本文整理汇总了C#中System.Resources.ResXDataNode类的典型用法代码示例。如果您正苦于以下问题：C# ResXDataNode类的具体用法？C# ResXDataNode怎么用？C# ResXDataNode使用的例子？那么恭喜您, 这里精选的类代码示例或许可以为您提供帮助。
ResXDataNode类属于System.Resources命名空间，在下文中一共展示了ResXDataNode类的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: Main
//引入命名空间
using System;
using System.Collections;
using System.ComponentModel.Design;
using System.Resources;
public class Example
{
private const string resxFilename = @".\CountryHeaders.resx";
public static void Main()
{
// Create a resource file to read.
CreateResourceFile();
// Enumerate the resources in the file.
ResXResourceReader rr = new ResXResourceReader(resxFilename);
rr.UseResXDataNodes = true;
IDictionaryEnumerator dict = rr.GetEnumerator();
while (dict.MoveNext()) {
ResXDataNode node = (ResXDataNode) dict.Value;
Console.WriteLine("{0,-20} {1,-20} {2}",
node.Name + ":",
node.GetValue((ITypeResolutionService) null),
! String.IsNullOrEmpty(node.Comment) ? "// " + node.Comment : "");
}
}
private static void CreateResourceFile()
{
ResXResourceWriter rw = new ResXResourceWriter(resxFilename);
string[] resNames = {"Country", "Population", "Area",
"Capital", "LCity" };
string[] columnHeaders = { "Country Name", "Population (2010}",
"Area", "Capital", "Largest City" };
string[] comments = { "The localized country name", "Estimated population, 2010",
"The area in square miles", "Capital city or chief administrative center",
"The largest city based on 2010 data" };
rw.AddResource("Title", "Country Information");
rw.AddResource("nColumns", resNames.Length);
for (int ctr = 0; ctr < resNames.Length; ctr++) {
ResXDataNode node = new ResXDataNode(resNames[ctr], columnHeaders[ctr]);
node.Comment = comments[ctr];
rw.AddResource(node);
}
rw.Generate();
rw.Close();
}
}输出：
Title: Country Information nColumns: 5 Country: Country Name // The localized country name Population: Population (2010} // Estimated population, 2010 Area: Area // The area in square miles Capital: Capital // Capital city or chief administrative center LCity: Largest City // The largest city based on 2010 data