=head1 Perl Slurp Ease

=head2 Introduction

One of the common Perl idioms is processing text files line by line:

	while( <FH> ) {

		do something with $_

	}

This idiom has several variants, but the key point is that it reads in

only one line from the file in each loop iteration. This has several

advantages, including limiting memory use to one line, the ability to

handle any size file (including data piped in via STDIN), and it is

easily taught and understood to Perl newbies. In fact newbies are the

ones who do silly things like this:

	while( <FH> ) {

		push @lines, $_ ;

	}

	foreach ( @lines ) {

		do something with $_

	}

Line by line processing is fine, but it isn't the only way to deal with

reading files. The other common style is reading the entire file into a

scalar or array, and that is commonly known as slurping. Now, slurping has

somewhat of a poor reputation, and this article is an attempt at

rehabilitating it. Slurping files has advantages and limitations, and is

not something you should just do when line by line processing is fine.

It is best when you need the entire file in memory for processing all at

once. Slurping with in memory processing can be faster and lead to

simpler code than line by line if done properly.

The biggest issue to watch for with slurping is file size. Slurping very

large files or unknown amounts of data from STDIN can be disastrous to

your memory usage and cause swap disk thrashing.  You can slurp STDIN if

you know that you can handle the maximum size input without

detrimentally affecting your memory usage. So I advocate slurping only

disk files and only when you know their size is reasonable and you have

a real reason to process the file as a whole.  Note that reasonable size

these days is larger than the bad old days of limited RAM. Slurping in a

megabyte is not an issue on most systems. But most of the

files I tend to slurp in are much smaller than that. Typical files that

work well with slurping are configuration files, (mini-)language scripts,

some data (especially binary) files, and other files of known sizes

which need fast processing.

Another major win for slurping over line by line is speed. Perl's IO

system (like many others) is slow. Calling C<< <> >> for each line

requires a check for the end of line, checks for EOF, copying a line,

munging the internal handle structure, etc. Plenty of work for each line

read in. Whereas slurping, if done correctly, will usually involve only

one I/O call and no extra data copying. The same is true for writing

files to disk, and we will cover that as well (even though the term

slurping is traditionally a read operation, I use the term ``slurp'' for

the concept of doing I/O with an entire file in one operation).

Finally, when you have slurped the entire file into memory, you can do

operations on the data that are not possible or easily done with line by

line processing. These include global search/replace (without regard for

newlines), grabbing all matches with one call of C<//g>, complex parsing

(which in many cases must ignore newlines), processing *ML (where line

endings are just white space) and performing complex transformations

such as template expansion.

=head2 Global Operations

Here are some simple global operations that can be done quickly and

easily on an entire file that has been slurped in. They could also be

done with line by line processing but that would be slower and require

more code.

A common problem is reading in a file with key/value pairs. There are

modules which do this but who needs them for simple formats? Just slurp

in the file and do a single parse to grab all the key/value pairs.

	my $text = read_file( $file ) ;

	my %config = $text =~ /^(\w+)=(.+)$/mg ;

That matches a key which starts a line (anywhere inside the string

because of the C</m> modifier), the '=' char and the text to the end of the

line (again, C</m> makes that work). In fact the ending C<$> is not even needed

since C<.> will not normally match a newline. Since the key and value are

grabbed and the C<m//> is in list context with the C</g> modifier, it will

grab all key/value pairs and return them. The C<%config>hash will be

assigned this list and now you have the file fully parsed into a hash.

Various projects I have worked on needed some simple templating and I

wasn't in the mood to use a full module (please, no flames about your

favorite template module :-). So I rolled my own by slurping in the

template file, setting up a template hash and doing this one line:

	$text =~ s/<%(.+?)%>/$template{$1}/g ;

That only works if the entire file was slurped in. With a little

extra work it can handle chunks of text to be expanded:

	$text =~ s/<%(\w+)_START%>(.+?)<%\1_END%>/ template($1, $2)/sge ;

Just supply a C<template> sub to expand the text between the markers and

you have yourself a simple system with minimal code. Note that this will

work and grab over multiple lines due the the C</s> modifier. This is

something that is much trickier with line by line processing.

Note that this is a very simple templating system, and it can't directly

handle nested tags and other complex features. But even if you use one

of the myriad of template modules on the CPAN, you will gain by having

speedier ways to read and write files.

Slurping in a file into an array also offers some useful advantages. 

One simple example is reading in a flat database where each record has

fields separated by a character such as C<:>:

	my @pw_fields = map [ split /:/ ], read_file( '/etc/passwd' ) ;

Random access to any line of the slurped file is another advantage. Also

a line index could be built to speed up searching the array of lines.

=head2 Traditional Slurping

Perl has always supported slurping files with minimal code. Slurping of

a file to a list of lines is trivial, just call the C<< <> >> operator

in a list context:

	my @lines = <FH> ;

and slurping to a scalar isn't much more work. Just set the built in

variable C<$/> (the input record separator to the undefined value and read

in the file with C<< <> >>:

	{

		local( $/, *FH ) ;

		open( FH, $file ) or die "sudden flaming death\n"

		$text = <FH>

	}

Notice the use of C<local()>. It sets C<$/> to C<undef> for you and when

the scope exits it will revert C<$/> back to its previous value (most

likely "\n").

Here is a Perl idiom that allows the C<$text> variable to be declared,

and there is no need for a tightly nested block. The C<do> block will

execute C<< <FH> >> in a scalar context and slurp in the file named by

C<$text>:

	local( *FH ) ;

	open( FH, $file ) or die "sudden flaming death\n"

	my $text = do { local( $/ ) ; <FH> } ;

Both of those slurps used localized filehandles to be compatible with

5.005. Here they are with 5.6.0 lexical autovivified handles:

	{

		local( $/ ) ;

		open( my $fh, $file ) or die "sudden flaming death\n"

		$text = <$fh>

	}

	open( my $fh, $file ) or die "sudden flaming death\n"

	my $text = do { local( $/ ) ; <$fh> } ;

And this is a variant of that idiom that removes the need for the open

call:

	my $text = do { local( @ARGV, $/ ) = $file ; <> } ;

The filename in C<$file> is assigned to a localized C<@ARGV> and the

null filehandle is used which reads the data from the files in C<@ARGV>.

Instead of assigning to a scalar, all the above slurps can assign to an

array and it will get the file but split into lines (using C<$/> as the

end of line marker).

There is one common variant of those slurps which is very slow and not

good code. You see it around, and it is almost always cargo cult code:

	my $text = join( '', <FH> ) ;

That needlessly splits the input file into lines (C<join> provides a

list context to C<< <FH> >>) and then joins up those lines again. The

original coder of this idiom obviously never read I<perlvar> and learned

how to use C<$/> to allow scalar slurping.

=head2 Write Slurping

While reading in entire files at one time is common, writing out entire

files is also done. We call it ``slurping'' when we read in files, but

there is no commonly accepted term for the write operation. I asked some

Perl colleagues and got two interesting nominations. Peter Scott said to

call it ``burping'' (rhymes with ``slurping'' and suggests movement in

the opposite direction). Others suggested ``spewing'' which has a

stronger visual image :-) Tell me your favorite or suggest your own. I

will use both in this section so you can see how they work for you.

Spewing a file is a much simpler operation than slurping. You don't have

context issues to worry about and there is no efficiency problem with

returning a buffer. Here is a simple burp subroutine:

	sub burp {

		my( $file_name ) = shift ;

		open( my $fh, ">$file_name" ) || 

				 die "can't create $file_name $!" ;

		print $fh @_ ;

	}

Note that it doesn't copy the input text but passes @_ directly to

print. We will look at faster variations of that later on.

=head2 Slurp on the CPAN

As you would expect there are modules in the CPAN that will slurp files

for you. The two I found are called Slurp.pm (by Rob Casey - ROBAU on

CPAN) and File::Slurp.pm (by David Muir Sharnoff - MUIR on CPAN).

Here is the code from Slurp.pm:

    sub slurp { 

	local( $/, @ARGV ) = ( wantarray ? $/ : undef, @_ ); 

	return <ARGV>;

    }

    sub to_array {

	my @array = slurp( @_ );

	return wantarray ? @array : \@array;

    }

    sub to_scalar {

	my $scalar = slurp( @_ );

	return $scalar;

    }

+The subroutine C<slurp()> uses the magic undefined value of C<$/> and

the magic file +handle C<ARGV> to support slurping into a scalar or

array. It also provides two wrapper subs that allow the caller to

control the context of the slurp. And the C<to_array()> subroutine will

return the list of slurped lines or a anonymous array of them according

to its caller's context by checking C<wantarray>. It has 'slurp' in

C<@EXPORT> and all three subroutines in C<@EXPORT_OK>.

namespace.>

The original File::Slurp.pm has this code:

sub read_file

{

	my ($file) = @_;

	local($/) = wantarray ? $/ : undef;

	local(*F);

	my $r;

	my (@r);

	open(F, "<$file") || croak "open $file: $!";

	@r = <F>;

	close(F) || croak "close $file: $!";

	return $r[0] unless wantarray;

	return @r;

}

This module provides several subroutines including C<read_file()> (more

on the others later). C<read_file()> behaves simularly to

C<Slurp::slurp()> in that it will slurp a list of lines or a single

scalar depending on the caller's context. It also uses the magic

undefined value of C<$/> for scalar slurping but it uses an explicit

open call rather than using a localized C<@ARGV> and the other module

did. Also it doesn't provide a way to get an anonymous array of the

lines but that can easily be rectified by calling it inside an anonymous

array constuctor C<[]>.

Both of these modules make it easier for Perl coders to slurp in

files. They both use the magic C<$/> to slurp in scalar mode and the

natural behavior of C<< <> >> in list context to slurp as lines. But

neither is optmized for speed nor can they handle C<binmode()> to

support binary or unicode files. See below for more on slurp features

and speedups.

=head2 Slurping API Design

The slurp modules on CPAN are have a very simple API and don't support

C<binmode()>. This section will cover various API design issues such as

efficient return by reference, C<binmode()> and calling variations.

Let's start with the call variations. Slurped files can be returned in

four formats: as a single scalar, as a reference to a scalar, as a list

of lines or as an anonymous array of lines. But the caller can only

provide two contexts: scalar or list. So we have to either provide an

API with more than one subroutine (as Slurp.pm did) or just provide one

subroutine which only returns a scalar or a list (not an anonymous

array) as File::Slurp does.

I have used my own C<read_file()> subroutine for years and it has the

same API as File::Slurp: a single subroutine that returns a scalar or a

list of lines depending on context. But I recognize the interest of

those that want an anonymous array for line slurping. For one thing, it

is easier to pass around to other subs and for another, it eliminates

the extra copying of the lines via C<return>. So my module provides only

one slurp subroutine that returns the file data based on context and any

format options passed in. There is no need for a specific

slurp-in-as-a-scalar or list subroutine as the general C<read_file()>

sub will do that by default in the appropriate context. If you want

C<read_file()> to return a scalar reference or anonymous array of lines,

you can request those formats with options. You can even pass in a

reference to a scalar (e.g. a previously allocated buffer) and have that

filled with the slurped data (and that is one of the fastest slurp

modes. see the benchmark section for more on that).  If you want to

slurp a scalar into an array, just select the desired array element and

that will provide scalar context to the C<read_file()> subroutine.

The next area to cover is what to name the slurp sub. I will go with

C<read_file()>. It is descriptive and keeps compatibilty with the

current simple and don't use the 'slurp' nickname (though that nickname

is in the module name). Also I decided to keep the  File::Slurp

namespace which was graciously handed over to me by its current owner,

David Muir.

Another critical area when designing APIs is how to pass in

arguments. The C<read_file()> subroutine takes one required argument

which is the file name. To support C<binmode()> we need another optional

argument. A third optional argument is needed to support returning a

slurped scalar by reference. My first thought was to design the API with

3 positional arguments - file name, buffer reference and binmode. But if

you want to set the binmode and not pass in a buffer reference, you have

to fill the second argument with C<undef> and that is ugly. So I decided

to make the filename argument positional and the other two named. The

subroutine starts off like this:

	sub read_file {

		my( $file_name, %args ) = @_ ;

		my $buf ;

		my $buf_ref = $args{'buf'} || \$buf ;

The other sub (C<read_file_lines()>) will only take an optional binmode

(so you can read files with binary delimiters). It doesn't need a buffer

reference argument since it can return an anonymous array if the called

in a scalar context. So this subroutine could use positional arguments,

but to keep its API similar to the API of C<read_file()>, it will also

use pass by name for the optional arguments. This also means that new

optional arguments can be added later without breaking any legacy

code. A bonus with keeping the API the same for both subs will be seen

how the two subs are optimized to work together.

Write slurping (or spewing or burping :-)) needs to have its API

designed as well. The biggest issue is not only needing to support

optional arguments but a list of arguments to be written is needed. Perl

6 will be able to handle that with optional named arguments and a final

slurp argument. Since this is Perl 5 we have to do it using some

cleverness. The first argument is the file name and it will be

positional as with the C<read_file> subroutine. But how can we pass in

the optional arguments and also a list of data? The solution lies in the

fact that the data list should never contain a reference.

Burping/spewing works only on plain data. So if the next argument is a

hash reference, we can assume it cointains the optional arguments and

the rest of the arguments is the data list. So the C<write_file()>

subroutine will start off like this:

	sub write_file {

		my $file_name = shift ;

		my $args = ( ref $_[0] eq 'HASH' ) ? shift : {} ;

Whether or not optional arguments are passed in, we leave the data list

in C<@_> to minimize any more copying. You call C<write_file()> like this:

	write_file( 'foo', { binmode => ':raw' }, @data ) ;

	write_file( 'junk', { append => 1 }, @more_junk ) ;

	write_file( 'bar', @spew ) ;

=head2 Fast Slurping

Somewhere along the line, I learned about a way to slurp files faster

than by setting $/ to undef. The method is very simple, you do a single

read call with the size of the file (which the -s operator provides).

This bypasses the I/O loop inside perl that checks for EOF and does all

sorts of processing. I then decided to experiment and found that

sysread is even faster as you would expect. sysread bypasses all of

Perl's stdio and reads the file from the kernel buffers directly into a

Perl scalar. This is why the slurp code in File::Slurp uses

sysopen/sysread/syswrite. All the rest of the code is just to support

the various options and data passing techniques.

=head2 Benchmarks

Benchmarks can be enlightening, informative, frustrating and

deceiving. It would make no sense to create a new and more complex slurp

module unless it also gained signifigantly in speed. So I created a

benchmark script which compares various slurp methods with differing

file sizes and calling contexts. This script can be run from the main

directory of the tarball like this:

	perl -Ilib extras/slurp_bench.pl

If you pass in an argument on the command line, it will be passed to

timethese() and it will control the duration. It defaults to -2 which

makes each benchmark run to at least 2 seconds of cpu time.

The following numbers are from a run I did on my 300Mhz sparc. You will

most likely get much faster counts on your boxes but the relative speeds

shouldn't change by much. If you see major differences on your

benchmarks, please send me the results and your Perl and OS

versions. Also you can play with the benchmark script and add more slurp

variations or data files.

The rest of this section will be discussing the results of the

benchmarks. You can refer to extras/slurp_bench.pl to see the code for

the individual benchmarks. If the benchmark name starts with cpan_, it

is either from Slurp.pm or File::Slurp.pm. Those starting with new_ are

from the new File::Slurp.pm. Those that start with file_contents_ are

from a client's code base. The rest are variations I created to

highlight certain aspects of the benchmarks.

The short and long file data is made like this:

	my @lines = ( 'abc' x 30 . "\n")  x 100 ;

	my $text = join( '', @lines ) ;

	@lines = ( 'abc' x 40 . "\n")  x 1000 ;

	$text = join( '', @lines ) ;

So the short file is 9,100 bytes and the long file is 121,000

bytes. 

=head3 	Scalar Slurp of Short File

	file_contents        651/s

	file_contents_no_OO  828/s

	cpan_read_file      1866/s

	cpan_slurp          1934/s

	read_file           2079/s

	new                 2270/s

	new_buf_ref         2403/s

	new_scalar_ref      2415/s

	sysread_file        2572/s

=head3 	Scalar Slurp of Long File

	file_contents_no_OO 82.9/s

	file_contents       85.4/s

	cpan_read_file       250/s

	cpan_slurp           257/s

	read_file            323/s

	new                  468/s

	sysread_file         489/s

	new_scalar_ref       766/s

	new_buf_ref          767/s

The primary inference you get from looking at the mumbers above is that

when slurping a file into a scalar, the longer the file, the more time

you save by returning the result via a scalar reference. The time for

the extra buffer copy can add up. The new module came out on top overall

except for the very simple sysread_file entry which was added to

highlight the overhead of the more flexible new module which isn't that

much. The file_contents entries are always the worst since they do a

list slurp and then a join, which is a classic newbie and cargo culted

style which is extremely slow. Also the OO code in file_contents slows

it down even more (I added the file_contents_no_OO entry to show this).

The two CPAN modules are decent with small files but they are laggards

compared to the new module when the file gets much larger.

=head3 	List Slurp of Short File

	cpan_read_file          589/s

	cpan_slurp_to_array     620/s

	read_file               824/s

	new_array_ref           824/s

	sysread_file            828/s

	new                     829/s

	new_in_anon_array       833/s

	cpan_slurp_to_array_ref 836/s

=head3 	List Slurp of Long File

	cpan_read_file          62.4/s

	cpan_slurp_to_array     62.7/s

	read_file               92.9/s

	sysread_file            94.8/s

	new_array_ref           95.5/s

	new                     96.2/s

	cpan_slurp_to_array_ref 96.3/s

	new_in_anon_array       97.2/s

This is perhaps the most interesting result of this benchmark. Five

different entries have effectively tied for the lead. The logical

conclusion is that splitting the input into lines is the bounding

operation, no matter how the file gets slurped. This is the only

benchmark where the new module isn't the clear winner (in the long file

entries - it is no worse than a close second in the short file

entries). 

Note: In the benchmark information for all the spew entries, the extra

number at the end of each line is how many wallclock seconds the whole

entry took. The benchmarks were run for at least 2 CPU seconds per

entry. The unusually large wallclock times will be discussed below.

=head3 	Scalar Spew of Short File

	cpan_write_file 1035/s	38

	print_file      1055/s	41

	syswrite_file   1135/s	44

	new             1519/s	2

	print_join_file 1766/s	2

	new_ref         1900/s	2

	syswrite_file2  2138/s	2

=head3 	Scalar Spew of Long File

	cpan_write_file 164/s	20

	print_file      211/s	26

	syswrite_file   236/s	25

	print_join_file 277/s	2

	new             295/s	2

	syswrite_file2  428/s	2

	new_ref         608/s	2

In the scalar spew entries, the new module API wins when it is passed a

reference to the scalar buffer. The C<syswrite_file2> entry beats it

with the shorter file due to its simpler code. The old CPAN module is

the slowest due to its extra copying of the data and its use of print.

=head3 List Spew of Short File

	cpan_write_file  794/s	29

	syswrite_file   1000/s	38

	print_file      1013/s	42

	new             1399/s	2

	print_join_file 1557/s	2

=head3 	List Spew of Long File

	cpan_write_file 112/s	12

	print_file      179/s	21

	syswrite_file   181/s	19

	print_join_file 205/s	2

	new             228/s	2

Again, the simple C<print_join_file> entry beats the new module when

spewing a short list of lines to a file. But is loses to the new module

when the file size gets longer. The old CPAN module lags behind the

others since it first makes an extra copy of the lines and then it calls

C<print> on the output list and that is much slower than passing to

C<print> a single scalar generated by join. The C<print_file> entry

shows the advantage of directly printing C<@_> and the

C<print_join_file> adds the join optimization.

Now about those long wallclock times. If you look carefully at the

benchmark code of all the spew entries, you will find that some always

write to new files and some overwrite existing files. When I asked David

Muir why the old File::Slurp module had an C<overwrite> subroutine, he

answered that by overwriting a file, you always guarantee something

readable is in the file. If you create a new file, there is a moment

when the new file is created but has no data in it. I feel this is not a

good enough answer. Even when overwriting, you can write a shorter file

than the existing file and then you have to truncate the file to the new

size. There is a small race window there where another process can slurp

in the file with the new data followed by leftover junk from the

previous version of the file. This reinforces the point that the only

way to ensure consistant file data is the proper use of file locks.

But what about those long times? Well it is all about the difference

between creating files and overwriting existing ones. The former have to

allocate new inodes (or the equivilent on other file systems) and the

latter can reuse the exising inode. This mean the overwrite will save on

disk seeks as well as on cpu time. In fact when running this benchmark,

I could hear my disk going crazy allocating inodes during the spew

operations. This speedup in both cpu and wallclock is why the new module

always does overwriting when spewing files. It also does the proper

truncate (and this is checked in the tests by spewing shorter files

after longer ones had previously been written). The C<overwrite>

subroutine is just an typeglob alias to C<write_file> and is there for

backwards compatibilty with the old File::Slurp module.

=head3 Benchmark Conclusion

Other than a few cases where a simpler entry beat it out, the new

File::Slurp module is either the speed leader or among the leaders. Its

special APIs for passing buffers by reference prove to be very useful

speedups. Also it uses all the other optimizations including using

C<sysread/syswrite> and joining output lines. I expect many projects

that extensively use slurping will notice the speed improvements,

especially if they rewrite their code to take advantage of the new API

features. Even if they don't touch their code and use the simple API

they will get a significant speedup.

=head2 Error Handling

Slurp subroutines are subject to conditions such as not being able to

open the file, or I/O errors. How these errors are handled, and what the

caller will see, are important aspects of the design of an API. The

classic error handling for slurping has been to call C<die()> or even

better, C<croak()>. But sometimes you want the slurp to either

C<warn()>/C<carp()> or allow your code to handle the error. Sure, this

can be done by wrapping the slurp in a C<eval> block to catch a fatal

error, but not everyone wants all that extra code. So I have added

another option to all the subroutines which selects the error

handling. If the 'err_mode' option is 'croak' (which is also the

default), the called subroutine will croak. If set to 'carp' then carp

will be called. Set to any other string (use 'quiet' when you want to

be explicit) and no error handler is called. Then the caller can use the

error status from the call.

C<write_file()> doesn't use the return value for data so it can return a

false status value in-band to mark an error. C<read_file()> does use its

return value for data, but we can still make it pass back the error

status. A successful read in any scalar mode will return either a

defined data string or a reference to a scalar or array. So a bare

return would work here. But if you slurp in lines by calling it in a

list context, a bare C<return> will return an empty list, which is the

same value it would get from an existing but empty file. So now,

C<read_file()> will do something I normally strongly advocate against,

i.e., returning an explicit C<undef> value. In the scalar context this

still returns a error, and in list context, the returned first value

will be C<undef>, and that is not legal data for the first element. So

the list context also gets a error status it can detect:

	my @lines = read_file( $file_name, err_mode => 'quiet' ) ;

	your_handle_error( "$file_name can't be read\n" ) unless

					@lines && defined $lines[0] ;

=head2 File::FastSlurp

	sub read_file {

		my( $file_name, %args ) = @_ ;

		my $buf ;

		my $buf_ref = $args{'buf_ref'} || \$buf ;

		my $mode = O_RDONLY ;

		$mode |= O_BINARY if $args{'binmode'} ;

		local( *FH ) ;

		sysopen( FH, $file_name, $mode ) or

					carp "Can't open $file_name: $!" ;

		my $size_left = -s FH ;

		while( $size_left > 0 ) {

			my $read_cnt = sysread( FH, ${$buf_ref},

					$size_left, length ${$buf_ref} ) ;

			unless( $read_cnt ) {

				carp "read error in file $file_name: $!" ;

				last ;

			}

			$size_left -= $read_cnt ;

		}

	# handle void context (return scalar by buffer reference)

		return unless defined wantarray ;

	# handle list context

		return split m|?<$/|g, ${$buf_ref} if wantarray ;

	# handle scalar context

		return ${$buf_ref} ;

	}

	sub write_file {

		my $file_name = shift ;

		my $args = ( ref $_[0] eq 'HASH' ) ? shift : {} ;

		my $buf = join '', @_ ;

		my $mode = O_WRONLY ;

		$mode |= O_BINARY if $args->{'binmode'} ;

		$mode |= O_APPEND if $args->{'append'} ;

		local( *FH ) ;

		sysopen( FH, $file_name, $mode ) or

					carp "Can't open $file_name: $!" ;

		my $size_left = length( $buf ) ;

		my $offset = 0 ;

		while( $size_left > 0 ) {

			my $write_cnt = syswrite( FH, $buf,

					$size_left, $offset ) ;

			unless( $write_cnt ) {

				carp "write error in file $file_name: $!" ;

				last ;

			}

			$size_left -= $write_cnt ;

			$offset += $write_cnt ;

		}

		return ;

	}

=head2 Slurping in Perl 6

As usual with Perl 6, much of the work in this article will be put to

pasture. Perl 6 will allow you to set a 'slurp' property on file handles

and when you read from such a handle, the file is slurped. List and

scalar context will still be supported so you can slurp into lines or a

optimized and bypass the stdio subsystem since it can use the slurp

property to trigger a call to special code. Otherwise some enterprising

individual will just create a File::FastSlurp module for Perl 6. The

code in the Perl 5 module could easily be modified to Perl 6 syntax and

semantics. Any volunteers?

=head2 In Summary

We have compared classic line by line processing with munging a whole

file in memory. Slurping files can speed up your programs and simplify

your code if done properly. You must still be aware to not slurp

humongous files (logs, DNA sequences, etc.) or STDIN where you don't

know how much data you will read in. But slurping megabyte sized files

is not an major issue on today's systems with the typical amount of RAM

installed. When Perl was first being used in depth (Perl 4), slurping

was limited by the smaller RAM size of 10 years ago. Now, you should be

able to slurp almost any reasonably sized file, whether it contains

configuration, source code, data, etc.

=head2 Acknowledgements