How to prevent Flex from ignoring previous analysis? - flex-lexer

I recently started using Lex, as a simple way to explain the problem I encoutered, supposing that I'm trying to realize a lexical analyser with Flex that print all the letters and also all the bigrams in a given text, that seems very easy and simple, but once I implemented it, I've realised that it shows bigrams first and only shows letters when they are single, example: for the following text
QQQZ ,JQR
The result is
Bigram QQ
Bigram QZ
Bigram JQ
Letter R
Done
This is my lex code
%{
%}
letter[A-Za-z]
Separ [ \t\n]
%%
{letter} {
printf(" Letter %c\n",yytext[0]);
}
{letter}{2} {
printf(" Bigram %s\n",yytext);
}
%%
main()
{ yylex();
printf("Done");
}
My question is How can realise the two analysis seperatly, knowing that my actual problem isn't as simple as this example

Lexical analysers divide the source text into separate tokens. If your problem looks like that, then (f)lex is an appropriate tool. If your problem does not look like that, then (f)lex is probably not the correct tool.
Doing two simultaneous analyses of text is not really a use case for (f)lex. One possibility would be to use two separate reentrant lexical analysers, arranging to feed them the same inputs. However, that will be a lot of work for a problem which could easily be solved in a few lines of C.
Since you say that your problem is different from the simple problem in your question, I did not bother to either write the simple C code or the rather more complicated code to generate and run two independent lexical analysers, since it is impossible to know whether either of those solutions is at all relevant.
If your problem really is matching two (or more) different lexemes from the same starting position, you could use one of two strategies, both quite ugly (IMHO):
I'm assuming the existence of handler functions:
void handle_letter(char ch);
void handle_bigram(char* s); /* Expects NUL-terminated string */
void handle_trigram(char* s); /* Expects NUL-terminated string */
For historical reasons, lex implements the REJECT action, which causes the current match to be discarded. The idea was to let you process a match, and then reject it in order to process a shorter (or alternate) match. With flex, the use of REJECT is highly discouraged because it is extremely inefficient and also prevents the lexer from resizing the input buffer, which arbitrarily limits the length of a recognisable token. However, in this particular use case it is quite simple:
[[:alpha:]][[:alpha:]][[:alpha:]] handle_trigram(yytext); REJECT;
[[:alpha:]][[:alpha:]] handle_bigram(yytext); REJECT;
[[:alpha:]] handle_letter(*yytext);
If you want to try this solution, I recommend using flex's debug facility (flex -d ...) in order to see what is going on.
See debugging options and REJECT documentation.
The solution I would actually recommend, although the code is a bit clunkier, is to use yyless() to reprocess part of the recognised token. This is quite a bit more efficient than REJECT; yyless() just changes a single pointer, so it has no impact on speed. Without REJECT, we have to know all the lexeme handlers which will be needed, but that's not very difficult. A complication is the interface for handle_bigram, which requires a NUL-terminated string. If your handler didn't impose this requirement, the code would be simpler.
[[:alpha:]][[:alpha:]][[:alpha:]] { handle_trigram(yytext);
char tmp = yytext[2];
yytext[2] = 0;
handle_bigram(yytext);
yytext[2] = tmp;
handle_letter(yytext[0]);
yyless(1);
}
[[:alpha:]][[:alpha:]] { handle_bigram(yytext);
handle_letter(yytext[0]);
yyless(1);
}
[[:alpha:]] handle_letter(*yytext);
See yyless() documentation

Related

Conditionals for flex

Is is possible to place conditional statements for rules in flex? I need this in order to match a specific rule only when some condition is true. Something like this:
%option c++
%option noyywrap
%%
/*if (condition) {*/
[0-9] {}
/*}*/
[0-9]{2} {}
. /* eat up any unmatched character */
%%
void yylex(void);
int main()
{
FlexLexer *lexer = new yyFlexLexer();
lexer->yylex();
delete lexer;
}
Or is it possible to modify the final c++ generated code, in order to match only some specific regex rules?
UPDATE:
Using start conditions doesn't seem to help. What I want is, depending on some external variable (like isNthRegexActive), to be able to match or not a specific regex.
For example, if I have 4 regex rules, and the first and 2nd are not active, the program should only check for the other 2, and always check for all of them (don't stop at first match - maybe use REJECT).
Example for 4 rules:
/* Declared at the top */
isActive[0] = false;
isActive[1] = false;
isActive[2] = true;
isActive[3] = true;
%%
[0-9]{4} { printf("1st: %s\n", yytext); REJECT;}
[0-3]{2}[0-3]{2} { printf("2nd: %s\n", yytext); REJECT; }
[1-3]{2}[0-3]{2} { printf("3rd: %s\n", yytext); REJECT; }
[1-2]{2}[1-2]{2} { printf("4th: %s\n", yytext); REJECT; }
.
%%
For the input: 1212 the result should be:
3rd: 1212
4th: 1212
Don't use REJECT unless you absolutely have no alternative. It massively slows down the lexical scan, artificially limits the size of the token buffer, and makes your lexical analysis very hard to reason about.
You might be thinking that a scanner generated by (f)lex tests each regular expression one at a time in order to select the best one for a given match. It does not work that way; that would be much too slow. What it does is, effectively, check all the regular expressions in parallel by using a precompiled deterministic state machine represented as a lookup table.
The state machine does exactly one transition for each input byte, using a simple O(1) lookup into the the transition table. (There are different table compression techniques which trade off table size against the constant in the O(1) lookup, but that doesn't change the basic logic.) What that all means is that you can use as many regular expressions as you wish; the time to do the lexical analysis does not depend on the number or complexity of the regular expressions. (Except for caching effects: if your transition table is really big, you might start running into cache misses during the transition lookups. In such cases, you might prefer a compression algorithm which compresses more.)
In most cases, you can use start conditions to achieve conditional matching, although you might need a lot of start conditions if there are a more than a few interacting conditions. Since the scanner can only have one active start condition, you'll need to generate a different start condition for each legal combination of the conditions you want to consider. That's usually most easily achieved through automatic generation of your scanner rules, but it can certainly be done by hand if there aren't too many.
It's hard to provide a more concrete suggestion without knowing what kinds of conditions you need to check.

Designing a Language Lexer

I'm currently in the process of creating a programming language. I've laid out my entire design and am in progress of creating the Lexer for it. I have created numerous lexers and lexer generators in the past, but have never come to adopt the "standard", if one exists.
Is there a specific way a lexer should be created to maximise capability to use it with as many parsers as possible?
Because the way I design mine, they look like the following:
Code:
int main() {
printf("Hello, World!");
}
Lexer:
[
KEYWORD:INT, IDENTIFIER:"main", LEFT_ROUND_BRACKET, RIGHT_ROUNDBRACKET, LEFT_CURLY_BRACKET,
IDENTIFIER:"printf", LEFT_ROUND_BRACKET, STRING:"Hello, World!", RIGHT_ROUND_BRACKET, COLON,
RIGHT_CURLY_BRACKET
]
Is this the way Lexer's should be made? Also as a side-note, what should my next step be after creating a Lexer? I don't really want to use something such as ANTLR or Lex+Yacc or Flex+Bison, etc. I'm doing it from scratch.
If you don't want to use a parser generator [Note 1], then it is absolutely up to you how your lexer provides information to your parser.
Even if you do use a parser generator, there are many details which are going to be project-dependent. Sometimes it is convenient for the lexer to call the parser with each token; other times is is easier if the parser calls the lexer; in some cases, you'll want to have a driver which interacts separately with each component. And clearly, the precise datatype(s) of your tokens will vary from project to project, which can have an impact on how you communicate as well.
Personally, I would avoid use of global variables (as in the original yacc/lex protocol), but that's a general style issue.
Most lexers work in streaming mode, rather than tokenizing the entire input and then handing the vector of tokens to some higher power. Tokenizing one token at a time has a number of advantages, particularly if the tokenization is context-dependent, and, let's face it, almost all languages have some impurity somewhere in their syntax. But, again, that's entirely up to you.
Good luck with your project.
Notes:
Do you also forgo the use of compilers and write all your code from scratch in assembler or even binary?
Is there a specific way a lexer should be created to maximise capability to use it with as many parsers as possible?
In the lexers I've looked at, the canonical API is pretty minimal. It's basically:
Token readNextToken();
The lexer maintains a reference to the source text and its internal pointers into where it is currently looking. Then, every time you call that, it scans and returns the next token.
The Token type usually has:
A "type" enum for which kind of token it is: string, operator, identifier, etc. There are usually special kinds for "EOF", meaning a special terminator token that is produced after the end of the input, and "ERROR" for the rare cases where a syntax error comes from the lexical grammar. This is mainly just unterminated string literals or totally unknown characters in the source.
The source text of the token.
Sometimes literals are converted to their proper value representation during lexing in which case you'll have that value too. So a number token would have "123" as text but also have the numeric value 123. Or you can do that during parsing/compilation.
Location within the source file of the token. This is for error reporting. Usually 1-based line and column, but can also just be start and end byte offsets. The latter is a little faster to produce and can be converted to line and column lazily if needed.
Depending on your grammar, you may need to be able to rewind the lexer too.

Good practice to parse data in a custom format

I'm writing a program that takes in input a straight play in a custom format and then performs some analysis on it (like number of lines and words for each character). It's just for fun, and a pretext for learning cool stuff.
The first step in that process is writing a parser for that format. It goes :
####Play
###Act I
##Scene 1
CHARACTER 1. Line 1, he's saying some stuff.
#Comment, stage direction
CHARACTER 2, doing some stuff. Line 2, she's saying some stuff too.
It's quite a simple format. I read extensively about basic parser stuff like CFG, so I am now ready to get some work done.
I have written my grammar in EBNF and started playing with flex/bison but it raises some questions :
Is flex/bison too much for such a simple parser ? Should I just write it myself as described here : Is there an alternative for flex/bison that is usable on 8-bit embedded systems? ?
What is good practice regarding the respective tasks of the tokenizer and the parser itself ? There is never a single solution, and for such a simple language they often overlap. This is especially true for flex/bison, where flex can perform some intense stuff with regex matching. For example, should "#" be a token ? Should "####" be a token too ? Should I create types that carry semantic information so I can directly identify for example a character ? Or should I just process it with flex the simplest way then let the grammar defined in bison decide what is what ?
With flex/bison, does it makes sense to perform the analysis while parsing or is it more elegant to parse first, then operate on the file again with some other tool ?
This got me really confused. I am looking for an elegant, perhaps simple solution. Any guideline ?
By the way, about the programing language, I don't care much. For now I am using C because of flex/bison but feel free to advise me on anything more practical as long as it is a widely used language.
It's very difficult to answer those questions without knowing what your parsing expectations are. That is, an example of a few lines of text does not provide a clear understanding of what the intended parse is; what the lexical and syntactic units are; what relationships you would like to extract; and so on.
However, a rough guess might be that you intend to produce a nested parse, where ##{i} indicates the nesting level (inversely), with i≥1, since a single # is not structural. That violates one principle of language design ("don't make the user count things which the computer could count more accurately"), which might suggest a structure more like:
#play {
#act {
#scene {
#location: Elsinore. A platform before the castle.
#direction: FRANCISCO at his post. Enter to him BERNARDO
BERNARDO: Who's there?
FRANCISCO: Nay, answer me: stand, and unfold yourself.
BERNARDO: Long live the king!
FRANCISCO: Bernardo?
or even something XML-like. But that would be a different language :)
The problem with parsing either of these with a classic scanner/parser combination is that the lexical structure is inconsistent; the first token on a line is special, but most of the file consists of unparsed text. That will almost inevitably lead to spreading syntactic information between the scanner and the parser, because the scanner needs to know the syntactic context in order to decide whether or not it is scanning raw text.
You might be able to avoid that issue. For example, you might require that a continuation line start with whitespace, so that every line not otherwise marked with #'s starts with the name of a character. That would be more reliable than recognizing a dialogue line just because it starts with the name of a character and a period, since it is quite possible for a character's name to be used in dialogue, even at the end of a sentence (which consequently might be the first word in a continuation line.)
If you do intend for dialogue lines to be distinguished by the fact that they start with a character name and some punctuation then you will definitely have to give the scanner access to the character list (as a sort of symbol table), which is a well-known but not particularly respected hack.
Consider the above a reflection about your second question ("What are the roles of the scanner and the parser?"), which does not qualify as an answer but hopefully is at least food for thought. As to your other questions, and recognizing that all of this is opinionated:
Is flex/bison too much for such a simple parser ? Should I just write it myself...
The fact that flex and bison are (potentially) more powerful than necessary to parse a particular language is a red herring. C is more powerful than necessary to write a factorial function -- you could easily do it in assembler -- but writing a factorial function is a good exercise in learning C. Similarly, if you want to learn how to write parsers, it's a good idea to start with a simple language; obviously, that's not going to exercise every option in the parser/scanner generators, but it will get you started. The question really is whether the language you're designing is appropriate for this style of parsing, not whether it is too simple.
With flex/bison, does it makes sense to perform the analysis while parsing or is it more elegant to parse first, then operate on the file again with some other tool?
Either can be elegant, or disastrous; elegance has more to do with how you structure your thinking about the problem at hand. Having said that, it is often better to build a semantic structure (commonly referred to as an AST -- abstract syntax tree) during the parse phase and then analyse that structure using other functions.
Rescanning the input file is very unlikely to be either elegant or effective.

Using ANTLR to analyze and modify source code; am I doing it wrong?

I'm writing a program where I need to parse a JavaScript source file, extract some facts, and insert/replace portions of the code. A simplified description of the sorts of things I'd need to do is, given this code:
foo(['a', 'b', 'c']);
Extract 'a', 'b', and 'c' and rewrite the code as:
foo('bar', [0, 1, 2]);
I am using ANTLR for my parsing needs, producing C# 3 code. Somebody else had already contributed a JavaScript grammar. The parsing of the source code is working.
The problem I'm encountering is figuring out how to actually properly analyze and modify the source file. Each approach that I try to take in actually solving the problem leads me to a dead end. I can't help but think that I'm not using the tool as it's intended or am just too much of a novice when it comes to dealing with ASTs.
My first approach was to parse using a TokenRewriteStream and implement the EnterRule_* partial methods for the rules I'm interested in. While this seems to make modifying the token stream pretty easy, there is not enough contextual information for my analysis. It seems that all I have access to is a flat stream of tokens, which doesn't tell me enough about the entire structure of code. For example, to detect whether the foo function is being called, simply looking at the first token wouldn't work because that would also falsely match:
a.b.foo();
To allow me to do more sophisticated code analysis, my second approach was to modify the grammar with rewrite rules to produce more of a tree. Now, the first sample code block produces this:
Program
CallExpression
Identifier('foo')
ArgumentList
ArrayLiteral
StringLiteral('a')
StringLiteral('b')
StringLiteral('c')
This is working great for analyzing the code. However, now I am unable to easily rewrite the code. Sure, I could modify the tree structure to represent the code I want, but I can't use this to output source code. I had hoped that the token associated with each node would at least give me enough information to know where in the original text I would need to make the modifications, but all I get are token indexes or line/column numbers. To use the line and column numbers, I would have to make an awkward second pass through the source code.
I suspect I'm missing something in understanding how to properly use ANTLR to do what I need. Is there a more proper way for me to solve this problem?
What you are trying to do is called program transformation, that is, the automated generation of one program from another. What you are doing "wrong" is assuming is parser is all you need, and discovering that it isn't and that you have to fill in the gap.
Tools that do that this well have parsers (to build ASTs), means to modify the ASTs (both procedural and pattern directed), and prettyprinters which convert the (modified) AST back into legal source code. You seem to be struggling with the the fact that ANTLR doesn't come with prettyprinters; that's not part of its philosophy; ANTLR is a (fine) parser-generator. Other answers have suggested using ANTLR's "string templates", which are not by themselves prettyprinters, but can be used to implement one, at the price of implementing one. This harder to do than it looks; see my SO answer on compiling an AST back to source code.
The real issue here is the widely made but false assumption that "if I have a parser, I'm well on my way to building complex program analysis and transformation tools." See my essay on Life After Parsing for a long discussion of this; basically, you need a lot more tooling that "just" a parser to do this, unless you want to rebuild a significant fraction of the infrastructure by yourself instead of getting on with your task. Other useful features of practical program transformation systems include typically source-to-source transformations, which considerably simplify the problem of finding and replacing complex patterns in trees.
For instance, if you had source-to-source transformation capabilities (of our tool, the DMS Software Reengineering Toolkit, you'd be able to write parts of your example code changes using these DMS transforms:
domain ECMAScript.
tag replace; -- says this is a special kind of temporary tree
rule barize(function_name:IDENTIFIER,list:expression_list,b:body):
expression->expression
= " \function_name ( '[' \list ']' ) "
-> "\function_name( \firstarg\(\function_name\), \replace\(\list\))";
rule replace_unit_list(s:character_literal):
expression_list -> expression_list
replace(s) -> compute_index_for(s);
rule replace_long_list(s:character_list, list:expression_list):
expression_list -> expression_list
"\replace\(\s\,\list)-> "compute_index_for\(\s\),\list";
with rule-external "meta" procedures "first_arg" (which knows how to compute "bar" given the identifier "foo" [I'm guessing you want to do this), and "compute_index_for" which given a string literals, knows what integer to replace it with.
Individual rewrite rules have parameter lists "(....)" in which slots representing subtrees are named, a left-hand side acting as a pattern to match, and an right hand side acting as replacement, both usually quoted in metaquotes " which seperates rewrite-rule language text from target-language (e.g. JavaScript) text. There's lots of meta-escapes ** found inside the metaquotes which indicate a special rewrite-rule-language item. Typically these are parameter names, and represent whatever type of name tree the parameter represents, or represent an external meta procedure call (such as first_arg; you'll note the its argument list ( , ) is metaquoted!), or finally, a "tag" such as "replace", which is a peculiar kind of tree that represent future intent to do more transformations.
This particular set of rules works by replacing a candidate function call by the barized version, with the additional intent "replace" to transform the list. The other two transformations realize the intent by transforming "replace" away by processing elements of the list one at a time, and pushing the replace further down the list until it finally falls off the end and the replacement is done. (This is the transformational equivalent of a loop).
Your specific example may vary somewhat since you really weren't precise about the details.
Having applied these rules to modify the parsed tree, DMS can then trivially prettyprint the result (the default behavior in some configurations is "parse to AST, apply rules until exhaustion, prettyprint AST" because this is handy).
You can see a complete process of "define language", "define rewrite rules", "apply rules and prettyprint" at (High School) Algebra as a DMS domain.
Other program transformation systems include TXL and Stratego. We imagine DMS as the industrial strength version of these, in which we have built all that infrastructure including many standard language parsers and prettyprinters.
So it's turning out that I can actually use a rewriting tree grammar and insert/replace tokens using a TokenRewriteStream. Plus, it's actually really easy to do. My code resembles the following:
var charStream = new ANTLRInputStream(stream);
var lexer = new JavaScriptLexer(charStream);
var tokenStream = new TokenRewriteStream(lexer);
var parser = new JavaScriptParser(tokenStream);
var program = parser.program().Tree as Program;
var dependencies = new List<IModule>();
var functionCall = (
from callExpression in program.Children.OfType<CallExpression>()
where callExpression.Children[0].Text == "foo"
select callExpression
).Single();
var argList = functionCall.Children[1] as ArgumentList;
var array = argList.Children[0] as ArrayLiteral;
tokenStream.InsertAfter(argList.Token.TokenIndex, "'bar', ");
for (var i = 0; i < array.Children.Count(); i++)
{
tokenStream.Replace(
(array.Children[i] as StringLiteral).Token.TokenIndex,
i.ToString());
}
var rewrittenCode = tokenStream.ToString();
Have you looked at the string template library. It is by the same person who wrote ANTLR and they are intended to work together. It sounds like it would suit do what your looking for ie. output matched grammar rules as formatted text.
Here is an article on translation via ANTLR

What is parsing in terms that a new programmer would understand? [closed]

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I am a college student getting my Computer Science degree. A lot of my fellow students really haven't done a lot of programming. They've done their class assignments, but let's be honest here those questions don't really teach you how to program.
I have had several other students ask me questions about how to parse things, and I'm never quite sure how to explain it to them. Is it best to start just going line by line looking for substrings, or just give them the more complicated lecture about using proper lexical analysis, etc. to create tokens, use BNF, and all of that other stuff? They never quite understand it when I try to explain it.
What's the best approach to explain this without confusing them or discouraging them from actually trying.
I'd explain parsing as the process of turning some kind of data into another kind of data.
In practice, for me this is almost always turning a string, or binary data, into a data structure inside my Program.
For example, turning
":Nick!User#Host PRIVMSG #channel :Hello!"
into (C)
struct irc_line {
char *nick;
char *user;
char *host;
char *command;
char **arguments;
char *message;
} sample = { "Nick", "User", "Host", "PRIVMSG", { "#channel" }, "Hello!" }
Parsing is the process of analyzing text made of a sequence of tokens to determine its grammatical structure with respect to a given (more or less) formal grammar.
The parser then builds a data structure based on the tokens. This data structure can then be used by a compiler, interpreter or translator to create an executable program or library.
(source: wikimedia.org)
If I gave you an english sentence, and asked you to break down the sentence into its parts of speech (nouns, verbs, etc.), you would be parsing the sentence.
That's the simplest explanation of parsing I can think of.
That said, parsing is a non-trivial computational problem. You have to start with simple examples, and work your way up to the more complex.
What is parsing?
In computer science, parsing is the process of analysing text to determine if it belongs to a specific language or not (i.e. is syntactically valid for that language's grammar). It is an informal name for the syntactic analysis process.
For example, suppose the language a^n b^n (which means same number of characters A followed by the same number of characters B). A parser for that language would accept AABB input and reject the AAAB input. That is what a parser does.
In addition, during this process a data structure could be created for further processing. In my previous example, it could, for instance, to store the AA and BB in two separate stacks.
Anything that happens after it, like giving meaning to AA or BB, or transform it in something else, is not parsing. Giving meaning to parts of an input sequence of tokens is called semantic analysis.
What isn't parsing?
Parsing is not transform one thing into another. Transforming A into B, is, in essence, what a compiler does. Compiling takes several steps, parsing is only one of them.
Parsing is not extracting meaning from a text. That is semantic analysis, a step of the compiling process.
What is the simplest way to understand it?
I think the best way for understanding the parsing concept is to begin with the simpler concepts. The simplest one in language processing subject is the finite automaton. It is a formalism to parsing regular languages, such as regular expressions.
It is very simple, you have an input, a set of states and a set of transitions. Consider the following language built over the alphabet { A, B }, L = { w | w starts with 'AA' or 'BB' as substring }. The automaton below represents a possible parser for that language whose all valid words starts with 'AA' or 'BB'.
A-->(q1)--A-->(qf)
/
(q0)
\
B-->(q2)--B-->(qf)
It is a very simple parser for that language. You start at (q0), the initial state, then you read a symbol from the input, if it is A then you move to (q1) state, otherwise (it is a B, remember the remember the alphabet is only A and B) you move to (q2) state and so on. If you reach (qf) state, then the input was accepted.
As it is visual, you only need a pencil and a piece of paper to explain what a parser is to anyone, including a child. I think the simplicity is what makes the automata the most suitable way to teaching language processing concepts, such as parsing.
Finally, being a Computer Science student, you will study such concepts in-deep at theoretical computer science classes such as Formal Languages and Theory of Computation.
Have them try to write a program that can evaluate arbitrary simple arithmetic expressions. This is a simple problem to understand but as you start getting deeper into it a lot of basic parsing starts to make sense.
Parsing is about READING data in one format, so that you can use it to your needs.
I think you need to teach them to think like this. So, this is the simplest way I can think of to explain parsing for someone new to this concept.
Generally, we try to parse data one line at a time because generally it is easier for humans to think this way, dividing and conquering, and also easier to code.
We call field to every minimum undivisible data. Name is field, Age is another field, and Surname is another field. For example.
In a line, we can have various fields. In order to distinguish them, we can delimit fields by separators or by the maximum length assign to each field.
For example:
By separating fields by comma
Paul,20,Jones
Or by space (Name can have 20 letters max, age up to 3 digits, Jones up to 20 letters)
Paul 020Jones
Any of the before set of fields is called a record.
To separate between a delimited field record we need to delimit record. A dot will be enough (though you know you can apply CR/LF).
A list could be:
Michael,39,Jordan.Shaquille,40,O'neal.Lebron,24,James.
or with CR/LF
Michael,39,Jordan
Shaquille,40,O'neal
Lebron,24,James
You can say them to list 10 nba (or nlf) players they like. Then, they should type them according to a format. Then make a program to parse it and display each record. One group, can make list in a comma-separated format and a program to parse a list in a fixed size format, and viceversa.
Parsing to me is breaking down something into meaningful parts... using a definable or predefined known, common set of part "definitions".
For programming languages there would be keyword parts, usable punctuation sequences...
For pumpkin pie it might be something like the crust, filling and toppings.
For written languages there might be what a word is, a sentence, what a verb is...
For spoken languages it might be tone, volume, mood, implication, emotion, context
Syntax analysis (as well as common sense after all) would tell if what your are parsing is a pumpkinpie or a programming language. Does it have crust? well maybe it's pumpkin pudding or perhaps a spoken language !
One thing to note about parsing stuff is there are usually many ways to break things into parts.
For example you could break up a pumpkin pie by cutting it from the center to the edge or from the bottom to the top or with a scoop to get the filling out or by using a sledge hammer or eating it.
And how you parse things would determine if doing something with those parts will be easy or hard.
In the "computer languages" world, there are common ways to parse text source code. These common methods (algorithims) have titles or names. Search the Internet for common methods/names for ways to parse languages. Wikipedia can help in this regard.
In linguistics, to divide language into small components that can be analyzed. For example, parsing this sentence would involve dividing it into words and phrases and identifying the type of each component (e.g.,verb, adjective, or noun).
Parsing is a very important part of many computer science disciplines. For example, compilers must parse source code to be able to translate it into object code. Likewise, any application that processes complex commands must be able to parse the commands. This includes virtually all end-user applications.
Parsing is often divided into lexical analysis and semantic parsing. Lexical analysis concentrates on dividing strings into components, called tokens, based on punctuationand other keys. Semantic parsing then attempts to determine the meaning of the string.
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Simple explanation: Parsing is breaking a block of data into smaller pieces (tokens) by following a set of rules (using delimiters for example),
so that this data could be processes piece by piece (managed, analysed, interpreted, transmitted, ets).
Examples: Many applications (like Spreadsheet programs) use CSV (Comma Separated Values) file format to import and export data. CSV format makes it possible for the applications to process this data with a help of a special parser.
Web browsers have special parsers for HTML and CSS files. JSON parsers exist. All special file formats must have some parsers designed specifically for them.

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