Dear group, 

I have a file with 645,984 lines.  This file is
composedcompletely of bocks.

For e.g.

[Unit111]
Name=NONE
Direction=2
NumAtoms=16
NumCells=32
UnitNumber=111
UnitType=3
NumberBlocks=1

[Unit111_Block1]
Name=31318_at
BlockNumber=1
NumAtoms=16
NumCells=32
StartPosition=0
StopPosition=15
CellHeader=X    Y       PROBE   FEAT    QUAL    EXPOS   POS     CBASE   PBASE
TBASE   ATOM    INDEX   CODONIND        CODON   REGIONTYPE      REGION
Cell1=24        636     N       control 31318_at        0       13      A       
A       A       0       407064  -1
-1      99      
Cell2=24        635     N       control 31318_at        0       13      A       
T       A       0       406424  -1
-1      99      
Cell3=631       397     N       control 31318_at        1       13      T       
A       T       1       254711
-1      -1      99      



[Unit113]
Name=NONE
Direction=2
NumAtoms=16
NumCells=32
UnitNumber=113
UnitType=3
NumberBlocks=1

[Unit113_Block1]
Name=31320_at
BlockNumber=1
NumAtoms=16
NumCells=32
StartPosition=0
StopPosition=15
CellHeader=X    Y       PROBE   FEAT    QUAL    EXPOS   POS     CBASE   PBASE
TBASE   ATOM    INDEX   CODONIND        CODON   REGIONTYPE      REGION
Cell1=68        63      N       control 31320_at        0       13      T       
A       T       0       40388   -1
-1      99      
Cell2=68        64      N       control 31320_at        0       13      T       
T       T       0       41028   -1
-1      99      
Cell3=99        194     N       control 31320_at        1       13      C       
C       C       1       124259  -1
-1      99      





I have a file with identifiers that are found in the
first file as :
Name=31320_at


I am interested in getting lines of block that are
present in first to be written as a file.  

I am search:

search = re.search ["_at")


my question:
how can i tell python to select some rows that have
particular pattern such as [Name] or Name of [Unit]. 
is there any way of doing this. 
please help me

thanks
kumar

__________________________________________________
Do You Yahoo!?
Tired of spam?  Yahoo! Mail has the best spam protection around 
http://mail.yahoo.com 
_______________________________________________
Tutor maillist  -  [EMAIL PROTECTED]
http://mail.python.org/mailman/listinfo/tutor

Reply via email to