LevelDB supports running on various operating systems. To adapt to different operating systems, it needs to encapsulate some system calls, such as file operations, thread operations, time operations, etc. In the exposed include files, the env.h file defines various interfaces used by LevelDB. This includes the Env class, which encapsulates file operations, directory operations, etc., as well as some file abstract classes such as SequentialFile, WritableFile, and RandomAccessFile for sequential reading, random reading, and writing files.

Through abstract interfaces, LevelDB can run on different operating systems by implementing the corresponding Env subclass for each platform. This article takes the POSIX system environment as an example to first look at how the abstracted file operation-related interfaces are implemented.

In the LevelDB source code, there’s a function for getting a Comparator that seemed a bit strange when I first saw it. It looks like it constructs a singleton, but it’s slightly more complex. The complete code is as follows:

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// util/comparator.cc
const Comparator* BytewiseComparator() {
  static NoDestructor<BytewiseComparatorImpl> singleton;
  return singleton.get();
}

Here, NoDestructor is a template class that, judging by its name, is used to prevent object destruction. Why prevent object destruction, and how is it achieved? This article will delve into these questions.

Anthropic has quietly released the Claude 3.5 model, which not only improves model performance but also supports Artifacts. After initial experience, I feel this is what the future of AI should look like, even more impressive than the previous GPT4-o.

Before Artifacts, if you wanted to use ChatGPT or other LLMs to help implement program functionality, you needed to first provide the functional requirements, then copy the AI’s code into your own environment to run. If it didn’t meet expectations, you had to ask again, modify the code, and run it again. This process needed to be repeated until satisfaction or giving up (some complex code is still not well written by AI currently).