We do our best to reduce file size without quality loss and without reducing visual quality. There appears to be a roughly 5-10% speed advantage over the standard library when comparing at similar compression levels. ![]() You can draw your own conclusions on what would be the most expensive for your case. For a web server, this means you can serve 88% more data, but have to pay for 6% more bandwidth. Looking at level 6, this package is 88% faster, but will output about 6% more data. In this case it is a collection of Go precompiled objects. This test is for typical data files stored on a server. ![]() The only downside is that it might skip some compressible data on false detections. Obviously there is no reason for the algorithms to try to compress input that cannot be compressed.
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