The tregex package
[Skip to Readme]
Properties
Versions  0.1.0.0 

Dependencies  base (==4.*), containers, haskellsrcexts, haskellsrcmeta, lens (>=4), mtl (>=2), QuickCheck (>2), recursionschemes (==4.*), templatehaskell, transformers [details] 
License  BSD3 
Author  Alejandro Serrano 
Maintainer  A.SerranoMena@uu.nl 
Category  Data 
Uploaded  Tue Feb 17 10:48:41 UTC 2015 by AlejandroSerrano 
Distributions  NixOS:0.1.0.0 
Downloads  369 total (81 in the last 30 days) 
Rating  (no votes yet) [estimated by rule of succession] 
Your Rating 

Status  Docs available [build log] Last success reported on 20150217 [all 1 reports] Hackage Matrix CI 
Downloads
 tregex0.1.0.0.tar.gz [browse] (Cabal source package)
 Package description (as included in the package)
Readme for tregex0.1.0.0
[back to package description]tregex
: matchers and grammars using tree regular expressions
tregex
defines a series of combinators to express tree regular
expressions over any Haskell data type. In addition, with the use
of some combinators (and a bit of Template Haskell), it defines
nice syntax for using this tree regular expressions for matching
and computing attributes over a term.
Defining your data type
In order to use tregex
, you need to define you data type in a
way amenable to inspection. In particular, it means that instead
of a closed data type, you need to define a pattern functor in
which recursion is described using the final argument, and which
should instantiate the Generic1
type class (this can be done
automatically if you are using GHC).
For example, the following block of code defines a Tree'
data
type in the required fashion:
{# LANGUAGE DeriveGeneric #}
import GHC.Generics
data Tree' f = Leaf'
 Branch' { elt :: Int, left :: f, right :: f }
deriving (Generic1, Show)
Notice the f
argument in the place where Tree'
would usually be
found. In addition, we have declared the constructors using '
at
the end, but we will get rid of them soon.
Now, if you want to create terms, you need to close the type, which
essentially makes the f
argument refer back to Tree'
. You do so
by using Fix
:
type Tree = Fix Tree'
However, this induces the need to add explicit Fix
constructors at
each level. To alleviate this problem, let's define pattern synonyms,
available from GHC 7.8 on:
pattern Leaf = Fix Leaf'
pattern Branch n l r = Fix (Branch' n l r)
From an outsider point of view, now your data type is a normal one,
with Leaf
and Branch
as its constructors:
aTree = Branch 2 (Branch 2 Leaf Leaf) Leaf
Tree regular expressions
Tree regular expressions are parametrized by a pattern functor: in this way they are flexible enough to be used with different data types, while keeping our loved Haskell type safety.
The available combinators to build regular expressions follow the syntax of Tree Automata Techniques and Applications, Chapter 2.
Emptiness
The expressions empty_
and none
do not match any value. They can be
used to signal an error branch on an expressions.
Whole language
You can match any possible term using any_
. It is commonly use in
combination with capture
to extract information from a term.
Choice
A regular expression of the form r1 <> r2
tries to match r1
, and if
it not possible, it tries to do so with r2
. Note than when capturing,
the first regular expression is given priority.
Injection
Of course, at some point you would like to check whether some term has a specific shape. In our case, this means that it has been constructed in some specific way. In order to do so, you need to inject the constructor as a tree regular expression. When doing so, you can use the same syntax as usual, but where at the recursive positions you write regular expressions again.
Let's make it clearer with an example. In our initial definition we had
a constructor Branch'
with type:
Branch' :: Int > f > f > Tree' f
Once you inject it using inj
, the resulting constructor becomes:
inj . Branch' :: Int > Regex' c f > Regex c' f > Tree' (Regex' c f)
Notice that fields with no f
do not change their type. Now, here is how
you would represent a tree whose top node is a 2:
topTwo = inj (Branch' 2 any_ any_)
In some cases, you don't want to check the value of a certain position
which is not recursive. In that case, you cannot use any_
, since we
are not talking about the type being built upon. For that case, you
may use the special value __
.
For example, here is how you would represent the shape of a tree which has at least one branch point:
someBranching = inj (Branch' __ any_ any_)
Iteration and concatenation
Iteration in tree regular expressions is not as easy as in word languages. The reason is that iteration may occur several times, and in different positions. For that reason, we need to introduce the notion of hole: a hole is a placeholder where iteration takes place.
In tregex
hole names are represented as lambdabound variables. Then,
you can use any of the functions square
, var
or #
to indicate a
position where the placeholder should be put. Iteration is then indicated
by a call to iter
or its postfix version ^*
.
The following two are ways to indicate a Tree
where all internal nodes
include the number 2
:
{# LANGUAGE PostfixOperators #}
regex1 = Regex $
iter $ \k >
inj (Branch' 2 (square k) (square k))
<> inj Leaf'
regex2 = Regex $ ( (\k > inj (Branch' 2 (k#) (k#)) <> inj Leaf')^* )
Notice that the use of PostfixOperators
enables a much terse language.
Iteration is an instance of a more general construction called concatenation, where a hole in an expression is filled by another given expression. The general shape of those are:
(\k > ... (k#) ...) <.> r  k is replaced by r in the first expression
Matching and capturing
You can check whether a term t
is matched by a regular expression r
by simply using:
r `matches` t
However, the full power of tree regular expression come at the moment you
start capturing subterms of your tree. A capture group is introduced
in a expression by either capture
or <<
, and all of them appearing
in a expression should be from the same type. For example, we can refine
the previous regex2
to capture leaves:
regex2 = Regex $ ( (\k > inj (Branch' 2 (k#) (k#)) <> "leaves" << inj Leaf')^* )
To check whether a term matches a expression and capture the subterms,
you need to call match
. The result is of type Maybe (Map c (m (Fix f)))
.
Let's see what it means:
 The outermost
Maybe
indicates whether the match is successful or not. A value ofNothing
indicates that the given term does not match the regular expression,  Capture groups are returned as a
Map
, whose keys are those given atcapture
or<<
. For that reason, you need capture identifiers to be instances ofOrd
,  Finally, you have a choice about how to save the found subterms,
given by the
Alternative m
. Most of the time, you will makem = []
, which means that all matches of the group will be returned as a list. Other option is usingm = Maybe
, where only the first match is returned.
Tree regular expression patterns
Capturing is quite simple, but comes with a problem: it becomes easy to
mistake the name of a capture group, so your code becomes quite brittle.
For that reason, tregex
includes matchers which you can use at the
same positions where pattern matching is usually done, and which take
care of linking capture groups to variable names, making it impossible
to mistake them.
To use them, you need to import Data.Regex.TH
. Then, a quasiquoter
named rx
is available to you. Here is an example:
{# LANGUAGE QuasiQuotes #}
example :: Tree > [Tree]
example [rx (\k > inj (Branch' 2 (k#) (k#)) <> leaves << inj Leaf')^* ]
= leaves
example _ = []
The name of the capture group, leaves
, is now available in the body
of the example
function. There is no need to look inside maps, this
is all taken care for you.
Note that when using the rx
quasiquoter, you have no choice about
the Alternative m
to use when matching. Instead, you always get as
value of each capture group a list of terms.
For those who don't like using quasiquotation, tregex
provides a
less magical version called with
. In this case, you need to introduce
the variables in a explicit manner, and then pattern match on a tuple
wrapped inside a Maybe
. The previous example would be written as:
{# LANGUAGE ViewPatterns #}
example :: Tree > [Tree]
example with (\leaves > Regex $ iter $ \k > inj (Branch' 2 (k#) (k#))
<> leaves << inj Leaf' )
> Just leaves
= leaves
example _ = []
Notice that the pattern is always similar with (\v1 v2 ... >
regular expression) > Just (v1,v2,...)
.
Random generation
You can use tregex
to generate random values of a type which satisfy a
certain tree regular expression. Of course, you might always generate
random values and then check that they match the given expression, but
this is usually very costly and maybe even statistically impossible.
Instead, you should use arbitraryFromRegex
.
instance Arbitrary Tree where
arbitrary = frequency
[ (1, return Leaf)
, (5, Branch <$> arbitrary <*> arbitrary <*> arbitrary) ]
> arbitraryFromRegex regex2
Note that in the previous example we also gave an instance declaration
for Arbitrary
. This class comes from the QuickCheck
package, and
is needed to generate unconstrained random values for the case in
which any_
is found.
Sometimes you may not be able or want to write such an instance. In that
case, you can use arbitraryFromRegexAndGen
, which takes an additional
argument from which any_
values are generated.
Attribute grammars
Attribute grammars are a powerful way to perform computations over a term. The main idea is that each node in your term (when seen as a tree) is traversed, and two sets of information are recorded at each point:
 Inherited attributes go from parent to children. When describing a grammar, each node needs to specify the value of inherited attributes of all their children,
 Synthesized attributes flow in the other direction. At each node, you need to described how to get the value of each synthesized attribute based on your inherited attributes and the synthesized attributes of children.
The most performant attribute grammar compilers, such as
UUAGC
only allow deciding which rule to apply on a node depending on
their topmost constructor. With tregex
you can look as
deep as you want to take this decision (but of course, performance
will suffer if you do this very often).
Here is an example of a grammar which computes a graphical
representation of a Tree
plus its number of leaves:
grammar = [
rule $ \l r >
inj (Branch' 2 (l << any_) (r << any_)) >> do
(lText,lN) < use (at l . syn)
(rText,rN) < use (at r . syn)
this.syn._1 .= "(" ++ lText ++ ")SPECIAL(" ++ rText ++ ")"
this.syn._2 .= lN + rN
, rule $ \l r >
inj (Branch' __ (l << any_) (r << any_)) >>> \(Branch e _ _) > do
check $ e >= 0
(lText,lN) < use (at l . syn)
(rText,rN) < use (at r . syn)
this.syn._1 .= "(" ++ lText ++ ")" ++ show e ++ "(" ++ rText ++ ")"
this.syn._2 .= lN + rN
, rule $ inj Leaf' >> do
this.syn._1 .= "leaf"
this.syn._2 .= Sum 1
]
Let's dissect it part by part.
First of all, a grammar is made of a series of rules. Each rule follows the same schema:
rule $ \v1 ... vn >
regular expression >> do
actions
rule
is the constant part which prefixes every rule. Then, you
have the set of variables which will be used to capture information
from the term, in a similar way to previous section. After that you
have the tree regular expression the term needs to match. Finally,
and separated by >>
, you find the actions to perform when this
rule is selected.
Two small extensions are shown in the second rule. By default,
>>
does not give you access to the matched term. However, if you
need to access some of its information (for example, because you
used __
, as in this case), you can use the alternative version
>>>
which gives this as an argument. The second extension is the
use of check
to pinpoint a logical condition which is not captured
by the regular expression itself.
The syntax for the actions relies heavily in lenses and operators
from the lens
package. In particular, you have four lenses:
this.inh
gives access to the inherited attributes of the node,at n . syn
gives access to the synthesized attributes of children,this.syn
is where you set the synthesized attributes of your node,at n . inh
is where you set the inherited attributes of children,
Furthermore, you can combine those with lenses over your inherited
and synthesized attribute data type to have more lightweight syntax.
In our case, the synthesized attributes are a tuple (String, Sum Int)
,
so we access them with _1
and _2
, as shown in the example.
The general rule is that you read values using use
, and set values
via .=
. If some value is not set, it defaults to the empty element
of your synthesized type, or to the value of parent node in the case
of inherited attributes.