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PDO large results


Try increasing your max_input_vars to 10000 in your php.ini and see if anything changes.

At the moment it is 1000 i guess and may you run into memory errors.


Categories : PHP

Related to : PDO large results
Search a listbox, results will not highlight when searching results found
Your logic would only work if the last item was the match. For Each item As String In lstMain.SelectedItems If item.ToUpper.Substring(0, 24).Contains(strSearchField.ToUpper) Then lstMain.SelectedItem = item Exit For 'so the found item stays selected End If Next or For i As Integer = 0 To lstMain.Items.Count - 1 If lstMain.Items(i).ToUpper.Substring(0, 24).Contains(strSearchField

Categories : Vb.Net
How to redirect (301) search results page which do not return results
Replace old-page.php code with redirection code to new-page.php. so in your case if you want to a new search.php code you should have two php files. First, the old-search.php which contains the following code, and then the new-search.php code which is the one that should be specified in the link. ---old-search.php--- <?php // PHP permanent URL redirection header("Location: http://www.yourdoma

Categories : PHP
creating sub-array form a large array based on the first element of the large array
import operator L = [['a', '2', '7'], ['b', '2', '9'],['a', '1', '4'],['c', '6', '1'],['b', '9', '9'],['a', '3', '2'],['c', '1', '5'],['b', '3', '7']] lists = {'a':[], 'b':[], 'c':[]} g = operator.itemgetter(1,2) for t in L: lists[t[0]].append(g(t)) print('aList:', lists['a']) print('bList:', lists['b']) print('cList:', lists['c']) Output: aList: [('2', '7'), ('1', '4'), ('3', '2')] bLis

Categories : Python
Pickling a trained classifier yields different results from the results obtained directly from a newly but identically trained classifier
There should not be any difference as @AndreasMueller stated, here's a modified example from http://scikit-learn.org/stable/tutorial/text_analytics/working_with_text_data.html#loading-the-20-newgroups-dataset using pickle: from sklearn.datasets import fetch_20newsgroups from sklearn.feature_extraction.text import CountVectorizer from sklearn.feature_extraction.text import TfidfTransformer from sk

Categories : Python
While Loop - Separate Title From Looped Results - Loop and Then Title For Each Set Of Results
How about creating a new array based upon the entries you want in the table. So your code would go something like (note $outputarray was added): Edit: This assumes there is only one Title per data set. If you want more than one title per set of records, you need to set something in the record that identifies a set. In this case, the easiest way was to make a multi-dimension array of the result

Categories : PHP
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