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‎Python4Everybody/Ch_11_RegExp/assigndraft.py‎

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# [x] extract the numbers in the file
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# [] cast as ints if necessary
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# [] compute the sum of the numbers
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import re
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handle = open('sampledata.txt')
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for line in handle:
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line = line.rstrip()
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x = re.findall('[0-9]+', line)
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if len(x) > 0:
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print(x)
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‎Python4Everybody/Ch_11_RegExp/assignment1.py‎

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#Finding Numbers in a Haystack
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#In this assignment you will read through and parse a file with text and numbers. You will extract all the numbers in the file and compute the sum of the numbers.
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#Data Files
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#We provide two files for this assignment. One is a sample file where we give you the sum for your testing and the other is the actual data you need to process for the assignment.
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#Sample data: http://py4e-data.dr-chuck.net/regex_sum_42.txt (There are 90 values with a sum=445833)
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#Actual data: http://py4e-data.dr-chuck.net/regex_sum_2003014.txt (There are 97 values and the sum ends with 724)
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#These links open in a new window. Make sure to save the file into the same folder as you will be writing your Python program. Note: Each student will have a distinct data file for the assignment - so only use your own data file for analysis.
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#Data Format
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#The file contains much of the text from the introduction of the textbook except that random numbers are inserted throughout the text. Here is a sample of the output you might see:
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#Why should you learn to write programs? 7746
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#12 1929 8827
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#Writing programs (or programming) is a very creative
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#7 and rewarding activity. You can write programs for
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#many reasons, ranging from making your living to solving
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#8837 a difficult data analysis problem to having fun to helping 128
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#someone else solve a problem. This book assumes that
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#everyone needs to know how to program ...
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#The sum for the sample text above is 27486. The numbers can appear anywhere in the line. There can be any number of numbers in each line (including none).
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#Handling The Data
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#The basic outline of this problem is to read the file, look for integers using the re.findall(), looking for a regular expression of '[0-9]+' and then converting the extracted strings to integers and summing up the integers.
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‎Python4Everybody/Ch_11_RegExp/charmatch.py‎

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# search for lines that start with 'F', followed by
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# 2 characters, followed by 'm'
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# the '..' in the ^F..m search are placeholders for
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# any strings, e.g. Fxxm, F12m, F!@m etc.
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import re
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hand = open('mbox-short.txt')
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for line in hand:
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line = line.rstrip()
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if re.search('^F..m:', line):
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print(line)
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‎Python4Everybody/Ch_11_RegExp/example.py‎

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‎Python4Everybody/Ch_11_RegExp/findall.py‎

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# this code uses findall() to find the lines with email addresses
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# and extract one or more addresses from each of those lines.
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import re
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s = 'A message from csev@umich.edu to cwen@iupui.edu about meeting @2PM'
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Ast = re.findall('\S+@\S+', s)
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print(Ast)
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# makes use of the ' \S ' two-character sequence that matches
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# a non-whitespace cjaracter (\S).abs
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# \S+ matches as many non-whitespace characters as possible.

‎Python4Everybody/Ch_11_RegExp/findall2.py‎

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import re
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hand = open('mbox-short.txt')
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for line in hand:
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line = line.rstrip()
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x = re.findall('\S+@\S+', line)
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if len(x) > 0:
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print(x)
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‎Python4Everybody/Ch_11_RegExp/findall3.py‎

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# search for lines that have an at sign between characters
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# the characters must be a letter or a number
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import re
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hand = open('mbox-short.txt')
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for line in hand:
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line = line.rstrip()
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x = re.findall('[a-zA-Z0-9]\S*@\S*[a-zA-Z]',line)
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if len(x) > 0:
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print(x)
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‎Python4Everybody/Ch_11_RegExp/greedy.py‎

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# greedy matching / when a string can match more than
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# one possible string it matches the largest found
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import re
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x = 'From: Using the : character'
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y = re.findall('^F.+:', x)
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print(y)
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# in the above, ' From Using the : ' is returned instead of merely 'From: ' as it
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# is longer
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# demonstrates greedy matching
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# greedy matching returns the largest possible string
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# the repeat characters (*) and (+) push outward in both directions
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# to match the largest possible string
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# so, the code below returns not only 'From' but 'From: Using the : '
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import re
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x = 'From: Using the : character'
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y = re.findall('^F.+:', x)
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print(y)
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# ^F == first character in the match is an F
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# .+ == one or more characters
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# : == last character in the match is a colon
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# Non-Greedy
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# the .+? returns one or more characters but not greedy
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# the example below returns 'From:'
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import re
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x = 'From: Using the : character'
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y = re.findall('^F.+?:', x)
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print(y)
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# fine-tuning str extraction
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# \S == at least one non-whitespace character (one or more)
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# \S+ == at least one non-whitespace character (one or more)
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# example below returns:
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# ['stephen.marquard@uct.ac.za']
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import re
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U = 'From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008'
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T = re.findall('\S+@\S+', U)
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print(T)
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# the following:
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# ^From (\S+@)\S+)
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# would look for str starting with From followed by a space
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# then the rest of expression
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import re
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U = 'From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008'
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T = re.findall('^From \S+@\S+', U)
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print(T)
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# N.B.: adding ( ) as in the example below tells it to
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# return what is inside the ( ) , although you still match
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# the strings beginning with From
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# i.e. what you place inside the ( ) is what is returned
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import re
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U = 'From stephen.marquard@uct.ac.za Sat Jan 5 09:14:16 2008'
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T = re.findall('^From (\S+@\S+)', U)
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print(T)

‎Python4Everybody/Ch_11_RegExp/matchext.py‎

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import re
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x = '2 numbers are 19 and 42'
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y = re.findall('[0-9]+',x)
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z = re.findall('[AEIOU]+', x)
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print(y)
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print(z)
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