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  • Apache RewriteRule: it is possible to 'detect' the first and second parameter?

    - by DaNieL
    Im really really a newbie in regexp and i cant figure out how to do that. My goal is to have the RewriteRule to 'slice' the request url in 3 parts: example.com/foo #should return: index.php?a=foo&b=&c= example.com/foo/bar #should return: index.php?a=foo&b=bar&c= example.com/foo/bar/baz #should return: index.php?a=foo&b=bar&c=baz example.com/foo/bar/baz/bee #should return: index.php?a=foo&b=bar&c=baz/bee example.com/foo/bar/baz/bee/apple #should return: index.php?a=foo&b=bar&c=baz/bee/apple example.com/foo/bar/baz/bee/apple/and/whatever/else/no/limit/in/those/extra/parameters #should return: index.php?a=foo&b=bar&c=baz/bee/apple/and/whatever/else/no/limit/in/those/extra/parameters In short, the first parameter in the url (foo) should be given to a, the second (bar) to b, and the rest of the string in c I wroted this one <IfModule mod_rewrite.c> RewriteEngine on RewriteCond %{REQUEST_FILENAME} !-f RewriteCond %{REQUEST_FILENAME} !-d RewriteCond %{REQUEST_URI} !=/favicon.ico RewriteRule ^(([a-z0-9/]))?(([a-z0-9/]+))?(([a-z0-9]+))(.*)$ index.php?a=$1&b=$2&c=$3 [L,QSA] </IfModule> but obviously doesnt work, and i dont even know if what i want is possible. Any suggestion?

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  • Mixing regular expression and other conditional expression in a bash if statement

    - by Tassos
    I can't get around this for quite sometime now. As I read along manuals and tutorials I'm getting more confused. I want an if statement with the following logic: if [ -n $drupal_version ] && [[ "$drupal_version" =~ DRUPAL-[6-9]-[1-9][1-9] ]]; then but I can't get it to work properly. When the script is evaluated using the "bash -x ... " script construct, works ok but when is run as a regular script my expression is not evaluated (eventhough the above condition should be met the else part is run). Could you provide any help?

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  • Converting Straight Quotes to Curly Quotes

    - by BlueVoid
    I have an application which uses a javascript based rules engine. I need a way to convert regular straight quotes into curl (or smart) quotes. It'd be easy to just do a string.replace for ["], only this will only insert one case of the curly quote. The best way I could think of was replace the first occurrence of a quote with a left curly quote and every other one following with a left, and the rest right curly. Is there a way to accomplish this using javascript?

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  • mod_rewrite to nginx rewrite rules

    - by Andrew Bestic
    I have converted most of my Apache HTTPd mod_rewrite rules over to nginx's HttpRewrite module (which calls PHP-FPM via FastCGI on every dynamic request). Simple rules which are defined by hard locations work fine: location = /favicon.ico { rewrite ^(.*)$ /_core/frontend.php?type=ico&file=include__favicon last; } I am still having trouble with regular expressions, which are parsed in mod_rewrite like this (note that I am accepting trailing slashes within the rules, as well as appending the query string to every request): mod_rewrite # File handler RewriteRule ^([a-z0-9-_,+=]+)\.([a-z]+)$ _core/frontend.php?type=$2&file=$1 [QSA,L] # Page handler RewriteRule ^([a-z0-9-_,+=]+)$ _core/frontend.php?route=$1 [QSA,L] RewriteRule ^([a-z0-9-_,+=]+)\/$ _core/frontend.php?route=$1 [QSA,L] RewriteRule ^([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)$ _core/frontend.php?route=$1/$2 [QSA,L] RewriteRule ^([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)\/$ _core/frontend.php?route=$1/$2 [QSA,L] RewriteRule ^([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)$ _core/frontend.php?route=$1/$2/$3 [QSA,L] RewriteRule ^([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)\/$ _core/frontend.php?route=$1/$2/$3 [QSA,L] I have come up with the following server configuration for the site, but I am met with unmatched rules after parsing a request (eg; GET /user/auth): attempted nginx rewrite location / { # File handler rewrite ^([a-z0-9-_,+=]+)\.([a-z]+)?(.*)$ /_core/frontend.php?type=$2&file=$1&$3 break; # Page handler rewrite ^([a-z0-9-_,+=]+)(\/*)?(.*)$ /_core/frontend.php?route=$1&$2 break; rewrite ^([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)(\/*)?(.*)$ /_core/frontend.php?route=$1/$2&$3 break; rewrite ^([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)\/([a-z0-9-_,+=]+)(\/*)?(.*)$ /_core/frontend.php?route=$1/$2/$3&$4 break; } What would you suggest for dealing with my File Handler (which is just filename.ext), and my Page Handler (which is a unique route request with up to 3 properties defined by a forward slash)? As I haven't gotten a response from this yet, I am also unsure if this will override my PHP parser which is defined with location ~ \.php {}, which is included before these rewrite rules. Bonus points if I can solve the parsing issues without the need to use a new rule for each number of route properties.

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  • SED - Regular Expression over multiple lines

    - by herrherr
    Hi there, I'm stuck with this for several hours now and cycled through a wealth of different tools to get the job done. Without success. It would be fantastic, if someone could help me out with this. Here is the problem: I have a very large CSV file (400mb+) that is not formatted correctly. Right now it looks something like this: Alan Smithee ist ein Anagramm von „The [...] „Alan Smythee“, und „Adam Smithee“." ,Alan Smithee Die Aussagenlogik ist der Bereich der Logik, der sich mit [...] ihrer Teilaussagen bestimmen. ,Aussagenlogik As you can probably see the words ",Alan Smithee" and ",Aussagenlogik" should actually be on the same line as the foregoing sentence. Then it would look something like this: Alan Smithee ist ein Anagramm von „The Smitheeeee [...] „Alan Smythee“, und „Adam Smithee“.,Alan Smithee Die Aussagenlogik ist der Bereich der Logik, der sich mit [...] ihrer Teilaussagen bestimmen.,Aussagenlogik Please note that the end of the sentence can contain quotes or not. In the end they should be replaced too. Here is what I came up with so far: sed -n '1h;1!H;${;g;s/\."?.*,//g;p;}' out.csv > out1.csv This should actually get the job done of matching the expression over multiple lines. Unfortunately it doesn't :) The expression is looking for the dot at the end of the sentence and the optional quotes plus a newline character that I'm trying to match with .*. Help much appreciated. And it doesn't really matter what tool gets the job done (awk, perl, sed, tr, etc.). Thanks, Chris

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  • Python regex to parse text file, get the items in list and count the list

    - by Nemo
    I have a text file which contains some data. I m particularly interested in finding the count of the number of items in v_dims v_dims pattern in my text file looks like this : v_dims={ "Sales", "Product Family", "Sales Organization", "Region", "Sales Area", "Sales office", "Sales Division", "Sales Person", "Sales Channel", "Sales Order Type", "Sales Number", "Sales Person", "Sales Quantity", "Sales Amount" } So I m thinking of getting all the elements in v_dims and dumping them out in a Python list. Then compute the len(mylist) to get the count of the items. The challenge is in getting all the elements of v_dims from my text file and putting them in an empty list. I m particularly interested in items in v_dims in my text file. The text file has data in the form of v_dims pattern i showed in my original post. Some data has nested patterns of v_dims. Thanks. Here's what I have tried and failed. Any help is appreciated. TIA. import re fname = "C:\Users\XXXX\Test.mrk" with open(fname, "r") as fo: content_as_string = fo.read() match = re.findall(r'v_dims={\"(.+?)\"}',content_as_string) Though I have a big text file, Here's a snippet of what's the structure of my text file version "1"; // Computer generated object language file object 'MRKR' "Main" { Data_Type=2, HeaderBlock={ Version_String="6.3 (25)" }, Printer_Info={ Orientation=0, Page_Width=8.50000000, Page_Height=11.00000000, Page_Header="", Page_Footer="", Margin_type=0, Top_Margin=0.50000000, Left_Margin=0.50000000, Bottom_Margin=0.50000000, Right_Margin=0.50000000 }, Marker_Options={ Close_All="TRUE", Hide_Console="FALSE", Console_Left="FALSE", Console_Width=217, Main_Style="Maximized", MDI_Rect={ 0, 0, 892, 1063 } }, Dives={ { Dive="A", Windows={ { View_Index=0, Window_Info={ Window_Rect={ 0, -288, 400, 1008 }, Window_Style="Maximized Front", Window_Name="Theater [Previous Qtr Diveplan-Dive A]" }, Dependent_bool="FALSE", Colset={ Dive_Type="Normal", Dimension_Name="Theater", Action_List={ Actions={ { Action_Type="Select", select_type=5 }, { Action_Type="Select", select_type=0, Key_Names={ "Theater" }, Key_Indexes={ { "AMERICAS" } } }, { Action_Type="Focus", Focus_Rows="True" }, { Action_Type="Dimensions", v_dims={ "Theater", "Product Family", "Division", "Region", "Install at Country Name", "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "PS Flag", "Avalanche Flag", "Product Item Family" }, Xtab_Bool="False", Xtab_Flip="False" }, { Action_Type="Select", select_type=5 }, { Action_Type="Select", select_type=0, Key_Names={ "Theater", "Product Family", "Division", "Region", "Install at Country Name", "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "PS Flag", "Avalanche Flag" }, Key_Indexes={ { "AMERICAS", "ATMOS", "Latin America CS Division", "37000 CS Region", "Mexico", "", "", "", "", "DIRECT", "EMC", "N", "0" } } } } }, Num_Palette_cols=0, Num_Palette_rows=0 }, Format={ Window_Type="Tabular", Tabular={ Num_row_labels=8 } } } } } }, Widget_Set={ Widget_Layout="Vertical", Go_Button=1, Picklist_Width=0, Sort_Subset_Dimensions="TRUE", Order={ } }, Views={ { Data_Type=1, dbname="Previous Qtr Diveplan", diveline_dbname="Current Qtr Diveplan", logical_name="Current Qtr Diveplan", cols={ { name="Total TSS installs", column_type="Calc[Total TSS installs]", output_type="Number", format_string="." }, { name="TSS Valid Connectivity Records", column_type="Calc[TSS Valid Connectivity Records]", output_type="Number", format_string="." }, { name="% TSS Connectivity Record", column_type="Calc[% TSS Connectivity Record]", output_type="Number" }, { name="TSS Not Applicable", column_type="Calc[TSS Not Applicable]", output_type="Number", format_string="." }, { name="TSS Customer Refusals", column_type="Calc[TSS Customer Refusals]", output_type="Number", format_string="." }, { name="% TSS Refusals", column_type="Calc[% TSS Refusals]", output_type="Number" }, { name="TSS Eligible for Physical Connectivity", column_type="Calc[TSS Eligible for Physical Connectivity]", output_type="Number", format_string="." }, { name="TSS Boxes with Physical Connectivty", column_type="Calc[TSS Boxes with Physical Connectivty]", output_type="Number", format_string="." }, { name="% TSS Physical Connectivity", column_type="Calc[% TSS Physical Connectivity]", output_type="Number" } }, dim_cols={ { name="Model", column_type="Dimension[Model]", output_type="None" }, { name="Model", column_type="Dimension[Model]", output_type="None" }, { name="Connect In Type", column_type="Dimension[Connect In Type]", output_type="None" }, { name="Connect Home Type", column_type="Dimension[Connect Home Type]", output_type="None" }, { name="SymmConnect Enabled", column_type="Dimension[SymmConnect Enabled]", output_type="None" }, { name="Theater", column_type="Dimension[Theater]", output_type="None" }, { name="Division", column_type="Dimension[Division]", output_type="None" }, { name="Region", column_type="Dimension[Region]", output_type="None" }, { name="Sales Order Number", column_type="Dimension[Sales Order Number]", output_type="None" }, { name="Product Item Family", column_type="Dimension[Product Item Family]", output_type="None" }, { name="Item Serial Number", column_type="Dimension[Item Serial Number]", output_type="None" }, { name="Sales Order Deal Number", column_type="Dimension[Sales Order Deal Number]", output_type="None" }, { name="Item Install Date", column_type="Dimension[Item Install Date]", output_type="None" }, { name="SYR Last Dial Home Date", column_type="Dimension[SYR Last Dial Home Date]", output_type="None" }, { name="Maintained By Group", column_type="Dimension[Maintained By Group]", output_type="None" }, { name="PS Flag", column_type="Dimension[PS Flag]", output_type="None" }, { name="Connect Home Refusal Reason", column_type="Dimension[Connect Home Refusal Reason]", output_type="None", col_width=177 }, { name="Cust Name", column_type="Dimension[Cust Name]", output_type="None" }, { name="Sales Order Channel Type", column_type="Dimension[Sales Order Channel Type]", output_type="None" }, { name="Sales Order Type", column_type="Dimension[Sales Order Type]", output_type="None" }, { name="Part Model Key", column_type="Dimension[Part Model Key]", output_type="None" }, { name="Ship Date", column_type="Dimension[Ship Date]", output_type="None" }, { name="Model Number", column_type="Dimension[Model Number]", output_type="None" }, { name="Item Description", column_type="Dimension[Item Description]", output_type="None" }, { name="Customer Classification", column_type="Dimension[Customer Classification]", output_type="None" }, { name="CS Customer Name", column_type="Dimension[CS Customer Name]", output_type="None" }, { name="Install At Customer Number", column_type="Dimension[Install At Customer Number]", output_type="None" }, { name="Install at Country Name", column_type="Dimension[Install at Country Name]", output_type="None" }, { name="TLA Serial Number", column_type="Dimension[TLA Serial Number]", output_type="None" }, { name="Product Version", column_type="Dimension[Product Version]", output_type="None" }, { name="Avalanche Flag", column_type="Dimension[Avalanche Flag]", output_type="None" }, { name="Product Family", column_type="Dimension[Product Family]", output_type="None" }, { name="Project Number", column_type="Dimension[Project Number]", output_type="None" }, { name="PROJECT_STATUS", column_type="Dimension[PROJECT_STATUS]", output_type="None" } }, Available_Columns={ "Total TSS installs", "TSS Valid Connectivity Records", "% TSS Connectivity Record", "TSS Not Applicable", "TSS Customer Refusals", "% TSS Refusals", "TSS Eligible for Physical Connectivity", "TSS Boxes with Physical Connectivty", "% TSS Physical Connectivity", "Total Installs", "All Boxes with Valid Connectivty Record", "% All Connectivity Record", "Overall Refusals", "Overall Refusals %", "All Eligible for Physical Connectivty", "Boxes with Physical Connectivity", "% All with Physical Conectivity" }, Remaining_columns={ { name="Total Installs", column_type="Calc[Total Installs]", output_type="Number", format_string="." }, { name="All Boxes with Valid Connectivty Record", column_type="Calc[All Boxes with Valid Connectivty Record]", output_type="Number", format_string="." }, { name="% All Connectivity Record", column_type="Calc[% All Connectivity Record]", output_type="Number" }, { name="Overall Refusals", column_type="Calc[Overall Refusals]", output_type="Number", format_string="." }, { name="Overall Refusals %", column_type="Calc[Overall Refusals %]", output_type="Number" }, { name="All Eligible for Physical Connectivty", column_type="Calc[All Eligible for Physical Connectivty]", output_type="Number" }, { name="Boxes with Physical Connectivity", column_type="Calc[Boxes with Physical Connectivity]", output_type="Number" }, { name="% All with Physical Conectivity", column_type="Calc[% All with Physical Conectivity]", output_type="Number" } }, calcs={ { name="Total TSS installs", definition="Total[Total TSS installs]", ts_flag="Not TS Calc" }, { name="TSS Valid Connectivity Records", definition="Total[PS Boxes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="% TSS Connectivity Record", definition="Total[PS Boxes w/ valid connectivity record (1=yes)] /Total[Total TSS installs]", ts_flag="Not TS Calc" }, { name="TSS Not Applicable", definition="Total[Bozes w/ valid connectivity record (1=yes)]-Total[Boxes Eligible (1=yes)]-Total[TSS Refusals]", ts_flag="Not TS Calc" }, { name="TSS Customer Refusals", definition="Total[TSS Refusals]", ts_flag="Not TS Calc" }, { name="% TSS Refusals", definition="Total[TSS Refusals]/Total[PS Boxes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="TSS Eligible for Physical Connectivity", definition="Total[TSS Eligible]-Total[Exception]", ts_flag="Not TS Calc" }, { name="TSS Boxes with Physical Connectivty", definition="Total[PS Physical Connectivity] - Total[PS Physical Connectivity, SymmConnect Enabled=\"Capable not enabled\"]", ts_flag="Not TS Calc" }, { name="% TSS Physical Connectivity", definition="Total[Boxes w/ phys conn]/Total[Boxes Eligible (1=yes)]", ts_flag="Not TS Calc" }, { name="Total Installs", definition="Total[Total Installs]", ts_flag="Not TS Calc" }, { name="All Boxes with Valid Connectivty Record", definition="Total[Bozes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="% All Connectivity Record", definition="Total[Bozes w/ valid connectivity record (1=yes)]/Total[Total Installs]", ts_flag="Not TS Calc" }, { name="Overall Refusals", definition="Total[Overall Refusals]", ts_flag="Not TS Calc" }, { name="Overall Refusals %", definition="Total[Overall Refusals]/Total[Bozes w/ valid connectivity record (1=yes)]", ts_flag="Not TS Calc" }, { name="All Eligible for Physical Connectivty", definition="Total[Boxes Eligible (1=yes)]-Total[Exception]", ts_flag="Not TS Calc" }, { name="Boxes with Physical Connectivity", definition="Total[Boxes w/ phys conn]-Total[Boxes w/ phys conn,SymmConnect Enabled=\"Capable not enabled\"]", ts_flag="Not TS Calc" }, { name="% All with Physical Conectivity", definition="Total[Boxes w/ phys conn]/Total[Boxes Eligible (1=yes)]", ts_flag="Not TS Calc" } }, merge_type="consolidate", merge_dbs={ { dbname="connectivityallproducts.mdl", diveline_dbname="/DI_PSREPORTING/connectivityallproducts.mdl" } }, skip_constant_columns="FALSE", categories={ { name="Geography", dimensions={ "Theater", "Division", "Region", "Install at Country Name" } }, { name="Mappings and Flags", dimensions={ "Connect Home Type", "Connect In Type", "SymmConnect Enabled", "Connect Home Refusal Reason", "Sales Order Channel Type", "Maintained By Group", "Customer Installable", "PS Flag", "Top Level Flag", "Avalanche Flag" } }, { name="Product Information", dimensions={ "Product Family", "Product Item Family", "Product Version", "Item Description" } }, { name="Sales Order Info", dimensions={ "Sales Order Deal Number", "Sales Order Number", "Sales Order Type" } }, { name="Dates", dimensions={ "Item Install Date", "Ship Date", "SYR Last Dial Home Date" } }, { name="Details", dimensions={ "Item Serial Number", "TLA Serial Number", "Part Model Key", "Model Number" } }, { name="Customer Infor", dimensions={ "CS Customer Name", "Install At Customer Number", "Customer Classification", "Cust Name" } }, { name="Other Dimensions", dimensions={ "Model" } } }, Maintain_Category_Order="FALSE", popup_info="false" } } };

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  • Python regular expression implementation details

    - by Tom
    A question that I answered got me wondering: How are regular expressions implemented in Python? What sort of efficiency guarantees are there? Is the implementation "standard", or is it subject to change? I thought that regular expressions would be implemented as DFAs, and therefore were very efficient (requiring at most one scan of the input string). Laurence Gonsalves raised an interesting point that not all Python regular expressions are regular. (His example is r"(a+)b\1", which matches some number of a's, a b, and then the same number of a's as before). This clearly cannot be implemented with a DFA. So, to reiterate: what are the implementation details and guarantees of Python regular expressions? It would also be nice if someone could give some sort of explanation (in light of the implementation) as to why the regular expressions "cat|catdog" and "catdog|cat" lead to different search results in the string "catdog", as mentioned in the question that I referenced before.

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  • Regular expression that contains in it...

    - by Fabiano PS
    I need my regexp to match, all the highlighted words, in order, following: Fri/Feb/10 - *Nesta* manh\303\203\302\243,* @*anestesya *entrou* \303\240s 08:18AM Fri/Feb/10 - *Nesta* tarde,* @*pernas *saiu* \303\240s 08:18AM I was trying something like: /[?=Nesta.?=@.?=(entrou|saiu)]/ So I don't care what is in between as long as it has: ' Nesta ' AND ' @' AND ' entrou ' OR ' saiu '

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  • Regular expression replace a word by a link

    - by AnhTu
    I want to write a regular expression that will replace the word Paris by a link, for only the word is not ready a part of a link. Example: i'm living <a href="Paris" atl="Paris link">in Paris</a>, near Paris <a href="gare">Gare du Nord</a>, i love Paris. would become i'm living.........near <a href="">Paris</a>..........i love <a href="">Paris</a>.

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  • Slug ID's with the same name?

    - by James Jeffery
    I want to create slug URL's from a users title in my system. If a user types "The best way's to get slim; period!", then I want the slug to be "the-best-ways-to-get-slim-period". Also, if someone has already created a page with that title I want the slug to be "the-best-ways-to-get-slim-period-1". My question is how can I check the database before a record is created? Ok, obviously I am going to have to perform a check in the database, and then a write. That's 2 queries. Is this the normal way to do it? Also, are there any conventional regular expressions for filtering non alpha/number characters and replacing spaces with hyphens? Any help is much appreciated. Thanks.

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  • How can I extract a URL from a sentence that is in a NSString?

    - by 0SX
    What I'm trying to accomplish is as follows. I have a NSString with a sentence that has a URL within the sentience. I'm needing to be able to grab the URL that is presented within any sentence that is within a NSString so for example: Let's say I had this NSString NSString *someString = @"This is a sample of a http://abc.com/efg.php?EFAei687e3EsA sentence with a URL within it."; I need to be able to extract http://abc.com/efg.php?EFAei687e3EsA from within that NSString. This NSString isn't static and will be changing structure and the url will not necessarily be in the same spot of the sentence. I've tried to look into the three20 code but it makes no sense to me. How else can this be done? Thanks for help.

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  • "Simple" Text replace function

    - by YourMomzThaBomb
    I have a string which is basically a list of "words" delimited by commas. These "words" can be pretty much any character e.g. "Bart Simpson, Ex-girlfriend, dude, radical" I'm trying to use javascript, jQuery, whatever i can to replace a word based on a search string with nothing (in essence, removing the word from the list). For example, the function is defined as such: function removeWord(myString, wordToReplace) {...}; So, passing the string listed above as myString and passing "dude" as wordToReplace would return the string "Bart Simpson, Ex-girlfriend, radical" Here's the line of code I was tinkering around with...please help me figure out what's wrong with it or some alternative (better) solution:$myString.val($myString.val().replace(/wordToReplace\, /, ""));

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  • How can I print lines that match a pattern in Perl?

    - by kivien
    Assuming the file.txt having just one sentence per line as follows:- John Depp is a great guy. He is very inteligent. He can do anything. Come and meet John Depp. The perl code is as follows:- open ( FILE, "file.txt" ) || die "can't open file!"; @lines = <FILE>; close (FILE); $string = "John Depp"; foreach $line (@lines) { if ($line =~ $string) { print "$line"; } } The output is going to be first and fourth line. I want to make it working for the file having random line breaks rather than one English sentence per line. I mean it should also work for the following:- John Depp is a great guy. He is very inteligent. He can do anything. Come and meet John Depp. The output should be first and fourth sentence. Any ideas please?

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  • Splitting a filename into words and numbers in Python

    - by danspants
    The following code splits a string into a list of words but does not include numbers: txt="there_once was,a-monkey.called phillip?09.txt" sep=re.compile(r"[\s\.,-_\?]+") sep.split(txt) ['there', 'once', 'was', 'a', 'monkey', 'called', 'phillip', 'txt'] This code gives me words and numbers but still includes "_" as a valid character: re.findall(r"\w+|\d+",txt) ['there_once', 'was', 'a', 'monkey', 'called', 'phillip', '09', 'txt'] What do I need to alter in either piece of code to end up with the desired result of: ['there', 'once', 'was', 'a', 'monkey', 'called', 'phillip', '09', 'txt']

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  • How to make this .htaccess rule case insensitive?

    - by alex
    This is a rule in my .htaccess # those CSV files are under the DOCROOT ... so let's hide 'em <FilesMatch "\.CSV$"> Order Allow,Deny Deny from all </FilesMatch> I've noticed however that if there is a file with a lowercase or mixed case extension of CSV, it will be ignored by the rule and displayed. How do I make this case insensitive? I hope it doesn't come down to "\.(?:CSV|csv)$" (which I'm not sure would even work, and doesn't cover all bases) Note: The files are under the docroot, and are uploaded automatically there by a 3rd party service, so I'd prefer to implement a rule my end instead of bothering them. Had I set this site up though, I'd go for above the docroot. Thanks

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  • Validate a string in a table in SQL Server - CLR function or T-SQL (Question updated)

    - by Ashish Gupta
    I need to check If a column value (string) in SQL server table starts with a small letter and can only contain '_', '-', numbers and alphabets. I know I can use a SQL server CLR function for that. However, I am trying to implement that validation using a scalar UDF and could make very little here...I can use 'NOT LIKE', but I am not sure how to make sure I validate the string irrespective of the order of characters or in other words write a pattern in SQL for this. Am I better off using a SQL CLR function? Any help will be appreciated.. Thanks in advance Thank you everyone for their comments. This morning, I chose to go CLR function way. For the purpose of what I was trying to achieve, I created one CLR function which does the validation of an input string and have that called from a SQL UDF and It works well. Just to measure the performance of t-SQL UDF using SQL CLR function vs t- SQL UDF, I created a SQL CLR function which will just check if the input string contains only small letters, it should return true else false and have that called from a UDF (IsLowerCaseCLR). After that I also created a regular t-SQL UDF(IsLowerCaseTSQL) which does the same thing using the 'NOT LIKE'. Then I created a table (Person) with columns Name(varchar) and IsValid(bit) columns and populate that with names to test. Data :- 1000 records with 'Ashish' as value for Name column 1000 records with 'ashish' as value for Name column then I ran the following :- UPDATE Person Set IsValid=1 WHERE dbo.IsLowerCaseTSQL (Name) Above updated 1000 records (with Isvalid=1) and took less than a second. I deleted all the data in the table and repopulated the same with same data. Then updated the same table using Sql CLR UDF (with Isvalid=1) and this took 3 seconds! If update happens for 5000 records, regular UDF takes 0 seconds compared to CLR UDF which takes 16 seconds! I am very less knowledgeable on t-SQL regular expression or I could have tested my actual more complex validation criteria. But I just wanted to know, even I could have written that, would that have been faster than the SQL CLR function considering the example above. Are we using SQL CLR because we can implement we can implement lot richer logic which would have been difficult otherwise If we write in regular SQL. Sorry for this long post. I just want to know from the experts. Please feel free to ask if you could not understand anything here. Thank you again for your time.

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  • javascript regular expression search a pattern A(xyz).

    - by Paul
    I need to find all substrings from a string that starting with a given string following with a left bracket and then any legal literal and then the right bracket. For example, a string is abcd(xyz)efcd(opq), I want to a function that returns "cd(xyz)" and "cd(opq)". I wrote a regular expression, but it returns only cd( and cd(...

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  • String parsing help

    - by Click Upvote
    I have a string like the following: $string = " <paragraph>apples are red...</paragraph> <paragraph>john is a boy..</paragraph> <paragraph>this is dummy text......</paragraph> "; I would like to split this string into an array contanining the text found between the <paragraph></paragraph> tags. E.g something like this: $string = " <paragraph>apples are red...</paragraph> <paragraph>john is a boy..</paragraph> <paragraph>this is dummy text......</paragraph> "; $paragraphs = splitParagraphs($string); /* $paragraphs now contains: $paragraphs[0] = apples are red... $paragraphs[1] = john is a boy... $paragraphs[1] = this is dummy text... */ Any ideas? P.S it should be case insensitive, <paragraph>, <PARAGRAPH>, <Paragraph> should all be treated the same way.

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  • Replacing Credit Card Numbers

    - by Del
    Hi, I'm using an sql to replace credit card numbers with xxxx and finding that REGEX_REPLACE does not consistently replace everything. Below is the SET command i'm using on the SQL SET COMMENTS_LONG = REGEXP_REPLACE (COMMENTS_LONG,'\D[1-6]\d{3}.\d{4}.\d{4}.\d{3}(\d{1}.\d{3})?|\D[1-6]\d{12,15}|\D[1-6]\d{3}.\d{3}.?\d{3}.\d{5}', ' XXXXXXXXXXXXXXXX') Before Elizabeth aclled to change address.5430-6000-2111-1931 A After Elizabeth aclled to change address XXXXXXXXXXXXXXXX1 A I tried increasing the number of X but result is the same. I also find that i have to put a space in front of the first X as it appears to move 1 char to the left.

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  • Using the @ symbol to identify users like twitter does

    - by Justin Phillips
    I'm creating my own version of twitter, I have no idea how to get my back end php script to pick up the @membername within the entered text. Including multiple @membername's for example @billy @joseph, @tyrone,@kesha message or @billy hit up @tyrone he's bugging @kesha about the money you owe him. Any scripts of use on how I can accomplish this?

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  • Greek characters, Regular Expressions, and C#

    - by craigmoliver
    I'm building a CMS for a scientific journal and that uses a lot of Greek characters. I need to validate a field to include a specific character set and Greek characters. Here's what I have now: [^a-zA-Z0-9-()/\s] How do I get this to include Greek characters in addition to alphanumeric, '(', ')', '-', and '_'? I'm using C#, by the way.

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