I am looking to match a pattern such as
(u'-<21 characters>', N),
21 character of 0-9, a-z, A-Z plus characters like ~!##$%^&*()_ ...
N is a number from 1 to 99
I am trying to find the specific way to retrieve the 21 characters as well as the number N and use them later on using the re.match method but I do not know how and the documentation is not understandable. How do I do so?
Here is one program that might do what you want.
Note the use of parentheses () to isolate the data you are looking for. Note also the use of m.group(1), m.group(2) to retrieve those saved items.
Note also the use of re.search() instead of re.match(). re.match() must match the data from the very beginning of the string. re.search(), on the other hand, will find the first match, regardless of its location in the string. (But also consider using re.findall(), if a string might have multiple matches.).
Don't be confused by my use of .splitlines(), it is just for the sake of the sample program. You could equally well do data = open('foo.txt') / for line in data:.
import re
data = '''
(u'--UE_y6auTgq3FXlvUMkbw', 10),
(u'--XBxRlD92RaV6TyUnP8Ow', 1),
(u'--sSW-WY3vyASh_eVPGUAw', 2),
(u'-0GkcDiIgVm0XzDZC8RFOg', 9),
(u'-0OlcD1Ngv3yHXZE6KDlnw', 1),
(u'-0QBrNvhrPQCaeo7mTo0zQ', 1)
'''
data = data.splitlines()
for line in data:
m = re.search(r"'(.+)', (\d+)", line)
if m:
chars = m.group(1)
N = int(m.group(2))
print("I found a match!: {}, {}".format(chars, N))
Related
I have text with values like:
this is a value £28.99 (0.28/ml)
I want to remove everything to return the price only so it returns:
£28.99
there could be any number of digits between the £ and .
I think
r"£[0-9]*\.[0-9]{2}"
matches the pattern I want to keep but i'm unsure on how to remove everything else and keep the pattern instead of replacing the pattern like in usual re.sub() cases.
I want to remove everything to return the price only so it returns:
Why not trying to extract the proper information instead?
import re
s = "this is a value £28.99 (0.28/ml)"
m = re.search("£\d*(\.\d+)?",s)
if m:
print(m.group(0))
to find several occurrences use findall or finditer instead of search
You don't care how many digits are before the decimal, so using the zero-or-more matcher was correct. However, you could just rely on the digit class (\d) to provide that more succinctly.
The same is true of after the decimal. You only need two so your limiting the matches to 2 is correct.
The issue then comes in with how you actually capture the value. You can use a capturing group to be sure that you only ever get the value you care about.
Complete regex:
(£\d*.\d{2})
Sample code:
import re
r = re.compile("(£\d*.\d{2})")
match = r.findall("this is a value £28.99 (0.28/ml)")
if match: # may bring back an empty list; check for that here
print(match[0]) # uses the first group, and will print £28.99
If it's a string, you can do something like this:
x = "this is a value £28.99 (0.28/ml)"
x_list = x.split()
for i in x_list:
if "£" in i: #or if i.startswith("£") Credit – Jean-François Fabre
value=i
print(value)
>>>£28.99
You can try:
import re
t = "this is a value £28.99 (0.28/ml)"
r = re.sub(".*(£[\d.]+).*", r"\1", t)
print(r)
Output:
£28.99
Python Demo
I have a file with two different types of data I'd like to parse with a regex; however, the data is similar enough that I can't find the correct way to distinguish it.
Some lines in my file are of form:
AED=FRI
AFN=FRI:SAT
AMD=SUN:SAT
Other lines are of form
AED=20180823
AMD=20150914
AMD=20150921
The remaining lines are headers and I'd like to discard them. For example
[HEADER: BUSINESS DATE=20160831]
My solution attempt so far is to match first three capital letters and an equal sign,
r'\b[A-Z]{3}=\b'
but after that I'm not sure how to distinguish between dates (eg 20180823) and days (eg FRI:SAT:SUN).
The results I'd expect from these parsing functions:
Regex weekday_rx = new Regex(<EXPRESSION FOR TYPES LIKE AED=FRI>);
Regex date_rx = new Regex(<EXPRESSION FOR TYPES LIKE AED=20160816>);
weekdays = [weekday_rx.Match(line) for line in infile.read()]
dates = [date_rx.Match(line) for line in infile.read()]
r'\S*\d$'
Will match all non-whitespace characters that end in a digit
Will match AED=20180823
r'\S*[a-zA-Z]$'
Matches all non-whitespace characters that end in a letter.
will match AED=AED=FRI
AFN=FRI:SAT
AMD=SUN:SAT
Neither will match
[HEADER: BUSINESS DATE=20160831]
This will match both
r'(\S*[a-zA-Z]$|\S*\d$)'
Replacing the * with the number of occurences you expect will be safer, the (a|b) is match a or match b
The following is a solution in Python :)
import re
p = re.compile(r'\b([A-Z]{3})=((\d)+|([A-Z])+)')
str_test_01 = "AMD=SUN:SAT"
m = p.search(str_test_01)
print (m.group(1))
print (m.group(2))
str_test_02 = "AMD=20150921"
m = p.search(str_test_02)
print (m.group(1))
print (m.group(2))
"""
<Output>
AMD
SUN
AMD
20150921
"""
Use pipes to express alternatives in regex. Pattern '[A-Z]{3}:[A-Z]{3}|[A-Z]{3}' will match both ABC and ABC:ABC. Then use parenthesis to group results:
import re
match = re.match(r'([A-Z]{3}:[A-Z]{3})|([A-Z]{3})', 'ABC:ABC')
assert match.groups() == ('ABC:ABC', None)
match = re.match(r'([A-Z]{3}:[A-Z]{3})|([A-Z]{3})', 'ABC')
assert match.groups() == (None, 'ABC')
You can research the concept of named groups to make this even more readable. Also, take a look at the docs for the match object for useful info and methods.
I'm a newbie at python.
So my file has lines that look like this:
-1 1:-0.294118 2:0.487437 3:0.180328 4:-0.292929 5:-1 6:0.00149028 7:-0.53117 8:-0.0333333
I need help coming up with the correct python code to extract every float preceded by a colon and followed by a space (ex: [-0.294118, 0.487437,etc...])
I've tried dataList = re.findall(':(.\*) ', str(line)) and dataList = re.split(':(.\*) ', str(line)) but these come up with the whole line. I've been researching this problem for a while now so any help would be appreciated. Thanks!
try this one:
:(-?\d\.\d+)\s
In your code that will be
p = re.compile(':(-?\d\.\d+)\s')
m = p.match(str(line))
dataList = m.groups()
This is more specific on what you want.
In your case .* will match everything it can
Test on Regexr.com:
In this case last element wasn't captured because it doesnt have space to follow, if this is a problem just remove the \s from the regex
This will do it:
import re
line = "-1 1:-0.294118 2:0.487437 3:0.180328 4:-0.292929 5:-1 6:0.00149028 7:-0.53117 8:-0.0333333"
for match in re.finditer(r"(-?\d\.\d+)", line, re.DOTALL | re.MULTILINE):
print match.group(1)
Or:
match = re.search(r"(-?\d\.\d+)", line, re.DOTALL | re.MULTILINE)
if match:
datalist = match.group(1)
else:
datalist = ""
Output:
-0.294118
0.487437
0.180328
-0.292929
0.00149028
-0.53117
-0.0333333
Live Python Example:
http://ideone.com/DpiOBq
Regex Demo:
https://regex101.com/r/nR4wK9/3
Regex Explanation
(-?\d\.\d+)
Match the regex below and capture its match into backreference number 1 «(-?\d\.\d+)»
Match the character “-” literally «-?»
Between zero and one times, as many times as possible, giving back as needed (greedy) «?»
Match a single character that is a “digit” (ASCII 0–9 only) «\d»
Match the character “.” literally «\.»
Match a single character that is a “digit” (ASCII 0–9 only) «\d+»
Between one and unlimited times, as many times as possible, giving back as needed (greedy) «+»
Given:
>>> s='-1 1:-0.294118 2:0.487437 3:0.180328 4:-0.292929 5:-1 6:0.00149028 7:-0.53117 8:-0.0333.333'
With your particular data example, you can just grab the parts that would be part of a float with a regex:
>>> re.findall(r':([\d.-]+)', s)
['-0.294118', '0.487437', '0.180328', '-0.292929', '-1', '0.00149028', '-0.53117', '-0.0333.333']
You can also split and partition, which would be substantially faster:
>>> [e.partition(':')[2] for e in s.split() if ':' in e]
['-0.294118', '0.487437', '0.180328', '-0.292929', '-1', '0.00149028', '-0.53117', '-0.0333.333']
Then you can convert those to a float using try/except and map and filter:
>>> def conv(s):
... try:
... return float(s)
... except ValueError:
... return None
...
>>> filter(None, map(conv, [e.partition(':')[2] for e in s.split() if ':' in e]))
[-0.294118, 0.487437, 0.180328, -0.292929, -1.0, 0.00149028, -0.53117, -0.0333333]
A simple oneliner using list comprehension -
str = "-1 1:-0.294118 2:0.487437 3:0.180328 4:-0.292929 5:-1 6:0.00149028 7:-0.53117 8:-0.0333333"
[float(s.split()[0]) for s in str.split(':')]
Note: this is simplest to understand (and pobably fastest) as we are not doing any regex evaluation. But this would only work for the particular case above. (eg. if you've to get the second number - in the above not so correctly formatted string would need more work than a single one-liner above).
My code does the following:
Take a large text file (i.e. a legal document that is 300 pages as a PDF).
Find a certain keyword (e.g. "small").
Return n words to the left and n words to the right of the keyword.
NOTE: In this context, a "word" is any string of non-space characters. "$cow123" would be a word, but "health care" would be two words.
Here is my problem:
The code takes an extremely long time to run on the 300 pages, and that time tends to increase very quickly as n increases.
Here is my code:
fileHandle = open('test_pdf.txt', mode='r')
document = fileHandle.read()
def search(searchText, doc, n):
#Searches for text, and retrieves n words either side of the text, which are returned separately
surround = r"\s*(\S*)\s*"
groups = re.search(r'{}{}{}'.format(surround*n, searchText, surround*n), doc).groups()
return groups[:n],groups[n:]
Here is the nasty culprit:
print search("\$27.5 million", document, 10)
Here's how you can test this code:
Copy the function definition from the code block above and run the following:
t = "The world is a small place, we $.205% try to take care of it."
print search("\$.205", t, 3)
I suspect that I have a nasty case of catastrophic backtracking, but I'm too new to regex to point my finger on the problem.
How do I speed up my code?
How about using re.search (or even string.find if you're only searching for fixed strings) to find the string, without any surrounding capturing groups. Then you use the position and length of the match (.start and .end on a re matchobject, or the return value of find plus the length of the search string). Get the substring before the match and do /\s*(\S*)\s*\z/ etc. on it, and get the substring after the match and do /\A\s*(\S*)\s*/ etc. on it.
Also, for help with your backtracking: you can use a pattern like \s+\S+\s+ instead of \s*\S*\s* (two chunks of whitespace have to be separated by a non-zero amount of non-whitespace, or else they wouldn't be two chunks), and you shouldn't butt up two consecutive \s*s like you do. I think r'\S+'.join([[r'\s+']*(n)) would give the right pattern for capturing n previous words (but my Python is rusty, so check that).
I see several problems here. The First, and probably worst, is that everything in your "surround" regex is, not just optional but independently optional. Given this string:
"Lorem ipsum tritani impedit civibus ei pri"
...when searchText = "tritani" and n = 1, this is what it has to go through before it finds the first match:
regex: \s* \S* \s* tritani
offset 0: '' 'Lorem' ' ' FAIL
'' 'Lorem' '' FAIL
'' 'Lore' '' FAIL
'' 'Lor' '' FAIL
'' 'Lo' '' FAIL
'' 'L' '' FAIL
'' '' '' FAIL
...then it bumps ahead one position and starts over:
offset 1: '' 'orem' ' ' FAIL
'' 'orem' '' FAIL
'' 'ore' '' FAIL
'' 'or' '' FAIL
'' 'o' '' FAIL
'' '' '' FAIL
... and so on. According to RegexBuddy's debugger, it takes almost 150 steps to reach the offset where it can make the first match:
position 5: ' ' 'ipsum' ' ' 'tritani'
And that's with just one word to skip over, and with n=1. If you set n=2 you end up with this:
\s*(\S*)\s*\s*(\S*)\s*tritani\s*(\S*)\s*\s*(\S*)\s*
I sure you can see where this is is going. Note especially that when I change it to this:
(?:\s+)(\S+)(?:\s+)(\S+)(?:\s+)tritani(?:\s+)(\S+)(?:\s+)(\S+)(?:\s+)
...it finds the first match in a little over 20 steps. This is one of the most common regex anti-patterns: using * when you should be using +. In other words, if it's not optional, don't treat it as optional.
Finally, you may have noticed the \s*\s* the auto-generated regex
You could try using mmap and appropriate regex flags, eg (untested):
import re
import mmap
with open('your file') as fin:
mf = mmap.mmap(fin.fileno(), 0, access=mmap.ACCESS_READ)
for match in re.finditer(your_re, mf, flags=re.DOTALL):
print match.group() # do something with your match
This'll only keep memory usage lower though...
The alternative is to have a sliding window of words (simple example of just single word before and after)...:
import re
import mmap
from itertools import islice, tee, izip_longest
with open('testingdata.txt') as fin:
mf = mmap.mmap(fin.fileno(), 0, access=mmap.ACCESS_READ)
words = (m.group() for m in re.finditer('\w+', mf, flags=re.DOTALL))
grouped = [islice(el, idx, None) for idx, el in enumerate(tee(words, 3))]
for group in izip_longest(*grouped, fillvalue=''):
if group[1] == 'something': # check criteria for group
print group
I think you are going about this completely backwards (I'm a little confused as to what you are doing in the first place!)
I would recommend checking out the re_search function I developed in the textools module of my cloud toolbox
with re_search you could solve this problem with something like:
from cloudtb import textools
data_list = textools.re_search('my match', pdf_text_str) # search for character objects
# you now have a list of strings and RegPart objects. Parse through them:
for i, regpart in enumerate(data_list):
if isinstance(regpart, basestring):
words = textools.re_search('\w+', regpart)
# do stuff with words
else:
# I Think you are ignoring these? Not totally sure
Here is a link on how to use and how it works:
http://cloudformdesign.com/?p=183
In addition to this, your regular expressions would also be printed out in more readable format.
You might also want to check out my tool Search The Sky or the similar tool Kiki to help you build and understand your regular expressions.
I am trying to use regular expressions in python to match the frame number component of an image file in a sequence of images. I want to come up with a solution that covers a number of different naming conventions. If I put it into words I am trying to match the last instance of one or more numbers between two dots (eg .0100.). Below is an example of how my current logic falls down:
import os
import re
def sub_frame_number_for_frame_token(path, token='#'):
folder = os.path.dirname(path)
name = os.path.basename(path)
pattern = r'\.(\d+)\.'
matches = list(re.finditer(pattern, name) or [])
if not matches:
return path
# Get last match.
match = matches[-1]
frame_token = token * len(match.group(1))
start, end = match.span()
apetail_name = '%s.%s.%s' % (name[:start], frame_token, name[end:])
return os.path.join(folder, apetail_name)
# Success
eg1 = 'xx01_010_animation.0100.exr'
eg1 = sub_frame_number_for_frame_token(eg1) # result: xx01_010_animation.####.exr
# Failure
eg2 = 'xx01_010_animation.123.0100.exr'
eg2 = sub_frame_number_for_frame_token(eg2) # result: xx01_010_animation.###.0100.exr
I realise there are other ways in which I can solve this issue (I have already implemented a solution where I am splitting the path at the dot and taking the last item which is a number) but I am taking this opportunity to learn something about regular expressions. It appears the regular expression creates the groups from left-to-right and cannot use characters in the pattern more than once. Firstly is there anyway to search the string from right-to-left? Secondly, why doesn't the pattern find two matches in eg2 (123 and 0100)?
Cheers
finditer will return an iterator "over all non-overlapping matches in the string".
In your example, the last . of the first match will "consume" the first . of the second. Basically, after making the first match, the remaining string of your eg2 example is 0100.exr, which doesn't match.
To avoid this, you can use a lookahead assertion (?=), which doesn't consume the first match:
>>> pattern = re.compile(r'\.(\d+)(?=\.)')
>>> pattern.findall(eg1)
['0100']
>>> pattern.findall(eg2)
['123', '0100']
>>> eg3 = 'xx01_010_animation.123.0100.500.9000.1234.exr'
>>> pattern.findall(eg3)
['123', '0100', '500', '9000', '1234']
# and "right to left"
>>> pattern.findall(eg3)[::-1]
['1234', '9000', '500', '0100', '123']
My solution uses a very simple hackish way of fixing it. It reverses the string path in the beginning of your function and reverses the return value at the end of it. It basically uses regular expressions to search the backwards version of your given strings. Hackish, but it works. I used the syntax shown in this question to reverse the string.
import os
import re
def sub_frame_number_for_frame_token(path, token='#'):
path = path[::-1]
folder = os.path.dirname(path)
name = os.path.basename(path)
pattern = r'\.(\d+)\.'
matches = list(re.finditer(pattern, name) or [])
if not matches:
return path
# Get last match.
match = matches[-1]
frame_token = token * len(match.group(1))
start, end = match.span()
apetail_name = '%s.%s.%s' % (name[:start], frame_token, name[end:])
return os.path.join(folder, apetail_name)[::-1]
# Success
eg1 = 'xx01_010_animation.0100.exr'
eg1 = sub_frame_number_for_frame_token(eg1) # result: xx01_010_animation.####.exr
# Failure
eg2 = 'xx01_010_animation.123.0100.exr'
eg2 = sub_frame_number_for_frame_token(eg2) # result: xx01_010_animation.123.####.exr
print(eg1)
print(eg2)
I believe the problem is that finditer returns only non-overlapping matches. Because both '.' characters are part of the regular expression, it doesn't consider the second dot as a possible start of another match. You can probably use the lookahead construct ?= to match the second dot without consuming it with "?=.".
Because of the way regular expressions work, I don't think there is an easy way to search right-to-left (though I suppose you could reverse the string and write the pattern backwards...).
If all you care about is the last \.(\d+)\., then anchor your pattern from the end of the string and do a simple re.search(_):
\.(\d+)\.(?:.*?)$
where (?:.*?) is non-capturing and non-greedy, so it will consume as few characters as possible between your real target and the end of the string, and those characters will not show up in matches.
(Caveat 1: I have not tested this. Caveat 2: That is one ugly regex, so add a comment explaining what it's doing.)
UPDATE: Actually I guess you could just do a ^.*(\.\d\.) and let the implicitly greedy .* match as much as possible (including matches that occur earlier in the string) while still matching your group. That makes for a simpler regex, but I think it makes your intentions less clear.