[Raku PDF Project] / PDF::Grammar
PDF-Grammar
Although PDF documents do not lend themselves to an overall BNF style grammar description; there are areas where these can be put to use, including:
- PDF file header and trailer/xref parsing
- Parsing of objects fetched via the xref index. Top level objects commomly include: dictionarys , streams, arrays or numbers.
- The overall file structure for FDF files (which are not indexed), or for full-scan recovery of PDF files (headers, objects, cross-reference tables and footers).
- Parsing the operands that make up content streams. These are used to markup text, forms, images and graphical elements.
PDF::Grammar is a set of Raku grammars for parsing and validation of real-world PDF examples. There are four grammars:
PDF::Grammar::Content
- describes the text and graphics operators that are used to produce page layout.
PDF::Grammar::Content::Fast
- is an optimized version of PDF::Grammar::Content.
PDF::Grammar::FDF
- this describes the file structure of FDF (Form Data) exchange files.
PDF::Grammar::PDF
- this describes the file structure of PDF documents,
including headers, trailers, top-level objects and the cross-reference table.
PDF::Grammar::Function
- a tokeniser for Postscript Calculator (type 4) functions.
PDF-Grammar has so far been tested against a number of sample of PDF documents and may still be subject to change.
I have been working off the PDF 32000-1:2008 1.7 specification. I’ve relaxed rules, when needed, to handle real-world examples.
Usage Notes
-
PDF input files typically contain a mixture of ASCII directives and binary data, plus byte-orientated addressing. For this reason:
- files should be read as binary (avoid encoding layers)
- strings should be decoded as
latin1
% rakudo -MPDF::Grammar::PDF -e"say PDF::Grammar::PDF.parse: slurp($f, :bin).decode('latin-1')"
-
This module is put to work by the down-stream PDF module. E.g. to uncompress a PDF, using the installed
pdf-rewriter
script:% pdf-rewriter.raku --uncompress flyer.pdf
Examples
-
parse some markup content:
% raku -M PDF::Grammar::Content -e"say PDF::Grammar::Content.parse('(Hello, world\041) Tj')"
-
parse a PDF file:
% rakudo -MPDF::Grammar::PDF -e"say PDF::Grammar::PDF.parsefile( $f )"
-
dump the contents of a PDF
use v6; use PDF::Grammar::PDF; use PDF::Grammar::PDF::Actions; sub MAIN(Str $pdf-file) { my $actions = PDF::Grammar::PDF::Actions.new; if PDF::Grammar::PDF.parsefile( $pdf-file, :$actions ) { say $/.ast.raku; } else { say "failed to parse PDF: $pdf-file"; } }
AST Reference
The action methods in this module return AST trees. Each node in the tree consists of a key, value pair, where the key is the AST Tag, indicating the type of the AST node.
For example, here’s the AST tree for the following parse:
use PDF::Grammar::PDF;
use PDF::Grammar::PDF::Actions;
my $actions = PDF::Grammar::PDF::Actions.new;
PDF::Grammar::PDF.parse( q:to"--END-DOC--", :rule<ind-obj>, :$actions);
3 0 obj <<
/Type /Pages
/Count 1
/Kids [4 0 R]
>>
endobj
--END-DOC--
say '# ' ~ $/.ast.raku;
# :ind-obj($[3, 0, :dict({:Count(:int(1)), :Kids(:array([:ind-ref($[4, 0])])), :Type(:name("Pages"))})])
Note that there’s also a lite
mode which skips types bool
, int
, real
and null
:
$actions .= new: :lite;
PDF::Grammar::PDF.parse( q:to"--END-", :rule<ind-obj>, :$actions);
3 0 obj << /Count 1 >> endobj
--END--
say '# ' ~ $/.ast.raku;
# :ind-obj($[3, 0, :dict({:Count(1)})])
This is an indirect object (ind-obj
), it contains a dictionary object (dict
). Entries in the dictionary are:
Count
with integer value (int
) of 1.Kids
, and array (array
) containing one indirect reference (ind-ref
).Type
with name (name
) ‘Pages’.
In most cases, the node type corresponds to the name of the rule or token that was used to construct the node.
This AST representation is used extensively throughout the PDF tool-chain. For example, as an intermediate format by PDF::Writer
for reserialization.
For reference, here is a list of all AST node types:
AST Tag | Raku Type | Description |
---|---|---|
array | Array[Any] | Array object type, e.g. [ 0 0 612 792 ] |
body | Array[Hash] | The FDF/PDF body consisting of ind-obj and comment entries. A PDF with revisions has multiple body segments |
bool | Bool | Boolean object type, e.g. true [1] |
comment | Str | (Write only) a comment string |
cos | Hash | A PDF or FDF document, consisting of a header and body array |
dict | Hash | Dictionary object type, e.g. << /Type /Catalog /Pages 3 0 R >> |
encoded | Str | Raw encoded stream data. This is returned as a latin-1 byte-string. |
entries | Array[Hash] | A list of entries in a cross reference segment |
decoded | Str | Uncompressed/unencrypted stream data |
gen-num | UInt | Object generation number |
header | Hash | PDF or FDF header, e.g. %PDF1.4 |
hex-string | Str | A hex-string, e.g. <736e6f6f7079> |
ind-ref | Array[UInt] | An indirect reference, .e.g. 23 2 R |
ind-obj | Any | An indirect object. This is a three element array that contains an object number, generation number and the object |
int | Int | Integer object type, e.g. 42 [1] |
obj-count | UInt | object count/number of entries in a cross reference segment |
obj-first-num | UInt | object first number in a cross reference segment |
obj-num | UInt | Object number |
offset | UInt | byte offset of an indirect object in the file. |
literal | Str | A literal string, e.g. (Hello, World!) |
name | Str | Name string, e.g. /Fred |
null | Mu | Null object type, e.g. null [1] |
real | Real | Real object type, e.g. 42.0 [1] |
start | UInt | Start position of stream data (returned by ind-obj-nibble rule) |
startxref | UInt | byte offset from the start of the file to the start of the trailer |
stream | Hash | Stream object type. A dictionary indirect object followed by stream data |
trailer | Hash | Trailer. This typically contains the trailer dict entry. |
type | Str | Document type; ‘pdf’, or ‘fdf’ |
version | Rat | The PDF / FDF version number, parsed from the header |
Note [1] Types bool
, int
, real
, and null
don’t appear in lite
mode.
See also
- PDF - Raku module for PDF manipulation, including compression, encryption and reading and writing of PDF data.