # 优化搜索范围 min_row = header_row + 1 max_row = min(ws.nrows, min_row + 5000) # 限制搜索行数 # 批量读取信号列数据 signal_values = ws.col_values(signal_col, min_row, max_row) # 搜索匹配的信号 for idx, value in enumerate(signal_values): if self.stop_requested: break if not value: continue cell_str = str(value) if search_term.lower() in cell_str.lower(): signal = cell_str row_idx = min_row + idx # 提取整行内容 row_content = self.extract_xlrd_row_content(ws, row_idx, header_row) # 添加到结果集 if signal not in self.results: self.results[signal] = {} # 使用短文件名避免特殊字符问题 short_name = os.path.basename(file_path) self.results[signal][short_name] = row_content # 添加到表格(显示前50字符摘要) summary = row_content[:50] + "..." if len(row_content) > 50 else row_content self.tree.insert("", tk.END, values=(signal, short_name, summary)) found += 1 except Exception as e: self.status_var.set(f"处理文件 {os.path.basename(file_path)} 出错: {str(e)}") return found def extract_xlrd_row_content(self, ws, row_idx, header_row): """为xls文件高效提取行内容""" content = [] try: row_values = ws.row_values(row_idx) except: return "" # 扩展到100列 for col_idx in range(min(len(row_values), 100)): try: cell_value = row_values[col_idx] if cell_value is not None and str(cell_value).strip() != '': # 使用列名缓存 col_key = f"{header_row}-{col_idx}" if col_key in self.column_cache: col_name = self.column_cache[col_key] else: try: col_name = ws.cell_value(header_row, col_idx) if not col_name: col_name = f"列{col_idx+1}" except: col_name = f"列{col_idx+1}" self.column_cache[col_key] = col_name content.append(f"{col_name}: {str(cell_value).strip()}") except: continue return "\n".join(content) def update_text_view(self): """更新文本对比视图""" # 清除现有文本区域 for widget in self.compare_container.winfo_children(): widget.destroy() if not self.results: return # 获取第一个信号作为默认显示 first_signal = next(iter(self.results.keys())) self.display_signal_comparison(first_signal) def on_table_select(self, event): """表格选择事件处理""" selected = self.tree.selection() if not selected: return item = self.tree.item(selected[0]) signal = item["values"][0] self.display_signal_comparison(signal) def display_signal_comparison(self, signal): """显示指定信号的对比""" # 清除现有文本区域 for widget in self.compare_container.winfo_children(): widget.destroy() if signal not in self.results: return signal_data = self.results[signal] files = list(signal_data.keys()) contents = list(signal_data.values()) # 创建列框架 for i, (file, content) in enumerate(zip(files, contents)): col_frame = ttk.Frame(self.compare_container) col_frame.grid(row=0, column=i, sticky="nsew", padx=5, pady=5) self.compare_container.columnconfigure(i, weight=1) # 文件名标签 file_label = ttk.Label(col_frame, text=file, font=("Arial", 10, "bold")) file_label.pack(fill=tk.X, pady=(0, 5)) # 文本区域 text_area = scrolledtext.ScrolledText(col_frame, wrap=tk.WORD, width=30, height=15) text_area.insert(tk.INSERT, content) text_area.configure(state="disabled") text_area.pack(fill=tk.BOTH, expand=True) # 保存引用 self.text_panes[file] = text_area def highlight_differences(self): """高亮显示文本差异""" if not self.text_panes: return # 获取所有行内容 all_contents = [] for text_area in self.text_panes.values(): text_area.configure(state="normal") text = text_area.get("1.0", tk.END).strip() text_area.configure(state="disabled") all_contents.append(text) # 如果所有内容相同,则不需要高亮 if len(set(all_contents)) == 1: self.status_var.set("所有文件行内容完全一致") return # 使用第一个文件作为基准 base_text = all_contents[0] # 对比并高亮差异 for i, (file, text_area) in enumerate(self.text_panes.items()): if i == 0: # 基准文件不需要处理 continue text_area.configure(state="normal") text_area.tag_configure("diff", background=self.highlight_color) # 清除之前的高亮 text_area.tag_remove("diff", "1.0", tk.END) # 获取当前文本 compare_text = text_area.get("1.0", tk.END).strip() # 使用序列匹配器查找差异 s = SequenceMatcher(None, base_text, compare_text) # 高亮差异部分 for tag in s.get_opcodes(): opcode = tag[0] start = tag[3] end = tag[4] if opcode != "equal": # 添加高亮标签 text_area.tag_add("diff", f"1.0+{start}c", f"1.0+{end}c") text_area.configure(state="disabled") self.status_var.set("差异已高亮显示") def choose_color(self): """选择高亮颜色""" color = askcolor(title="选择高亮颜色", initialcolor=self.highlight_color) if color[1]: self.highlight_color = color[1] self.color_btn.configure(bg=self.highlight_color) def export_report(self): """导出差异报告""" if not self.results: messagebox.showwarning("警告", "没有可导出的结果") return try: # 创建报告数据结构 report_data = [] for signal, files_data in self.results.items(): for file, content in files_data.items(): report_data.append({ "信号": signal, "文件": file, "行内容": content }) # 换为DataFrame df = pd.DataFrame(report_data) # 保存到Excel save_path = filedialog.asksaveasfilename( defaultextension=".xlsx", filetypes=[("Excel文件", "*.xlsx")], title="保存差异报告" ) if save_path: df.to_excel(save_path, index=False) self.status_var.set(f"报告已保存到: {save_path}") except Exception as e: messagebox.showerror("错误", f"导出报告失败: {str(e)}") def clear_cache(self): """清除缓存""" try: for file in os.listdir(self.cache_dir): if file.endswith(".cache"): os.remove(os.path.join(self.cache_dir, file)) self.file_cache = {} self.column_cache = {} self.status_var.set("缓存已清除") except Exception as e: self.status_var.set(f"清除缓存失败: {str(e)}") def manual_column_select(self): """手动指定列名位置""" if not self.files: messagebox.showinfo("提示", "请先选择文件夹") return # 创建手动选择窗口 manual_window = tk.Toplevel(self.root) manual_window.title("手动指定列名位置") manual_window.geometry("400x300") # 文件选择 ttk.Label(manual_window, text="选择文件:").pack(pady=(10, 5)) file_var = tk.StringVar() file_combo = ttk.Combobox(manual_window, textvariable=file_var, values=[os.path.basename(f) for f in self.files]) file_combo.pack(fill=tk.X, padx=20, pady=5) file_combo.current(0) # 行号输入 ttk.Label(manual_window, text="列名行号:").pack(pady=(10, 5)) row_var = tk.StringVar(value="1") row_entry = ttk.Entry(manual_window, textvariable=row_var) row_entry.pack(fill=tk.X, padx=20, pady=5) # 列号输入 ttk.Label(manual_window, text="信号列号:").pack(pady=(10, 5)) col_var = tk.StringVar(value="1") col_entry = ttk.Entry(manual_window, textvariable=col_var) col_entry.pack(fill=tk.X, padx=20, pady=5) # 确认按钮 def confirm_selection(): try: file_idx = file_combo.current() file_path = self.files[file_idx] header_row = int(row_var.get()) signal_col = int(col_var.get()) # 保存到缓存 header_info = {"header_row": header_row, "signal_col": signal_col} self.save_header_cache(file_path, header_info) messagebox.showinfo("成功", f"已为 {os.path.basename(file_path)} 设置列名位置:行{header_row} 列{signal_col}") manual_window.destroy() except Exception as e: messagebox.showerror("错误", f"无效输入: {str(e)}") ttk.Button(manual_window, text="确认", command=confirm_selection).pack(pady=20) if __name__ == "__main__": root = tk.Tk() app = EnhancedSignalComparator(root) root.mainloop() 1、现在更改之后,读取的速度更慢了,在大文件的搜索中,一直在已处理中,速度太慢了,甚至没有改之前快,请搜索网络上类似的处理,优化处理流程
最新发布
07-24
评论
添加红包

请填写红包祝福语或标题

红包个数最小为10个

红包金额最低5元

当前余额3.43前往充值 >
需支付:10.00
成就一亿技术人!
领取后你会自动成为博主和红包主的粉丝 规则
hope_wisdom
发出的红包
实付
使用余额支付
点击重新获取
扫码支付
钱包余额 0

抵扣说明:

1.余额是钱包充值的虚拟货币,按照1:1的比例进行支付金额的抵扣。
2.余额无法直接购买下载,可以购买VIP、付费专栏及课程。

余额充值