package httpimport (    "io"    "log/slog"    "mime/multipart"    "net/http"    "strings")type BatchItemResult struct {    Name string `json:"name"`    Metadata *struct {        Format string `json:"format"`        Width  int    `json:"width"`        Height int    `json:"height"`        Bytes  int    `json:"bytes"`    }`json:"metadata,omitempty"`    Error string `json:"error,omitempty"`}type BatchResponse struct {    Results []*BatchItemResult `json:"results"`    Count   int                `json:"count"`    Success int                `json:"success"`    Failed  int                `json:"failed"`}// handleProcessBatch processes multiple uploaded images (multipart/form-data) under the field name "files".// It returns metadata for each image or an error per item without failing the whole batch unless the request is malformed.func (s*Server)handleProcessBatch(w http.ResponseWriter,r *http.Request) {    // Enforce max body size overall.    r.Body =http.MaxBytesReader(w,r.Body,s.cfg.MaxUploadBytes)    if ct :=r.Header.Get("Content-Type"); !strings.HasPrefix(ct,"multipart/form-data") {        s.writeJSON(w,http.StatusBadRequest,map[string]string{"error":"content type must be multipart/form-data"})        return    }    if err :=r.ParseMultipartForm(s.cfg.MaxUploadBytes);err !=nil {        status :=http.StatusBadRequest        if strings.Contains(err.Error(),"request body too large") {            status =http.StatusRequestEntityTooLarge        }        s.writeJSON(w,status,map[string]string{"error":"invalid multipart form: " +err.Error()})        return    }    // Accept files under the key "files". If absent, attempt to fallback to any file parts.    var fileHeaders []*multipart.FileHeader    if r.MultipartForm !=nil &&len(r.MultipartForm.File["files"]) >0 {        fileHeaders =r.MultipartForm.File["files"]    }else if r.MultipartForm !=nil {        // Fallback: gather all files across keys.        for _,fhs :=range r.MultipartForm.File {            fileHeaders =append(fileHeaders,fhs...)        }    }    if len(fileHeaders) ==0 {        s.writeJSON(w,http.StatusBadRequest,map[string]string{"error":"no files provided (expect key 'files')"})        return    }    resp := &BatchResponse{Results:make([]*BatchItemResult,0,len(fileHeaders))}    for _,fh :=range fileHeaders {        item := &BatchItemResult{Name:fh.Filename}        f,err :=fh.Open()        if err !=nil {            item.Error ="open file: " +err.Error()            resp.Results =append(resp.Results,item)            resp.Failed++            continue        }        data,err :=io.ReadAll(f)        _ =f.Close()        if err !=nil {            item.Error ="read file: " +err.Error()            resp.Results =append(resp.Results,item)            resp.Failed++            continue        }        meta,err :=s.proc.ExtractMetadata(data)        if err !=nil {            item.Error =err.Error()            resp.Results =append(resp.Results,item)            resp.Failed++            continue        }        // Copy into anonymous struct to decouple from internal type if it changes.        item.Metadata = &struct {            Format string `json:"format"`            Width  int    `json:"width"`            Height int    `json:"height"`            Bytes  int    `json:"bytes"`        }{Format:meta.Format,Width:meta.Width,Height:meta.Height,Bytes:meta.Bytes}        resp.Results =append(resp.Results,item)        resp.Success++    }    resp.Count =len(resp.Results)    s.log.LogAttrs(r.Context(),slog.LevelInfo,"batch processed",slog.Int("count",resp.Count),slog.Int("success",resp.Success),slog.Int("failed",resp.Failed))    s.writeJSON(w,http.StatusOK,resp)}

import numpyas npimport pandasas pdiris_data = pd.read_csv("iris_dataset.csv")def describe(species:str) -> pd.Series:
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subset =data[data["species"] == species]          subset =iris_data[iris_data["species"] == species]if subset.empty:raise ValueError(f"{species} missing from sample")return subset[["petal","sepal"]].agg(["mean","std"]).loc["mean"]def summary():
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for speciesin np.sort(data["species"].unique()):     for speciesin np.sort(iris_data["species"].unique()):try:stats = describe(species)except ValueError:print(f"{species}: no records")continueprint(f"{species}: petal={stats['petal']:.2f} sepal={stats['sepal']:.2f}")if __name__ =="__main__":summary()