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As an example, let's implement conversion for https://en.cppreference.com/w/cpp/chrono/system_clock[``std::chrono::system_clock::time_point``s] using https://en.wikipedia.org/wiki/ISO_8601[ISO 8601] format.
As an example, let's implement conversion for例如，我们来使用 https://en.wikipedia.org/wiki/ISO_8601[ISO 8601]格式，对 https://en.cppreference.com/w/cpp/chrono/system_clock[``std::chrono::system_clock::time_point``s] using https://en.wikipedia.org/wiki/ISO_8601[ISO 8601] format.实现转换。
06/05/2026
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Normally, you wouldn't be able to provide conversions for types from third-party libraries and standard types, because it would require yout to put `tag_invoke` overloads into namespaces you do not control. But with contexts you can put the overloads into your namespaces. This is because the context will add its associated namespaces into the list of namespaces where `tag_invoke` overloads are searched.
Normally, you wouldn't be able to provide conversions for types from third-party libraries and standard types, because it would require yout to put `tag_invoke` overloads into namespaces you do not control. But with contexts you can put the overloads into your namespaces. This is because the context will add its associated namespaces into the list of namespaces where `tag_invoke` overloads are searched.通常，您无法为第三方库或标准库中的类型提供转换函数，因为这需要将`tag_invoke`重载放入您无法控制的命名空间中。但借助上下文，您可以将这些重载放在自己的命名空间里。这是因为上下文会将其关联的命名空间添加到搜索`tag_invoke`重载的命名空间列表中。
06/05/2026
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Conversions for Third-Party Types
Conversions for Third-Party Types第三方类型的转换
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Note, that if there is no dedicated `tag_invoke` overload for a given type and a given context, the implementation falls back to overloads without context. Thus it is easy to combine contextual conversions with conversions provided by the library:
Note, that if there is no dedicated `tag_invoke` overload for a given type and a given context, the implementation falls back to overloads without context. Thus it is easy to combine contextual conversions with conversions provided by the library:请注意，如果对于给定类型和给定上下文没有专用的`tag_invoke`重载，实现将回退到不带上下文的重载。因此，可以轻松地将上下文相关的转换与库提供的转换结合起来：
06/05/2026
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These `tag_invoke` overloads take an extra `as_string` parameter, which disambiguates this specific representation of `ip_address` from all other potential representations. In order to take advantage of them one needs to pass an `as_string` object to <<ref_value_from>> or <<ref_value_to>> as the last argument:
These 这些`tag_invoke` overloads take an extra `as_string` parameter, which disambiguates this specific representation of `ip_address` from all other potential representations. In order to take advantage of them one needs to pass an `as_string` object to <重载接受一个额外的`as_string`参数，用于将`ip_address`的这种特定表示形式与其他所有可能的表示形式区分开来。要使用这些重载，需要将`as_string`对象作为最后一个参数传递给 &lt;<ref_value_from>> or <&gt; 或 &lt;<ref_value_to>> as the last argument:&gt;：</ref_value_to></ref_value_from>
06/05/2026
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Let's implement conversion from `user_ns::ip_address` to a JSON string:
Let's implement conversion from 我们来实现从`user_ns::ip_address` to a JSON string:到JSON字符串的转换：
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= Contextual Conversions Previously in this section we've been assuming that there is a particular fitting JSON representation for a type. But this is not always the case. Often one needs to represent particular value with JSON of certain format in one situation and with another format in a different situation. This can be achieved with Boost.JSON by providing an extra argument---context.
= Contextual Conversions Previously in this section we've been assuming that there is a particular fitting JSON representation for a type. But this is not always the case. Often one needs to represent particular value with JSON of certain format in one situation and with another format in a different situation. This can be achieved with Boost.JSON by providing an extra argument---context.上下文相关的转换 此前在本节中，我们一直假定某个类型存在一种特定且合适的 JSON 表示形式。但实际情况并非总是如此。很多时候，同一个值在不同场景下需要以不同的 JSON 格式来表示。在 Boost.JSON 中，可以通过提供一个额外的参数——上下文（context）——来实现这一点。
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To avoid creating such temporaries with an incorrect {ref_memory_resource}, using <<ref_value>>'s member functions <<ref_value_emplace_array>>, <<ref_value_emplace_object>>, and <<ref_value_emplace_string>> can be helpful.
To avoid creating such temporaries with an incorrect {ref_memory_resource}, using <<ref_value>>'s member functions <为避免创建使用错误 {ref_memory_resource} 的临时对象，可以借助 &lt;<ref_value>&gt; 的成员函数 &lt;<ref_value_emplace_array>>, <&gt;、&lt;<ref_value_emplace_object>>, and <&gt; 和 &lt;<ref_value_emplace_string>> can be helpful.&gt;。</ref_value_emplace_string></ref_value_emplace_object></ref_value_emplace_array></ref_value>
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This implementation explicitly creates an <<ref_array>> rather than relying on assignment from an initializer list. But the array uses default {ref_memory_resource}, not the one used by `jv`.
This implementation explicitly creates an <<ref_array>> rather than relying on assignment from an initializer list. But the array uses default {ref_memory_resource}, not the one used by `jv`.该实现显式创建了一个 &lt;<ref_array>&gt;，而不是依赖于初始化列表的赋值。但该数组使用的是默认的 {ref_memory_resource}，而不是`jv`所使用的内存资源。</ref_array>
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``` void tag_invoke( const value_from_tag&, value& jv, ip_address const& addr ) { jv = array{ b[0], b[1], b[2], b[3] }; } ```
``` void tag_invoke( const value_from_tag&amp;, value&amp; jv, ip_address const&amp; addr ) { jv = array{ b[0], b[1], b[2], b[3] }; } ```
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For example, consider this alternative implementation of `tag_invoke` for `ip_address` from the section <<custom_conversions>>.
For example, consider this alternative implementation of `tag_invoke` for `ip_address` from the section <<例如，考虑&lt;<custom_conversions>&gt;节中针对`ip_address`的`tag_invoke`的替代实现。</custom_conversions>>.
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As the conversion result is set via an output parameter of type `value&`, the intended <<ref_storage_ptr>> is correctly propagated. But users still should take care to not create temporaries using the default {ref_memory_resource} by accident.
As the conversion result is set via an output parameter of type `value&`, the intended <<ref_storage_ptr>> is correctly propagated. But users still should take care to not create temporaries using the default {ref_memory_resource} by accident.由于转换结果是通过类型为`value&amp;`的输出参数设置的，因此预期的&lt;<ref_storage_ptr>&gt;会被正确传播。但用户仍需注意，避免意外创建使用默认 {ref_memory_resource} 的临时对象。</ref_storage_ptr>
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<<ref_value_to>> does not have a similar parameter, as <<ref_value>> is not created.
<&lt;<ref_value_to>> does not have a similar parameter, as <<ref_value>> is not created.&gt; 没有类似的参数，因为该函数不会创建 &lt;<ref_value>&gt; 对象。</ref_value></ref_value_to>
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= Allocation Control As <<ref_value_from>> creates a <<ref_value>> object, users may want to control the way memory is allocated for it. For this reason the function has an optional <<ref_storage_ptr>> parameter, that is used to set the {ref_memory_resource} for the result.
= Allocation Control As <<ref_value_from>> creates a <<ref_value>> object, users may want to control the way memory is allocated for it. For this 分配控制 由于&lt;<ref_value_from>&gt;会创建一个&lt;<ref_value>&gt;对象，用户可能希望控制其内存分配方式。因此，该函数具有一个可选的 &lt;<ref_storage_ptr>&gt; 参数，用于为结果指定{ref_memory_reason the function has an optional <<ref_storage_ptr>> parameter, that is used to set the {ref_memory_resource} for the result.urce}。</ref_storage_ptr></ref_value></ref_value_from>
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{icon_good} The fastest available JSON parser.
{icon_good} The fastest available JSON parser.为目前最快的JSON解析器。
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{icon_bad} Read-only, can only be populated by the provided SIMD JSON parser.
{icon_bad} Read-only, can only be populated by the provided为只读类型，仅能通过所提供的 SIMD JSON parser.解析器进行填充。
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{icon_bad} Sequential access only, via `ParsedJson::BasicIterator`
{icon_bad} Sequential access only, via仅支持通过 `ParsedJson::BasicIterator` 进行顺序访问
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This is quite an interesting data structure, which is optimized to work well with the SIMD parser. It makes very good design choices for the intended use-case. However it is not well suited as a vocabulary type due to the necessary limitations.
This is quite an interesting data structure, which is optimized to work well with the SIMD parser. It makes very good design choices for the intended use-case. However it is not well suited as a vocabulary type due to the necessary limitations.这是一种相当有趣的数据结构，专为与 SIMD 解析器协同工作而优化。它在目标使用场景下做出了非常优秀的设计选择。然而，由于其必要的限制，它不太适合作为通用类型。
06/05/2026

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