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Switch case with fallthrough?
... should occur before do_what_you_are_supposed_to_do(), collapsing both "2" and "3" into a single case fails to address this. I'm unsure if editing the question to make this clearer is reasonable, since it's obvious that many people have found this answer helpful.
– Tyson
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Python module for converting PDF to text [closed]
...n Activestate which uses pypdf but the text generated had no space between and was of no use.
13 Answers
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Find the index of a dict within a list, by matching the dict's value
...answered Dec 8 '10 at 20:03
toklandtokland
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Split string with delimiters in C
How do I write a function to split and return an array for a string with delimiters in the C programming language?
20 Answe...
How can I easily view the contents of a datatable or dataview in the immediate window
Sometimes I will be at a breakpoint in my code and I want to view the contents of a DataTable variable (or a DataTable in a DataSet ). The quick watch doesn't give you a very clear view of the contents. How can I view them easily?
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Does C have a “foreach” loop construct?
... \
for(T * item = list->head; item != NULL; item = item->next)
And can be used like
for_each_item(i, processes) {
i->wakeup();
}
Iteration over an array is also possible:
#define foreach(item, array) \
for(int keep = 1, \
count = 0,\
size = sizeof (...
What is 'Pattern Matching' in functional languages?
I'm reading about functional programming and I've noticed that Pattern Matching is mentioned in many articles as one of the core features of functional languages.
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How to test android referral tracking?
...mplementing some code to do my own referral tracking on downloads from the Android market.
8 Answers
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How to find list of possible words from a letter matrix [Boggle Solver]
...ictionary word that could be a solution must use only the grid's
# letters and have length >= 3. (With a case-insensitive match.)
import re
alphabet = ''.join(set(''.join(grid)))
bogglable = re.compile('[' + alphabet + ']{3,}$', re.I).match
words = set(word.rstrip('\n') for word in open('words')...
Is there a rule-of-thumb for how to divide a dataset into training and validation sets?
Is there a rule-of-thumb for how to best divide data into training and validation sets? Is an even 50/50 split advisable? Or are there clear advantages of having more training data relative to validation data (or vice versa)? Or is this choice pretty much application dependent?
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