解析发送到数据快照服务器的MadExcept错误报告的最佳方法是什么?

时间:2018-10-24 09:01:08

标签: delphi mime datasnap madexcept

我将datasnap rest服务器配置为madexcept的自定义脚本上传位置。

一切正常,直到我尝试解析报表中设置的变量为止。他们添加了

function V1RestMethod.UpdateBugReport: TJSONArray;
var
  LReq:TWebRequest; 
  LAppName:string;   
begin
  LReq:=GetDataSnapWebModule.Request;
  LAppName:= LReq.ContentFields.Values['appname'];  
end;

我认识到报告是作为 multipart / form-data 发送的,因此我尝试将 Web.ReqMulti 包含到我的单元中,以使用 TMultipartContentParser进行解析 在REST方法中看起来像这样

LAppName

此时,LReq.ContentFields.Count为空,因为application/octet-stream为0

解析此错误报告的推荐方法是什么?

更新_1:

似乎TMultipartContentParser似乎正确解析了所有文件(from mpl_toolkits.mplot3d import Axes3D import matplotlib.pyplot as plt import numpy as np from matplotlib import cm def random_point( r=1 ): ct = 2*np.random.rand() - 1 st = np.sqrt( 1 - ct**2 ) phi = 2* np.pi * np.random.rand() x = r * st * np.cos( phi) y = r * st * np.sin( phi) z = r * ct return np.array( [x, y, z ] ) def near( p, pntList, d0 ): cnt=0 for pj in pntList: dist=np.linalg.norm( p - pj ) if dist < d0: cnt += 1 - dist/d0 return cnt """ https://stackoverflow.com/questions/22128909/plotting-the-temperature-distribution-on-a-sphere-with-python """ pointList = np.array([ random_point( 10.05 ) for i in range( 65 ) ] ) fig = plt.figure() ax = fig.add_subplot( 1, 1, 1, projection='3d') u = np.linspace( 0, 2 * np.pi, 120) v = np.linspace( 0, np.pi, 60 ) # create the sphere surface XX = 10 * np.outer( np.cos( u ), np.sin( v ) ) YY = 10 * np.outer( np.sin( u ), np.sin( v ) ) ZZ = 10 * np.outer( np.ones( np.size( u ) ), np.cos( v ) ) WW = XX.copy() for i in range( len( XX ) ): for j in range( len( XX[0] ) ): x = XX[ i, j ] y = YY[ i, j ] z = ZZ[ i, j ] WW[ i, j ] = near(n p.array( [x, y, z ] ), pointList, 3) WW = WW / np.amax( WW ) myheatmap = WW # ~ ax.scatter( *zip( *pointList ), color='#dd00dd' ) ax.plot_surface( XX, YY, ZZ, cstride=1, rstride=1, facecolors=cm.jet( myheatmap ) ) plt.show() ),但未解析纯文本。

0 个答案:

没有答案