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Walter Lozano authored
YAML is a nice format, very easy to read, unfortunately the Python YAML library is very inefficient both CPU and memory wise. Loading the same content using JSON takes 10 times less memory and time. Since dashboard is always struggling with OOM, let's use JSON for the data it produces. As reference, below results of importing a 10 MB file with YAML and JSON are presented yaml-json $ ./test.py yaml Time 15.507138013839722 seg Memory (70914086, 394044198) bytes (current, peak) yaml-json $ ./test.py json Time 0.6210496425628662 seg Memory (58913059, 67501787) bytes (current, peak) Signed-off-by:
Walter Lozano <walter.lozano@collabora.com>
Walter Lozano authoredYAML is a nice format, very easy to read, unfortunately the Python YAML library is very inefficient both CPU and memory wise. Loading the same content using JSON takes 10 times less memory and time. Since dashboard is always struggling with OOM, let's use JSON for the data it produces. As reference, below results of importing a 10 MB file with YAML and JSON are presented yaml-json $ ./test.py yaml Time 15.507138013839722 seg Memory (70914086, 394044198) bytes (current, peak) yaml-json $ ./test.py json Time 0.6210496425628662 seg Memory (58913059, 67501787) bytes (current, peak) Signed-off-by:
Walter Lozano <walter.lozano@collabora.com>