I would like to intercept string starting with \*#\*
followed by a number between 0 and 7
and ending with: ##
so something like \*#\*0##
but I could not find a regex for this
Assuming you want to allow only one # before and two after, I'd do it like this:
r'^(\#{1}([0-7])\#{2})'
It's important to note that Alex's regex will also match things like
###7######
########1###
which may or may not matter.
My regex above matches a string starting with #[0-7]## and ignores the end of the string. You could tack a $ onto the end if you wanted it to match only if that's the entire line.
The first backreference gives you the entire #<number>## string and the second backreference gives you the number inside the #.
None of the above examples are taking into account the *#*
^\*#\*[0-7]##$
Pass : *#*7##
Fail : *#*22324324##
Fail : *#3232#
The ^ character will match the start of the string, \* will match a single asterisk, the # characters do not need to be escape in this example, and finally the [0-7] will only match a single character between 0 and 7.
r'\#[0-7]\#\#'
The regular expression should be like ^#[0-7]##$
As I understand the question, the simplest regular expression you need is:
rex= re.compile(r'^\*#\*([0-7])##$')
The {1} constructs are redundant.
After doing rex.match (or rex.search, but it's not necessary here), .group(1) of the match object contains the digit given.
EDIT: The whole matched string is always available as match.group(0). If all you need is the complete string, drop any parentheses in the regular expression:
rex= re.compile(r'^\*#\*[0-7]##$')
Related
This is a follow up to this SO post which gives a solution to replace text in a string column
How to replace text in a column of a Pandas dataframe?
df['range'] = df['range'].str.replace(',','-')
However, this doesn't seem to work with double periods or a question mark followed by a period
testList = ['this is a.. test stence', 'for which is ?. was a time']
testDf = pd.DataFrame(testList, columns=['strings'])
testDf['strings'].str.replace('..', '.').head()
results in
0 ...........e
1 .............
Name: strings, dtype: object
and
testDf['strings'].str.replace('?.', '?').head()
results in
error: nothing to repeat at position 0
Add regex=False parameter, because as you can see in the docs, regex it's by default True:
-regex bool, default True
Determines if assumes the passed-in pattern is a regular expression:
If True, assumes the passed-in pattern is a regular expression.
And ? . are special characters in regular expressions.
So, one way to do it without regex will be this double replacing:
testDf['strings'].str.replace('..', '.',regex=False).str.replace('?.', '?',regex=False)
Output:
strings
0 this is a. test stence
1 for which is ? was a time
Replace using regular expression. In this case, replace any sepcial character '.' followed immediately by white space. This is abit curly, I advice you go with #Mark Reed answer.
testDf.replace(regex=r'([.](?=\s))', value=r'')
strings
0 this is a. test stence
1 for which is ? was a time
str.replace() works with a Regex where . is a special character which denotes "any" character. If you want a literal dot, you need to escape it: "\.". Same for other special Regex characters like ?.
First, be aware that the Pandas replace method is different from the standard Python one, which operates only on fixed strings. The Pandas one can behave as either the regular string.replace or re.sub (the regular-expression substitute method), depending on the value of a flag, and the default is to act like re.sub. So you need to treat your first argument as a regular expression. That means you do have to change the string, but it also has the benefit of allowing you to do both substitutions in a single call.
A regular expression isn't a string to be searched for literally, but a pattern that acts as instructions telling Python what to look for. Most characters just ask Python to match themselves, but some are special, and both . and ? happen to be in the special category.
The easiest thing to do is to use a character class to match either . or ? followed by a period, and remember which one it was so that it can be included in the replacement, just without the following period. That looks like this:
testDF.replace(regex=r'([.?])\.', value=r'\1')
The [.?] means "match either a period or a question mark"; since they're inside the [...], those normally-special characters don't need to be escaped. The parentheses around the square brackets tell Python to remember which of those two characters is the one it actually found. The next thing that has to be there in order to match is the period you're trying to get rid of, which has to be escaped with a backslash because this one's not inside [...].
In the replacement, the special sequence \1 means "whatever you found that matched the pattern between the first set of parentheses", so that's either the period or question mark. Since that's the entire replacement, the following period is removed.
Now, you'll notice I used raw strings (r'...') for both; that keeps Python from doing its own interpretation of the backslashes before replace can. If the replacement were just '\1' without the r it would replace them with character code 1 (control-A) instead of the first matched group.
To replace both the ? and . at the same time you can separate by | (the regex OR operator).
testDf['strings'].str.replace('\?.|\..', '.')
Prefix the .. with a \, because you need to escape as . is a regex character:
testDf['strings'].str.replace('\..', '.')
You can do the same with the ?, which is another regex character.
testDf['strings'].str.replace('\?.', '.')
I want a regular expression to match a string that may or may not start with plus symbol and then contain any number of digits.
Those should be matched
+35423452354554
or
3423564564
This should work
\+?\d+
Matches an optional + at the beginning of the line and digits after it
EDIT:
As of OP's request of clarification: 3423kk55 is matched because so it is the first part (3423). To match a whole string only use this instead:
^\+?\d+$
It'll look something like this:
\+?\d+
The \+ means a literal plus sign, the ? means that the preceding group (the plus sign) can appear 0 or 1 times, \d indicates a digit character, and the final + requires that the preceding group (the digit) appears one or more times.
EDIT: When using regular expressions, bear in mind that there's a difference between find and matches (in Java at least, though most regex implementations have similar methods). find will find the substring somewhere in the owning string, and matches will try to match the entire string against the pattern, failing if there are extra characters before or after. Ensure you're using the right method, and remember that you can add a ^ to force the beginning of the line and a $ to force the end of the line (making the entire thing look like ^\+?\d+$.
Simple ^\+?\d+$
Start line, then 1 or 0 plus signs, followed by at least 1 digit, then end of lnie
A Perl regular expression for it could be: \+?\d+
I am using Python 2.7 and have a question with regards to regular expressions. My string would be something like this...
"SecurityGroup:Pub HDP SG"
"SecurityGroup:Group-Name"
"SecurityGroup:TestName"
My regular expression looks something like below
[^S^e^c^r^i^t^y^G^r^o^u^p^:].*
The above seems to work but I have the feeling it is not very efficient and also if the string has the word "group" in it, that will fail as well...
What I am looking for is the output should find anything after the colon (:). I also thought I can do something like using group 2 as my match... but the problem with that is, if there are spaces in the name then I won't be able to get the correct name.
(SecurityGroup):(\w{1,})
Why not just do
security_string.split(':')[1]
To grab the second part of the String after the colon?
You could use lookbehind:
pattern = re.compile(r"(?<=SecurityGroup:)(.*)")
matches = re.findall(pattern, your_string)
Breaking it down:
(?<= # positive lookbehind. Matches things preceded by the following group
SecurityGroup: # pattern you want your matches preceded by
) # end positive lookbehind
( # start matching group
.* # any number of characters
) # end matching group
When tested on the string "something something SecurityGroup:stuff and stuff" it returns matches = ['stuff and stuff'].
Edit:
As mentioned in a comment, pattern = re.compile(r"SecurityGroup:(.*)") accomplishes the same thing. In this case you are matching the string "SecurityGroup:" followed by anything, but only returning the stuff that follows. This is probably more clear than my original example using lookbehind.
Maybe this:
([^:"]+[^\s](?="))
Regex live here.
I bumped into the problem while playing around in Python: when I create a random string, let's say "test 1981", the following Python call returns with an empty string.
>>> re.search('\d?', "test 1981").group()
''
I was wondering why this is. I was reading through some other posts, and it seems that it has to do with greedy vs. non-greedy operators. Is it that the '?' checks to see if the first value is a digit, and if it's not, it takes the easier, quicker path and just outputs nothing?
Any clarification would help. Thanks!
Your pattern matches a digit or the empty string. It starts at the first character and tries to match a digit, what it is doing next is trying to match the alternative, means the empty string, voilà a match is found before the first character.
I think you expected it to move on and try to match on the next character, but that is not done, first it tries to match what the quantifier allows on the first position. And that is 0 or one digit.
The use of the optional quantifier makes only sense in combination with a required part, say you want a digit followed by an optional one:
>>> re.search('\d\d?', "test 1981").group()
'19'
Otherwise your pattern is always true.
Regex
\d?
simply means that it should optionally (?) match single digit (\d).
If you use something like this, it will work as you expect (match single digit anywhere in the string):
\d
re.search('\d?', "test 1981").group() greedily matches the first match of the pattern (0 or 1 digits) it can find. In this case that's zero digits. Note that re.search('\d?', "1981 test").group() actually matches the string '1' at the beginning of the string. What you're probably looking for here is re.search('\d+', "test 1981").group(), which finds the whole string 1981 no matter where it is.
I need to match the following sets of input:
foo_abc_bar
foo_bar
and get "abc" or an empty string as the result.
So this is the regular expression I wrote:
r'foo_(abc|)[_|]bar'
But for some reason, this does not match with the second string that I have given.
On further inspection, I found that [_|] does not match an empty string.
So, how do I solve this problem?
To make abc_ optional, you could use the question mark operator:
(abc_)?
Thus, the entire regex becomes:
r'foo_(abc_)?bar'
With this regex, the second underscore (if present) will become part of the capture group. If you don't want that, you could either remove it post-match with .rstrip('_') or use a slightly more complex regex:
r'foo_(?:(abc)_)?bar'
I found that [_|] does not match an empty string.
That's right. Square brackets denote a character group. The [_|] would match exactly one underscore or exactly one vertical bar, and nothing else. In other words, the vertical bar loses its special meaning when it appears inside a character group.
if you want a string pattern like this
xxx_xxx_xxx
xxx_xxx
then you need
([A-Za-z]{3})((_[A-Za-z]{3})+)?
but this will work also
r'foo(_abc)?_bar'
? means optional (may or may not match).