NAME Data::Clean::JSON - Clean data so it is safe to output to JSON VERSION version 0.14 SYNOPSIS use Data::Clean::JSON; my $cleanser = Data::Clean::JSON->get_cleanser; my $data = { code=>sub {}, re=>qr/abc/i }; my $cleaned; # modifies data in-place $cleaned = $cleanser->clean_in_place($data); # ditto, but deep clone first, return $cleaned = $cleanser->clone_and_clean($data); # now output it use JSON; print encode_json($cleaned); # prints '{"code":"CODE","re":"(?^i:abc)"}' DESCRIPTION This class cleans data from anything that might be problematic when encoding to JSON. This includes coderefs, globs, and so on. Data that has been cleaned will probably not be convertible back to the original, due to information loss (for example, coderefs converted to string "CODE"). The design goals are good performance, good defaults, and just enough flexibility. The original use-case is for returning JSON response in HTTP API service. This module is significantly faster than modules like Data::Rmap or Data::Visitor::Callback because with something like Data::Rmap you repeatedly invoke callback for each data item. This module, on the other hand, generates a cleanser code using eval(), using native Perl for() loops. If "LOG_CLEANSER_CODE" environment is set to true, the generated cleanser code will be logged using Log::Any at trace level. You can see it, e.g. using Log::Any::App: % LOG_CLEANSER_CODE=1 TRACE=1 perl -MLog::Any::App -MData::Clean::JSON \ -e'$c=Data::Clean::JSON->new; ...' METHODS CLASS->get_cleanser => $obj Return a singleton instance, with default options. Use "new()" if you want to customize options. CLASS->new(%opts) => $obj Create a new instance. For list of known options, see Data::Clean::Base. Data::Clean::JSON sets some defaults. DateTime => [call_method => 'epoch'] Regexp => ['stringify'] SCALAR => ['deref_scalar'] -ref => ['replace_with_ref'] -circular => ['replace_with_str', 'CIRCULAR'] -obj => ['unbless'] $obj->clean_in_place($data) => $cleaned Clean $data. Modify data in-place. $obj->clone_and_clean($data) => $cleaned Clean $data. Clone $data first. ENVIRONMENT LOG_CLEANSER_CODE FAQ Why clone/modify? Why not directly output JSON? So that the data can be used for other stuffs, like outputting to YAML, etc. Why is it slow? If you use "new()" instead of "get_cleanser()", make sure that you do not construct the Data::Clean::JSON object repeatedly, as the constructor generates the cleanser code first using eval(). A short benchmark (run on my slow Atom netbook): % bench -MData::Clean::JSON -b'$c=Data::Clean::JSON->new' \ 'Data::Clean::JSON->new->clone_and_clean([1..100])' \ '$c->clone_and_clean([1..100])' Benchmarking sub { Data::Clean::JSON->new->clean_in_place([1..100]) }, sub { $c->clean_in_place([1..100]) } ... a: 302 calls (291.3/s), 1.037s (3.433ms/call) b: 7043 calls (4996/s), 1.410s (0.200ms/call) Fastest is b (17.15x a) Second, you can turn off some checks if you are sure you will not be getting bad data. For example, if you know that your input will not contain circular references, you can turn off circular detection: $cleanser = Data::Clean::JSON->new(-circular => 0); Benchmark: $ perl -MData::Clean::JSON -MBench -E ' $data = [[1],[2],[3],[4],[5]]; bench { circ => sub { state $c = Data::Clean::JSON->new; $c->clone_and_clean($data) }, nocirc => sub { state $c = Data::Clean::JSON->new(-circular=>0); $c->clone_and_clean($data) } }, -1' circ: 9456 calls (9425/s), 1.003s (0.106ms/call) nocirc: 13161 calls (12885/s), 1.021s (0.0776ms/call) Fastest is nocirc (1.367x circ) The less number of checks you do, the faster the cleansing process will be. Why am I getting 'Not a CODE reference at lib/Data/Clean/Base.pm line xxx'? [2013-08-07 ] This error message is from Data::Clone::clone() when it is cloning an object. If you are cleaning objects, instead of using clone_and_clean(), try using clean_in_place(). Or, clone your data first using something else like Storable. SEE ALSO Data::Rmap Data::Visitor::Callback HOMEPAGE Please visit the project's homepage at . SOURCE Source repository is at . BUGS Please report any bugs or feature requests on the bugtracker website When submitting a bug or request, please include a test-file or a patch to an existing test-file that illustrates the bug or desired feature. AUTHOR Steven Haryanto COPYRIGHT AND LICENSE This software is copyright (c) 2014 by Steven Haryanto. This is free software; you can redistribute it and/or modify it under the same terms as the Perl 5 programming language system itself.