Davide Conti > Data-Generate-0.02 > Data::Generate

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NAME ^

Data::Generate - Create various types of synthetic data by parsing "regex-like" data creation rules.

VERSION ^

Version 0.02

SYNOPSIS ^

 use Data::Generate;
 #----------------------------------------#
 #                 Example 1              #
 #----------------------------------------# 

 # Output type is varchar with maxlength 2. 
 # Output data should be letters from q to z.
 my $input_rule = q { VC(2) [q-z]}; 

 # parse the rule and return a generator object if rule is valid.
 my $generator= Data::Generate::parse($input_rule) or die "error".$!;

 # prints the maximal number of unique data that can be generated.
 print $generator->get_degrees_of_freedom(); 

 # create a dataset on the fly and return it in an array of scalars.
 my $Data= $generator->get_unique_data(10); 
 # --> $Data contains ['q','r','s','t','u','v','w','x','y','z']; 

 #----------------------------------------#
 #                 Example 2              #
 #----------------------------------------#

 # ... a more complex example ...
 # generate varchar data with 2 kinds of values:
 #   -> 36% values like ( 12222,15222, ...)
 #   -> 64% values like (AAXQ,BAXQ,...) 
 my $input_rule = q { 
     VC(24) [14][2579]{4}       (36%) 
            | [A-G]{2}[X-Z][QN] (64%)  
    };

 my $generator= Data::Generate::parse($input_rule);
 my $Data= $generator->get_unique_data(10); 
 ...


 #----------------------------------------#
 #                 Example 3              #
 #----------------------------------------#

 # ... an example with dates ...
 # generate a range of dates:
 my $input_rule = q { 
     DATE '1999' 'nov' [07,thu-fri] '09' : '09' : '09'  
 };
 my $generator= Data::Generate::parse($input_rule);
 my $Data= $generator->get_unique_data(10); 
 #   -> returns a set of date values (format 'YYYYMMDD HH:MI:SS') 
 #      corresponding to  the 7th and all Thursdays and Fridays 
 #      of November 1999.    

FUNCTIONS ^

parse(rules)
  Parse given data generation rules and load them into a Data::Generate object.
  Return either an error or a Data::Generate object.

METHODS ^

$self->get_degrees_of_freedom()
  Return an integer scalar containig the maximal number of unique values 
  that can be produced from the current Data::Generate object.  
$self->get_unique_data(nr_of_values)
  Return an array of unique values with "nr_of_values" elements.
  Issue a warning and produce only $self->get_degrees_of_freedom() values
  if nr_of_values > $self->get_degrees_of_freedom(). 

DESCRIPTION ^

This module generates data by parsing given text statements (data creation rules). These statements are flexible and powerful regex-like way to control the production of synthetic data. Think about a program that instead of selecting data which matches a regex filter expression, produces it. For example, from the rule [a-c], the generator would produce the array a,b,c. The module works as following:

Specify data creation rules.

my $generator= Data::Generate::parse('VC(24) [0-9][2-3]');

At this step first you define one kind of output datatype (for ex. VC(24)= "output is a string with max length 24") and then with the rest of the expression define what it should look like. If parsing is successful a Data Generator object is instantiated.

Get data

my $Data= $generator->get_unique_data(10);

To really get the data, users must call the get_unique_data method by indicating the desired number of output values. The generator returns the values contained in an array reference. Please remark that output format is fixed according to the data type.

DESIGN CONCEPTS ^

This module has been designed so that the returned output array fulfills the following characteristics by efficient memory usage (i.e. no internal generation of output values before knowing the number of rows that should be produced). These are:

Uniqueness The returned output array should be composed of the unique values (so that it can for example be used to fill a primary key of a table).
Defined cardinality. Given a set of data generation rules, the maximal number of rows should be predictable in advance, so that for ex., when generated values are dependent from each other (see for ex. foreign key dependency in databases), one can predict the cardinality without getting all values before.
Flat random data distribution Distrubution of output values should be flat over all possibilities, despite the existence of any internal structure.
Data distribution accuracy When you have a data generation statement with multiple rules, relative weight between the rules should be (as far as possible) respected (see example 2 above).

To achieve this, during rule parsing, the module resolves each term internally to a list which contains all possible matching values. For example if it has to parse the expression:

 ...[A-C] [1-9]... 

the program expands and keeps in memory the two separate value lists:

 (A,B,C) and (1,2,3,4,5,6,7,8,9).

If data has to be produced, the generator randomly picks up an element from each list and it produces the output value by concatenating all chosen elements together (as a kind of cross product). For example, when asked to produce 4 values based on the expression [A-C] [1-9], the generator goes through the two lists (A,B,C) and (1,2,3,4,5,6,7,8,9) and it produces the output by picking up random combinations (ex. 'B5', 'A1','C7' and 'A2').

ERROR HANDLING

Uniqueness and other characteristics of the data can sometimes be broken very easily by accidental erros in user's statements. Consider for example the expression below (integer type).

 ...[0-1] [0,10] ... 

In this case, if a string type would be used, we could get the values:

 '00','10','110','010'

however, if a numeric type is used, we only get the values:

 0,10,110

this is because the program recognizes 010 and 10 as equivalent in respect to integers and removes automatically 010 from the output values. Users not aware of this behaviour are likely to overestimate the maximal number of available unique data. To prevent this kind of errors, the program checks user entries against boundary constraints (uniqueness, cardinality, etc.) and tries to fix these problems by himself (it generates however a warning to inform the user).

BASIC SYNTAX ^

BASIC SYNTAX, TYPE DECLARATION

The high-level syntax of data creation rules is the combination of following elements:

STATEMENT: TYPE DECLARATION RULE [WEIGTH] [| RULE [WEIGTH] ...] ;

With the type declaration you fix the kind of datatype (string,varchar, integer,date or float) that should be produced. The general form above is preserved for all types, however each type has its own specific syntax rules. The (type dependent) data output format is always fixed. We'll come back to these types more in details later.

RULES

The next element, the data creation rules is the combination of one or more terms. White spaces are used as separators between terms:

RULE: TERM [ TERM ...]

Term expressions are the lowest level syntax elements. This can be a direct literal value (see for example later quoted string expressions), or a range of values. When the program generates the output, it concatenates all term expressions of a rule together (like a kind of AND operation).

With the pipe (|) operator you can assign multiple rules to the same output result. The generator in this case, produces the output values by alternatively applying the assigned rules (like a kind of OR operation). In addition you can pass a weigth parameter (syntax: (<percent_value>%)), to control how much one or the other rule should be used to produce output data.For example, the statement:

  'VARCHAR(2)[0-9](15.5%)|[A-Z](84.5%);' 

produces a data distribution with about 15% of the values as numbers between 0 and 9 and the rest as the letters from A to Z.

TERM EXPRESSIONS

Term expressions are in general datatype dependent, however some basic elements are common to several types. These are:

File lists. Syntax: '<'file_path'>'

File lists can be used for all datatypes. With this statement you let the program load a file as a list of values.In this case the program goes through all file records and takes those which match the given datatype.

Ranges. Syntax: { '['low-high']' | '['low..high']' | '['value1,value2,value3']' | ... etc .}

Range expressions are quick and powerful way to generate a list of values. For string types in particular, the syntax is similar to regular expressions as shown in examples below:

  ...[A-C]...

returns the characters 'A','B','C'

  ...[Ace]...

returns the characters 'A','c','e'

  ...[^A-Z]...

returns anything (^ operator) except all uppercase characters. See leter for an exact description of range syntax for each type.

Literals. Syntax: 'value'

Here the program just takes the quoted string and concatenates to the other terms. Literal values are very useful if you need to pre- or postfix the generated values with some predetermined character sequence.Example:

  ...'0x' [A-C]...

returns the values '0xA','0xB','0xC'

Additional Elements, Quantifiers.Syntax: TERM '{'nr of repetitions'}'

For many kinds of terms you can give a repetition parameter (<quantifier>). In this case the term expression is repeated according to the quantifier. Altough this concept is borrowed from regular expression, here the quantifier is fixed and has to be an unsigned integer number. Quantifiers can be very practical as following example shows:

  ...[0-1]{8}...

returns the binary representation of numbers from 0 to 256.

For some datatypes (strings) you can use quantifiers for all kinds of terms, also including the lists but for others you cannot. We'll now describe the syntax rules of each type in depth.

STRING TYPE SYNTAX. ^

STATEMENT: 'STRING' strrule [weigth] [| strrule [weigth] ...];

strrule: strterm ['{'quantifier'}'] [ strterm ['{'quantifier'}'] ...]

strterm: { integer | literal | range | filelist}

String types allow the most flexibility in the combination of terms (for each term type you can use quantifiers). In addition no fixed length is required (no type length checking). Here the detailed description of all string terms:

Integer. Syntax: '['number1..number2']' ['{'quantifier'}'].

This expression is a kind of specialized range term and it returns a range of consecutive numbers between number1 and number2 (with optional quantifier) For example:

 STRING [9..11]{2} 

returns the numeric strings '99','910','911','109','1010','1011','119' ,'1110','1111'

Literals. Syntax: 'value' ['{'quantifier'}'].

The quoted string is just taken over and concatenated to the other terms.

Ranges. Syntax: ... see regex syntax for '[' ... ']' expressions.

As stated before the syntax of these expressions in string content is very close to regex syntax. There are however following differences:

  1.Quantifers must be a unsigned integer value. For ex. [0-1]{12} 
  is allowed but [0-1]{1..12} is forbidden.

  2.You cannot use character classes (\d,\D,\w,\W,etc).

See also examples at the end of the string type section.

Filelists. Syntax: '<'file_path'>'.

File records are loaded without special checks, quantifiers allowed.

Examples:

  my $generator=parse(q{STRING [0-1] 'AX'{2}});
  print $generator->get_unique_data(2);
  # ...returns '0AXAX', '1AXAX'.

  my $generator=parse(q{STRING [AB1-2]{2}});
  print $generator->get_unique_data(8);
  # ...returns 'AA','AB','A1','A2','BA',... 

  my $generator=parse(q{ <./family_name> <./first_name> });
  print $generator->get_unique_data(10);
  # ...combines two lists togehter   

VARCHAR TYPE SYNTAX. ^

STATEMENT: { 'VARCHAR'|'VARCHAR2'|'VC'} '('length')' strrule [weigth] [| strrule [weigth] ...];

Varchar types have the same syntax as string types, except in the declaration, where they require a maxlength parameter.The maxlength parameter works in the following way:

  At runtime the program checks if the output string becomes longer than 
  the maxlength. If that is the case, then the program cuts the last 
  part of the string and generates a warning.  

Example:

  my $generator=parse(q{VC(4) [0-1]{5}});
  print $generator->get_unique_data(4);
  # ...returns '0000', '0001', etc. instead of '00000', '00001'....
  # and generates a warning due to the truncated values 

INTEGER TYPE SYNTAX. ^

STATEMENT: 'INTEGER' '(' length ')' intrule [weigth] [| intrule [weigth] ...];

intrule: [ '+' | '-' | '+/-' ] integer-term [ '{' quantifier '}' ] [ integer-term [ '{' quantifier '}' ] ...]

integer-term: { numeric-range | numeric-literal | filelist}

Integer type declaration requires a length parameter.Unfortunately (due to the internal representation of perl integers) the maximal allowed length here is 9 digits.

Particularity with integers (and floats too) is the optional +/- sign at the beginning, which controls wheter positive or negative numbers (or both signs) should be generated.

Integer and all other kinds of numeric datatypes use a specialized version of term expressions. These are numeric ranges and numeric literals. These terms have following characteristics:

1.Syntax:

- numeric-literals: value.

- numeric--ranges: '[' {lowvalue '-' highvalue | value } [ ',' {lowvalue '-' highvalue | value } ... ]']'

2.Values inside numeric ranges and numeric literals must be unsigned integer numbers (0,1,2,..etc).

3.Values are unquoted everywhere.

4.Values in numeric ranges must be separated by a period (i.e. here for a range with the numbers 2,25 you write [2,25] and not [2 25] or [225]).

For integers you can also use filelists at term-level (see later the difference with float filelists). Syntax:

'<'file_path'>'['{'quantifier'}'].

Here file data records have to be unsigned integer numbers (other records get discarded by the program after the file gets loaded).

For integer datatypes, as for strings, quantifiers are allowed for all kinds of terms.

Please remark also that, due to the numeric nature of integer types, superfluos leading zeros must be taken away from the output values (see also "DESIGN CONCEPTS").In addition, for positive numbers, the + sign is also removed from output values.

Examples:

  my $generator=parse(q{INT (9) +/- 0 [0,3]{2} });
  print $generator->get_unique_data(7);
  # ...returns 0,3,30,33,-3,-30-33  
  # .ie. no leading zeros, no leading '+' sign 

FLOAT TYPE SYNTAX. ^

STATEMENT: 'FLOAT' '(' length ')' { floatrule | float-filelist} [weigth] [| { floatrule | float-filelist}[weigth] ...];

float-filelist: '<'file_path'>'

floatrule: int_part fraction_part [exponent_part]

int_part: [ '+' | '-' | '+/-' ] integer-term [ '{' quantifier '}' ] [ integer-term [ '{' quantifier '}' ] ...]

integer-term: { numeric-range | numeric-literal }

fraction_part: '.' fractterm [ '{' quantifier '}' ] [ fractterm [ '{' quantifier '}' ] ...]

fractterm: { numeric-range | numeric-literal }

exponent_part: { 'E' [ '+' | '-' ] exponent_number

Floats are quite complex numeric types. You can however decompose float syntax into these main parts:

Type declaration.Float type declaration ('FLOAT (length)' ) requires a length parameter.As integer types there is a limit (14 digits without sign and period) to the maximal length that can be used for a float number.
Leading part. The syntax of the leading part (which is everything on the mantissa after the declaration and before the decimal point) follows the syntax of integer datatypes with the exception that you cannot use file lists at term level. For the rest see the description of numeric ranges and numeric literals above and the examples below.
Fractional part. In the fractional part (everything on the mantissa after the decimal point) you can only use numeric ranges and numeric literals. Please notice that for this kind of data the module handles zero's in opposite way as for integer types:

While in integer expressions, leading zeros required a special treatment (because for example 01 and 1 are the same number), in fractional expressions we have to take care of the trailing zeros (because for example 1.010 and 1.01 are the same number).

Exponent part. In the exponent part you can only use finite integer numbers ('E +3','E -5' ...). This part is an optional component.See examples.

ADDITIONAL REMARKS ON FLOATS

File lists Oppositely to previous datatypes,you cannot use file lists at term level, instead (because of the complexity of float numbers) you can only use them at rule level. In this case, while parsing a file, the modules tries to convert each record into a float value or skip it when conversion fails.
Output data Before generating output, the modules tries to compact generated data as much as possible. That means that superflous +signs,exponents and decimal points are eliminated from output values. For ex. if the number zero was entered as '-0.000 E + 14' the module returns just '0'.

Examples:

  my $generator=parse(q{ FLOAT (9) +/- [3,0]{2} . [0,5]{2}});
  print $generator->get_unique_data(10);
  # ...returns -33.55,-33.05,-33,...,-0.05,0,0.05,...,33.55

  my $generator=parse(q{ FLOAT (9)  <./float_list.txt> );
  # ...tries to load all records of the file as float values.
  # Please remark here the monolithic syntax (file lists at rule level): 
  #   no leading +/- sign, no trailing exponent, no decimal point. 

  my $generator=parse(q{ FLOAT (9) - 1  . [1,2] (50%)| + 3  . 0 [0,6] (50%)});
  print $generator->get_unique_data(4);
  # ...returns -1.2,-1.1,3,3.06

DATE TYPE SYNTAX ^

STATEMENT: 'DATE' ['(' precision ')'] { daterule | date-filelist} [weigth] [| { daterule | date-filelist}[weigth] ...];

date-filelist: '<'file_path'>'

daterule: date-part [ time-part ['.' time-fraction-part] ]

date_part: year-term month-term day-term

year-term: { numeric-range | numeric-literal }

month-term: { month-range | month-value }

month-range: '[' {month-lowvalue '-' month-highvalue | month-value } [ ',' {month-lowvalue '-' month-highvalue | month-value } ... ]']'

month-(low,high)value: { "a number between 1 and 12" | "any valid literal expression for a month (ex. 'jan' for january)" }

day-term: { day-range | day-literal }

day-range: '[' {day-lowvalue '-' day-highvalue | day-value } [ ',' {day-lowvalue '-' day-highvalue | day-value } ... ]']'

day-(low,high)value: { "a number between 1 and 31" | "any valid literal expression for a weekday (ex. 'sat' for saturday)" }

time-part: hour-term ':' minute-term ':' second-term

hour-term: { numeric-range | numeric-literal }

minute-term: { numeric-range | numeric-literal }

second-term: { numeric-range | numeric-literal }

time-fraction-part: '.' fraction [ '{' quantifier '}' ] [ fraction [ '{' quantifier '}' ] ...]

fraction: { numeric-range | numeric-literal }

Dates are the most complex datatypes, because they are built up by several components. Dates have following basic characteristics:

Examples:

  my $generator=parse(q{ 
      DATE [1985-1986][01-3][2-4] [11-15] : [11-15] : [11-15] (50%) |
        '1998' [01-03,08-09]  [07-15,22] '11' : '12' : '24' (25%) |
       [2001,2006][09,nov][07,mon,thu-fri] '09' : '09' : '09' (25%) });

  print $generator->get_unique_data(...);
  # ... returns three different datasets with 1/2 having the dates 1985-1986, 
  # ... 1/4 for the year 1998 and 1/4 for the years 2001 and 2006.

INTERNAL METHODS ^

Here a list of the internal methods of the module. These methods are not supposed to be called by the user.

- add_term_range
- add_value_column
- add_weekday_term_range
- bind_actual_vchain
- bind_actual_vcol
- bind_vchain
- bind_vcol_literal
- bind_vcol_range
- calculate_degrees_of_freedom
- calculate_occupation_levels
- calculate_vchain_list_degrees_of_freedom
- calculate_vchain_list_weigth
- calculate_weigth
- check_input_card
- check_input_limits
- check_range_order
- check_reverse_flag
- fisher_yates_shuffle
- get_value_column_reverse
- is_valid
- map_vchain_indexes
- merge_vchain_float_lists
- new
- load_parser
- reset_actual_vchain
- reset_actual_vcol
- set_occupation_ratio
- vchain_date_fraction_process
- vchain_float_process
- vchain_fraction_process
- vchain_integer_process
- vchain_number_reprocess
- vcol_chain
- vcol_date_process
- vcol_file_process

DEPENDENCIES ^

Please install following libraries previous running this module:

- Parse::RecDescent
- Date::Parse
- Date::DayOfWeek

TODO ^

- Integration of more datatypes (Bigint,etc).
- Integration of character classes (\w,\d, etc).
- Better descriptions for warnings and fatal errors.
- Create a method get_nonunique_data .

BUGS ^

- Special characters ("\n",etc.) are not always handled correctly.
- When using numeric files lists in combination with numeric types, not-numbers (ex 'A') are converted to 0. It would be better if they were skipped.

CAVEATS ^

When multiple rules are used (ex ... [14] (36%)|[1-2](64%) ... ) duplicates are only detected at the end, just before output creation. This effect may lead to wrong cardinality and to wrong data distributions. When this happens the program generates a warning.

HISTORY ^

- 0.01 Initial version
- 0.02 Correct bug in calculation of degrees of freedom

ACKNOWLEDGEMENTS ^

 Many thanks to Slawa Kopytek <skopytek@gmail.com> who had the patience to 
 read and correct my 'swiss-italian' english documentation.

AUTHOR ^

 Davide Conti <daconti.mail@gmail.com>

 Copyright (C) 2006 Davide Conti <daconti.mail@gmail.com>
 All rights reserved.

 You may distribute this package 
 under the terms of the Artistic License.

 No WARRANTY whatsoever.
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