现在JSF变量解析器和视图就可以使用包装的值。
The wrapped value is now available to the JSF variable resolver, and thus the view.
要获得与Spring的真正集成，需要比定制变量解析器更好的解决方案。
To achieve true integration with Spring, you need a better solution than a custom variable resolver.
另一方面，如果选择通过值绑定访问行数据，则必须咨询J SF变量解析器。
On the other hand, if you choose to access row data through the value binding, then you must consult the JSF variable resolver.
本地JSF变量解析器首先查找与名称courses相匹配的jsf托管bean。
The native JSF variable resolver first looks for a JSF managed bean that matches the name courses.
如果FacesContext不可用，则变量解析器就不能访问任何的Springbean。
If the FacesContext isn't available, then the variable resolver can't access any of the Spring beans.
正如之前所讨论的，我最初将Spring容器集成到Seam中所采用的变量解析器方法有其自身的局限。
As discussed earlier, the variable-resolver approach I originally used to integrate the Spring container into Seam has its limitations.
其中的问题是，Spring变量解析器依赖于FacesContext定位 Spring容器。
The trouble is, the Spring variable resolver relies on the FacesContext to locate the Spring container.
spring - web包是spring发布的一部分，附带有自定义J SF变量解析器，可构建此桥梁。
The spring-web package, part of the spring distribution, ships with a custom JSF variable resolver to establish this bridge.
Spring附带了一个变量解析器实现类，允许您在JSF表达式中引用 Spring托管Bean。
Spring comes with a variable resolver implementation class that lets you reference Spring managed beans in JSF expressions.
Spring变量解析器是使用变量解析器节点在faces - config . xml文件中配置的，如清单1所示。
The Spring variable resolver is configured in the faces-config.xml file using the variable resolver node, as shown in Listing 1.
首先需要确保已经配置了Spring-JSF集成，它由 Spring框架附带的一个定制变量解析器进行处理（见参考资料）。
You first need to ensure that you have the Spring-JSF integration configured, which is handled by a custom variable resolver included with the Spring framework (see Resources).
还演示了将变量解析器指令用于DelegatingVariableResolver和el表达式，以使用容器提供的managecustomer托管bean。
It also demonstrates the use of the variable-resolver directive for DelegatingVariableResolver and an el expression to apply the ManageCustomer managed bean instance provided by the container.
我利用环境变量sgml_catalog_files这种方法，因为SGML解析器也使用它(耐心一些，我将在本文的下一节讨论它)。
I use the method that makes use of the environment variable SGML_CATALOG_FILES because it is also used by the SGML parser (patience, I come to it in the next section of this article).
我所有的旧的特别的解析器都采用了这种风格：读一些字符、作决定、累加一些变量、清空、重复。
All my old AD hoc parsers were imperative in flavor: read some characters, make some decisions, accumulate some variables, rinse, repeat.
JRubyAST是解析器的输出结果，仅仅是源代码的树形表示，包含不同种类的节点，例如有类、方法和变量。
The JRuby AST is the output of the parser and is just a tree representation of the source code, containing different kinds of nodes, for example for classes, methods, variables.
JRubyAST是解析器的输出结果，仅仅是源代码的树形表示，包含不同种类的节点，例如有类、方法和变量。
The JRuby AST is the output of the parser and is just a tree representation of the source code, containing different kinds of nodes, for example for classes, methods, variables.
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