I have an issue where extracting data from database it sometimes (quite often) adds spaces in between strings of texts that should not be there.
What I'm trying to do is create a small script that will look at these strings and remove the spaces.
The problem is that the spaces can be in any position in the string, and the string is a variable that changes.
Example:
"StaffID": "0000 25" <- The space in the number should not be there.
Is there a way to have the script look at this particular line, and if it finds spaces, to remove them.
Or:"DateOfBirth": "23-10-199 0" <-It would also need to look at these spaces and remove them.
The problem is that the same data also has lines such as:
"Address": " 91 Broad street" <- The spaces should be here obviously.
I've tried using TRIM, but that only removes spaces from start/end.
Worth mentioning that the data extracted is in json format and is then imported using API into the new system.
You should think about the logic of what you want to do, and whether or not it's programmatically possible to determine if you can teach your script where it is or is not appropriate to put spaces. As it is, this is one of the biggest problems facing AI research right now, so unfortunately you're probably going to have to do this by hand.
If it were me, I'd specify the kind of data format that I expect from each column, and try my best to attempt to parse those strings. For example, if you know that StaffID doesn't contain spaces, you can have a rule that just deletes them:
$staffid = $staffid.replace("\s+",'')
There are some more complicated things that you can do with forced formatting (.replace) that have already been covered in this answer, but again, that requires some expectation of exactly what data is going to come out of what column.
You might want to look more closely at where those spaces are coming from, rather than process the output like this. Is the retrieval script doing it? Maybe you can optimize the database that you're drawing from?
Related
Disclaimer: I have no engineering background whatsoever - please don't hold it against me ;)
What I'm trying to do:
Scan a bunch of text strings and find the ones that
are more than one word
contain title case (at least one capitalized word after the first one)
but exclude specific proper nouns that don't get checked for title case
and disregard any parameters in curly brackets
Example: Today, a Man walked his dogs named {FIDO} and {Fifi} down the Street.
Expectation: Flag the string for title capitalization because of Man and Street, not because of Today, {FIDO} or {Fifi}
Example: Don't post that video on TikTok.
Expectation: No flag because TikTok is a proper noun
I have bits and pieces, none of them error-free from what https://www.regextester.com/ keeps telling me so I'm really hoping for help from this community.
What I've tried (in piece meal but not all together):
(?=([A-Z][a-z]+\s+[A-Z][a-z]+))
^(?!(WordA|WordB)$)
^((?!{*}))
I think your problem is not really solvable solely with regex...
My recommendation would be splitting the input via [\s\W]+ (e.g. with python's re.split, if you really need strings with more than one word, you can check the length of the result), filtering each resulting word if the first character is uppercase (e.g with python's string.isupper) and finally filtering against a dictionary.
[\s\W]+ matches all whitespace and non-word characters, yielding words...
The reasoning behind this different approach: compiling all "proper nouns" in a regex is kinda impossible, using "isupper" also works with non-latin letters (e.g. when your strings are unicode, [A-Z] won't be sufficient to detect uppercase). Filtering utilizing a dictionary is a way more forward approach and much easier to maintain (I would recommend using set or other data type suited for fast lookups.
Maybe if you can define your use case more clearer we can work out a pure regex solution...
I am using Scala to parse CSV files. Some of these files have fields which are non-textual data like images or octet-streams. I would like to use Apache Spark's textFile() method to split up the CSV into rows, and
split(",[ ]*(?=([^\"]*\"[^\"]*\")*[^\"]*$)")
to split the row into fields. Unfortunatly this does not work with files that have these mentioned binary fields. There are two problems: 1) The octet-streams can contain newlines which make textFile() split rows which should be one, and 2) The octet-streams contain commas and/or double quotes which are not escaped and mess up my schema.
The files are usually big, couple of MBs up to couple of 100MBs. I have to take the CSV's as they are, although I could preprocess them.
All I want to achieve is a working split function so I can ignore the field with the octet-stream. Nevertheless, a great bonus would be to extract the textual information in the octet-stream.
So how would I go forward to solve my problems?
Edit: A typical record obtained with cat, the newlines are from the file, not for cosmetic purposes (shortened):
7,url,user,02/24/2015 02:29:00 AM,03/22/2015 03:12:36 PM,octet-stream,27156,"MSCF^#^#^#^#�,^#^#^#^#^#^#D^#^#^#^#^#^#^#^C^A^A^#^C^#^D^#^#^#^#^#^T^#^#^#^#^#^P^#�,^#^#^X=^#^#^#^#^#^#^#^#^#^#�^#^#^#^E^#^A^#��^A^#^#^#^#^#^#^#WF6�!^#Info.txt^#=^B^#^#��^A^#^#^#WF7�^#^#List.xml^#^�^#^#��^A^#^#^#WF:�^#^#Filename.txt^#��>��
^#�CK�]�r��^Q��T�^O�^#�-�j�]��FI�Ky��Ei�Je^K""!�^Qx #�*^U^?�^_�;��ħ�^LI^#$(�^Q���b��\N����t�����+������ȷgvM�^L̽�LǴL�^L��^ER��w^Ui^M��^X�Kޓ�^QJȧ��^N~��&�x�bB��D]1�^B|^G���g^SyG�����:����^_P�^T�^_�����U�|B�gH=��%Z^NY���,^U�^VI{��^S�^U�!�^Lpw�T���+�a�z�l������b����w^K��or��pH� ��ܞ�l��z�^\i=�z�:^C�^S!_ESCW��ESC""��g^NY2��s�� u���X^?�^R^R+��b^]^Ro�r���^AR�h�^D��^X^M�^]ޫ���ܰ�^]���0^?��^]�92^GhCx�DN^?
mY<{��L^Zk�^\���M�^V^HE���-Ե�$f�f����^D�e�^R:�u����� ^E^A�Ȑ�^B�^E�sZ���Yo��8Eސ�}��&JY���^A9^P������^P����~Jʭy��`�^9«�""�U� �:�}3���6�Hߧ�v���A7^Xi^L^]�sA�^Q�7�5d�^Xo˛�tY
Bp��4�Y���7DkV_���\^_q~�w�|�a�s̆���#�g�ӳu�^�!W}�n��Rgż_2�]�p�2}��b�G9�M^Q
�����:�X����bR[ԳZV!^G����^U�tq�&�Y6b��GR���s#mn6Z=^ZH^]�b��R^G�C�0R��{r1��4�#�
=r/X2�^O�����r^M�Rȕ�goG^X-����}���P+˥Qf�#��^C�Բ�z1�I�j����6�^Np���ܯ^P�[�^Tzԏ���^F2�e��\�E�6c�%���$�:E�*�*©t�y�J�,�S�2U�S�^X}ME�]��]�i��G�su�""��!�-��!r'ܷe_et Y^K^?0���l^A��^^�m�1/q����|�_r�5$�%�([x��W^E�G^^y���#����Z2^?ڠ�^_��^AҶ�OO��^]�vq%:j�^?�jX��\�]����^S�^^n�^C��>.^CY^O-� �_�\K����:p�<7Sֺnj���-Yk�r���^Q^M�n�J^B��^Z0^?�(^C��^W³!�g�Z�~R�A^M�^O^^�%;��Ԗ�p^S�w���*m^S���jڒ|�����<�^S�;Z^^Fc�1���^O�G_o����8��CS���w��^?��n�2~��m���G;��rx4�(�]�'��^E���eƧ�x��.�w�9WO�^^�י3��0,�y��H�Y�.H�x�""'���h}灢^T�Gm;^XE�̼�J��c�^^;�^A�qZ1ׁBZ^Q�^A^FB�^QbQ�_�3|ƺ�EvZ���^S�w���^P���9^MT��ǩY[+�+�9�Ԩ�^O�^Q���Fy(+�9p�^^Mj�2��Y^?��ڞ��^Ķb�^Z�ψMр}�ڣ�^^S�^?��^U�^Wڻ����z�^#��uk��k^^�>^O�^W�ݤO�h�^G�����Kˇ�.�R|�)-��e^G�^]�/J����U�ϴ�a���i5HO�^L�ESCg�R'���.����d���+~�}��ڝ^Y5]l�3jg54M�������2t�5^Y}�q)��^O;�X\�q^Ox~Vۗ�t�^\f� >k;^G�K5��,��X�t/�ǧ^G""5��4^MiΟ�n��^B^]�|�����V��ߌ֗Q~�H���8��t��5��ܗ�
�Z�^c�6N�ESCG����^_��>��t^L^R�^:�x���^]v�{^#+KM��qԎ�.^S�%&��=^W-�=�^S�����^CI���&^]_�s�˞�y�z�Jc^W�kڠ�^\��^]j�����^O��;�oY^^�^V59;�c��^B��T�nb����^C��^N��s�x�<{�9-�F�T�^N�5�^Se-���^T�Y[���`^ZsL��v�բ<C�+�~�^ۚ��""�Yκ2^_�^VxT�>��/ݳ^U�m�^#���3^Ge�n^Vc�V�^#�NVn�,�q��^^^]gy�R�S��Ȃ$���>A�d����xg�^GB3�M�J�^QJ^]�^\�{.�D��碎�^W�8a����qޠl?,'^R�^X�Cgy�P[����mڞ��H�Z�s�SD&蠤�s�E��nu�O#O<��3wj`C-%w�W�J�^WP^T�^]r^NT�TC�Lq�Z�f�!�;�l�Y��Gb��>�ud�hx�Ԭ^N)9�^N!k�҉s�35v������.�""^]��~4������۴�Z^]u�^Ti^^�i:�)K��P᳕!�#�^?�>��EE^VE-u�^SgV^L��<��^D�O<�+�J.�c�Z#>�.l����^S�
ESC��(��E�j�π쬖���2{^U&b\��P^S�`^O^XdL�^ 6bu��FD��^#^#^#^#","field_x, data",field_y,field_z
Expected output would be an array
("7","url","user","02/24/2015 02:29:00 AM","03/22/2015 03:12:36 PM","octet-stream","27156","field_x, data",field_y",field_z")
Or, but this is probably another question, such an array (like running strings on the octet-stream field):
("7","url","user","02/24/2015 02:29:00 AM","03/22/2015 03:12:36 PM","octet-stream","27156","Info.txt List.xml Filename.txt","field_x, data",field_y",field_z")
Edit 2: Every file that has a binary field also contains a length field for it. So instead of splitting directly I can walk left to right through my record and extract the fields. This is certainly a great improvement of my current situation but problem 1) still persists. How can I split those files reliably?
I took a closer look at the files and a header looks like this:
RecordId, Field_A, Content_Type, Content_Length, Content, Field_B
(Where Content_Type can be "octet-stream", Content_Length the number of bytes in the Content field, and Content obviously the data). And good for me, the value of Field_B is predictable, let's assume for a certain file it's always "Hello World".
So instead of using Spark's default behaviour splitting on newlines, how can I achieve that Spark is only splitting on newlines following "Hello World"? (I also edited the question title since the focus of the question changed)
As answered in Spark: Reading files using different delimiter than new line, I used textinputformat.record.delimiter to split on "Hello World\n" because I am a bit lucky that the last column always contains the same value. After that I simply walk left to right through the record and when I reach the length field I skip the next n bytes. Everything works now. Thanks for pointing me in the right direction.
There are two problems: 1) The octet-streams can contain newlines
which make textFile() split rows which should be one, and 2) The
octet-streams contain commas and/or double quotes which are not
escaped and mess up my schema.
Well, actually that csv file is properly escaped:
the multiline field is enclosed in double quotes: "MSCF^# .. ^#^#" (which also handles possible separators inside the field)
double quotes inside the field are escaped with another double quote as it should be: Je^K""!
Of course a simple split will not work in this case (and should never be used on csv data), but any csv reader able to handle multiline fields should parse that data correctly.
Also keep in mind that the double quotes inside the octet-stream have to be unescaped, or that data won't be valid (another reason not to use split, but a csv reader that handles this).
I asked a question earlier today and got a really quick answer from llbrink. I really should have asked that question before I spent several hours trying to find an answer.
So - here's another question that I have never found an answer for (although I have created a work-around which seems very cludgy).
My AHK program asks the user for a login name. The program then compares the login name with an existing list of names in a file.
The login name in the file may contain spaces, but there are never spaces at the beginning of the name. When the user enters the name, he may include spaces at the beginning. This means that when my program compares the name with those in the file, it can not find a match (because of the extra spaces).
I want to find a way of stripping the spaces from the beginning of the input.
My work-round has been to split the input string into an array (which does ignore leading spaces) and then use the first element of the array. This is my code :
name := DoStrip(name)
DoStrip(xyz) ; strip leading and trailing spaces from string
{
StringSplit, out, xyz, `,, %A_Space%
Return out1
}
This seems to be a very laboured way to do it - is there a better way ?
I don't see a problem with your example if it works on all cases.
There is a much simpler way; just use Autotrim which works like this.
AutoTrim, On ; not required it is on by default
my_variable = %my_variable%
There are also many other different ways to trim string in autohotkey,
which you can combine into something useful.
You can also use #LTrim and #RTrim to remove white spaces at the beginning and at the end of the string.
We restored from a backup in a different format to a new MySQL structure (which is setup correctly for UTF-8 support). We have weird characters showing in the browser, but we're not sure what they're called so we can find a master list of what they translate to.
I have noticed that they do, in fact, correlate to a specific character. For example:
â„¢ always translates to ™
— always translates to —
• always translates to ·
I referenced this post, which got me started, but this is far from a complete list. Either I'm not searching for the correct name, or the "master list" of these bad-to-good conversions as a reference doesn't exist.
Reference:
Detecting utf8 broken characters in MySQL
Also, when trying to search via MySQL query, if I search for â, I always get MySQL treating it as an "a". Is there any way to tweak my MySQL queries so that they are more literal searches? We don't use internationalization much so I can safely assume any fields containing the â character is considered to be a problematic entry, which would need to be remedied by our "fixit" script we're building.
Instead of designing a "fixit" script to go through and replace this data, I think it would be better to simply fix the issue directly. It seems like the data was originally stored in a different format than UTF-8 so that when you brought it into the table that was set up for UTF-8, it garbled the text. If you have the opportunity, go back to your original backup to determine the format the data was stored in. If you can't do that, you will probably need to do a bit of trial and error to figure out which format the data is in. However, once you know that, conversion is easy. Read the following article's section on Repairing:
http://www.istognosis.com/en/mysql/35-garbled-data-set-utf8-characters-to-mysql-
Basically you are going to set the column to BINARY and then set it to the original charset. That should make the text appear properly (a good check to know you are using the correct charset). Once that is done, set the column to UTF-8. This will convert the data properly and it will correct the problems you are currently experiencing.
"artistName":"Travie McCoy", "collectionName":"Billionaire (feat. Bruno Mars) - Single", "trackName":"Billionaire (feat. Bruno Mars)",
i wish to get the artist name so Travie McCoy from within that code using regex, please not i am using regexkitlite for the iphone sdk if this changes things.
Thanks
"?artistName"?\s*:\s*"([^"]*)("|$) should do the trick. It even handles some variations in the string:
White space before and after the :
artistName with and without the quotes
missing " at the end of the artist name if it is the last thing on the line
But there will be many more variations in the input you might encounter that this regex will not match.
Also you don’t want to use a regex for matching this for performance reasons. Right now you might only be interested in the artistName field. But some time later you will want information from the other fields. If you just change the field name in the regex you’ll have to match the whole string again. Much better to use a parser and transform the whole string into a dictionary where you can access the different fields easily. Parsing the whole string shouldn’t take much longer than matching the last key/value pair using a regex.
This looks like some kind of JSON, there are lots of good and complete parsers available. It isn’t hard to write one yourself though. You could write a simple recursive descent parser in a couple of hours. I think this is something every programmer should have done at least once.
\"?artistName\"?\s*:\s*\"([^\"]*)(\"|$)
Thats for objective c