How is it that json serialization is so much faster than yaml serialization in Python?

Question

I have code that relies heavily on yaml for cross-language serialization and while working on speeding some stuff up I noticed that yaml was insanely slow compared to other

Answer 1

In general, it's not the complexity of the output that determines the speed of parsing, but the complexity of the accepted input. The JSON grammar is very concise. The YAML parsers are comparatively complex, leading to increased overheads.

JSON’s foremost design goal is simplicity and universality. Thus, JSON is trivial to generate and parse, at the cost of reduced human readability. It also uses a lowest common denominator information model, ensuring any JSON data can be easily processed by every modern programming environment.

In contrast, YAML’s foremost design goals are human readability and support for serializing arbitrary native data structures. Thus, YAML allows for extremely readable files, but is more complex to generate and parse. In addition, YAML ventures beyond the lowest common denominator data types, requiring more complex processing when crossing between different programming environments.

I'm not a YAML parser implementor, so I can't speak specifically to the orders of magnitude without some profiling data and a big corpus of examples. In any case, be sure to test over a large body of inputs before feeling confident in benchmark numbers.

Update Whoops, misread the question. :-( Serialization can still be blazingly fast despite the large input grammar; however, browsing the source, it looks like PyYAML's Python-level serialization constructs a representation graph whereas simplejson encodes builtin Python datatypes directly into text chunks.