I'm cleaning up some ancient HTML help files and there are a lot of double-spaces that I'd like to clean up (replace each double-space with single).
Sample: <li><b>% Successful</b>. The percentage of jobs that returned a confirmation.</li>
I want to find double-spaces only before the start of sentences or between words (so between the setting label or between 'percentage' and 'of', not spaces in isolation or before the XML tags).
I tried a simple search for two spaces, but that also brings up the tab/space mixture that the creator used for formatting the indents, so I'm getting five useless results for every relevant one.
Is there a single regex that would help with both use cases, or is it better to use two different ones for each format? I'm fine either way, just am still pretty new to regexes and not sure where to start on this one.
Spaces between periods and text (three here for a better visual):
<li><b>Submit Time</b>. The time the job was scheduled.</li>
Spaces between words (three here as well):
<li><b>End Time</b>. The date/time when the job was completed or canceled.</li>
I'm looking for multiple spaces either between words or at the start of sentences (generally after the setting name period).
Related
I have a string variable containing school names and I need to find all the possible combination of each word in this string variable in stata:
For example variation of a word "Academy" would be:
Academy,
Academy,
acdamey,
aacdemy,
dmcaamy,
aacedmy,
and so on.
I need this to standardize the raw data of school names, which has many typos of each word due to data entry issues, like the ones given above for "academy".
Depending whether your data is already in the Excel sheets or a file, you can either use regex trying to match all possible combinations (and probably fix them when found) or parse the strings first before bringing them into Excel. In either case you could make a file (or Excel list/table/area/etc.) that includes all the common typos and pick each typo as regex match to use when comparing to your actual input.
Making regexp that would actually find all possible cases is next to impossible, especially if there are cases where very similar (but correct) names for schools exist. In any case direct regexps would be very messy and complex, so I would advice you to parse the data by finding first the correct form, excluding it and then using (greedy) search/regex to find the typoed versions. You can then save the typos to use them as a filter/match/pattern.
To get some sort of starting ideas, check this links:
Regex: Search for verb roots
Read text file and extract string into Excel sheet using regex
P.s You should keep the count of all strings/school names and finally get a list of all names that did not match correct form or any of your regexp filters, so you can manually insert/correct them.
I have a recursive list of folders that I need to find characters in, but I do not want subfolders included in the result. I need to find many different characters that will be an issue when migrating data, including asterisks, double periods, etc.
For this example I will use double-period (..). I only need the first, fourth, and seventh lines
/System/Modules/Aspect/dmc_attachments_aspect..J5_D65
/System/Modules/Aspect/dmc_attachments_aspect..J5_D65/External Interfaces
/System/Modules/Aspect/dmc_attachments_aspect..J5_D65/Miscellaneous
/System/Modules/Collaboration/com.documentum.services.collaboration.IAttachmentsManager..J5_D65
/System/Modules/Collaboration/com.documentum.services.collaboration.IAttachmentsManager..J5_D65/External Interfaces
/System/Modules/Collaboration/com.documentum.services.collaboration.IAttachmentsManager..J5_D65/Miscellaneous
/System/Modules/TBO/dm_message_archive..J5_D65
/System/Modules/TBO/dm_message_archive..J5_D65/External Interfaces
Another example would be an asterisk -- I only need the first, fourth, and seventh lines.
/Public/Test/*Training
/Public/Test/*Training*/Documentation
/Public/Test/*Training*/SOPs
/Public/Test/Project**Tracking
/Public/Test/Project**Tracking/01
/Public/Test/Project**Tracking/02
/Public/Home*
/Public/Home*/Test
Is there a regex I could use to meet this? I am happy running multiple queries/reports and updating the main character (.. or *)
I wanted to give some clarity on the issue so I can avoid the XY problem.
We are migrating data from Documentum to SharePoint, and Documentum does not have the same file and folder name restrictions, so we will have to address those ahead of the migration or on the fly. I have a big text file (950k lines) containing all of the folders currently in Documentum, and I am attempting to find all folders that will not migrate due to containing these characters.
The issue is that doing a basic egrep '\*' will give not just the top level folder containing this character but all subfolders, which will throw off counts.
Let's say you were looking for the double period:
.*\.\.[^/]*$
would match two periods followed by an unlimited number of non-slash characters until the end of the string. In general, replace \.\. with whatever you are looking for.
Check it out at regex101.com. (Asterisk version here).
I have a text file in Notepad++ that contains about 66,000 words all in 1 line, and it is a set of 200 "lines" of output that are all unique and placed in 1 line in the basic JSON form {output:[{output1},{output2},...}]}.
There is a set of characters matching the RegEx expression "id":.........,"kind":"track" that occurs about 285 times in total, and I am trying to either single them out, or copy all of them at once.
Basically, without some super complicated RegEx terms, I am stuck because I can't figure out how to highlight all of them at once, and also the Remove Unbookmarked Lines feature does not apply because this is all in one line. I have only managed to be able to Mark every single occurrence.
So does this require a large number of steps to get the file into multiple lines and work from there, or is there something else I am missing?
Edit: I have come up with a set of Macro schemes that make the process of doing this manually work much faster. It's another alternative but still takes a few steps and quite some time.
Edit 2: I intended there to be an answer for actually just highlighting the different sections all at once, but I guess that it not possible. The answer here turns out to be more useful in my case, allowing me to have a list of IDs without everything else.
You seem to already have a regex which matches single instances of your pattern, so assuming it works and that we must use Notepad++ for this:
Replace .*?("id":.........,"kind":"track").*?(?="id".........,"kind":"track"|$) with \1.
If this textfile is valid JSON, this opens you up to other, non-notepad++ options, like using Python with the json module.
Edited to remove unnecessary steps
Intro
I work in a facility where we have microscopes. These guys can be asked to generate 4D movies of a sample: they take e.g. 10 pictures at different Z position, then wait a certain amount of time (next timepoint) and take 10 slices again.
They can be asked to save a file for each slice, and they use an explicit naming pattern, something like 2009-11-03-experiment1-Z07-T42.tif. The file names are numbered to reflect the Z position and the time point
Question
Once you have all these file names, you can use a regex pattern to extract the Z and T value, if you know the backbone pattern of the file name. This I know how to do.
The question I have is: do you know a way to automatically generate regex pattern from the file name list? For instance, there is an awesome tool on the net that does similar thing: txt2re.
What algorithm would you use to parse all the file name list and generate a most likely regex pattern?
There is a Perl module called String::Diff which has the ability to generate a regular expression for two different strings. The example it gives is
my $diff = String::Diff::diff_regexp('this is Perl', 'this is Ruby');
print "$diff\n";
outputs:
this\ is\ (?:Perl|Ruby)
Maybe you could feed pairs of filenames into this kind of thing to get an initial regex. However, this wouldn't give you capturing of numbers etc. so it wouldn't be completely automatic. After getting the diff you would have to hand-edit or do some kind of substitution to get a working final regex.
First of all, you are trying to do this the hard way. I suspect that this may not be impossible but you would have to apply some artificial intelligence techniques and it would be far more complicated than it is worth. Either neural networks or a genetic algorithm system could be trained to recognize the Z numbers and T numbers, assuming that the format of Z[0-9]+ and T[0-9]+ is always used somewhere in the regex.
What I would do with this problem is to write a Python script to process all of the filenames. In this script, I would match twice against the filename, one time looking for Z[0-9]+ and one time looking for T[0-9]+. Each time I would count the matches for Z-numbers and T-numbers.
I would keep four other counters with running totals, two for Z-numbers and two for T-numbers. Each pair would represent the count of filenames with 1 match, and the ones with multiple matches. And I would count the total number of filenames processed.
At the end, I would report as follows:
nnnnnnnnnn filenames processed
Z-numbers matched only once in nnnnnnnnnn filenames.
Z-numbers matched multiple times in nnnnnn filenames.
T-numbers matched only once in nnnnnnnnnn filenames.
T-numbers matched multiple times in nnnnnn filenames.
If you are lucky, there will be no multiple matches at all, and you could use the regexes above to extract your numbers. However, if there are any significant number of multiple matches, you can run the script again with some print statements to show you example filenames that provoke a multiple match. This would tell you whether or not a simple adjustment to the regex might work.
For instance, if you have 23,768 multiple matches on T-numbers, then make the script print every 500th filename with multiple matches, which would give you 47 samples to examine.
Probably something like [ -/.=]T[0-9]+[ -/.=] would be enough to get the multiple matches down to zero, while also giving a one-time match for every filename. Or at worst, [0-9][ -/.=]T[0-9]+[ -/.=]
For Python, see this question about TemplateMaker.
I recently discussed editors with a co-worker. He uses one of the less popular editors and I use another (I won't say which ones since it's not relevant and I want to avoid an editor flame war). I was saying that I didn't like his editor as much because it doesn't let you do find/replace with regular expressions.
He said he's never wanted to do that, which was surprising since it's something I find myself doing all the time. However, off the top of my head I wasn't able to come up with more than one or two examples. Can anyone here offer some examples of times when they've found regex find/replace useful in their editor? Here's what I've been able to come up with since then as examples of things that I've actually had to do:
Strip the beginning of a line off of every line in a file that looks like:
Line 25634 :
Line 632157 :
Taking a few dozen files with a standard header which is slightly different for each file and stripping the first 19 lines from all of them all at once.
Piping the result of a MySQL select statement into a text file, then removing all of the formatting junk and reformatting it as a Python dictionary for use in a simple script.
In a CSV file with no escaped commas, replace the first character of the 8th column of each row with a capital A.
Given a bunch of GDB stack traces with lines like
#3 0x080a6d61 in _mvl_set_req_done (req=0x82624a4, result=27158) at ../../mvl/src/mvl_serv.c:850
strip out everything from each line except the function names.
Does anyone else have any real-life examples? The next time this comes up, I'd like to be more prepared to list good examples of why this feature is useful.
Just last week, I used regex find/replace to convert a CSV file to an XML file.
Simple enough to do really, just chop up each field (luckily it didn't have any escaped commas) and push it back out with the appropriate tags in place of the commas.
Regex make it easy to replace whole words using word boundaries.
(\b\w+\b)
So you can replace unwanted words in your file without disturbing words like Scunthorpe
Yesterday I took a create table statement I made for an Oracle table and converted the fields to setString() method calls using JDBC and PreparedStatements. The table's field names were mapped to my class properties, so regex search and replace was the perfect fit.
Create Table text:
...
field_1 VARCHAR2(100) NULL,
field_2 VARCHAR2(10) NULL,
field_3 NUMBER(8) NULL,
field_4 VARCHAR2(100) NULL,
....
My Regex Search:
/([a-z_])+ .*?,?/
My Replacement:
pstmt.setString(1, \1);
The result:
...
pstmt.setString(1, field_1);
pstmt.setString(1, field_2);
pstmt.setString(1, field_3);
pstmt.setString(1, field_4);
....
I then went through and manually set the position int for each call and changed the method to setInt() (and others) where necessary, but that worked handy for me. I actually used it three or four times for similar field to method call conversions.
I like to use regexps to reformat lists of items like this:
int item1
double item2
to
public void item1(int item1){
}
public void item2(double item2){
}
This can be a big time saver.
I use it all the time when someone sends me a list of patient visit numbers in a column (say 100-200) and I need them in a '0000000444','000000004445' format. works wonders for me!
I also use it to pull out email addresses in an email. I send out group emails often and all the bounced returns come back in one email. So, I regex to pull them all out and then drop them into a string var to remove from the database.
I even wrote a little dialog prog to apply regex to my clipboard. It grabs the contents applies the regex and then loads it back into the clipboard.
One thing I use it for in web development all the time is stripping some text of its HTML tags. This might need to be done to sanitize user input for security, or for displaying a preview of a news article. For example, if you have an article with lots of HTML tags for formatting, you can't just do LEFT(article_text,100) + '...' (plus a "read more" link) and render that on a page at the risk of breaking the page by splitting apart an HTML tag.
Also, I've had to strip img tags in database records that link to images that no longer exist. And let's not forget web form validation. If you want to make a user has entered a correct email address (syntactically speaking) into a web form this is about the only way of checking it thoroughly.
I've just pasted a long character sequence into a string literal, and now I want to break it up into a concatenation of shorter string literals so it doesn't wrap. I also want it to be readable, so I want to break only after spaces. I select the whole string (minus the quotation marks) and do an in-selection-only replace-all with this regex:
/.{20,60} /
...and this replacement:
/$0"ΒΆ + "/
...where the pilcrow is an actual newline, and the number of spaces varies from one incident to the next. Result:
String s = "I recently discussed editors with a co-worker. He uses one "
+ "of the less popular editors and I use another (I won't say "
+ "which ones since it's not relevant and I want to avoid an "
+ "editor flame war). I was saying that I didn't like his "
+ "editor as much because it doesn't let you do find/replace "
+ "with regular expressions.";
The first thing I do with any editor is try to figure out it's Regex oddities. I use it all the time. Nothing really crazy, but it's handy when you've got to copy/paste stuff between different types of text - SQL <-> PHP is the one I do most often - and you don't want to fart around making the same change 500 times.
Regex is very handy any time I am trying to replace a value that spans multiple lines. Or when I want to replace a value with something that contains a line break.
I also like that you can match things in a regular expression and not replace the full match using the $# syntax to output the portion of the match you want to maintain.
I agree with you on points 3, 4, and 5 but not necessarily points 1 and 2.
In some cases 1 and 2 are easier to achieve using a anonymous keyboard macro.
By this I mean doing the following:
Position the cursor on the first line
Start a keyboard macro recording
Modify the first line
Position the cursor on the next line
Stop record.
Now all that is needed to modify the next line is to repeat the macro.
I could live with out support for regex but could not live without anonymous keyboard macros.