how to parse structured text file?

[Petr Jakes]

I have a file which contains data in the format shown in the sample
bellow.
How can I parse it to get following:
(14,trigger,gua rd,do_action,15 )

Thanks a lot for your postings
Petr Jakes

type:
4
bgrColor:
255 255 255
fgrColor:
0 0 0
objId:
16
Num.Pts:
2
177 104
350 134
objStartId:
14
objEndId:
15
eventName:
trigger
eventCond:
guard
eventAction:
do_action

[Paul McGuire]

Re: how to parse structured text file?

A problem fit for pyparsing! Download pyparsing at
http://pyparsing.sourceforge.net.

Assuming you always have these fields, in this order, this program will
figure them out. If not, you'll need to tweak the pyparsing
definitions as needed.

-- Paul


data = """type:
4
bgrColor:
255 255 255
fgrColor:
0 0 0
objId:
16
Num.Pts:
2
177 104
350 134
objStartId:
14
objEndId:
15
eventName:
trigger
eventCond:
guard
eventAction:
do_action
"""

from pyparsing import *

# define literals for field labels
type_ = Literal("type")
bgrColor = Literal("bgrCol or")
fgrColor = Literal("fgrCol or")
objId = Literal("objId" )
numPts = Literal("Num.Pt s")
objStartId = Literal("objSta rtId")
objEndId = Literal("objEnd Id")
eventName = Literal("eventN ame")
eventCond = Literal("eventC ond")
eventAction = Literal("eventA ction")

# define an integer, and tell parser to convert them to ints
intvalue = Word(nums).setP arseAction( lambda s,l,toks: int(toks[0]) )

# define an alphabetic identifier
alphavalue = Word(alphas,alp hanums+"_")

# define a 2D coordinate, with results names for fields
coordvalue = Group( intvalue.setRes ultsName("X") +
intvalue.setRes ultsName("Y") )

# define an RGB color value, with results names for fields
colorvalue = Group( intvalue.setRes ultsName("R") +
intvalue.setRes ultsName("G") +
intvalue.setRes ultsName("B") )

# compose an entry definition, using above-defined expressions, with
results names for fields
entry = ( type_ + ":" + "4" +
bgrColor + ":" + colorvalue.setR esultsName("bgr Color") +
fgrColor + ":" + colorvalue.setR esultsName("fgr Color") +
objId + ":" + intvalue.setRes ultsName("objId ") +
numPts + ":" + Group( intvalue.setRes ultsName("numpt s") +
OneOrMore( coordvalue ).setResultsNam e("coords")
).setResultsNam e("pts") +
objStartId + ":" + intvalue.setRes ultsName("objSt artId") +
objEndId + ":" + intvalue.setRes ultsName("objEn dId") +
eventName + ":" + alphavalue.setR esultsName("eve ntName") +
eventCond + ":" + alphavalue.setR esultsName("eve ntCond") +
eventAction + ":" + alphavalue.setR esultsName("eve ntAction")
)

# scan through input data, and retrieve data fields as desired
for entryData,start ,end in entry.scanStrin g(data):
print
"(%(objStartId) d,%(eventName)s ,%(eventCond)s, %(eventAction)s ,%(objEndId)d)"
% entryData
print entryData.objId
print entryData.bgrCo lor
print entryData.fgrCo lor
print [ (pt.X,pt.Y) for pt in entryData.pts.c oords ]
print [ tuple(pt) for pt in entryData.pts.c oords ]


Prints:
(14,trigger,gua rd,do_action,15 )
16
[255, 255, 255]
[0, 0, 0]
[(177, 104), (350, 134)]
[(177, 104), (350, 134)]