二进制解析器还是序列化？
我想存储游戏中不同对象的图表，它们的类可能相关也可能不相关，它们可能包含也可能不包含简单结构的向量。
- 我希望解析操作能够很快，数据可以很大。
- 添加新东西不应该很困难，也不应该破坏向后兼容性。
- 较小的文件大小很重要
- 可读性计数
我的意思是，使对象序列化自己，这是有效的，但我需要为此为不同的对象编写不同的序列化方法。
通过二进制解析/组合，我的意思是，创建一个新的解析器/组合器树来保存和读取这些对象的数据，并将其传递给我的对象推/拉它们的数据。
我也可以使用 json，但它的读取速度可能相当慢，而且当涉及相当大的矩阵和数字集时，它的大小效果不是很好。
I want to store a graph of different objects for a game, their classes may or may not be related, they may or may not contain vectors of simple structures.
- I want parsing operation to be fast, data can be pretty big.
- Adding new things should not be hard, and it should not break backward compatibility.
- Smaller file size is kind of important
- Readability counts
By serialization I mean, making objects serialize themselves, which is effective, but I will need to write different serialization methods for different objects for that.
By binary parsing/composing I mean, creating a new tree of parsers/composers that holds and reads data for these objects, and passing this around to have my objects push/pull their data.
I can also use json, but it can be pretty slow for reading, and it is not very size effective when it comes to pretty big sets of matrices, and numbers.
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评论（3）
逐点：
因此，文本为三票，二进制为一票。就我个人而言，除了图像（以及“自然”二进制的其他数据）之外，我会使用文本来表示所有内容。然后，将所有内容存储在一个大的 zip 文件中（我可以想到有几个游戏会这样做或类似的事情）。
好读物：文本化的重要性和纯文本的力量。
Point by point:
So that's three votes for text, one point for binary. Personally, I'd go with text for everything except images (and other data which is "naturally" binary). Then, store everything in a big zip file (I can think of several games do this or something close to it).
Good reads: The Importance of Being Textual and Power Of Plain Text.
查看 Google 的协议缓冲区或 Apache 的 thrift。虽然它被宣传为一种轻松编写有线协议的方法，但它基本上是一种对象序列化机制，可以用多种语言创建绑定，具有高效的二进制表示、简单的版本控制、快速的性能，并且得到良好的支持。
Check out protocol buffers from Google or thrift from Apache. Although billed as a way to write wire protocols easily, it's basically an object serialization mechanism that can create bindings in a dozen languages, has efficient binary representation, easy versioning, fast performance, and is well-supported.
我们正在使用 Boost.Serialization。不知道它与 samkass 提供的产品相比表现如何。
We're using Boost.Serialization. Don't know how it performs next to those offered by samkass.