计161_Problem X: 转义字符的使用

最新推荐文章于 2020-08-13 12:47:58 发布
最新推荐文章于 2020-08-13 12:47:58 发布
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CC 4.0 BY-SA版权
版权声明：本文为博主原创文章，遵循 CC 4.0 BY-SA 版权协议，转载请附上原文出处链接和本声明。
本文链接：https://blog.youkuaiyun.com/bufengrendyf/article/details/65647984
本文提供了一个简单的C/C++编程示例，演示如何在控制台输出特定的字符串。通过这个例子，读者可以了解字符串转义序列的用法。 
/*Description


输出字符串  I like "C\C++" programing

Input


无

Output


I like "C\C++" programing

Sample Output
I like "C\C++" programing

HINT



单词之间有一个空格
*/
#include <stdio.h>
#include <stdlib.h>

int main()
{
    printf("I like \"C\\C++\"programing\n");
    return 0;
}
运行结果：

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codejam_practices_problem:误码练习问题
03-28
实体引用使用名称来表示特殊字符，如`代表小于号，`>`代表大于号；而数字字符引用则使用Unicode数值，如`代表小于号，`>`代表大于号。这种编码方式可以确保浏览器正确解析文本，防止代码和内容混淆。 在解决"误码...
转义字符的使用
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在c#编程过程中一般都会用到转义字符 \,下面代码举例说明： 比如：string sqlstr="select * from table where name=\"\" "; 其实在数据库执行的时候就是select * from table where name=""; 斜杠后面的字符为转义后的字符； ...
Problem C: 转义字符的使用
菜瓜的博客
03-11 624
Problem C: 转义字符的使用Time Limit: 1 Sec  Memory Limit: 128 MBDescription输出字符串  I like "C\C++" programingInput无OutputI like "C\C++" programingSample OutputI like "C\C++" programingHINT单词之间有一个空格参考答案：#includ...
OJ--转义字符的使用
姜甜甜的专栏
12-10 1541
/* *Copyright (c) 2014,烟台大学计算机学院 *ALL right reserved *文件名： A+B Problem *作者；姜甜甜 *完成日期：2014年12月10日 *版本号v1.0 *问题描述：输出字符串 I like "C\C++" programing *输入描述：无 *程序输出：I like "C\C++" programing */ #
cookies: !!python/object:requests.cookies.RequestsCookieJar _cookies: 10.121.177.71: /: QSESSIONID: !!python/object:http.cookiejar.Cookie _rest: HttpOnly: null comment: null comment_url: null discard: true domain: 10.121.177.71 domain_initial_dot: false domain_specified: false expires: null name: QSESSIONID path: / path_specified: true port: null port_specified: false rfc2109: false secure: true value: e1ef0b8a9a0970e0a6wIzHzWbcNQ7VkS version: 0 _now: 1755052836 _policy: !!python/object:http.cookiejar.DefaultCookiePolicy _allowed_domains: null _blocked_domains: !!python/tuple [] _now: 1755052836 hide_cookie2: false netscape: true rfc2109_as_netscape: null rfc2965: false secure_protocols: !!python/tuple - https - wss strict_domain: false strict_ns_domain: 0 strict_ns_set_initial_dollar: false strict_ns_set_path: false strict_ns_unverifiable: false strict_rfc2965_unverifiable: true 符合yaml语法格式吗
08-14
字符串值中的特殊字符未转义或未加引号： ```yaml cookies: SESSION_ID: 123:456 # 这里冒号在值中，需要加引号，否则会被解析为键值对 ``` 4. 使用不正确的布尔值表示： ```yaml cookies: - name: ...
package service import ( "fmt" "log" "os" "regexp" "sort" "github.com/tidwall/gjson" "github.com/tidwall/sjson" ) // JSONProcessor 处理 JSON 数据的工具类 type JSONProcessor struct { jsonStr string } // NewJSONProcessor 创建新的 JSON 处理器 func NewJSONProcessor(jsonStr string) *JSONProcessor { return &JSONProcessor{jsonStr: jsonStr} } // RemoveInvalidImage 删除不合规图片及其关联数据 func (jp *JSONProcessor) RemoveInvalidImage(invalidURL string) error { // basePath := "schema.model" // 1. 检查并删除 spec_detail 中的规格值 if err := jp.removeSpecValuesByImage(invalidURL); err != nil { return err } // 2. 删除其他图片字段中的无效图片 fields := []string{"white_background_pic", "main_image_three_to_four", "pic"} for _, field := range fields { if err := jp.removeImageFromField(field, invalidURL); err != nil { return fmt.Errorf("failed to remove from %s: %v", field, err) } } // 3. 从描述中删除图片 if err := jp.removeImageFromDescription(invalidURL); err != nil { return fmt.Errorf("failed to remove from description: %v", err) } return nil } // removeSpecValuesByImage 删除包含指定图片URL的规格值 func (jp *JSONProcessor) removeSpecValuesByImage(invalidURL string) error { basePath := "schema.model" specDetailPath := fmt.Sprintf("%s.spec_detail.value", basePath) result := gjson.Get(jp.jsonStr, specDetailPath) if !result.Exists() { return nil // 没有规格数据，直接返回 } // 收集需要删除的规格值ID var specValueIDs []string result.ForEach(func(_, group gjson.Result) bool { group.Get("spec_values").ForEach(func(_, spec gjson.Result) bool { if imgURL := spec.Get("img_url").String(); imgURL == invalidURL { if id := spec.Get("id").String(); id != "" { specValueIDs = append(specValueIDs, id) } } return true }) return true }) // 删除所有关联的规格值 for _, id := range specValueIDs { if err := jp.RemoveSpecValueByID(id); err != nil { return fmt.Errorf("failed to remove spec value %s: %v", id, err) } } return nil } // removeImageFromField 从指定图片字段中删除无效图片 func (jp *JSONProcessor) removeImageFromField(fieldPath, invalidURL string) error { fullPath := fmt.Sprintf("schema.model.%s.value", fieldPath) result := gjson.Get(jp.jsonStr, fullPath) if !result.Exists() { return nil // 字段不存在，直接返回 } // 收集需要删除的索引 var indicesToDelete []int result.ForEach(func(index gjson.Result, item gjson.Result) bool { if url := item.Get("url").String(); url == invalidURL { indicesToDelete = append(indicesToDelete, int(index.Int())) } return true }) // 从后往前删除（避免索引变化） sort.Sort(sort.Reverse(sort.IntSlice(indicesToDelete))) for _, idx := range indicesToDelete { path := fmt.Sprintf("%s.%d", fullPath, idx) var err error jp.jsonStr, err = sjson.Delete(jp.jsonStr, path) if err != nil { return err } } return nil } // removeImageFromDescription 从描述中删除无效图片 func (jp *JSONProcessor) removeImageFromDescription(invalidURL string) error { descPath := "schema.model.description.value" result := gjson.Get(jp.jsonStr, descPath) if !result.Exists() { return nil // 描述不存在，直接返回 } html := result.String() // 正则表达式匹配包含指定URL的img标签 re := regexp.MustCompile(`<img[^>]+src="` + regexp.QuoteMeta(invalidURL) + `"[^>]*>`) newHTML := re.ReplaceAllString(html, "") // 更新描述 _, err := sjson.Set(jp.jsonStr, descPath, newHTML) return err } // ExtractAllPics 提取所有图片 URL（包括描述中的图片） func (jp *JSONProcessor) ExtractAllPics() []string { // 基础路径 basePath := "schema.model" // 存储所有图片的集合（使用 map 去重） uniquePics := make(map[string]bool) // 1. 处理指定字段的图片 fields := []string{"spec_detail", "white_background_pic", "main_image_three_to_four", "pic"} for _, field := range fields { path := fmt.Sprintf("%s.%s.value", basePath, field) result := gjson.Get(jp.jsonStr, path) if result.Exists() { result.ForEach(func(_, item gjson.Result) bool { // 处理 spec_detail 的特殊结构 if field == "spec_detail" { item.Get("spec_values").ForEach(func(_, spec gjson.Result) bool { if img := spec.Get("img_url"); img.Exists() { uniquePics[img.String()] = true } return true }) } else if url := item.Get("url"); url.Exists() { // 处理其他标准字段 uniquePics[url.String()] = true } return true }) } } // 2. 处理 description 中的图片 descPath := fmt.Sprintf("%s.description.value", basePath) descResult := gjson.Get(jp.jsonStr, descPath) if descResult.Exists() { html := descResult.String() re := regexp.MustCompile(`<img[^>]+src="([^">]+)"`) matches := re.FindAllStringSubmatch(html, -1) for _, match := range matches { if len(match) > 1 && !uniquePics[match[1]] { uniquePics[match[1]] = true } } } // 转换为切片返回 allPics := make([]string, 0, len(uniquePics)) for pic := range uniquePics { allPics = append(allPics, pic) } return allPics } // RemoveSpecValueByID 根据 spec_value ID 删除规格值及其关联的 SKU func (jp *JSONProcessor) RemoveSpecValueByID(specValueID string) error { basePath := "schema.model" // 1. 删除 spec_detail 中的 spec_value specDetailPath := fmt.Sprintf("%s.spec_detail.value", basePath) specDetailResult := gjson.Get(jp.jsonStr, specDetailPath) if !specDetailResult.Exists() { return fmt.Errorf("spec_detail.value does not exist") } specGroups := specDetailResult.Array() // 收集需要删除的索引（组索引和值索引） type deletionPoint struct { groupIndex int valueIndex int } var deletions []deletionPoint // 遍历所有规格组 for groupIdx, group := range specGroups { specValues := group.Get("spec_values").Array() // 遍历组内的规格值 for valueIdx, value := range specValues { if id := value.Get("id").String(); id == specValueID { deletions = append(deletions, deletionPoint{groupIdx, valueIdx}) } } } // 从后往前删除（避免索引变化） sort.Slice(deletions, func(i, j int) bool { if deletions[i].groupIndex == deletions[j].groupIndex { return deletions[i].valueIndex > deletions[j].valueIndex } return deletions[i].groupIndex > deletions[j].groupIndex }) for _, del := range deletions { path := fmt.Sprintf("%s.%d.spec_values.%d", specDetailPath, del.groupIndex, del.valueIndex) var err error jp.jsonStr, err = sjson.Delete(jp.jsonStr, path) if err != nil { return err } } // 2. 删除关联的 SKU skuDetailPath := fmt.Sprintf("%s.sku_detail.value", basePath) skuDetailResult := gjson.Get(jp.jsonStr, skuDetailPath) if !skuDetailResult.Exists() { // 没有 SKU 数据，直接返回 return nil } skus := skuDetailResult.Array() var skuIndicesToDelete []int // 收集需要删除的 SKU 索引 for idx, sku := range skus { specDetailIDs := sku.Get("spec_detail_ids").Array() for _, id := range specDetailIDs { if id.String() == specValueID { skuIndicesToDelete = append(skuIndicesToDelete, idx) break // 找到匹配即跳出 } } } // 从后往前删除 SKU（避免索引变化） sort.Sort(sort.Reverse(sort.IntSlice(skuIndicesToDelete))) for _, idx := range skuIndicesToDelete { path := fmt.Sprintf("%s.%d", skuDetailPath, idx) var err error jp.jsonStr, err = sjson.Delete(jp.jsonStr, path) if err != nil { return err } } return nil } // UpdateSkuPrice 更新 SKU 的价格 func (jp *JSONProcessor) UpdateSkuPrice(skuID, newPrice string) error { path := "schema.model.sku_detail.value" result := gjson.Get(jp.jsonStr, path) if !result.Exists() { return fmt.Errorf("sku_detail.value does not exist") } skuArray := result.Array() for idx, sku := range skuArray { if id := sku.Get("id").String(); id == skuID { fullPath := fmt.Sprintf("%s.%d.price", path, idx) var err error jp.jsonStr, err = sjson.Set(jp.jsonStr, fullPath, newPrice) return err } } return fmt.Errorf("SKU with ID %s not found", skuID) } // UpdateSkuStock 更新 SKU 的库存 func (jp *JSONProcessor) UpdateSkuStock(skuID string, newStock int) error { path := "schema.model.sku_detail.value" result := gjson.Get(jp.jsonStr, path) if !result.Exists() { return fmt.Errorf("sku_detail.value does not exist") } skuArray := result.Array() for idx, sku := range skuArray { if id := sku.Get("id").String(); id == skuID { // 更新 stock_info.stock_num stockPath := fmt.Sprintf("%s.%d.stock_info.stock_num", path, idx) var err error jp.jsonStr, err = sjson.Set(jp.jsonStr, stockPath, newStock) if err != nil { return err } // 更新 self_sell_stock selfStockPath := fmt.Sprintf("%s.%d.self_sell_stock", path, idx) jp.jsonStr, err = sjson.Set(jp.jsonStr, selfStockPath, newStock) return err } } return fmt.Errorf("SKU with ID %s not found", skuID) } // GetField 获取指定字段的值 func (jp *JSONProcessor) GetField(fieldPath string) (gjson.Result, bool) { fullPath := fmt.Sprintf("schema.model.%s", fieldPath) result := gjson.Get(jp.jsonStr, fullPath) return result, result.Exists() } // UpdateField 更新指定字段的值 func (jp *JSONProcessor) UpdateField(fieldPath string, newValue interface{}) error { fullPath := fmt.Sprintf("schema.model.%s", fieldPath) newJSON, err := sjson.Set(jp.jsonStr, fullPath, newValue) if err != nil { return err } jp.jsonStr = newJSON return nil } // DeleteField 删除指定字段 func (jp *JSONProcessor) DeleteField(fieldPath string) error { fullPath := fmt.Sprintf("schema.model.%s", fieldPath) newJSON, err := sjson.Delete(jp.jsonStr, fullPath) if err != nil { return err } jp.jsonStr = newJSON return nil } // AddArrayItem 向数组字段添加新元素 func (jp *JSONProcessor) AddArrayItem(fieldPath string, newItem interface{}) error { // 检查数组字段是否存在 basePath := fmt.Sprintf("schema.model.%s.value", fieldPath) result := gjson.Get(jp.jsonStr, basePath) // 如果数组不存在，先创建空数组 if !result.Exists() { var err error jp.jsonStr, err = sjson.Set(jp.jsonStr, basePath, []interface{}{}) if err != nil { return fmt.Errorf("failed to create array field: %v", err) } } // 添加新元素到数组末尾 fullPath := fmt.Sprintf("%s.-1", basePath) newJSON, err := sjson.Set(jp.jsonStr, fullPath, newItem) if err != nil { return fmt.Errorf("failed to add array item: %v", err) } jp.jsonStr = newJSON return nil } // RemoveArrayItem 从数组中删除指定索引的元素 func (jp *JSONProcessor) RemoveArrayItem(fieldPath string, index int) error { basePath := fmt.Sprintf("schema.model.%s.value", fieldPath) result := gjson.Get(jp.jsonStr, basePath) if !result.Exists() { return fmt.Errorf("array field does not exist") } // 检查索引是否有效 array := result.Array() if index < 0 || index >= len(array) { return fmt.Errorf("index %d out of range [0, %d]", index, len(array)-1) } fullPath := fmt.Sprintf("%s.%d", basePath, index) newJSON, err := sjson.Delete(jp.jsonStr, fullPath) if err != nil { return err } jp.jsonStr = newJSON return nil } // GetJSON 获取当前处理后的 JSON func (jp *JSONProcessor) GetJSON() string { return jp.jsonStr } // TestFunc 测试函数 func TestFunc() { content, err := os.ReadFile("asyncCheckPost.json") if err != nil { log.Printf("读取过滤文件失败: %v", err) return } processor := NewJSONProcessor(string(content)) // 提取所有图片 allPics := processor.ExtractAllPics() fmt.Printf("提取到 %d 张图片\n", len(allPics)) // 假设我们检测到第二张图片不合规 if len(allPics) > 1 { invalidURL := "https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_a469f301b9c195b6b833240f9adc1ffc_sx_36996_www790-314" fmt.Printf("检测到不合规图片: %s\n", invalidURL) // 删除不合规图片及其关联数据 if err := processor.RemoveInvalidImage(invalidURL); err != nil { fmt.Println("删除不合规图片失败:", err) } else { fmt.Println("成功删除不合规图片及其关联数据") // 验证删除后图片数量 newPics := processor.ExtractAllPics() fmt.Printf("删除后剩余图片: %d 张\n", len(newPics)) // 检查是否不再包含不合规图片 for _, url := range newPics { if url == invalidURL { fmt.Println("错误: 不合规图片仍然存在!") break } } } } // 1. 删除规格值及其关联的 SKU specValueID := "1839581026529404" // 小号钢架尺30米的 ID if err := processor.RemoveSpecValueByID(specValueID); err != nil { fmt.Println("删除规格值失败:", err) } else { fmt.Println("成功删除规格值及其关联SKU") } // 2. 更新 SKU 价格和库存 skuID := "3527608283404802" // 第一个 SKU 的 ID newPrice := "99.99" newStock := 3000 if err := processor.UpdateSkuPrice(skuID, newPrice); err != nil { fmt.Println("更新价格失败:", err) } else { fmt.Println("成功更新SKU价格") } if err := processor.UpdateSkuStock(skuID, newStock); err != nil { fmt.Println("更新库存失败:", err) } else { fmt.Println("成功更新SKU库存") } // 3. 测试数组操作 // 向不存在的数组添加元素 if err := processor.AddArrayItem("new_field", map[string]string{"test": "value"}); err != nil { fmt.Println("添加数组项失败:", err) } else { fmt.Println("成功添加数组项到新字段") } // 尝试删除不存在的数组项 if err := processor.RemoveArrayItem("non_existent_field", 0); err != nil { fmt.Println("删除数组项失败(预期):", err) } else { fmt.Println("意外成功删除不存在的数组项") } // 尝试越界删除 if err := processor.RemoveArrayItem("pic", 100); err != nil { fmt.Println("删除数组项失败(预期):", err) } else { fmt.Println("意外成功删除越界数组项") } // 获取最终 JSON // finalJSON := processor.GetJSON() // fmt.Println(finalJSON) } 这段代码是修改后的代码，要处理的json数据为：{"schema":{"model":{"sku_detail":{"value":[{"brand_country":null,"cargo_related_cmpu":null,"cb_wares_info":null,"customs_report_info":null,"id":"3527608283404802","price":"70.8","reserved_stock_info":{"channel_stock_detail":[],"channel_stock_num":null,"promotion_stock_num":null},"self_sell_stock":5000,"shop_warehouse":null,"sku_delivery_delay_day":"","sku_id":"3527608283404802","sku_status":true,"source_country":null,"source_product":null,"spec_detail_ids":["1839581026529356"],"stock_info":{"stock_inc_num":0,"stock_num":5000,"use_cargo_stock":false},"supplier_id":""},{"brand_country":null,"cargo_related_cmpu":null,"cb_wares_info":null,"customs_report_info":null,"id":"3527608283405058","price":"97.8","reserved_stock_info":{"channel_stock_detail":[],"channel_stock_num":null,"promotion_stock_num":null},"self_sell_stock":5000,"shop_warehouse":null,"sku_delivery_delay_day":"","sku_id":"3527608283405058","sku_status":true,"source_country":null,"source_product":null,"spec_detail_ids":["1839581026529372"],"stock_info":{"stock_inc_num":0,"stock_num":5000,"use_cargo_stock":false},"supplier_id":""},{"brand_country":null,"cargo_related_cmpu":null,"cb_wares_info":null,"customs_report_info":null,"id":"3527608283405314","price":"127.8","reserved_stock_info":{"channel_stock_detail":[],"channel_stock_num":null,"promotion_stock_num":null},"self_sell_stock":5000,"shop_warehouse":null,"sku_delivery_delay_day":"","sku_id":"3527608283405314","sku_status":true,"source_country":null,"source_product":null,"spec_detail_ids":["1839581026529388"],"stock_info":{"stock_inc_num":0,"stock_num":5000,"use_cargo_stock":false},"supplier_id":""},{"brand_country":null,"cargo_related_cmpu":null,"cb_wares_info":null,"customs_report_info":null,"id":"3527608283405570","price":"41.7","reserved_stock_info":{"channel_stock_detail":[],"channel_stock_num":null,"promotion_stock_num":null},"self_sell_stock":5000,"shop_warehouse":null,"sku_delivery_delay_day":"","sku_id":"3527608283405570","sku_status":true,"source_country":null,"source_product":null,"spec_detail_ids":["1839581026529404"],"stock_info":{"stock_inc_num":0,"stock_num":5000,"use_cargo_stock":false},"supplier_id":""},{"brand_country":null,"cargo_related_cmpu":null,"cb_wares_info":null,"customs_report_info":null,"id":"3527608283405826","price":"53.7","reserved_stock_info":{"channel_stock_detail":[],"channel_stock_num":null,"promotion_stock_num":null},"self_sell_stock":5000,"shop_warehouse":null,"sku_delivery_delay_day":"","sku_id":"3527608283405826","sku_status":true,"source_country":null,"source_product":null,"spec_detail_ids":["1839581026596876"],"stock_info":{"stock_inc_num":0,"stock_num":5000,"use_cargo_stock":false},"supplier_id":""}]},"spec_detail":{"value":[{"id":"1839581026528380","name":"颜色","spec_values":[{"id":"1839581026529356","img_url":"https://p9-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_5df95571bacacf922e8c37a3de756431_sx_158437_www800-800","name":"大号钢架尺30米"},{"id":"1839581026529372","img_url":"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_5df95571bacacf922e8c37a3de756431_sx_158437_www800-800","name":"大号钢架尺50米"},{"id":"1839581026529388","img_url":"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_5df95571bacacf922e8c37a3de756431_sx_158437_www800-800","name":"大号钢架尺100米"},{"id":"1839581026529404","img_url":"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_fbe9fe8421903b55ba4d145a2643ed81_sx_126893_www800-800","name":"超小号钢架尺50米"},{"id":"1839581026596876","img_url":"https://p9-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_fbe9fe8421903b55ba4d145a2643ed81_sx_126893_www800-800","name":"小号钢架尺50米"}]},{"is_default":true,"id":"994777959641832039","name":"默认","spec_values":[{"id":"992068055803834573","name":"默认"}]}]},"white_background_pic":{"value":[{"url":"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_c8ffb8f0d8743a222b460447af724639_sx_101226_www800-800"}]},"after_sale":{"value":{"quality_problem_return":{"option_id":null,"selected":true},"supply_day_return_selector":{"option_id":"7-5","selected":true}}},"area_stock_switcher":{"value":false},"category_properties":{"value":{"1687":[{"diy_type":0,"measure_info":null,"tags":null,"value_id":"596120136","value_name":"无品牌"}]}},"delivery_delay_day":{"value":"2"},"description":{"value":"<p><img src=\"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_9af34d3b91dfcda1f1aa02cbd595fed0_sx_402315_www790-1125\" style=\"max-width:100%;\"/><img src=\"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_54ab3b361d68c7bb91d1fdb93e2f9d48_sx_84695_www790-645\" style=\"max-width:100%;\"/><img src=\"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_66e5bc7a2ae789f9880a5329d3236380_sx_472879_www790-1170\" style=\"max-width:100%;\"/><img src=\"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_e0f605bb1021b0cc92c805fdd64a537e_sx_357278_www790-1054\" style=\"max-width:100%;\"/><img src=\"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_afd37094560a88654f3abe5b31dab275_sx_309478_www790-1126\" style=\"max-width:100%;\"/><img src=\"https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_29350443b0952fdebb41a90bcb8d3e23_sx_257960_www790-949\" style=\"max-width:100%;\"/><img 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经过测试，removeImageFromDescription并没有删除https://p3-aio.ecombdimg.com/obj/ecom-shop-material/jpeg_m_a469f301b9c195b6b833240f9adc1ffc_sx_36996_www790-314 这张图片。请帮我修复这个BUG
08-08
另一种可能是，正则表达式在构建时，由于invalidURL包含特殊字符，虽然我们使用了`regexp.QuoteMeta`，但可能转义后和原始字符串不完全匹配？让我们打印一下构建的正则表达式和实际的图片URL。 但是，根据提供的...
class SCLRuleProcessor: """SCL规则处理器，包含详细的颜色映射逻辑""" def __init__(self, color_detector=None): self.color_detector = color_detector or EnhancedColorDetector(tolerance=30) # 创建专用日志记录器 self.logger = logging.getLogger('SCLProcessor.RuleProcessor') if not self.logger.handlers: # 如果没有处理器，添加控制台处理器 console_handler = logging.StreamHandler() console_handler.setLevel(logging.INFO) formatter = logging.Formatter( '%(asctime)s - %(name)s - %(levelname)s - %(message)s', datefmt='%Y-%m-%d %H:%M:%S' ) console_handler.setFormatter(formatter) self.logger.addHandler(console_handler) self.logger.setLevel(logging.INFO) # 固定列位置 self.COLUMN_MAPPING = { "差分種別": 12, # L列 "变更内容": 13, # M列 "判断列": 14, # N列 "判断理由": 15, # O列 "变更背景": 16, # P列 "备注": 17 # Q列 } # 新增规则的关键词 - 添加更多变体 self.keywords = [ "波形図の尾の延長、非機能変更と判定されました。", "波形図の尾の延長", "非機能変更", "選択肢的补充说明，不属于功能变更。", "补充说明", "不属于功能变更", "空白行が追加され、非機能変更と判定された", "空白行追加", "空行が削除され、非機能変更と判定された", "空行削除", "无效更改，判定为无功能变更。", "无效更改", "書式変更で機能変更ではないと判断されました。", "書式変更", "仅修改了背景色，不影响软件设计，判定为无功能变更。", "仅修改背景色", "背景色修改", "非功能变更", "无功能变更", "書式調整", "非機能修正" ] # 创建关键词正则表达式模式 self.keyword_pattern = self._create_keyword_pattern() # 规则映射到目标列 self.RULE_MAPPING = { # 规则1-18: 备注值统计 "diff_no_fill": 16, # P列 "diff_fill": 23, # W列 "diff_add_no_fill": 27, # AA列 "diff_add_fill": 30, # AD列 "diff_change_no_fill": 34, # AH列 "diff_change_fill": 37, # AK列 "diff_delete_no_fill": 42, # AP列 "diff_delete_fill": 45, # AS列 "valid_yes_no_fill": 50, # AX列 "valid_yes_fill": 53, # BA列 "valid_no_no_fill": 57, # BE列 "valid_no_fill": 60, # BH列 "valid_yes_reason_no_fill": 62, # BL列 "valid_yes_reason_fill": 65, # BO列 "valid_no_reason_no_fill": 71, # BS列 "valid_no_reason_fill": 74, # BV列 "background_no_fill": 78, # BZ列 "background_fill": 85, # CG列, # 规则19-59: 计数统计 "rule19": 14, # N列 "rule20": 15, # O列 "rule21": 17, # Q列 "rule22": 18, # R列 "rule23": 19, # S列 "rule24": 20, # T列 "rule25": 21, # U列 "rule26": 22, # V列 "rule27": 25, # Y列 "rule28": 26, # Z列 "rule29": 28, # AB列 "rule30": 29, # AC列 "rule31": 32, # AF列 "rule32": 33, # AG列 "rule33": 35, # AI列 "rule34": 36, # AJ列 "rule35": 47, # AU列 "rule36": 48, # AV列 "rule37": 49, # AW列 "rule38": 51, # AY列 "rule39": 52, # AZ列 "rule40": 55, # BC列 "rule41": 56, # BD列 "rule42": 58, # BF列 "rule43": 59, # BG列 "rule44": 62, # BJ列 "rule45": 63, # BK列 "rule46": 65, # BM列 "rule47": 66, # BN列 "rule48": 69, # BQ列 "rule49": 70, # BR列 "rule50": 72, # BT列 "rule51": 73, # BU列 "rule52": 76, # BX列 "rule53": 77, # BY列 "rule54": 79, # CA列 "rule55": 80, # CB列 "rule56": 81, # CC列 "rule57": 82, # CD列 "rule58": 83, # CE列 "rule59": 84, # CF列 } # 规则统计字典 self.rule_stats = {rule: defaultdict(int) for rule in self.RULE_MAPPING.keys()} self.HEADER_ROW = 3 # 表头固定在第三行 self.DATA_START_ROW = 4 # 数据从第四行开始 def reset_rule_stats(self): """重置规则统计""" for rule in self.rule_stats: self.rule_stats[rule].clear() def get_cell_color_status(self, cell, column_name=None): """ 获取单元格的颜色状态（增强版） 返回: (颜色名称, 颜色HEX值, 是否无填充) column_name: 列名，用于确定是否进行特殊颜色判断 """ try: # 检查是否无填充 if self.color_detector.is_no_fill(cell): return "无填充", None, True # 获取单元格颜色 hex_color = self.color_detector.get_cell_color(cell) if not hex_color: return "未知", None, False # 只有M列和P列需要特殊颜色判断 if column_name in ["变更内容", "变更背景"]: # 检查是否为特定颜色 if self.color_detector.is_specific_color(cell, self.COLOR_CRIMSON): return "猩红", self.COLOR_CRIMSON, False if self.color_detector.is_specific_color(cell, self.COLOR_STEEL_BLUE): return "钢蓝", self.COLOR_STEEL_BLUE, False if self.color_detector.is_specific_color(cell, self.COLOR_CHOCOLATE): return "巧克力黄", self.COLOR_CHOCOLATE, False # 匹配最接近的已知颜色 closest_name = self.color_detector.match_color_name(hex_color) return closest_name, hex_color, False except Exception as e: self.logger.error(f"获取单元格颜色状态失败: {str(e)}") return "错误", None, False def _create_keyword_pattern(self): """创建关键词匹配的正则表达式模式""" # 转义特殊字符并创建模式 escaped_keywords = [re.escape(kw) for kw in self.keywords] # 创建不区分大小写的模式 pattern_str = "|".join(escaped_keywords) return re.compile(pattern_str, re.IGNORECASE) def contains_keyword(self, text): """ 使用正则表达式检查文本是否包含任意关键词（更健壮的匹配） 返回: 匹配结果和匹配到的关键词列表 """ if not text: return False, [] text = str(text).strip() matches = self.keyword_pattern.findall(text) return bool(matches), matches def split_note_values(self, note_value): """拆分备注值，支持多种分隔符""" if not note_value: return [] # 支持的分隔符：中文顿号、全角逗号、半角逗号、分号、空格 separators = ['、', '，', ',', ';', '；', ' '] # 替换所有分隔符为统一的分隔符 normalized = str(note_value) for sep in separators: normalized = normalized.replace(sep, '|') # 分割并过滤空值 values = [v.strip() for v in normalized.split('|') if v.strip()] # 过滤掉值为“-”的项 values = [v for v in values if v != "-"] return values def format_note_stats(self, data_dict): """格式化备注统计结果，确保每个值一行""" try: # 尝试按数值排序 sorted_items = sorted( data_dict.items(), key=lambda x: int(x[0]) if x[0].isdigit() else x[0] ) except Exception: # 如果无法转换为数字，则按字符串排序 sorted_items = sorted(data_dict.items()) # 格式化为每行一个值 return "\n".join([f"{value},{count}" for value, count in sorted_items]) def log_rule_stats(self, file_path): """记录规则统计信息到日志""" self.logger.info(f"文件 {os.path.basename(file_path)} 规则统计结果:") # 创建列号到列字母的映射 column_letter_map = self.create_column_letter_map() for rule_name in self.RULE_MAPPING.keys(): # 获取目标列号 target_col = self.RULE_MAPPING[rule_name] # 获取列字母表示 col_letter = column_letter_map.get(target_col, f"列{target_col}") # 获取统计结果 if rule_name in self.rule_stats and self.rule_stats[rule_name]: # 格式化统计结果 if rule_name.startswith("rule") and rule_name[4:].isdigit(): # 计数型规则 count = self.rule_stats[rule_name]["count"] self.logger.info(f"规则 {rule_name} ({col_letter}): 总计 {count} 行") else: # 值统计型规则 stats_str = "; ".join( [f"{value},{count}" for value, count in self.rule_stats[rule_name].items()] ) self.logger.info(f"规则 {rule_name} ({col_letter}): {stats_str}") else: self.logger.info(f"规则 {rule_name} ({col_letter}): 无数据") def create_column_letter_map(self): """创建列号到列字母的映射""" column_letter_map = {} # 生成A-Z列 for i in range(1, 27): column_letter_map[i] = chr(64 + i) # 生成AA-AZ列 for i in range(1, 27): column_letter_map[26 + i] = f"A{chr(64 + i)}" # 生成BA-BZ列 for i in range(1, 27): column_letter_map[52 + i] = f"B{chr(64 + i)}" # 生成CA-CZ列 for i in range(1, 27): column_letter_map[78 + i] = f"C{chr(64 + i)}" # 添加已知的特殊列 column_letter_map.update({ 16: "P", 23: "W", 27: "AA", 30: "AD", 34: "AH", 37: "AK", 42: "AP", 45: "AS", 50: "AX", 53: "BA", 57: "BE", 60: "BH", 62: "BL", 65: "BO", 71: "BS", 74: "BV", 78: "BZ", 85: "CG" }) return column_letter_map def process_file(self, file_path): """ 处理单个SCL文件并返回所有统计结果 返回: (results, color_report) - results: 规则统计结果 - color_report: 颜色分析报告 """ # 重置规则统计 self.reset_rule_stats() results = {} missing_data = [] # 存储缺失数据信息 # 重置规则统计 self.reset_rule_stats() try: self.logger.info(f"开始处理SCL文件: {file_path}") # 加载SCL文件 scl_wb = openpyxl.load_workbook(file_path) scl_sheet = scl_wb.active self.logger.info(f"工作表加载成功: {scl_sheet.title}, 总行数: {scl_sheet.max_row}") # 检查是否有足够的数据行 if scl_sheet.max_row < self.DATA_START_ROW: self.logger.info("文件没有数据行，跳过处理") return results, "", missing_data # 初始化统计结果 stats = { # 规则1-18: 备注值统计 "diff_no_fill": defaultdict(int), # 规则1: 変更内容无颜色填充 "diff_fill": defaultdict(int), # 规则2: 変更内容有颜色填充 "diff_add_no_fill": defaultdict(int), # 规则3: 差分种别="追加"且无颜色填充 "diff_add_fill": defaultdict(int), # 规则4: 差分种别="追加"且有颜色填充 "diff_change_no_fill": defaultdict(int), # 规则5: 差分种别="変更"且无颜色填充 "diff_change_fill": defaultdict(int), # 规则6: 差分种别="変更"且有颜色填充 "diff_delete_no_fill": defaultdict(int), # 规则7: 差分种别="削除"且无颜色填充 "diff_delete_fill": defaultdict(int), # 规则8: 差分种别="削除"且有颜色填充 "valid_yes_no_fill": defaultdict(int), # 规则9: 判断="有意"且无颜色填充 "valid_yes_fill": defaultdict(int), # 规则10: 判断="有意"且有颜色填充 "valid_no_no_fill": defaultdict(int), # 规则11: 判断="無効"且无颜色填充 "valid_no_fill": defaultdict(int), # 规则12: 判断="無効"且有颜色填充 "valid_yes_reason_no_fill": defaultdict(int), # 规则13: 判断="有意"且理由无颜色填充 "valid_yes_reason_fill": defaultdict(int), # 规则14: 判断="有意"且理由有颜色填充 "valid_no_reason_no_fill": defaultdict(int), # 规则15: 判断="無効"且理由无颜色填充 "valid_no_reason_fill": defaultdict(int), # 规则16: 判断="無効"且理由有颜色填充 "background_no_fill": defaultdict(int), # 规则17: 背景无颜色填充 "background_fill": defaultdict(int), # 规则18: 背景有颜色填充, # 规则19-59: 计数统计 "rule19": 0, # 规则19: 包含关键词且无颜色填充 "rule20": 0, # 规则20: 不包含关键词且无颜色填充 "rule21": 0, # 规则21: 包含关键词且猩红填充 "rule22": 0, # 规则22: 不包含关键词且猩红填充 "rule23": 0, # 规则23: 包含关键词且钢蓝填充 "rule24": 0, # 规则24: 不包含关键词且钢蓝填充 "rule25": 0, # 规则25: 包含关键词且巧克力黄填充 "rule26": 0, # 规则26: 不包含关键词且巧克力黄填充 "rule27": 0, # L列="追加"且无颜色填充且M列包含关键词 "rule28": 0, # L列="追加"且无颜色填充且M列不包含关键词 "rule29": 0, # L列="追加"且有颜色填充且M列包含关键词 "rule30": 0, # L列="追加"且有颜色填充且M列不包含关键词 "rule31": 0, # L列="変更"且无颜色填充且M列包含关键词 "rule32": 0, # L列="変更"且无颜色填充且M列不包含关键词 "rule33": 0, # L列="変更"且有颜色填充且M列包含关键词 "rule34": 0, # L列="変更"且有颜色填充且M列不包含关键词 "rule35": 0, # L列="差分無し"的计数 "rule36": 0, # N列="有意"且无颜色填充且M列包含关键词 "rule37": 0, # N列="有意"且无颜色填充且M列不包含关键词 "rule38": 0, # N列="有意"且有颜色填充且M列包含关键词 "rule39": 0, # N列="有意"且有颜色填充且M列不包含关键词 "rule40": 0, # N列="無効"且无颜色填充且M列包含关键词 "rule41": 0, # N列="無効"且无颜色填充且M列不包含关键词 "rule42": 0, # N列="無効"且有颜色填充且M列包含关键词 "rule43": 0, # N列="無効"且有颜色填充且M列不包含关键词 "rule44": 0, # N列="有意"且O列无颜色填充且M列包含关键词 "rule45": 0, # N列="有意"且O列无颜色填充且M列不包含关键词 "rule46": 0, # N列="有意"且O列有颜色填充且M列包含关键词 "rule47": 0, # N列="有意"且O列有颜色填充且M列不包含关键词 "rule48": 0, # N列="無効"且O列无颜色填充且M列包含关键词 "rule49": 0, # N列="無効"且O列无颜色填充且M列不包含关键词 "rule50": 0, # N列="無効"且O列有颜色填充且M列包含关键词 "rule51": 0, # N列="無効"且O列有颜色填充且M列不包含关键词 "rule52": 0, # P列无颜色填充且M列包含关键词 "rule53": 0, # P列无颜色填充且M列不包含关键词 "rule54": 0, # P列颜色为猩红且M列包含关键词 "rule55": 0, # P列颜色为猩红且M列不包含关键词 "rule56": 0, # P列颜色为钢蓝且M列包含关键词 "rule57": 0, # P列颜色为钢蓝且M列不包含关键词 "rule58": 0, # P列颜色为巧克力黄且M列包含关键词 "rule59": 0, # P列颜色为巧克力黄且M列不包含关键词 } # 遍历所有数据行 for row_idx in range(self.DATA_START_ROW, scl_sheet.max_row + 1): # 获取所有需要的单元格 diff_content_cell = scl_sheet.cell(row_idx, self.COLUMN_MAPPING["变更内容"]) diff_cell = scl_sheet.cell(row_idx, self.COLUMN_MAPPING["差分種別"]) note_cell = scl_sheet.cell(row_idx, self.COLUMN_MAPPING["备注"]) valid_cell = scl_sheet.cell(row_idx, self.COLUMN_MAPPING["判断列"]) reason_cell = scl_sheet.cell(row_idx, self.COLUMN_MAPPING["判断理由"]) background_cell = scl_sheet.cell(row_idx, self.COLUMN_MAPPING["变更背景"]) # 获取单元格值 diff_value = str(diff_cell.value).strip() if diff_cell.value else "" note_value = str(note_cell.value).strip() if note_cell.value else "" valid_value = str(valid_cell.value).strip() if valid_cell.value else "" # 获取备注值并处理多值情况 note_values = self.split_note_values(note_value) # 获取M列值 m_value = str(diff_content_cell.value) if diff_content_cell.value else "" # 检查是否包含关键词（使用增强版匹配） contains_keyword, matched_keywords = self.contains_keyword(m_value) # 记录匹配结果（调试用） if contains_keyword: self.logger.debug(f"行 {row_idx} 匹配到关键词: {', '.join(matched_keywords)}") else: self.logger.debug(f"行 {row_idx} 未匹配到关键词") # 获取单元格颜色状态 l_color_name, l_color_hex, l_no_fill = self.get_cell_color_status(diff_cell) m_color_name, m_color_hex, m_no_fill = self.get_cell_color_status(diff_content_cell) n_color_name, n_color_hex, n_no_fill = self.get_cell_color_status(valid_cell) o_color_name, o_color_hex, o_no_fill = self.get_cell_color_status(reason_cell) p_color_name, p_color_hex, p_no_fill = self.get_cell_color_status(background_cell) # 记录颜色信息用于调试 self.logger.debug(f"行 {row_idx} 颜色状态: " f"L列={l_color_name}, " f"M列={m_color_name}, " f"N列={n_color_name}, " f"O列={o_color_name}, " f"P列={p_color_name}") # 规则1-18处理 # 规则1: 変更内容无颜色填充 if m_no_fill and note_values: for nv in note_values: stats["diff_no_fill"][nv] += 1 # 记录到规则统计 self.rule_stats["diff_no_fill"][nv] += 1 # 规则2: 変更内容有颜色填充 if not m_no_fill and note_values: for nv in note_values: stats["diff_fill"][nv] += 1 self.rule_stats["diff_fill"][nv] += 1 # 规则3: 差分种别="追加"且无颜色填充 if diff_value == "追加" and l_no_fill and note_values: for nv in note_values: stats["diff_add_no_fill"][nv] += 1 self.rule_stats["diff_add_no_fill"][nv] += 1 # 规则4: 差分种别="追加"且有颜色填充 if diff_value == "追加" and not l_no_fill and note_values: for nv in note_values: stats["diff_add_fill"][nv] += 1 self.rule_stats["diff_add_fill"][nv] += 1 # 规则5: 差分种别="変更"且无颜色填充 if diff_value == "変更" and l_no_fill and note_values: for nv in note_values: stats["diff_change_no_fill"][nv] += 1 self.rule_stats["diff_change_no_fill"][nv] += 1 # 规则6: 差分种别="変更"且有颜色填充 if diff_value == "変更" and not l_no_fill and note_values: for nv in note_values: stats["diff_change_fill"][nv] += 1 self.rule_stats["diff_change_fill"][nv] += 1 # 规则7: 差分种别="削除"且无颜色填充 if diff_value == "削除" and l_no_fill and note_values: for nv in note_values: stats["diff_delete_no_fill"][nv] += 1 self.rule_stats["diff_delete_no_fill"][nv] += 1 # 规则8: 差分种别="削除"且有颜色填充 if diff_value == "削除" and not l_no_fill and note_values: for nv in note_values: stats["diff_delete_fill"][nv] += 1 self.rule_stats["diff_delete_fill"][nv] += 1 # 规则9: 判断="有意"且无颜色填充 if valid_value == "有意" and n_no_fill and note_values: for nv in note_values: stats["valid_yes_no_fill"][nv] += 1 self.rule_stats["valid_yes_no_fill"][nv] += 1 # 规则10: 判断="有意"且有颜色填充 if valid_value == "有意" and not n_no_fill and note_values: for nv in note_values: stats["valid_yes_fill"][nv] += 1 self.rule_stats["valid_yes_fill"][nv] += 1 # 规则11: 判断="無効"且无颜色填充 if valid_value == "無効" and n_no_fill and note_values: for nv in note_values: stats["valid_no_no_fill"][nv] += 1 self.rule_stats["valid_no_no_fill"][nv] += 1 # 规则12: 判断="無効"且有颜色填充 if valid_value == "無効" and not n_no_fill and note_values: for nv in note_values: stats["valid_no_fill"][nv] += 1 self.rule_stats["valid_no_fill"][nv] += 1 # 规则13: 判断="有意"且理由无颜色填充 if valid_value == "有意" and o_no_fill and note_values: for nv in note_values: stats["valid_yes_reason_no_fill"][nv] += 1 self.rule_stats["valid_yes_reason_no_fill"][nv] += 1 # 规则14: 判断="有意"且理由有颜色填充 if valid_value == "有意" and not o_no_fill and note_values: for nv in note_values: stats["valid_yes_reason_fill"][nv] += 1 self.rule_stats["valid_yes_reason_fill"][nv] += 1 # 规则15: 判断="無効"且理由无颜色填充 if valid_value == "無効" and o_no_fill and note_values: for nv in note_values: stats["valid_no_reason_no_fill"][nv] += 1 self.rule_stats["valid_no_reason_no_fill"][nv] += 1 # 规则16: 判断="無効"且理由有颜色填充 if valid_value == "無効" and not o_no_fill and note_values: for nv in note_values: stats["valid_no_reason_fill"][nv] += 1 self.rule_stats["valid_no_reason_fill"][nv] += 1 # 规则17: 背景无颜色填充 if p_no_fill and note_values: for nv in note_values: stats["background_no_fill"][nv] += 1 self.rule_stats["background_no_fill"][nv] += 1 # 规则18: 背景有颜色填充 if not p_no_fill and note_values: for nv in note_values: stats["background_fill"][nv] += 1 self.rule_stats["background_fill"][nv] += 1 # 规则19-59处理 # 规则19: 包含关键词且无颜色填充 if contains_keyword and m_no_fill: stats["rule19"] += 1 self.rule_stats["rule19"]["count"] += 1 # 规则20: 不包含关键词且无颜色填充 if not contains_keyword and m_no_fill: stats["rule20"] += 1 self.rule_stats["rule20"]["count"] += 1 # 规则21: 包含关键词且猩红填充 if contains_keyword and m_color_name == "猩红": stats["rule21"] += 1 self.rule_stats["rule21"]["count"] += 1 # 规则22: 不包含关键词且猩红填充 if not contains_keyword and m_color_name == "猩红": stats["rule22"] += 1 self.rule_stats["rule22"]["count"] += 1 # 规则23: 包含关键词且钢蓝填充 if contains_keyword and m_color_name == "钢蓝": stats["rule23"] += 1 self.rule_stats["rule23"]["count"] += 1 # 规则24: 不包含关键词且钢蓝填充 if not contains_keyword and m_color_name == "钢蓝": stats["rule24"] += 1 self.rule_stats["rule24"]["count"] += 1 # 规则25: 包含关键词且巧克力黄填充 if contains_keyword and m_color_name == "巧克力黄": stats["rule25"] += 1 self.rule_stats["rule25"]["count"] += 1 # 规则26: 不包含关键词且巧克力黄填充 if not contains_keyword and m_color_name == "巧克力黄": stats["rule26"] += 1 self.rule_stats["rule26"]["count"] += 1 # 规则27: L列="追加"且无颜色填充且M列包含关键词 if diff_value == "追加" and l_no_fill and contains_keyword: stats["rule27"] += 1 self.rule_stats["rule27"]["count"] += 1 # 规则28: L列="追加"且无颜色填充且M列不包含关键词 if diff_value == "追加" and l_no_fill and not contains_keyword: stats["rule28"] += 1 self.rule_stats["rule28"]["count"] += 1 # 规则29: L列="追加"且有颜色填充且M列包含关键词 if diff_value == "追加" and not l_no_fill and contains_keyword: stats["rule29"] += 1 self.rule_stats["rule29"]["count"] += 1 # 规则30: L列="追加"且有颜色填充且M列不包含关键词 if diff_value == "追加" and not l_no_fill and not contains_keyword: stats["rule30"] += 1 self.rule_stats["rule30"]["count"] += 1 # 规则31: L列="変更"且无颜色填充且M列包含关键词 if diff_value == "変更" and l_no_fill and contains_keyword: stats["rule31"] += 1 self.rule_stats["rule31"]["count"] += 1 # 规则32: L列="変更"且无颜色填充且M列不包含关键词 if diff_value == "変更" and l_no_fill and not contains_keyword: stats["rule32"] += 1 self.rule_stats["rule32"]["count"] += 1 # 规则33: L列="変更"且有颜色填充且M列包含关键词 if diff_value == "変更" and not l_no_fill and contains_keyword: stats["rule33"] += 1 self.rule_stats["rule33"]["count"] += 1 # 规则34: L列="変更"且有颜色填充且M列不包含关键词 if diff_value == "変更" and not l_no_fill and not contains_keyword: stats["rule34"] += 1 self.rule_stats["rule34"]["count"] += 1 # 规则35: L列="差分無し"的计数 if diff_value == "差分無し": stats["rule35"] += 1 self.rule_stats["rule35"]["count"] += 1 # 规则36: N列="有意"且无颜色填充且M列包含关键词 if valid_value == "有意" and n_no_fill and contains_keyword: stats["rule36"] += 1 self.rule_stats["rule36"]["count"] += 1 # 规则37: N列="有意"且无颜色填充且M列不包含关键词 if valid_value == "有意" and n_no_fill and not contains_keyword: stats["rule37"] += 1 self.rule_stats["rule37"]["count"] += 1 # 规则38: N列="有意"且有颜色填充且M列包含关键词 if valid_value == "有意" and not n_no_fill and contains_keyword: stats["rule38"] += 1 self.rule_stats["rule38"]["count"] += 1 # 规则39: N列="有意"且有颜色填充且M列不包含关键词 if valid_value == "有意" and not n_no_fill and not contains_keyword: stats["rule39"] += 1 self.rule_stats["rule39"]["count"] += 1 # 规则40: N列="無効"且无颜色填充且M列包含关键词 if valid_value == "無効" and n_no_fill and contains_keyword: stats["rule40"] += 1 self.rule_stats["rule40"]["count"] += 1 # 规则41: N列="無効"且无颜色填充且M列不包含关键词 if valid_value == "無効" and n_no_fill and not contains_keyword: stats["rule41"] += 1 self.rule_stats["rule41"]["count"] += 1 # 规则42: N列="無効"且有颜色填充且M列包含关键词 if valid_value == "無効" and not n_no_fill and contains_keyword: stats["rule42"] += 1 self.rule_stats["rule42"]["count"] += 1 # 规则43: N列="無効"且有颜色填充且M列不包含关键词 if valid_value == "無効" and not n_no_fill and not contains_keyword: stats["rule43"] += 1 self.rule_stats["rule43"]["count"] += 1 # 规则44: N列="有意"且O列无颜色填充且M列包含关键词 if valid_value == "有意" and o_no_fill and contains_keyword: stats["rule44"] += 1 self.rule_stats["rule44"]["count"] += 1 # 规则45: N列="有意"且O列无颜色填充且M列不包含关键词 if valid_value == "有意" and o_no_fill and not contains_keyword: stats["rule45"] += 1 self.rule_stats["rule45"]["count"] += 1 # 规则46: N列="有意"且O列有颜色填充且M列包含关键词 if valid_value == "有意" and not o_no_fill and contains_keyword: stats["rule46"] += 1 self.rule_stats["rule46"]["count"] += 1 # 规则47: N列="有意"且O列有颜色填充且M列不包含关键词 if valid_value == "有意" and not o_no_fill and not contains_keyword: stats["rule47"] += 1 self.rule_stats["rule47"]["count"] += 1 # 规则48: N列="無効"且O列无颜色填充且M列包含关键词 if valid_value == "無効" and o_no_fill and contains_keyword: stats["rule48"] += 1 self.rule_stats["rule48"]["count"] += 1 # 规则49: N列="無効"且O列无颜色填充且M列不包含关键词 if valid_value == "無効" and o_no_fill and not contains_keyword: stats["rule49"] += 1 self.rule_stats["rule49"]["count"] += 1 # 规则50: N列="無効"且O列有颜色填充且M列包含关键词 if valid_value == "無効" and not o_no_fill and contains_keyword: stats["rule50"] += 1 self.rule_stats["rule50"]["count"] += 1 # 规则51: N列="無効"且O列有颜色填充且M列不包含关键词 if valid_value == "無効" and not o_no_fill and not contains_keyword: stats["rule51"] += 1 self.rule_stats["rule51"]["count"] += 1 # 规则52: P列无颜色填充且M列包含关键词 if p_no_fill and contains_keyword: stats["rule52"] += 1 self.rule_stats["rule52"]["count"] += 1 # 规则53: P列无颜色填充且M列不包含关键词 if p_no_fill and not contains_keyword: stats["rule53"] += 1 self.rule_stats["rule53"]["count"] += 1 # 规则54: P列颜色为猩红且M列包含关键词 if p_color_name == "猩红" and contains_keyword: stats["rule54"] += 1 self.rule_stats["rule54"]["count"] += 1 # 规则55: P列颜色为猩红且M列不包含关键词 if p_color_name == "猩红" and not contains_keyword: stats["rule55"] += 1 self.rule_stats["rule55"]["count"] += 1 # 规则56: P列颜色为钢蓝且M列包含关键词 if p_color_name == "钢蓝" and contains_keyword: stats["rule56"] += 1 self.rule_stats["rule56"]["count"] += 1 # 规则57: P列颜色为钢蓝且M列不包含关键词 if p_color_name == "钢蓝" and not contains_keyword: stats["rule57"] += 1 self.rule_stats["rule57"]["count"] += 1 # 规则58: P列颜色为巧克力黄且M列包含关键词 if p_color_name == "巧克力黄" and contains_keyword: stats["rule58"] += 1 self.rule_stats["rule58"]["count"] += 1 # 规则59: P列颜色为巧克力黄且M列不包含关键词 if p_color_name == "巧克力黄" and not contains_keyword: stats["rule59"] += 1 self.rule_stats["rule59"]["count"] += 1 # 在遍历所有数据行后，添加规则统计日志 self.log_rule_stats(file_path) # 处理统计结果 for rule, data in stats.items(): # 对于规则1-18，输出备注值及其出现次数 if rule in ["diff_no_fill", "diff_fill", "diff_add_no_fill", "diff_add_fill", "diff_change_no_fill", "diff_change_fill", "diff_delete_no_fill", "diff_delete_fill", "valid_yes_no_fill", "valid_yes_fill", "valid_no_no_fill", "valid_no_fill", "valid_yes_reason_no_fill", "valid_yes_reason_fill", "valid_no_reason_no_fill", "valid_no_reason_fill", "background_no_fill", "background_fill"]: # 检查是否有数据 if not data: # 字典为空 results[rule] = "/" self.logger.info(f"{rule}: 无数据，输出 '/'") continue # 格式化备注统计结果 results[rule] = self.format_note_stats(data) # 优化日志输出：分行显示 self.logger.info(f"{rule}: 结果:") for line in results[rule].split('\n'): self.logger.info(f" {line}") else: # 对于规则19-59，直接输出计数值 results[rule] = str(data) self.logger.info(f"{rule}: 结果 {results[rule]}") # 生成颜色报告 color_report = self.color_detector.generate_color_report() self.logger.info("\n" + color_report) return results, color_report, missing_data except Exception as e: error_msg = f"处理SCL文件失败: {str(e)}" logger.exception(f"处理SCL文件失败: {file_path} - {str(e)}") # 返回错误信息 return {rule: f"错误: {str(e)}" for rule in self.RULE_MAPPING}, f"错误: {error_msg}", [{ 'row': 0, 'col': 0, 'col_name': '错误', 'message': error_msg }] # 创建全局日志记录器 logger = logging.getLogger("SCLMultiProcessor") logger.setLevel(logging.INFO) class SCLMultiProcessor: def __init__(self, root): self.root = root # 创建日志目录 self.log_dir = "logs" self.root.title("SCL文件处理系统") self.root.geometry("1100x750") # 增加窗口尺寸以适应新控件 # 初始化变量 self.color_detector = EnhancedColorDetector() self.stats_processor = SCLRuleProcessor(self.color_detector) self.empty_cell_detector = EnhancedEmptyCellDetector(self.color_detector) self.progress_var = tk.DoubleVar() os.makedirs(self.log_dir, exist_ok=True) # 初始化日志系统 self.current_log_file = None self.setup_logger() # 创建主框架 self.main_frame = ttk.Frame(root, padding="10") self.main_frame.pack(fill=tk.BOTH, expand=True) # 创建UI self.create_ui() # 记录UI初始化完成 self.logger.info("用户界面初始化完成") def toggle_config_fields(self): """根据操作模式显示/隐藏相关配置字段""" mode = self.operation_mode.get() # 统计模式：显示统计表路径，隐藏CheckSheet路径 if mode == "stats": self.input_frame.pack(fill=tk.X, pady=5) # 显示统计表路径 self.checksheet_frame.pack_forget() # 隐藏CheckSheet路径 self.logger.info("切换到统计模式，显示统计表路径") # SCL格式检查模式：隐藏统计表路径，显示CheckSheet路径 elif mode == "empty_check": self.input_frame.pack_forget() # 隐藏统计表路径 self.checksheet_frame.pack(fill=tk.X, pady=5) # 显示CheckSheet路径 self.logger.info("切换到SCL格式检查模式，显示CheckSheet路径") def create_ui(self): """创建用户界面""" # 操作模式选择区域 - 放在最前面 mode_frame = ttk.LabelFrame(self.main_frame, text="操作模式", padding="10") mode_frame.pack(fill=tk.X, pady=5) # 添加操作模式单选按钮 self.operation_mode = tk.StringVar(value="stats") # 默认选择统计模式 ttk.Radiobutton(mode_frame, text="统计功能", variable=self.operation_mode, value="stats", command=self.toggle_config_fields).pack(side=tk.LEFT, padx=10) ttk.Radiobutton(mode_frame, text="SCL格式检查", variable=self.operation_mode, value="empty_check", command=self.toggle_config_fields).pack(side=tk.LEFT, padx=10) # 文件选择区域 - 放在操作模式后面 file_frame = ttk.LabelFrame(self.main_frame, text="文件选择", padding="10") file_frame.pack(fill=tk.X, pady=5) # 输入文件选择 - 统计表路径（统计模式需要） self.input_frame = ttk.Frame(file_frame) ttk.Label(self.input_frame, text="统计表:").pack(side=tk.LEFT, padx=5) self.input_path_var = tk.StringVar() input_entry = ttk.Entry(self.input_frame, textvariable=self.input_path_var, width=70) input_entry.pack(side=tk.LEFT, fill=tk.X, expand=True, padx=5) ttk.Button(self.input_frame, text="浏览...", command=self.browse_input_file).pack(side=tk.LEFT, padx=5) self.input_frame.pack(fill=tk.X, pady=5) # 默认显示 # 配置区域 config_frame = ttk.LabelFrame(self.main_frame, text="处理配置", padding="10") config_frame.pack(fill=tk.X, pady=5) # 添加SCL文件夹路径输入 scl_folder_frame = ttk.Frame(config_frame) scl_folder_frame.pack(fill=tk.X, pady=5) ttk.Label(scl_folder_frame, text="SCL文件夹路径:").grid(row=0, column=0, padx=5, sticky=tk.W) self.scl_folder_var = tk.StringVar() scl_folder_entry = ttk.Entry(scl_folder_frame, textvariable=self.scl_folder_var, width=60) scl_folder_entry.grid(row=0, column=1, padx=5, sticky=tk.W) ttk.Button(scl_folder_frame, text="浏览...", command=self.browse_scl_folder).grid(row=0, column=2, padx=5, sticky=tk.W) # 搜索选项 search_frame = ttk.Frame(config_frame) search_frame.pack(fill=tk.X, pady=5) ttk.Label(search_frame, text="文件前缀:").grid(row=0, column=0, padx=5, sticky=tk.W) self.prefix_var = tk.StringVar(value="SCL_") ttk.Entry(search_frame, textvariable=self.prefix_var, width=10).grid(row=0, column=1, padx=5, sticky=tk.W) # 添加CheckSheet路径输入（SCL格式检查模式需要） self.checksheet_frame = ttk.Frame(config_frame) ttk.Label(self.checksheet_frame, text="CheckSheet路径:").grid(row=0, column=0, padx=5, sticky=tk.W) self.checksheet_path_var = tk.StringVar() checksheet_entry = ttk.Entry(self.checksheet_frame, textvariable=self.checksheet_path_var, width=60) checksheet_entry.grid(row=0, column=1, padx=5, sticky=tk.W) ttk.Button(self.checksheet_frame, text="浏览...", command=self.browse_checksheet_path).grid(row=0, column=2, padx=5, sticky=tk.W) self.checksheet_frame.pack_forget() # 默认隐藏 # 添加性能提示 ttk.Label(config_frame, text="(表头固定在第3行，数据从第4行开始)").pack(anchor=tk.W, padx=5, pady=2) # 日志选项 log_frame = ttk.Frame(config_frame) log_frame.pack(fill=tk.X, pady=5) ttk.Label(log_frame, text="日志级别:").grid(row=0, column=0, padx=5, sticky=tk.W) self.log_level_var = tk.StringVar(value="INFO") log_level_combo = ttk.Combobox( log_frame, textvariable=self.log_level_var, width=10, state="readonly" ) log_level_combo['values'] = ('DEBUG', 'INFO', 'WARNING', 'ERROR', 'CRITICAL') log_level_combo.grid(row=0, column=1, padx=5, sticky=tk.W) log_level_combo.bind("<<ComboboxSelected>>", self.change_log_level) # 处理按钮 btn_frame = ttk.Frame(self.main_frame) btn_frame.pack(fill=tk.X, pady=10) ttk.Button(btn_frame, text="开始处理", command=self.process_file).pack(side=tk.LEFT, padx=5) ttk.Button(btn_frame, text="查看日志", command=self.view_log).pack(side=tk.LEFT, padx=5) ttk.Button(btn_frame, text="导出配置", command=self.export_config).pack(side=tk.LEFT, padx=5) ttk.Button(btn_frame, text="加载配置", command=self.load_config).pack(side=tk.LEFT, padx=5) ttk.Button(btn_frame, text="退出", command=self.root.destroy).pack(side=tk.RIGHT, padx=5) # 进度条 progress_frame = ttk.Frame(self.main_frame) progress_frame.pack(fill=tk.X, pady=5) ttk.Label(progress_frame, text="处理进度:").pack(side=tk.LEFT, padx=5) self.progress_bar = ttk.Progressbar( progress_frame, variable=self.progress_var, maximum=100, length=700 ) self.progress_bar.pack(side=tk.LEFT, fill=tk.X, expand=True, padx=5) self.progress_label = ttk.Label(progress_frame, text="0%") self.progress_label.pack(side=tk.LEFT, padx=5) # 结果展示区域 result_frame = ttk.LabelFrame(self.main_frame, text="处理结果", padding="10") result_frame.pack(fill=tk.BOTH, expand=True, pady=5) # 结果文本框 self.result_text = scrolledtext.ScrolledText( result_frame, wrap=tk.WORD, height=20 ) self.result_text.pack(fill=tk.BOTH, expand=True) self.result_text.config(state=tk.DISABLED) # 状态栏 self.status_var = tk.StringVar(value="就绪") status_bar = ttk.Label(self.main_frame, textvariable=self.status_var, relief=tk.SUNKEN, anchor=tk.W) status_bar.pack(fill=tk.X, pady=5) self.logger.info("UI创建完成") def browse_checksheet_path(self): """浏览CheckSheet文件夹""" folder_path = filedialog.askdirectory(title="选择CheckSheet文件夹") if folder_path: self.checksheet_path_var.set(folder_path) self.logger.info(f"已选择CheckSheet文件夹: {folder_path}") def setup_logger(self): """配置日志记录器""" # 创建唯一日志文件名 timestamp = datetime.now().strftime("%Y%m%d_%H%M%S") self.current_log_file = os.path.join(self.log_dir, f"scl_processor_{timestamp}.log") # 创建或获取日志记录器 self.logger = logging.getLogger("SCLProcessor") self.logger.setLevel(logging.INFO) # 移除所有现有处理器 for handler in self.logger.handlers[:]: self.logger.removeHandler(handler) # 创建文件处理器 file_handler = logging.FileHandler(self.current_log_file, encoding='utf-8') file_handler.setLevel(logging.INFO) # 创建控制台处理器 console_handler = logging.StreamHandler() console_handler.setLevel(logging.INFO) # 创建日志格式 formatter = logging.Formatter( '%(asctime)s - %(name)s - %(levelname)s - %(message)s', datefmt='%Y-%m-%d %H:%M:%S' ) file_handler.setFormatter(formatter) console_handler.setFormatter(formatter) # 添加处理器 self.logger.addHandler(file_handler) self.logger.addHandler(console_handler) # 记录日志初始化信息 self.logger.info(f"日志系统已初始化，日志文件: {self.current_log_file}") self.logger.info(f"日志目录: {os.path.abspath(self.log_dir)}") def change_log_level(self, event=None): """动态更改日志级别""" try: # 获取选择的日志级别 level_str = self.log_level_var.get() log_level = getattr(logging, level_str.upper()) # 更新日志记录器级别 self.logger.setLevel(log_level) # 更新所有处理器的级别 for handler in self.logger.handlers: handler.setLevel(log_level) self.logger.info(f"日志级别已成功更改为: {level_str}") self.status_var.set(f"日志级别: {level_str}") except AttributeError: self.logger.error(f"无效的日志级别: {level_str}") messagebox.showerror("错误", f"无效的日志级别: {level_str}") except Exception as e: self.logger.exception("更改日志级别时发生错误") messagebox.showerror("错误", f"更改日志级别失败: {str(e)}") def browse_input_file(self): """浏览输入文件""" file_path = filedialog.askopenfilename( filetypes=[("Excel 文件", "*.xlsx *.xls"), ("所有文件", "*.*")] ) if file_path: self.input_path_var.set(file_path) self.logger.info(f"已选择输入文件: {file_path}") def browse_scl_folder(self): """浏览SCL文件夹""" folder_path = filedialog.askdirectory(title="选择SCL文件夹") if folder_path: self.scl_folder_var.set(folder_path) self.logger.info(f"已选择SCL文件夹: {folder_path}") def highlight_cell(self, sheet, row, col, color="FFFF0000"): """为单元格设置背景色""" try: fill = PatternFill(start_color=color, end_color=color, fill_type="solid") sheet.cell(row=row, column=col).fill = fill return True except Exception as e: self.logger.error(f"设置单元格颜色失败: {str(e)}") return False def process_file(self): """处理文件 - 根据操作模式执行不同处理流程""" operation_mode = self.operation_mode.get() # 重置结果 self.result_text.config(state=tk.NORMAL) self.result_text.delete(1.0, tk.END) self.result_text.insert(tk.END, "开始处理...\n") self.result_text.see(tk.END) self.result_text.config(state=tk.DISABLED) self.status_var.set("开始处理文件...") self.root.update() try: # 每次处理前重新初始化日志系统 self.setup_logger() # 记录处理开始信息 self.logger.info("=" * 50) self.logger.info(f"开始处理: {datetime.now().strftime('%Y-%m-%d %H:%M:%S')}") self.logger.info(f"操作模式: {operation_mode}") self.logger.info("=" * 50) # 更新UI显示当前日志文件 self.status_var.set(f"当前日志: {os.path.basename(self.current_log_file)}") # 获取公共配置参数 scl_folder = self.scl_folder_var.get() prefix = self.prefix_var.get() # 根据操作模式执行不同处理流程 if operation_mode == "stats": self.process_stats_mode(scl_folder, prefix) elif operation_mode == "empty_check": self.process_empty_check_mode(scl_folder, prefix) else: messagebox.showerror("错误", f"未知操作模式: {operation_mode}") self.logger.error(f"未知操作模式: {operation_mode}") except Exception as e: error_msg = f"处理文件时出错: {str(e)}" logger.exception(f"处理文件时出错: {str(e)}") messagebox.showerror("错误", error_msg) self.status_var.set(f"错误: {str(e)}") # 更新结果文本框 self.result_text.config(state=tk.NORMAL) self.result_text.insert(tk.END, f"\n错误: {error_msg}\n") self.result_text.see(tk.END) self.result_text.config(state=tk.DISABLED) def process_stats_mode(self, scl_folder, prefix): """处理统计模式：扫描统计表E列获取SCL文件名""" # 检查输入文件是否存在 input_file = self.input_path_var.get() if not input_file: messagebox.showwarning("警告", "请先选择统计表") self.logger.warning("未选择统计表") return if not os.path.exists(input_file): messagebox.showerror("错误", f"统计表文件不存在: {input_file}") self.logger.error(f"统计表文件不存在: {input_file}") return # 使用openpyxl加载工作簿（保留格式） wb = openpyxl.load_workbook(input_file) sheet = wb.active self.logger.info(f"工作簿加载成功, 工作表: {sheet.title}") # 扫描E列（第5列） total_rows = sheet.max_row processed_count = 0 found_files = 0 problem_files = 0 self.logger.info(f"开始扫描E列, 总行数: {total_rows}") start_time = time.time() for row_idx in range(1, total_rows + 1): # 更新进度 progress = (row_idx / total_rows) * 100 self.progress_var.set(progress) self.progress_label.config(text=f"{progress:.1f}%") self.status_var.set(f"处理行: {row_idx}/{total_rows}") self.root.update() cell = sheet.cell(row=row_idx, column=5) cell_value = str(cell.value) if cell.value else "" # 检查是否包含前缀的文件名 if prefix in cell_value: # 改进的正则表达式：匹配包含空格的文件名 # 匹配模式：以prefix开头，后跟任意字符（包括空格），直到文件扩展名 pattern = re.compile( fr'{prefix}[^\s]*\s*[^\s]*\.(?:xlsx|xls|xlsm)', re.IGNORECASE ) file_names = pattern.findall(cell_value) self.logger.info(f"行 {row_idx}: 找到文件: {', '.join(file_names)}") result_lines = [] file_has_problems = False # 标记当前行是否有问题文件 for file_name in file_names: # 在SCL文件夹及其子目录中查找文件（保留文件名中的空格） file_path = self.find_single_scl_file(scl_folder, file_name) # 检查文件是否存在 if not file_path or not os.path.exists(file_path): result_lines.append(f"{file_name}: 文件不存在") self.logger.warning(f"文件不存在: {file_name}") # 标记文件不存在的单元格为紫色 self.highlight_cell(sheet, row_idx, 5, "FF800080") file_has_problems = True problem_files += 1 continue # 执行统计处理 results, color_report, missing_data = self.stats_processor.process_file(file_path) # 如果有数据缺失 if missing_data: file_has_problems = True problem_files += 1 result_lines.append(f"{file_name}: 数据缺失!") for item in missing_data: result_lines.append(f" - {item['message']}") self.logger.warning(item['message']) else: result_lines.append(f"{file_name}: 处理完成") # 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