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This module provides a just-in-time compiler for HTML::Template. If your template needs to be compiled - either because it has changed or because it has never been compiled - then HTML::Template::JIT uses HTML::Template and Inline::C to compile your template to native machine instructions. The resulting compiled template is much faster than a normal cached template. Benchmarks show HTML::Template::JIT, with a precompiled template, performing 4 to 8 times faster than HTML::Template in cache mode.

Other JSON modules require setting several parameters before calling the conversion methods to do what I want. This module does things by default that I think should be done when working with JSON in Perl. This module also encodes and decodes faster than JSON.pm and JSON::Syck in my benchmarks. This means that any piece of data in Perl will get converted to something in JSON instead of throwing an exception. It also means that output will be strict JSON, while accepted input will be flexible, without having to set any options.

Sometimes you want to make sure that your "faster" algorithm really is faster than the old way. This lets you check. It might also be useful to check that your super whizzo XS or Inline::C version is actually faster. This module is based on the standard Benchmark module. If you have lots of timings to compare and you don't want to keep running the same benchmarks all the time, you can pass in a result object from Benchmark::timethis() instead of sub routine reference.

The cdecimal is a fast drop-in replacement for the decimal module in Python's standard library. Both modules provide complete implementations of the General Decimal Arithmetic Specification. Typical performance gains are between 30x for I/O heavy benchmarks and 80x for numerical programs. In a database benchmark, cdecimal exhibits a speedup of 12x over decimal.py. decimal cdecimal speedup pi 42.75s 0.58s 74x telco 172.19s 5.68s 30x psycopg 3.57s 0.29s 12x All Python versions from 2.5 up to 3.2 are supported. For the few remaining differences, read the cdecimal documentation. cdecimal has been included in Python-3.3.

paq is a family of archivers with the best lossless compression ratios now available across a wide variety of test data, according to several benchmarks. A comparison of paq to other compression methods, on a 2GHz T3200, when compressing a large text file: Format Size Time (sec) Memory comp decomp ----------- --------- -------------- ------- Uncompressed 3,152,896 compress 1,319,521 1.6 0.2 .1 MB gzip -9 1,022,810 0.7 0.1 .1 MB bzip2 -9 860,097 0.6 0.4 5 MB p7zip (7z) 824,573 1.5 0.1 195 MB xz -6 822,016 ? ? ? zpaq c1 (fast) 806,959 2 2 38 MB zpaq c2 (mid) 699,191 8 8 112 MB zpaq c3 (max) 644,190 20 20 246 MB The port uses the open ZPAQ specification, and contains: a public-domain C++ API for reading and writing ZPAQ compressed data to or from files or objects in memory; serial and multi-threaded archivers; extra preprocessors for compression; and stubs for creating self-extracting archives.