How can I extract the groups from this regex from a file object (data.txt)?
import numpy as np
import re
import os
ifile = open("data.txt",'r')
# Regex pattern
pattern = re.compile(r"""
^Time:(\d{2}:\d{2}:\d{2}) # Time: 12:34:56 at beginning of line
\r{2} # Two carriage return
\D+ # 1 or more non-digits
storeU=(\d+\.\d+)
\s
uIx=(\d+)
\s
storeI=(-?\d+.\d+)
\s
iIx=(\d+)
\s
avgCI=(-?\d+.\d+)
""", re.VERBOSE | re.MULTILINE)
time = [];
for line in ifile:
match = re.search(pattern, line)
if match:
time.append(match.group(1))
The problem in the last part of the code, is that I iterate line by line, which obviously doesn't work with multiline regex. I have tried to use pattern.finditer(ifile)
like this:
for match in pattern.finditer(ifile):
print match
... just to see if it works, but the finditer method requires a string or buffer.
I have also tried this method, but can't get it to work
matches = [m.groups() for m in pattern.finditer(ifile)]
Any idea?
After comment from Mike and Tuomas, I was told to use .read().. Something like this:
ifile = open("data.txt",'r').read()
This works fine, but would this be the correct way to search through the file? Can't get it to work...
for i in pattern.finditer(ifile):
match = re.search(pattern, i)
if match:
time.append(match.group(1))
Solution
# Open file as file object and read to string
ifile = open("data.txt",'r')
# Read file object to string
text = ifile.read()
# Close file object
ifile.close()
# Regex pattern
pattern_meas = re.compile(r"""
^Time:(\d{2}:\d{2}:\d{2}) # Time: 12:34:56 at beginning of line
\n{2} # Two newlines
\D+ # 1 or more non-digits
storeU=(\d+\.\d+) # Decimal-number
\s
uIx=(\d+) # Fetch uIx-variable
\s
storeI=(-?\d+.\d+) # Fetch storeI-variable
\s
iIx=(\d+) # Fetch iIx-variable
\s
avgCI=(-?\d+.\d+) # Fetch avgCI-variable
""", re.VERBOSE | re.MULTILINE)
file_times = open("output_times.txt","w")
for match in pattern_meas.finditer(text):
output = "%s,\t%s,\t\t%s,\t%s,\t\t%s,\t%s\n" % (match.group(1), match.group(2), match.group(3), match.group(4), match.group(5), match.group(6))
file_times.write(output)
file_times.close()
Maybe it can be written more compact and pythonic though....