Data::Google::Visualization::DataTable - Easily create Google DataTable objects


Data-Google-Visualization-DataTable documentation Contained in the Data-Google-Visualization-DataTable distribution.

Index


Code Index:

NAME

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Data::Google::Visualization::DataTable - Easily create Google DataTable objects

VERSION

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version 0.08

DESCRIPTION

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Easily create Google DataTable objects without worrying too much about typed data

OVERVIEW

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Google's excellent Visualization suite requires you to format your Javascript data very carefully. It's entirely possible to do this by hand, especially with the help of the most excellent JSON::XS but it's a bit fiddly, largely because Perl doesn't natively support data types and Google's API accepts a super-set of JSON - see JSON vs Javascript below.

This module is attempts to hide the gory details of preparing your data before sending it to a JSON serializer - more specifically, hiding some of the hoops that have to be jump through for making sure your data serializes to the right data types.

More about the Google Visualization API.

Every effort has been made to keep naming conventions as close as possible to those in the API itself.

To use this module, a reasonable knowledge of Perl is assumed. You should be familiar with Perl references (perlreftut) and Perl objects (perlboot).

SYNOPSIS

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 use Data::Google::Visualization::DataTable;

 my $datatable = Data::Google::Visualization::DataTable->new();

 $datatable->add_columns(
 	{ id => 'date',     label => "A Date",        type => 'date', p => {}},
 	{ id => 'datetime', label => "A Datetime",    type => 'datetime' },
 	{ id => 'timeofday',label => "A Time of Day", type => 'timeofday' },
 	{ id => 'bool',     label => "True or False", type => 'boolean' },
 	{ id => 'number',   label => "Number",        type => 'number' },
 	{ id => 'string',   label => "Some String",   type => 'string' },
 );

 $datatable->add_rows(

 # Add as array-refs
 	[
 		{ v => DateTime->new() },
 		{ v => Time::Piece->new(), f => "Right now!" },
 		{ v => [6, 12, 1], f => '06:12:01' },
 		{ v => 1, f => 'YES' },
 		15.6, # If you're getting lazy
 		{ v => 'foobar', f => 'Foo Bar', p => { display => 'none' } },
 	],

 # And/or as hash-refs (but only if you defined id's for each of your columns)
 	{
 		date      => DateTime->new(),
 		datetime  => { v => Time::Piece->new(), f => "Right now!" },
 		timeofday => [6, 12, 1],
 		bool      => 1,
 		number    => 15.6,
 		string    => { v => 'foobar', f => 'Foo Bar' },
 	},

 );

 # Get the data...

 # Fancy-pants
 my $output = $datatable->output_javascript(
 	columns => ['date','number','string' ],
 	pretty  => 1,
 );

 # Vanilla
 my $output = $datatable->output_javascript();

COLUMNS, ROWS AND CELLS

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We've tried as far as possible to stay as close as possible to the underlying API, so make sure you've had a good read of: Google Visualization API.

Columns

Columns are specified using a hashref, and follow exactly the format of the underlying API itself. All of type, id, label, pattern, and p are supported. The contents of p will be passed directly to JSON::XS to serialize as a whole.

Rows

A row is either a hash-ref where the keys are column IDs and the values are cells, or an array-ref where the values are cells.

Cells

Cells can be specified in several ways, but the best way is using a hash-ref that exactly conforms to the API. v is NOT checked against your data type - but we will attempt to convert it. If you pass in an undefined value, it will return a JS 'null', regardless of the data type. f needs to be a string if you provide it. p will be bassed directly to JSON::XS.

For any of the date-like fields (date, datetime, timeofday), you can pass in 4 types of values. We accept DateTime objects, Time::Piece objects, epoch seconds (as a string - converted internally using localtime (localtime in perlfunc)), or an array-ref of values that will be passed directly to the resulting Javascript Date object eg:

 Perl:
  date => [ 5, 4, 3 ]
 JS:
  new Date( 5, 4, 3 )

Remember that JS dates 0-index the month.

For non-date fields, if you specify a cell using a string or number, rather than a hashref, that'll be mapped to a cell with v set to the string you specified.

boolean: we test the value you pass in for truth, the Perl way, although undef values will come out as null, not 0.

Properties

Properties can be defined for the whole datatable (using set_properties), for each column (using p), for each row (using p) and for each cell (again using p). The documentation provided is a little unclear as to exactly what you're allowed to put in this, so we provide you ample rope and let you specify anything you like.

When defining properties for rows, you must use the hashref method of row creation. If you have a column with id of p, you must use _p as your key for defining properties.

METHODS

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new

Constructor. Accepts a hashref of arguments, of which the only valid one currently is p - a datatable-wide properties element (see Properties above and the Google docs).

add_columns

Accepts zero or more columns, in the format specified above, and adds them to our list of columns. Returns the object. You can't call this method after you've called add_rows for the first time.

add_rows

Accepts zero or more rows, either as a list of hash-refs or a list of array-refs. If you've provided hash-refs, we'll map the key name to the column via its ID (you must have given every column an ID if you want to do this, or it'll cause a fatal error).

If you've provided array-refs, we'll assume each cell belongs in subsequent columns - your array-ref must have the same number of members as you have set columns.

pedantic

We do some data checking for sanity, and we'll issue warnings about things the API considers bad data practice - using reserved words or fancy characters and IDs so far. If you don't want that, simple say:

 $object->pedantic(0);

Defaults to true.

set_properties

Sets the datatable-wide properties value. See the Google docs.

json_xs_object

You may want to configure your JSON::XS object in some magical way. This is a read/write accessor to it. If you didn't understand that, or why you'd want to do that, you can ignore this method.

output_javascript

Returns a Javascript serialization of your object. You can optionally specify two parameters:

pretty - bool - defaults to false - that specifies if you'd like your Javascript spread-apart with whitespace. Useful for debugging.

columns - array-ref of strings - pick out certain columns only (and in the order you specify). If you don't provide an argument here, we'll use them all and in the order set in add_columns.

output_json

An alias to output_javascript above, with a very misleading name, as it outputs Javascript, not JSON - see JSON vs Javascript below.

JSON vs Javascript

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Please note this module outputs Javascript, and not JSON. JSON is a subset of Javascript, and Google's API requires a similar - but different - subset of Javascript. Specifically some values need to be set to native Javascript objects, such as (and currently limited to) the Date object. That means we output code like:

 {"v":new Date( 2011, 2, 21, 2, 6, 25 )}

which is valid Javascript, but not valid JSON.

BUG BOUNTY

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Find a reproducible bug, file a bug report, and I (Peter Sergeant) will donate $10 to The Perl Foundation (or Wikipedia). Feature Requests are not bugs :-) Offer subject to author's discretion...

$20 donated 31Dec2010 to TPF re properties handling bug

$10 donated 11Nov2010 to TPF re null display bug

SUPPORT

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If you find a bug, please use this modules page on the CPAN bug tracker to raise it, or I might never see.

AUTHOR

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Peter Sergeant pete@clueball.com on behalf of Investor Dynamics - Letting you know what your market is thinking.

SEE ALSO

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Python library that does the same thing

JSON::XS - The underlying module

Google Visualization API.

Github Page for this code

COPYRIGHT

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Data-Google-Visualization-DataTable documentation Contained in the Data-Google-Visualization-DataTable distribution.
package Data::Google::Visualization::DataTable;
BEGIN {
  $Data::Google::Visualization::DataTable::VERSION = '0.08';
}

use strict;
use warnings;

use Carp qw(croak carp);
use Storable qw(dclone);
use JSON::XS;
use Time::Local;

sub new {
	my $class = shift;
	my $args  = shift;
	my $self = {
		columns              => [],
		column_mapping       => {},
		rows                 => [],
		json_xs              => JSON::XS->new()->canonical(1)->allow_nonref,
		all_columns_have_ids => 0,
		column_count         => 0,
		pedantic             => 1
	};
	$self->{'properties'} = $args->{'p'} if defined $args->{'p'};
	bless $self, $class;
	return $self;
}

our %ACCEPTABLE_TYPES = map { $_ => 1 } qw(
	date datetime timeofday boolean number string
);

our %JAVASCRIPT_RESERVED = map { $_ => 1 } qw(
	break case catch continue default delete do else finally for function if in
	instanceof new return switch this throw try typeof var void while with
	abstract boolean byte char class const debugger double enum export extends
	final float goto implements import int interface long native package
	private protected public short static super synchronized throws transient
	volatile const export import
);

sub add_columns {
	my ($self, @columns) = @_;

	croak "You can't add columns once you've added rows"
		if @{$self->{'rows'}};

	# Add the columns to our internal store
	for my $column ( @columns ) {

		# Check the type
		my $type = $column->{'type'};
		croak "Every column must have a 'type'" unless $type;
		croak "Unknown column type '$type'" unless $ACCEPTABLE_TYPES{ $type };

		# Check label and ID are sane
		for my $key (qw( label id pattern ) ) {
			if ( $column->{$key} && ref( $column->{$key} ) ) {
				croak "'$key' needs to be a simple string";
			}
		}

		# Check the 'p' column is ok if it was provided, and convert now to JSON
		if ( defined($column->{'p'}) ) {
			eval { $self->json_xs_object->encode( $column->{'p'} ) };
			croak "Serializing 'p' failed: $@" if $@;
		}

		# ID must be unique
		if ( $column->{'id'} ) {
			my $id = $column->{'id'};
			if ( grep { $id eq $_->{'id'} } @{ $self->{'columns'} } ) {
				croak "We already have a column with the id '$id'";
			}
		}

		# Pedantic checking of that ID
		if ( $self->pedantic ) {
			if ( $column->{'id'} ) {
				if ( $column->{'id'} !~ m/^[a-zA-Z0-9_]+$/ ) {
					carp "The API recommends that t ID's should be both simple:"
						. $column->{'id'};
				} elsif ( $JAVASCRIPT_RESERVED{ $column->{'id'} } ) {
					carp "The API recommends avoiding Javascript reserved " .
						"words for IDs: " . $column->{'id'};
				}
			}
		}

		# Add that column to our collection
		push( @{ $self->{'columns'} }, $column );
	}

	# Reset column statistics
	$self->{'column_mapping'} = {};
	$self->{'column_count'  } = 0;
	$self->{'all_columns_have_ids'} = 1;

	# Map the IDs to column indexes, redo column stats, and encode the column
	# data
	my $i = 0;
	for my $column ( @{ $self->{'columns'} } ) {

		$self->{'column_count'}++;

		# Encode as JSON
		delete $column->{'json'};
		my $column_json = $self->json_xs_object->encode( $column );
		$column->{'json'} = $column_json;

		# Column mapping
		if ( $column->{'id'} ) {
			$self->{'column_mapping'}->{ $column->{'id'} } = $i;
		} else {
			$self->{'all_columns_have_ids'} = 0;
		}
		$i++;
	}

	return $self;
}

sub add_rows {
	my ( $self, @rows_to_add ) = @_;

	# Loop over our input rows
	for my $row (@rows_to_add) {

		my @columns;
		my $properties;

		# Map hash-refs to columns
		if ( ref( $row ) eq 'HASH' ) {

			# Grab the properties, if they exist
			if ( exists $self->{'column_mapping'}->{'p'} ) {
				$properties = delete $row->{'_p'};
			} else {
				$properties = delete $row->{'p'};
			}

			# We can't be going forward unless they specified IDs for each of
			# their columns
			croak "All your columns must have IDs if you want to add hashrefs" .
				" as rows" unless $self->{'all_columns_have_ids'};

			# Loop through the keys, populating @columns
			for my $key ( keys %$row ) {
				# Get the relevant column index for the key, or handle 'p'
				# properly
				unless ( exists $self->{'column_mapping'}->{ $key } ) {
					croak "Couldn't find a column with id '$key'";
				}
				my $index = $self->{'column_mapping'}->{ $key };

				# Populate @columns with the data-type and value
				$columns[ $index ] = [
					$self->{'columns'}->[ $index ]->{'type'},
					$row->{ $key }
				];

			}

		# Map array-refs to columns
		} elsif ( ref( $row ) eq 'ARRAY' ) {

			# Populate @columns with the data-type and value
			my $i = 0;
			for my $col (@$row) {
				$columns[ $i ] = [
					$self->{'columns'}->[ $i ]->{'type'},
					$col
				];
				$i++;
			}

		# Rows must be array-refs or hash-refs
		} else {
			croak "Rows must be array-refs or hash-refs: $row";
		}

		# Force the length of columns to be the same as actual columns, to
		# handle undef values better.
		$columns[ $self->{'column_count'} - 1 ] = undef
			unless defined $columns[ $self->{'column_count'} - 1 ];

		# Convert each cell in to the long cell format
		my @formatted_columns;
		for ( @columns ) {
			if ( $_ ) {
				my ($type, $column) = @$_;

				if ( ref( $column ) eq 'HASH' ) {
					# Check f is a simple string if defined
					if ( defined($column->{'f'}) && ref( $column->{'f'} ) ) {
						croak "Cell's 'f' values must be strings: " .
							$column->{'f'};
					}
					# If p is defined, check it serializes
					if ( defined($column->{'p'}) ) {
						croak "'p' must be a reference"
							unless ref( $column->{'p'} );
						eval { $self->json_xs_object->encode( $column->{'p'} ) };
						croak "Serializing 'p' failed: $@" if $@;
					}
					# Complain about any unauthorized keys
					if ( $self->pedantic ) {
						for my $key ( keys %$column ) {
							carp "'$key' is not a recognized key"
								unless $key =~ m/^[fvp]$/;
						}
					}
					push( @formatted_columns, [ $type, $column ] );
				} else {
					push( @formatted_columns, [ $type, { v => $column } ] );
				}
			# Undefined that become nulls
			} else {
				push( @formatted_columns, [ 'null', { v => undef } ] );
			}
		}

		# Serialize each cell
		my @cells;
		for (@formatted_columns) {
			my ($type, $cell) = @$_;

			# Force 'f' to be a string
			if ( defined( $cell->{'f'} ) ) {
				$cell->{'f'} .= '';
			}

			# Handle null/undef
			if ( ! defined($cell->{'v'}) ) {
				push(@cells, $self->json_xs_object->encode( $cell ) );

			# Convert boolean
			} elsif ( $type eq 'boolean' ) {
				$cell->{'v'} = $cell->{'v'} ? \1 : \0;
				push(@cells, $self->json_xs_object->encode( $cell ) );

			# Convert number
			} elsif ( $type eq 'number' ) {
				$cell->{'v'} = 0 unless $cell->{'v'}; # Force false values to 0
				$cell->{'v'} += 0; # Force numeric for JSON encoding
				push(@cells, $self->json_xs_object->encode( $cell ) );

			# Convert string
			} elsif ( $type eq 'string' ) {
				$cell->{'v'} .= '';
				push(@cells, $self->json_xs_object->encode( $cell ) );

			# It's a date!
			} else {
				my @date_digits;

				# Date digits specified manually
				if ( ref( $cell->{'v'} ) eq 'ARRAY' ) {
					@date_digits = @{ $cell->{'v'} };
				# We're going to have to retrieve them ourselves
				} else {
					my @initial_date_digits;

					# Epoch timestamp
					if (! ref( $cell->{'v'} ) ) {
						my ($sec,$min,$hour,$mday,$mon,$year) =
							localtime( $cell->{'v'} );
						@initial_date_digits =
							( $year, $mon, $mday, $hour, $min, $sec );

					} elsif ( $cell->{'v'}->isa('DateTime') ) {
						my $dt = $cell->{'v'};
						@initial_date_digits = (
							$dt->year, ( $dt->mon - 1 ), $dt->day,
							$dt->hour, $dt->min, $dt->sec, $dt->millisecond
						);

					} elsif ( $cell->{'v'}->isa('Time::Piece') ) {
						my $tp = $cell->{'v'};
						@initial_date_digits = (
							$tp->year, $tp->_mon, $tp->mday,
							$tp->hour, $tp->min, $tp->sec
						);

					} else {
						croak "Unknown date format";
					}

					if ( $type eq 'date' ) {
						@date_digits = @initial_date_digits[ 0 .. 2 ];
					} elsif ( $type eq 'datetime' ) {
						@date_digits = @initial_date_digits[ 0 .. 5 ];
					} else { # Time of day
						@date_digits = @initial_date_digits[ 3, -1 ];
					}
				}

				my $json_date = join ', ', @date_digits;
				if ( $type eq 'timeofday' ) {
					$json_date = '[' . $json_date . ']';
				} else {
					$json_date = 'new Date( ' . $json_date . ' )';
				}

				my $placeholder = '%%%PLEHLDER%%%';
				$cell->{'v'} = $placeholder;
				my $json_string = $self->json_xs_object->encode( $cell );
				$json_string =~ s/"$placeholder"/$json_date/;
				push(@cells, $json_string );
			}
		}

		my %data = ( cells => \@cells );
		$data{'properties'} = $properties if defined $properties;

		push( @{ $self->{'rows'} }, \%data );
	}

	return $self;
}

sub pedantic {
	my ($self, $arg) = @_;
	$self->{'pedantic'} = $arg if defined $arg;
	return $self->{'pedantic'};
}

sub set_properties {
	my ( $self, $arg ) = @_;
	$self->{'properties'} = $arg;
	return $self->{'properties'};
}

sub json_xs_object {
	my ($self, $arg) = @_;
	$self->{'json_xs'} = $arg if defined $arg;
	return $self->{'json_xs'};
}

sub output_json { my ( $self, %params ) = @_; $self->output_javascript( %params ) }

sub output_javascript {
	my ($self, %params) = @_;

	my ($columns, $rows) = $self->_select_data( %params );

	my ($t, $s, $n) = ('','','');
	if ( $params{'pretty'} ) {
		$t = "    ";
		$s = " ";
		$n = "\n";
	}

	# Columns
	my $columns_string = join ',' .$n.$t.$t, @$columns;

	# Rows
	my @rows = map {
		my $tt = $t x 3;
		# Turn the cells in to constituent values
		my $individual_row_string = join ',' .$n.$tt.$t, @{$_->{'cells'}};
		# Put together the output itself
		my $output =
			'{' .$n.
			$tt. '"c":[' .$n.
			$tt.$t. $individual_row_string .$n.
			$tt.']';

		# Add properties
		if ( $_->{'properties'} ) {
			my $properties = $self->_encode_properties( $_->{'properties'} );
			$output .= ',' .$n.$tt.'"p":' . $properties;
		}

		$output .= $n.$t.$t.'}';
		$output;
	} @$rows;
	my $rows_string = join ',' . $n . $t . $t, @rows;

	my $return =
		'{' .$n.
		$t.     '"cols": [' .$n.
		$t.     $t.    $columns_string .$n.
		$t.     '],' .$n.
		$t.     '"rows": [' .$n.
		$t.     $t.    $rows_string .$n.
		$t.     ']';

	if ( defined $self->{'properties'} ) {
		my $properties = $self->_encode_properties( $self->{'properties'} );
		$return .= ',' .$n.$t.'"p":' . $properties;
	}

	$return .= $n.'}';
	return $return;
}

sub _select_data {
	my ($self, %params) = @_;

	my $rows    = dclone $self->{'rows'};
	my $columns = [map { $_->{'json'} } @{$self->{'columns'}}];

	# Select certain columns by id only
	if ( $params{'columns'} && @{ $params{'columns'} } ) {
		my @column_spec;

		# Get the name of each column
		for my $column ( @{$params{'columns'}} ) {

		# And push it's place in the array in to our specification
			my $index = $self->{'column_mapping'}->{ $column };
			croak "Couldn't find a column named '$column'" unless
				defined $index;
			push(@column_spec, $index);
		}

		# Grab the column selection
		my @new_columns;
		for my $index (@column_spec) {
			my $column = splice( @{$columns}, $index, 1, '' );
			push(@new_columns, $column);
		}

		# Grab the row selection
		my @new_rows;
		for my $original_row (@$rows) {
			my @new_cells;
			for my $index (@column_spec) {
				my $column = splice( @{$original_row->{'cells'}}, $index, 1, '' );
				push(@new_cells, $column);
			}
			my $new_row = $original_row;
			$new_row->{'cells'} = \@new_cells;

			push(@new_rows, $new_row);
		}

		$rows = \@new_rows;
		$columns = \@new_columns;
	}

	return ( $columns, $rows );
}

sub _encode_properties {
	my ( $self, $properties ) = @_;
	return $self->json_xs_object->encode( $properties );
}

1;