In writing a grammar/parser for a regex, I'm wondering why the following constructions are both syntactically and semantically valid in the regex syntax (at least as far as I can understand it)?
Repetitions of a character class, such as:
Repetitions of a zero-width assertion, such as:
Assertions at a bogus position, such as:
To me, this sort of seems like having a syntax that would allow having a construction like SELECT SELECT SELECT SELECT SELECT col FROM tbl. In other words, why isn't the regex syntax defined as more strict than it is in practice?
To start with, that's not a very good analogy. Your statement with multiple SELECT keywords is not, as far as I know, part of the SQL grammar, so it's simply ungrammatical. Repeated elements in a character class are more like the SQL construct:
SELECT * FROM table WHERE Value IN (1, 2, 3, 2, 3, 2, 3)
I think most (if not all) SQL processors would allow that. You could argue that it would be nice if a warning message were issued, but the usual SQL interface (where a query is sent from client to server and a result returned) does not leave space for a warning.
It's certainly the case that repeated characters in a character class are often an indication that the regular expression was written by a novice with only a fuzzy idea of what a character class is. If you hang out in SO's flex-lexer long enough, you'll see how often students write regular expressions like [a-z|A-Z|0-9], or even [begin|end]. If flex detected duplicate characters in character classes, those mistakes would receive warnings, which might or might not be useful to the student coder. (Reading and understanding warning messages is not, apparently, an innate skill.) But it needs to be asked, Who is the target audience for a tool like Flex, and I think the answer is not "impatient beginners who won't read documentation". Certainly, a non-novice programmer might also make that kind of mistake, usually as a result of a typo, but it's not common and it will probably easily be detected during debugging.
If you've already started to work on a parser for regular expressions, you should already know why these rules are not usually a feature of regular expression libraries. Every rule you place on a syntax must be:
precisely defined,
documented,
implemented,
acted upon appropriately (which may mean complicating the interface in order to allow for warnings).
and all of that needs to be thoroughly tested.
That's a lot of work to prevent something which is not even technically an error. And catching those errors (if they are errors) will probably make the "grammar" for the regular expressions context-sensitive. (In other words, you can't write a context-free grammar which forbids duplication inside a character class.)
Moreover, practically all of those expressions might show up in the wild, typically in the case that the regular expression was programmatically generated. For example, suppose you have a set of words, and you want to write a regular expression which will match any sequence of characters not in any of the words. The simple solution is [^firstsecondthirdwordandtherest]+. Of course, you could have gone to the trouble of deduping the individual letters in the words, -- a simple task in some programming languages, but more complicated in others -- but should it be necessary?
With respect to your other two examples, with repeated and non-terminal $, there are actual regex libraries in which those interpreted in some different way. Many older regex libraries (including (f)lex) only treat $ as a zero-length end-of-string assertion if it appears at the very end of the regex; such libraries would treat all of those $s other than the last one in a$$$$$$$$ as matching a literal $. Others treat $ as an end-of-line assertion, rather than an end-of-string assertion. But I don't know of any which treat those as errors.
There's a pretty good argument that a didactic tool, such as regex101, might usefully issue warnings for doubtful regular expressions, a task usually called "linting". But for a production regex library, there is little to be gained, and a lot of pain.
I have this .bib file for reference management while writing my thesis in LaTeX:
#article{garg2017patch,
title={Patch testing in patients with suspected cosmetic dermatitis: A retrospective study},
author={Garg, Taru and Agarwal, Soumya and Chander, Ram and Singh, Aashim and Yadav, Pravesh},
journal={Journal of Cosmetic Dermatology},
year={2017},
publisher={Wiley Online Library}
}
#article{hauso2008neuroendocrine,
title={Neuroendocrine tumor epidemiology},
author={Hauso, Oyvind and Gustafsson, Bjorn I and Kidd, Mark and Waldum, Helge L and Drozdov, Ignat and Chan, Anthony KC and Modlin, Irvin M},
journal={Cancer},
volume={113},
number={10},
pages={2655--2664},
year={2008},
publisher={Wiley Online Library}
}
#article{siperstein1997laparoscopic,
title={Laparoscopic thermal ablation of hepatic neuroendocrine tumor metastases},
author={Siperstein, Allan E and Rogers, Stanley J and Hansen, Paul D and Gitomirsky, Alexis},
journal={Surgery},
volume={122},
number={6},
pages={1147--1155},
year={1997},
publisher={Elsevier}
}
If anyone wants to know what bib file is, you can find it detailed here.
I'd like to parse this with Perl 6 to extract the key along with the title like this:
garg2017patch: Patch testing in patients with suspected cosmetic dermatitis: A retrospective study
hauso2008neuroendocrine: Neuroendocrine tumor epidemiology
siperstein1997laparoscopic: Laparoscopic thermal ablation of hepatic neuroendocrine tumor metastases
Can you please help me to do this, maybe in two ways:
Using basic Perl 6
Using a Perl 6 Grammar
TL;DR
A complete and detailed answer that does just exactly as #Suman asks.
An introductory general answer to "I want to parse X. Can anyone help?"
A one-liner in a shell
I'll start with terse code that's perfect for some scenarios[1], and which someone might write if they're familiar with shell and Raku basics and in a hurry:
> raku -e 'for slurp() ~~ m:g / "#article\{" (<-[,]>+) \, \s+
"title=\{" (<-[}]>+) \} / -> $/ { put "$0: $1\n" }' < derm.bib
This produces precisely the output you specified:
garg2017patch: Patch testing in patients with suspected cosmetic dermatitis: A retrospective study
hauso2008neuroendocrine: Neuroendocrine tumor epidemiology
siperstein1997laparoscopic: Laparoscopic thermal ablation of hepatic neuroendocrine tumor metastases
Same single statement, but in a script
Skipping shell escapes and adding:
Whitespace.
Comments.
► use tio.run to run the code below
for slurp() # "slurp" (read all of) stdin and then
~~ m :global # match it "globally" (all matches) against
/ '#article{' (<-[,]>+) ',' \s+ # a "nextgen regex" that uses (`(...)`) to
'title={' (<-[}]>+) '}' / # capture the article id and title and then
-> $/ { put "$0: $1\n" } # for each article, print "article id: title".
Don't worry if the above still seems like pure gobbledygook. Later sections explain the above while also introducing code that's more general, clean, and readable.[2]
Four statements instead of one
my \input = slurp;
my \pattern = rule { '#article{' ( <-[,]>+ ) ','
'title={' ( <-[}]>+ ) }
my \articles = input .match: pattern, :global;
for articles -> $/ { put "$0: $1\n" }
my declares a lexical variable. Raku supports sigils at the start of variable names. But it also allows devs to "slash them out" as I have done.
my \pattern ...
my \pattern = rule { '#article{' ( <-[,]>+ ) ','
'title={' ( <-[}]>+ ) }
I've switched the pattern syntax from / ... / in the original one-liner to rule { ... }. I did this to:
Eliminate the risk of pathological backtracking
Classic regexes risk pathological backtracking. That's fine if you can just kill a program that's gone wild, but click the link to read how bad it can get! 🤪 We don't need backtracking to match the .bib format.
Communicate that the pattern is a rule
If you write a good deal of pattern matching code, you'll frequently want to use rule { ... }. A rule eliminates any risk of the classic regex problem just described (pathological backtracking), and has another superpower. I'll cover both aspects below, after first introducing the adverbs corresponding to those superpowers.
Raku regexes/rules can be (often are) used with "adverbs". These are convenient shortcuts that modify how patterns are applied.
I've already used an adverb in the earlier versions of this code. The "global" adverb (specified using :global or its shorthand alias :g) directs the matching engine to consume all of the input, generating a list of as many matches as it contains, instead of returning just the first match.
While there are shorthand aliases for adverbs, some are used so repeatedly that it's a lot tidier to bundle them up into distinct rule declarators. That's why I've used rule. It bundles up two adverbs appropriate for matching many data formats like .bib files:
:ratchet (alias :r)
:sigspace (alias :s)
Ratcheting (:r / :ratchet) tells the compiler that when an "atom" (a sub-pattern in a rule that is treated as one unit) has matched, there can be no going back on that. If an atom further on in the pattern in the same rule fails, then the whole rule immediately fails.
This eliminates any risk of the "pathological backtracking" discussed earlier.
Significant space handling (:s / :sigspace) tells the compiler that an atom followed by literal spacing that is in the pattern indicates that a "token" boundary pattern, aka ws should be appended to the atom.
Thus this adverb deals with tokenizing. Did you spot that I'd dropped the \s+ from the pattern compared to the original one in the one-liner? That's because :sigspace, which use of rule implies, takes care of that automatically:
say 'x#y x # y' ~~ m:g:s /x\#y/; # (｢x#y｣) <-- only one match
say 'x#y x # y' ~~ m:g /x \# y/; # (｢x#y｣) <-- only one match
say 'x#y x # y' ~~ m:g:s /x \# y/; # (｢x#y｣ ｢x # y｣) <-- two matches
You might wonder why I've reverted to using / ... / to show these two examples. Turns out that while you can use rule { ... } with the .match method (described in the next section), you can't use rule with m. No problem; I just used :s instead to get the desired effect. (I didn't bother to use :r for ratcheting because it makes no difference for this pattern/input.)
To round out this dive into the difference between classic regexes (which can also be written regex { ... }) and rule rules, let me mention the other main option: token. The token declarator implies the :ratchet adverb, but not the :sigspace one. So it also eliminates the pathological backtracking risk of a regex (or / ... /) but, just like a regex, and unlike a rule, a token ignores whitespace used by a dev in writing out the rule's pattern.
my \articles = input .match: pattern, :global
This line uses the method form (.match) of the m routine used in the one-liner solution.
The result of a match when :global is used is a list of Match objects rather than just one. In this case we'll get three, corresponding to the three articles in the input file.
for articles -> $/ { put "$0: $1\n" }
This for statement successively binds a Match object corresponding to each of the three articles in your sample file to the symbol $/ inside the code block ({ ... }).
Per Raku doc on $/, "$/ is the match variable, so it usually contains objects of type Match.". It also provides some other conveniences; we take advantage of one of these conveniences related to numbered captures:
The pattern that was matched earlier contained two pairs of parentheses;
The overall Match object ($/) provides access to these two Positional captures via Positional subscripting (postfix []), so within the for's block, $/[0] and $/[1] provide access to the two Positional captures for each article;
Raku aliases $0 to $/[0] (and so on) for convenience, so most devs use the shorter syntax.
Interlude
This would be a good time to take a break. Maybe just a cuppa, or return here another day.
The last part of this answer builds up and thoroughly explains a grammar-based approach. Reading it may provide further insight into the solutions above and will show how to extend Raku's parsing to more complex scenarios.
But first...
A "boring" practical approach
I want to parse this with Raku. Can anyone help?
Raku may make writing parsers less tedious than with other tools. But less tedious is still tedious. And Raku parsing is currently slow.
In most cases, the practical answer when you want to parse well known formats and/or really big files is to find and use an existing parser. This might mean not using Raku at all, or using an existing Raku module, or using an existing non-Raku parser in Raku.
A suggested starting point is to search for the file format on modules.raku.org or raku.land. Look for a publicly shared parsing module already specifically packaged for Raku for the given file format. Then do some simple testing to see if you have a good solution.
At the time of writing there are no matches for 'bib'.
Even if you don't know C, there's almost certainly a 'bib' parsing C library already available that you can use. And it's likely to be the fastest solution. It's typically surprisingly easy to use an external library in your own Raku code, even if it's written in another programming language.
Using C libs is done using a feature called NativeCall. The doc I just linked may well be too much or too little, but please feel free to visit the freenode IRC channel #raku and ask for help. (Or post an SO question.) We're friendly folk. :)
If a C lib isn't right for a particular use case, then you can probably still use packages written in some other language such as Perl, Python, Ruby, Lua, etc. via their respective Inline::* language adapters.
The steps are:
Install a package (that's written in Perl, Python or whatever);
Make sure it runs on your system using a compiler of the language it's written for;
Install the appropriate Inline language adapter that lets Raku run packages in that other language;
Use the "foreign" package as if it were a Raku package containing exported Raku functions, classes, objects, values, etc.
(At least, that's the theory. Again, if you need help, please pop on the IRC channel or post an SO question.)
The Perl adapter is the most mature so I'll use that as an example. Let's say you use Perl's Text::BibTex packages and now wish to use Raku with that package. First, setup it up as it's supposed to be per its README. Then, in Raku, write something like:
use Text::BibTeX::BibFormat:from<Perl5>;
...
#blocks = $entry.format;
Explanation of these two lines:
The first line is how you tell Raku that you wish to load a Perl module.
(It won't work unless Inline::Perl5 is already installed and working. But it should be if you're using a popular Raku bundle. And if not, you should at least have the module installer zef so you can run zef install Inline::Perl5.)
The last line is just a mechanical Raku translation of the #blocks = $entry->format; line from the SYNOPSIS of the Perl package Text::BibTeX::BibFormat.
A Raku grammar / parser
OK. Enough "boring" practical advice. Let's now try have some fun creating a grammar based Raku parser good enough for the example from your question.
► use glot.io to run the code below
unit grammar bib;
rule TOP { <article>* }
rule article { '#article{' $<id>=<-[,]>+ ','
<kv-pairs>
'}'
}
rule kv-pairs { <kv-pair>* % ',' }
rule kv-pair { $<key>=\w* '={' ~ '}' $<value>=<-[}]>* }
With this grammar in place, we can now write something like:
die "Use CommaIDE?" unless bib .parsefile: 'derm.bib';
for $<article> -> $/ { put "$<id>: $<kv-pairs><kv-pair>[0]<value>\n" }
to generate exactly the same output as the previous solutions.
When a match or parse fails, by default Raku just returns Nil, which is, well, rather terse feedback.
There are several nice debugging options to figure out what's going on with a regex or grammar, but the best option by far is to use CommaIDE's Grammar-Live-View.
If you haven't already installed and used Comma, you're missing one of the best parts of using Raku. The features built in to the free version of Comma ("Community Edition") include outstanding grammar development / tracing / debugging tools.
Explanation of the 'bib' grammar
unit grammar bib;
The unit declarator is used at the start of a source file to tell Raku that the rest of the file declares a named package of code of a particular type.
The grammar keyword specifies a grammar. A grammar is like a class, but contains named "rules" -- not just named methods, but also named regexs, tokens, and rules. A grammar also inherits a bunch of general purpose rules from a base grammar.
rule TOP {
Unless you specify otherwise, parsing methods (.parse and .parsefile) that are called on a grammar start by calling the grammar's rule named TOP (declared with a rule, token, regex, or method declarator).
As a, er, rule of thumb, if you don't know if you should be using a rule, regex, token, or method for some bit of parsing, use a token. (Unlike regex patterns, tokens don't risk pathological backtracking.)
But I've used a rule. Like token patterns, rules also avoid the pathological backtracking risk. But, in addition rules interpret some whitespace in the pattern to be significant, in a natural manner. (See this SO answer for precise details.)
rules are typically appropriate towards the top of the parse tree. (Tokens are typically appropriate towards the leaves.)
rule TOP { <article>* }
The space at the end of the rule (between the * and pattern closing }) means the grammar will match any amount of whitespace at the end of the input.
<article> invokes another named rule in this grammar.
Because it looks like one should allow for any number of articles per bib file, I added a * (zero or more quantifier) at the end of <article>*.
rule article { '#article{' $<id>=<-[,]>+ ','
<kv-pairs>
'}'
}
If you compare this article pattern with the ones I wrote for the earlier Raku rules based solutions, you'll see various changes:
Rule in original one-liner
Rule in this grammar
Kept pattern as simple as possible.
Introduced <kv-pairs> and closing }
No attempt to echo layout of your input.
Visually echoes your input.
<[...]> is the Raku syntax for a character class, like[...] in traditional regex syntax. It's more powerful, but for now all you need to know is that the - in <-[,]> indicates negation, i.e. the same as the ^ in the [^,] syntax of ye olde regex. So <-[,]>+ attempts a match of one or more characters, none of which are ,.
$<id>=<-[,]>+ tells Raku to attempt to match the quantified "atom" on the right of the = (i.e. the <-[,]>+ bit) and store the results at the key <id> within the current match object. The latter will be hung from a branch of the parse tree; we'll get to precisely where later.
rule kv-pairs { <kv-pair>* % ',' }
This pattern illustrates one of several convenient Raku regex features. It declares you want to match zero or more kv-pairs separated by commas.
(In more detail, the % regex infix operator requires that matches of the quantified atom on its left are separated by the atom on its right.)
rule kv-pair { $<key>=\w* '={' ~ '}' $<value>=<-[}]>* }
The new bit here is '={' ~ '}'. This is another convenient regex feature. The regex Tilde operator parses a delimited structure (in this case one with a ={ opener and } closer) with the bit between the delimiters matching the quantified regex atom on the right of the closer. This confers several benefits but the main one is that error messages can be clearer.
I could have used the ~ approach in the /.../ regex in the one-liner, and vice-versa. But I wanted this grammar solution to continue the progression toward illustrating "better practice" idioms.
Constructing / deconstructing the parse tree
for $<article> { put "$<id>: $<kv-pairs><kv-pair>[0]<value>\n" }`
$<article>, $<id> etc. refer to named match objects that are stored somewhere in the "parse tree". But how did they get there? And exactly where is "there"?
Returning to the top of the grammar:
rule TOP {
If a .parse is successful, a single 'TOP' level match object is returned. (After a parse is complete the variable $/ is also bound to that top match object.) During parsing a tree will have been formed by hanging other match objects off this top match object, and then others hung off those, and so on.
Addition of match objects to a parse tree is done by adding either a single generated match object, or a list of them, to either a Positional (numbered) or Associative (named) capture of a "parent" match object. This process is explained below.
rule TOP { <article>* }
<article> invokes a match of the rule named article. An invocation of the rule <article> has two effects:
Raku tries to match the rule.
If it matches, Raku captures that match by generating a corresponding match object and adding it to the parse tree under the key <article> of the parent match object. (In this case the parent is the top match object.)
If the successfully matched pattern had been specified as just <article>, rather than as <article>*, then only one match would have been attempted, and only one value, a single match object, would have been generated and added under the key <article>.
But the pattern was <article>*, not merely <article>. So Raku attempts to match the article rule as many times as it can. If it matches at all, then a list of one or more match objects is stored as the value of the <article> key. (See my answer to "How do I access the captures within a match?" for a more detailed explanation.)
$<article> is short for $/<article>. It refers to the value stored under the <article> key of the current match object (which is stored in $/). In this case that value is a list of 3 match objects corresponding to the 3 articles in the input.
rule article { '#article{' $<id>=<-[,]>+ ','
Just as the top match object has several match objects hung off of it (the three captures of article matches that are stored under the top match object's <article> key), so too do each of those three article match objects have their own "child" match objects hanging off of them.
To see how that works, let's consider just the first of the three article match objects, the one corresponding to the text that starts "#article{garg2017patch,...". The article rule matches this article. As it's doing that matching, the $<id>=<-[,]>+ part tells Raku to store the match object corresponding to the id part of the article ("garg2017patch") under that article match object's <id> key.
Hopefully this is enough (quite possibly way too much!) and I can at last exhaustively (exhaustingly?) explain the last line of code, which, once again, was:
for $<article> -> $/ { put "$<id>: $<kv-pairs><kv-pair>[0]<value>\n" }`
At the level of the for, the variable $/ refers to the top of the parse tree generated by the parse that just completed. Thus $<article>, which is shorthand for $/<article>, refers to the list of three article match objects.
The for then iterates over that list, binding $/ within the lexical scope of the -> $/ { ... } block to each of those 3 article match objects in turn.
The $<id> bit is shorthand for $/<id>, which inside the block refers to the <id> key within the article match object that $/ has been bound to. In other words, $<id> inside the block is equivalent to $<article><id> outside the block.
The $<kv-pairs><kv-pair>[0]<value> follows the same scheme, albeit with more levels and a positional child (the [0]) in the midst of all the key (named/ associative) children.
(Note that there was no need for the article pattern to include a $<kv-pairs>=<kv-pairs> because Raku just presumes a pattern of the form <foo> should store its results under the key <foo>. If you wish to disable that, write a pattern with a non-alpha character as the first symbol. For example, use <.foo> if you want to have exactly the same matching effect as <foo> but just not store the matched input in the parse tree.)
Phew!
When the automatically generated parse tree isn't what you want
As if all the above were not enough, I need to mention one more thing.
The parse tree strongly reflects the tree structure of the grammar's rules calling one another from the top rule down to leaf rules. But the resulting structure is sometimes inconvenient.
Often one still wants a tree, but a simpler one, or perhaps some non-tree data structure.
The primary mechanism for generating exactly what you want from a parse, when the automatic results aren't suitable, is make. (This can be used in code blocks inside rules or factored out into Action classes that are separate from grammars.)
In turn, the primary use case for make is to generate a sparse tree of nodes hanging off the parse tree, such as an AST.
Footnotes
[1] Basic Raku is good for exploratory programming, spikes, one-offs, PoCs and other scenarios where the emphasis is on quickly producing working code that can be refactored later if need be.
[2] Raku's regexes/rules scale up to arbitrary parsing, as introduced in the latter half of this answer. This contrasts with past generations of regex which could not.[3]
[3] That said, ZA̡͊͠͝LGΌ ISͮ̂҉̯͈͕̹̘̱ TO͇̹̺ͅƝ̴ȳ̳ TH̘Ë͖́̉ ͠P̯͍̭O̚N̐Y̡ remains a great and relevant read. Not because Raku rules can't parse (X)HTML. In principle they can. But for a task as monumental as correctly handling full arbitrary in-the-wild XHTML I would strongly recommend you use an existing parser written expressly for that purpose. And this applies generally for existing formats; it's best not to reinvent the wheel. But the good news with Raku rules is that if you need to write a full parser, not just a bunch of regexes, you can do so, and it need not involve going insane!
I'm trying to write a predictive editor for a grammar written in Rascal. The heart of this would be a function taking as input a list of symbols and returning as output a list of symbol types, such that an instance of any of those types would be a syntactically legal continuation of the input symbols under the grammar. So if the input list was [4,+] the output might be [integer]. Is there a clever way to do this in Rascal? I can think of imperative programming ways of doing it, but I suspect they don't take proper advantage of Rascal's power.
That's a pretty big question. Here's some lead to an answer but the full answer would be implementing it for you completely :-)
Reify an original grammar for the language you are interested in as a value using the # operator, so that you have a concise representation of the grammar which can be queried easily. The representation is defined over the modules Type, ParseTree which extends Type and Grammar.
Construct the same representation for the input query. This could be done in many ways. A kick-ass, language-parametric, way would be to extend Rascal's parser algorithm to return partial trees for partial input, but I believe this would be too much hassle now. An easier solution would entail writing a grammar for a set of partial inputs, i.e. the language grammar with at specific points shorter rules. The grammar will be ambiguous but that is not a problem in this case.
Use tags to tag the "short" rules so that you can find them easily later: syntax E = #short E "+";
Parse with the extended and now ambiguous grammar;
The resulting parse trees will contain the same representation as in ParseTree that you used to reify the original grammar, except in that one the rules are longer, as in prod(E, [E,+,E],...)
then select the trees which serve you best for the goal of completion (which use the #short tag), and extract their productions "prod", which look like this prod(E,[E,+],...). For example using the / operator: [candidate : /candidate:prod(_,_,/"short") := trees], and you could use a cursor position to find candidates which are close by instead of all short trees in there.
Use list matching to find prefixes in the original grammar, like if (/match:prod(_,[*prefix, predicted, *postfix],_) := grammar) ..., prefix is your query as extracted from the #short rules. predicted is your answer and postfix is whatever would come after.
yield the predicted symbol back as a type for the user to read: "<type(predicted, ())>" (will pretty print it nicely even if it's some complex regexp type and does the quoting right etc.)
Sorry about the vagueness of this question, and maybe I want a different exchange? Not sure. Anyway, here goes:
I'd like to be able to determine if two mathematical expressions are 'the same'. I don't need full equivalence testing, which I understand is impossible anyway. Basically, I'd like to make a function that looks like this:
areTheSame(expression1, expression2, [testing methods])
where [testing methods] might include: 'exact', 'allow commutativity', 'allow distribution', ...
'exact' would be easy: expression1 == expression2 if their strings
are exactly equal
'allow commutativity' would be more difficult. For instance, if
expression1 is y=3*x and expression2 is y=x*3, then under 'allow
commutativity', they would be the same. Ditto here for 'y=x' and 'x=y'.
'allow distribution' would allow 'y=2*(x-3)' to be equal to
'y=2*x-6'.
others?
Ideally, I'd like to be lazy! I'd love to find some library that
supports parsing expressions from latex representations (or MathML, which is xml already, maybe it's easier to parse)
supports equivalence testing with some flags or something that
govern how exact the comparison should be, as above.
is written in c or c++ (or Objective-C - this is for an iOS project)
is not GPL.
4 rules out SymbolicC++ and GiNaC afaik. Mathomatic is LGPL, which I'm not sure about in the context of apple's app-Store (and I would really not like to have to give out object files)
Any ideas? Thanks!
This may not be an answer, but it's too long to be a comment. :)
My first thought: this is not an easy or common problem, so you probably won't have much luck finding a library to do it for you. Finding a library that does some of the non-critical parts, on the other hand, shouldn't be difficult.
What you probably want to do is parse the expressions to create an abstract syntax tree (you'll probably find lots of libraries for that), then recursively analyze the AST yourself to test whatever definition of sameness you're after.
In iOS, a decent place to start might be (horribly ab)using NSExpression and NSPredicate. These have constructor methods that parse a string and return a structure of expression and predicate objects.
Recursively walk that structure. For each predicate, check to see if the predicateOperatorType matches... if it doesn't, the predicates aren't the same. If it does, look at the left predicate's leftExpression and the right predicate's leftExpression. Each expression has a function that tells you what its operator is (add, subtract, etc). If they don't match, the expressions aren't the same. (Do the same check for the other side.) If they do, recurse: look at each expression's sub-expressions and do a similar check, and so on until you get to expressions that are constant values or variables.
That's a rough sketch of how to see if two predicates (and the expressions they contain) "match". For "sort of the same", just relax each check you perform while recursively walking the tree and/or add more checks; e.g. if you get to an expression whose function is add, check for commutativity by comparing its sub-expressions to the corresponding ones in the other predicate in either order. (Also, there are probably other libraries that'll parse basic math expressions and get you an AST you can walk however you like.)
That still won't get you everything you're after — "allow distribution" gets you into the realm of full-fledged CAS software. Maybe look into whether the likes of Wolfram Alpha have web service APIs?
I have a requirement but I don't know much about implementation detail.
I have a query string like -->
(title:java or author:john) and date:[20110303 TO 20110308]
basically the query string is composed with lucene syntax.
What I really need to do is parse query string into AST and convert AST to lucene query.
I'm not familiar with compiler or parser technology and I ran into Irony project.
Can someone point me how to and where to start? Using Irony or hand-made will be okay.
Thanks a lot.
Sorry for the late response:
Generally speaking, to create a parser, it's best to describe the grammar in the abstract, then generate the parser using a parser generator.
I created the lucene-query-parser.js library using a PEG grammar, which is in the Github repo here. That grammar is specific to PEG.js and uses JavaScript to implement an AST style result for the parsed query.
It's not necessary to return an AST style structure, but I found that to be most useful for the project that I wrote the syntax for. You could re-implement the grammar to return any sort of parser result that you wanted to.
If your query String is in Lucene syntax, then simply pass it to the parse(String) method of Lucene's QueryParser.
That will return a Query object representing the query String.
If you need to extend or modify the standard lucene syntax, then you could start by looking at the JavaCC Grammar for QueryParser.
Others have modified it in the past to add support for RegExps
You could also look at the Myna parser which is a JavaScript parsing library that has a sample Lucene grammar. The Myna parser automatically generates an AST that you can easily transform into whatever form you want.