Ok, so I've asked a bunch of smaller questions about this project, but I still don't have much confidence in the designs I'm coming up with, so I'm going to ask a question on a broader scale.
I am parsing pre-requisite descriptions for a course catalog. The descriptions almost always follow a certain form, which makes me think I can parse most of them.
From the text, I would like to generate a graph of course pre-requisite relationships. (That part will be easy, after I have parsed the data.)
Some sample inputs and outputs:
"CS 2110" => ("CS", 2110) # 0
"CS 2110 and INFO 3300" => [("CS", 2110), ("INFO", 3300)] # 1
"CS 2110, INFO 3300" => [("CS", 2110), ("INFO", 3300)] # 1
"CS 2110, 3300, 3140" => [("CS", 2110), ("CS", 3300), ("CS", 3140)] # 1
"CS 2110 or INFO 3300" => [[("CS", 2110)], [("INFO", 3300)]] # 2
"MATH 2210, 2230, 2310, or 2940" => [[("MATH", 2210), ("MATH", 2230), ("MATH", 2310)], [("MATH", 2940)]] # 3
If the entire description is just a course, it is output directly.
If the courses are conjoined ("and"), they are all output in the same list
If the course are disjoined ("or"), they are in separate lists
Here, we have both "and" and "or".
One caveat that makes it easier: it appears that the nesting of "and"/"or" phrases is never greater than as shown in example 3.
What is the best way to do this? I started with PLY, but I couldn't figure out how to resolve the reduce/reduce conflicts. The advantage of PLY is that it's easy to manipulate what each parse rule generates:
def p_course(p):
'course : DEPT_CODE COURSE_NUMBER'
p[0] = (p[1], int(p[2]))
With PyParse, it's less clear how to modify the output of parseString(). I was considering building upon @Alex Martelli's idea of keeping state in an object and building up the output from that, but I'm not sure exactly how that is best done.
def addCourse(self, str, location, tokens):
self.result.append((tokens[0][0], tokens[0][1]))
def makeCourseList(self, str, location, tokens):
dept = tokens[0][0]
new_tokens = [(dept, tokens[0][1])]
new_tokens.extend((dept, tok) for tok in tokens[1:])
self.result.append(new_tokens)
For instance, to handle "or" cases:
def __init__(self):
self.result = []
# ...
self.statement = (course_data + Optional(OR_CONJ + course_data)).setParseAction(self.disjunctionCourses)
def disjunctionCourses(self, str, location, tokens):
if len(tokens) == 1:
return tokens
print "disjunction tokens: %s" % tokens
How does disjunctionCourses() know which smaller phrases to disjoin? All it gets is tokens, but what's been parsed so far is stored in result, so how can the function tell which data in result corresponds to which elements of token? I guess I could search through the tokens, then find an element of result with the same data, but that feel convoluted...
Also, there are many descriptions that include misc text, like:
"CS 2110 or permission of instructor"
"INFO 3140 or equivalent experience"
"PYSCH 2210 and sophomore standing"
But it isn't critical that I parse that text.
What's a better way to approach this problem?
def parse(astr):
astr=astr.replace(',','')
astr=astr.replace('and','')
tokens=astr.split()
dept=None
number=None
result=[]
option=[]
for tok in tokens:
if tok=='or':
result.append(option)
option=[]
continue
if tok.isalpha():
dept=tok
number=None
else:
number=int(tok)
if dept and number:
option.append((dept,number))
else:
if option:
result.append(option)
return result
if __name__=='__main__':
tests=[ ("CS 2110" , [[("CS", 2110)]]),
("CS 2110 and INFO 3300" , [[("CS", 2110), ("INFO", 3300)]]),
("CS 2110, INFO 3300" , [[("CS", 2110), ("INFO", 3300)]]),
("CS 2110, 3300, 3140", [[("CS", 2110), ("CS", 3300), ("CS", 3140)]]),
("CS 2110 or INFO 3300", [[("CS", 2110)], [("INFO", 3300)]]),
("MATH 2210, 2230, 2310, or 2940", [[("MATH", 2210), ("MATH", 2230), ("MATH", 2310)], [("MATH", 2940)]])]
for test,answer in tests:
result=parse(test)
if result==answer:
print('GOOD: {0} => {1}'.format(test,answer))
else:
print('ERROR: {0} => {1} != {2}'.format(test,result,answer))
break
yields
GOOD: CS 2110 => [[('CS', 2110)]]
GOOD: CS 2110 and INFO 3300 => [[('CS', 2110), ('INFO', 3300)]]
GOOD: CS 2110, INFO 3300 => [[('CS', 2110), ('INFO', 3300)]]
GOOD: CS 2110, 3300, 3140 => [[('CS', 2110), ('CS', 3300), ('CS', 3140)]]
GOOD: CS 2110 or INFO 3300 => [[('CS', 2110)], [('INFO', 3300)]]
GOOD: MATH 2210, 2230, 2310, or 2940 => [[('MATH', 2210), ('MATH', 2230), ('MATH', 2310)], [('MATH', 2940)]]
For simple grammars I really like Parsing Expression Grammars (PEGs), which amount to a disciplined, structured way of writing a recursive-descent parser. In a dynamically typed language like Python you can do useful things without having a separate "parser generator". That means no nonsense with reduce-reduce conflicts or other arcana of LR parsing.
I did a little searching and pyPEG appears to be a nice library for Python.
I don't pretend to know much about parsing a grammar, and for your case the solution by unutbu is all you'll need. But I learnt a fair bit about parsing from Eric Lippert in his recent series of blog posts.
http://blogs.msdn.com/b/ericlippert/archive/2010/04/26/every-program-there-is-part-one.aspx
It's a 7 part series that goes through creating and parsing a grammar, then optimizing the grammar to make parsing easier and more performant. He produces C# code to generate all combinations of particular grammars, but it shouldn't be too much of a stretch to convert that into python to parse a fairly simple grammar of your own.
I know that this question is about a decade old and has certainly been answered now. I am mainly posting this answer to prove myself that I have understood PEG parsers at last. I'm using the fantastic parsimonious module here.
That being said, you could come up with a parsing grammar, build an ast and visit this one to obtain the desired structure:
from parsimonious.nodes import NodeVisitor
from parsimonious.grammar import Grammar
from itertools import groupby
grammar = Grammar(
r"""
term = course (operator course)*
course = coursename? ws coursenumber
coursename = ~"[A-Z]+"
coursenumber = ~"\d+"
operator = ws (and / or / comma) ws
and = "and"
or = (comma ws)? "or"
comma = ","
ws = ~"\s*"
"""
)
class CourseVisitor(NodeVisitor):
def __init__(self):
self.current = None
self.courses = []
self.listnum = 1
def generic_visit(self, node, children):
pass
def visit_coursename(self, node, children):
if node.text:
self.current = node.text
def visit_coursenumber(self, node, children):
course = (self.current, int(node.text), self.listnum)
self.courses.append(course)
def visit_or(self, node, children):
self.listnum += 1
courses = ["CS 2110", "CS 2110 and INFO 3300",
"CS 2110, INFO 3300", "CS 2110, 3300, 3140",
"CS 2110 or INFO 3300", "MATH 2210, 2230, 2310, or 2940"]
for course in courses:
tree = grammar.parse(course)
cv = CourseVisitor()
cv.visit(tree)
courses = [list(v) for _, v in groupby(cv.courses, lambda x: x[2])]
print(courses)
Here, we walk our way from bottom to top, starting with brickets like whitespace, the operators or, and and , which will eventually lead to the course and finally the term. The visitor class builds the desired (well, kind of, one needs to get rid of the last tuple element) structure.
If you get reduce/reduce conflicts you need to specify the precedence of "or" and "and". Im guessing "and" binds tightest, meaning "CS 101 and CS 102 or CS 201" means [[CS 101, CS 102] [CS 201]].
If you can find examples of both then the grammar is ambigous and you are out of luck. However you might be able to let this ambiguity be left underspecified, all depending on what you are going to do with the results.
PS, Looks like the language is regular, you could consider a DFA.
来源：https://stackoverflow.com/questions/2945357/how-best-to-parse-a-simple-grammar