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.