From Perl's documentation:
study takes extra time to study SCALAR ($_ if unspecified) in anticipation of doing
many pattern matches on the string before it is next modified. This may or may not save
time, depending on the nature and number of patterns you are searching and the distribution
of character frequencies in the string to be searched;
I'm trying to speed up some regular expression-driven parsing that I'm doing in Python, and I remembered this trick from Perl. I realize I'll have to benchmark to determine if there is a speedup, but I can't find an equivalent method in Python.
Perl’s study doesn’t really do much anymore. The regex compiled has gotten a whole, whole lot smarter than it was when study was created.
For example, it compiles alternatives into a trie structure with Aho–Corasick prediction.
Run with perl -Mre=debug to see the sorts of cleverness the regex compiler and execution engine apply.
As far as I know there's nothing like this built into Python. But according to the perldoc:
The way study works is this: a linked list of every character in the
string to be searched is made, so we know, for example, where all the
'k' characters are. From each search string, the rarest character is
selected, based on some static frequency tables constructed from some
C programs and English text. Only those places that contain this
"rarest" character are examined.
This doesn't sound very sophisticated, and you could probably hack together something equivalent yourself.
esmre is kind of vaguely similar. And as #Frg noted, you'll want to use re.compile if you're reusing a single regex (to avoid re-parsing the regex itself over and over).
Or you could use suffix trees (here's one implementation, or here's a C extension with unicode support) or suffix arrays (implementation).
Related
I wrote a lexical analyzer for cpp codes in python, but the problem is when I use input.split(" ") it won't recognize codes like x=2 or function() as three different tokens unless I add an space between them manually, like: x = 2 .
also it fails to recognize the tokens at the beginning of each line.
(if i add spaces between each two tokens and also at the beginning of each line, my code works correctly)
I tried splitting the code first by lines then by space but it got complicated and still I wasn't able to solve the first problem.
Also I thought about splitting it by operators, yet I couldn't actually implement it. plus I need the operators to be recognized as tokens as well, so this might not be a good idea.
I would appreciate it if anyone could give any solution or suggestion, Thank You.
f=open("code.txt")
input=f.read()
input=input.split(" ")
f=open("code.txt")
input=f.read()
input1=input.split("\n")
for var in input1:
var=var.split(" ")
Obviously, if you try to have success splitting such an expression like x=2 and also x = 2... it seems pretty obvious that isn't going to work.
What you are looking is for a solution that works with both right?
Basic solution is to use an and operator, and use the conditions that you need to parse. Note that this solution isn't scalable, neither fits into the category of good practices, but it can help you to figure out better but harder solutions.
if input.split(' ') and input.split('='):
An intermediate solution would be to use regex.
Regex isn't an easy topic, but you can checkout online documentation, and then you have wonderful online tools to check your regex codes.
Regex 101
The last one, would be to convert your input data into an AST, which stands for abstract syntax tree. This is the technique employed by C++ compilers like, for example, Clang.
This last one is a real hard topic, so for figure out a basic lexer, probably will be really time consuming, but maybe it could fit your needs.
The usual approach is to scan the incoming text from left to right. At each character position, the lexical analyser selects the longest string which fits some pattern for a "lexeme", which is either a token or ignored input (whitespace and comments, for example). Then the scan continues at the next character.
Lexical patterns are often described using regular expressions, but the standard regular expression module re is not as much help as it could be for this procedure, because it does not have the facility of checking multiple regular expressions in parallel. (And neither does the possible future replacement, the regex module.) Or, more precisely, the library can check multiple expressions in parallel (using alternation syntax, (...|...|...)), but it lacks an interface which can report which of the alternatives was matched. [Note 1]. So it would be necessary to try every possible pattern one at a time and select whichever one turns out to have the longest match.
Note that the matches are always anchored at the current input point; the lexical analyser does not search for a matching pattern. Every input character becomes part of some lexeme, even if that lexeme is ignored, and lexemes do not overlap.
You can write such an analyser by hand for a simple language, but C++ is hardly a simple language. Hand-built lexical analysers most certainly exist, but all the ones I've seen are thousands of lines of not very readable code. So it's usually easier to build an analyzer automatically using software designed for that purpose. These have been around for a long time -- Lex was written almost 50 years ago, for example -- and if you are planning on writing more than one lexical analyser, you would be well advised to investigate some of the available tools.
Notes
The PCRE2 and Oniguruma regex libraries provide a "callout" feature which I believe could be used for this purpose. I haven't actually seen it used in lexical analysis, but it's a fairly recent addition, particularly for Oniguruma, and as far as I can see, the Python bindings for those two libraries do not wrap the callout feature. (Although, as usual with Python bindings to C libraries, documentation is almost non-existent, so I can't say for certain.)
I've seen regex patterns that use explicitly numbered repetition instead of ?, * and +, i.e.:
Explicit Shorthand
(something){0,1} (something)?
(something){1} (something)
(something){0,} (something)*
(something){1,} (something)+
The questions are:
Are these two forms identical? What if you add possessive/reluctant modifiers?
If they are identical, which one is more idiomatic? More readable? Simply "better"?
To my knowledge they are identical. I think there maybe a few engines out there that don't support the numbered syntax but I'm not sure which. I vaguely recall a question on SO a few days ago where explicit notation wouldn't work in Notepad++.
The only time I would use explicitly numbered repetition is when the repetition is greater than 1:
Exactly two: {2}
Two or more: {2,}
Two to four: {2,4}
I tend to prefer these especially when the repeated pattern is more than a few characters. If you have to match 3 numbers, some people like to write: \d\d\d but I would rather write \d{3} since it emphasizes the number of repetitions involved. Furthermore, down the road if that number ever needs to change, I only need to change {3} to {n} and not re-parse the regex in my head or worry about messing it up; it requires less mental effort.
If that criteria isn't met, I prefer the shorthand. Using the "explicit" notation quickly clutters up the pattern and makes it hard to read. I've worked on a project where some developers didn't know regex too well (it's not exactly everyone's favorite topic) and I saw a lot of {1} and {0,1} occurrences. A few people would ask me to code review their pattern and that's when I would suggest changing those occurrences to shorthand notation and save space and, IMO, improve readability.
I can see how, if you have a regex that does a lot of bounded repetition, you might want to use the {n,m} form consistently for readability's sake. For example:
/^
abc{2,5}
xyz{0,1}
foo{3,12}
bar{1,}
$/x
But I can't recall ever seeing such a case in real life. When I see {0,1}, {0,} or {1,} being used in a question, it's virtually always being done out of ignorance. And in the process of answering such a question, we should also suggest that they use the ?, * or + instead.
And of course, {1} is pure clutter. Some people seem to have a vague notion that it means "one and only one"--after all, it must mean something, right? Why would such a pathologically terse language support a construct that takes up a whole three characters and does nothing at all? Its only legitimate use that I know of is to isolate a backreference that's followed by a literal digit (e.g. \1{1}0), but there are other ways to do that.
They're all identical unless you're using an exceptional regex engine. However, not all regex engines support numbered repetition, ? or +.
If all of them are available, I'd use characters rather than numbers, simply because it's more intuitive for me.
They're equivalent (and you'll find out if they're available by testing your context.)
The problem I'd anticipate is when you may not be the only person ever needing to work with your code.
Regexes are difficult enough for most people. Anytime someone uses an unusual syntax, the question
arises: "Why didn't they do it the standard way? What were they thinking that I'm missing?"
I've seen regex patterns that use explicitly numbered repetition instead of ?, * and +, i.e.:
Explicit Shorthand
(something){0,1} (something)?
(something){1} (something)
(something){0,} (something)*
(something){1,} (something)+
The questions are:
Are these two forms identical? What if you add possessive/reluctant modifiers?
If they are identical, which one is more idiomatic? More readable? Simply "better"?
To my knowledge they are identical. I think there maybe a few engines out there that don't support the numbered syntax but I'm not sure which. I vaguely recall a question on SO a few days ago where explicit notation wouldn't work in Notepad++.
The only time I would use explicitly numbered repetition is when the repetition is greater than 1:
Exactly two: {2}
Two or more: {2,}
Two to four: {2,4}
I tend to prefer these especially when the repeated pattern is more than a few characters. If you have to match 3 numbers, some people like to write: \d\d\d but I would rather write \d{3} since it emphasizes the number of repetitions involved. Furthermore, down the road if that number ever needs to change, I only need to change {3} to {n} and not re-parse the regex in my head or worry about messing it up; it requires less mental effort.
If that criteria isn't met, I prefer the shorthand. Using the "explicit" notation quickly clutters up the pattern and makes it hard to read. I've worked on a project where some developers didn't know regex too well (it's not exactly everyone's favorite topic) and I saw a lot of {1} and {0,1} occurrences. A few people would ask me to code review their pattern and that's when I would suggest changing those occurrences to shorthand notation and save space and, IMO, improve readability.
I can see how, if you have a regex that does a lot of bounded repetition, you might want to use the {n,m} form consistently for readability's sake. For example:
/^
abc{2,5}
xyz{0,1}
foo{3,12}
bar{1,}
$/x
But I can't recall ever seeing such a case in real life. When I see {0,1}, {0,} or {1,} being used in a question, it's virtually always being done out of ignorance. And in the process of answering such a question, we should also suggest that they use the ?, * or + instead.
And of course, {1} is pure clutter. Some people seem to have a vague notion that it means "one and only one"--after all, it must mean something, right? Why would such a pathologically terse language support a construct that takes up a whole three characters and does nothing at all? Its only legitimate use that I know of is to isolate a backreference that's followed by a literal digit (e.g. \1{1}0), but there are other ways to do that.
They're all identical unless you're using an exceptional regex engine. However, not all regex engines support numbered repetition, ? or +.
If all of them are available, I'd use characters rather than numbers, simply because it's more intuitive for me.
They're equivalent (and you'll find out if they're available by testing your context.)
The problem I'd anticipate is when you may not be the only person ever needing to work with your code.
Regexes are difficult enough for most people. Anytime someone uses an unusual syntax, the question
arises: "Why didn't they do it the standard way? What were they thinking that I'm missing?"
I am learning Python, and need to format "From" fields received from IMAP. I tried it using str.find() and str.strip(), and also using regex. With find(), etc. my function runs quite a bit faster than with re (I timed it). So, when is it better to use re? Does anybody have any good links/articles related to that? Python documentation obviously doesn't mention that...
find only matches an exact sequence of characters, while a regular expression matches a pattern. Naturally only looking an for exact sequence is faster (even if your regex pattern is also an exact sequence, there is still some overhead involved).
As a consequence of the above, you should use find if you know the exact sequence, and a regular expression (or something else) when you don't. The exact approach you should use really depends on the complexity of the problem you face.
As a side note, the python re module provides a compile method that allows you to pre-compile a regex if you are going to be using it repeatedly. This can substantially improve speed if you are using the same pattern many times.
If you intend to do something complex you should use re . It is more scalable than using string methods.
String methods are good for doing something simple and not worth bothering with regular expressions.
So, it depends on what are you doing, but usually you should use regular expressions since they are more powerful.
I am seeking direction and attempting to label this problem:
I am attempting to build a simple inference engine (is there a better name?) in Python which will take a string and -
1 - create a list of tokens by simply creating a list of white space separated values
2 - categorise these tokens, using regular expressions
3 - Use a higher level set of rules to make decisions based on the categorisations
Example:
"90001" - one token, matches the zipcode regex, a rule exists for a string containing just a zipcode causes a certain behaviour to occur
"30 + 14" - three tokens, regexs for numerical value and mathematical operators match, a rule exists for a numerical value followed by a mathematical operator followed by another numerical value causes a certain behaviour to occur
I'm struggling with how best to do step #3, the higher level set of rules. I'm sure that some framework must exist. Any ideas? Also, how would you characterise this problem? Rule based system, expert system, inference engine, something else?
Thanks!
I'm very surprised that step #3 is the one giving you trouble...
Assuming you can label/categorize properly each token (and that prior to categorization you can find the proper tokens, as there may be many ambiguous cases...), the "Step #3" problem seems one that could easily be tackled with a context free grammar where each of the desired actions (such as ZIP code lookup or Mathematical expression calculation...) would be symbols with their production rule itself made of the possible token categories. To illustrate this in BNF notation, we could have something like
<SimpleMathOperation> ::= <NumericalValue><Operator><NumericalValue>
Maybe your concern is that when things get complicated, it will become difficult to express the whole requirement in terms of non-conflicting grammar rules. Or maybe your concern is that one could add rules dynamically, hence forcing the grammar "compilation" logic to be integrated with the program ? Whatever the concern, I think that this 3rd step will comparatively be trivial.
On the other hand, and unless the various categories (and underlying input text) are such that they can be described with a regular language as well (as you seem to hint in the question), a text parser and classifier (Steps #1 and #2...) is typically a less than trivial affair..
Some example Python libraries that simplify writing and evaluating grammars:
pijnu
pyparsing
It looks like you search for "grammar inference" (grammar induction) library.