Compare performance of JSON, BespON, YAML, and TOML in Python
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Benchmark BespON in Python

Code for comparing performance of JSON, BespON, YAML, and TOML in Python. It uses whatever standard/popular Python packages are installed for these formats. All timing is performed with timeit.

Benchmark results should be interpreted with the understanding that they may be highly dependent on the form of the benchmark data. In formats in which data may have multiple representations, the exact representation used may also play a significant role.

Decoding benchmark




  • --bespon_py <path>: Use bespon package at specified path, rather than installed bespon package.
  • --timeit_number <number>: Number of times that the benchmark code is executed during each timed run (default: 1).
  • --timeit_repeat <number>: Number of timed runs that are performed per package (default: 10). The minimum time obtained for each package is reported.
  • --template_number <number>: Each package is used with a dataset that is created by concatenating a data template this many times (default: 1000). Note that the data template contains a template field {num} that is formatted with successive integers from 0 up to the number of concatenations, so that the final dataset does not contain duplicate data.
  • --py_out: By default, results are printed to stdout as a sorted table. This causes them to be printed as a string representation of a Python dict instead.

Data template: The built-in data template is a mix of dicts and lists of strings.

key{num} =
    first_subkey{num} = "Some text that goes on for a while {num}"
    second_subkey{num} = "Some more text that also goes on and on {num}"
    third_subkey{num} =
      * "first list item {num}"
      * "second list item {num}"
      * "third list item {num}"

Output: Results are printed to stdout. For example,

Python 3.6 (CPython, Linux)
json            0.0015381950000090683
yaml (CLoader)  0.05863191299999926
bespon          0.09437812199999485
toml            0.16262568400000532
pytoml          0.44667368100002136
yaml            0.9945613440000045

If --py_out is used, then the result is a string representation of a Python dict that contains complete information about the run. For example,

{'python': 'Python 3.6 (CPython, Linux)', 'template_number': 1000,
 'timeit_number': 1, 'timeit_repeat': 10,
 'results': {'json': 0.0015339250000465654, 'bespon': 0.09245784400002321,
             'yaml': 0.9864068850000081, 'yaml (CLoader)': 0.05825553699997954,
             'toml': 0.16168690499995364, 'pytoml': 0.4443770299999983}}

Notes on use

Decoding benchmarks can take a long time to run if the option --template_number is increased significantly beyond 1000 when the pytoml package is being used, due to nonlinear performance scaling.