Data::Maker - Simple, flexibile and extensible generation of realistic data


An extremely basic example:

  use Data::Maker;

  my $maker = Data::Maker->new(
    record_count => 10_000,
    fields => [
      { name => 'phone', format => '(\d\d\d)\d\d\d-\d\d\d\d' } 

  while (my $record = $maker->next_record) {
    print $record->phone->value . "\n";

A more complete example:

  use Data::Maker;
  use Data::Maker::Field::Person::LastName;
  use Data::Maker::Field::Person::FirstName;

  my $maker = Data::Maker->new(
    record_count => 10_000,
    delimiter => "\t",
    fields => [
        name => 'lastname', 
        class => 'Data::Maker::Field::Person::LastName'
        name => 'firstname', 
        class => 'Data::Maker::Field::Person::FirstName'
        name => 'phone', 
        class => 'Data::Maker::Field::Format',
        args => {
          format => '(\d\d\d)\d\d\d-\d\d\d\d',

  while (my $record = $maker->next_record) {
    print $record->delimited . "\n";



Whatever kind of test or demonstration data you need, Data::Maker will help you make lots of it.

And if you happen to need one of the various types of data that is available as predefined field types, it will be even easier.


Data::Maker was not specifically designed for performance, though obviously performance is a consideration.

My latest benchmarking has generally been around 200 records per second, for a fairly typical assortment of fields, but obviously this varies with different types of fields and certainly with different quantities of fields.

I think it's a good idea to benchmark each field type. I added most of them to a benchmarking script that creates a certain number of records (in this case 250) with one field at a time, and then that same number of records with all of the fields in it. Obviously the time required to generate an entire record increases with each field that is added.

Here are those results (new benchmarks based on version 0.20):

  Data::Maker::Field::Format                          2891.54 records/s
  Data::Maker::Field::Person::FirstName               3709.70 records/s
  Data::Maker::Field::Person::LastName                3753.64 records/s
  Data::Maker::Field::Code                            3706.50 records/s
  Data::Maker::Field::Person::Gender                  3546.64 records/s
  Data::Maker::Field::DateTime                         422.07 records/s
  Data::Maker::Field::Lorem                           3474.74 records/s
  Data::Maker::Field::Person::SSN                     2947.59 records/s
  Data::Maker::Record (with all of the above fields)   375.29 records/s

These benchmarks were run on a 2.66 GHz Intel Core 2 Duo MacBook Pro with 4 GB of memory. In the future I will benchmark additional hardware and put that information in another document.

To run the same benchmarks yourself, run the t/ script.

I recently heard about Data::Faker, which seems to have had similar goals. I had not heard of Data::Faker when I first published Data::Maker and, at the time of this writing, Data::Faker has not been updated in four and a half years.



Returns a new Data::Maker object. Any PARAMS passed to the constructor will be set as properties of the object.


random LIST

Just makes a quick random selection from a list of choices. It's just like calling Perl's `rand()` without having to mention the list more than once, and just like using Data::Maker::Field::Set with less syntax (and it works where using a Field subclass would not be appropriate). A good use of this (and the reason it was written) is when you want a random number of records created. You can set record_count to generate a random number of records between 3 and 19 with this code:

  $maker->record_count( Data::Maker->random(3..19) );



The BUILD method is a Moose thing. It is run immediately after the object is created. Currently used in Data::Maker only to seed the randomness, if a seed was provided.

field_by_name NAME

Given the name of a field, this method returns the Field object


This method not only gets the next record, but it also triggers the generation of the data itself.

in_progress NAME

This method is used to get the already-generated value of a field in the list, before the entire record has been created and blessed as a Record object. This was created for, and is mostly useful for, fields that depend upon the values of other fields. For example, the Data::Maker::Field::Person::Gender class uses this, so that the gender of the person will match the first name of the person.

Prints out a delimited list of all of the labels, only if a delimiter was provided to the Data::Maker object

add_field HASHREF

Takes a hashref that describes a field attribute and adds it to the field list


The following Moose attributes are used (the data type of each attribute is also listed):

fields (ArrayRef[HashRef])

A list of hashrefs, each of which describes one field to be generated. Each field needs to define the subclass of Data::Maker::Field that is used to generate that field. The order of the fields has some relevance, particularly in the context of Data::Maker::Record. For example, the delimited method returns the fields in the order in which they are listed here.

Note: It may make more sense in the future for each field to have a "sequence" attribute, so methods such as delimited would return then in a different order than that in which they are generated. The order in which fields are generated matters in the event that one field relies on data from another (for example, the Data::Maker::Field::Person::Gender field class relies on a first name that must have already been generated).

record_count (Num)

The number of records desired

data_sources (HashRef)

Used internally by Data::Maker. It's a hashref to store open file handles.

record_counts (HashRef)

A hashref of record counts. Not sure why this was used. It's mentioned in Data::Maker::Field::File


The optional delimiter... could be anything. Usually a comma, tab, pipe, etc

generated (Num)

Returns the number of records that have been generated so far.

seed (Num)

The optional random seed. Provide a seed to ensure that the randomly-generated data comes out the same each time you run it. This is actually super-cool when you need this kind of thing.


Thanks to my employer, Informatics Corporation of America, for its commitment to Perl and to giving back to the Perl community. Thanks to Mark Frost for the idea about optionally seeding the randomness to ensure the same output each time a program is run, if that's what you need to do. Thanks to Adam Corum for a very useful idea about how to do numeric ranges more efficiently than my boneheaded idea.


John Ingram (


Copyright 2010 by John Ingram. All rights reserved. This program is free software; you can redistribute it and/or modify it under the same terms as Perl itself.