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How to limit depth for recursive file list?
... Dec 22 '10 at 13:31
Alberto ZaccagniAlberto Zaccagni
27.4k99 gold badges6969 silver badges101101 bronze badges
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How to get git diff with full context?
...he line count followed by the file name, so the second use of the filename can be omitted also. I'm updating my answer to reflect this.
– Ezra
Nov 22 '16 at 17:36
4
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What's the idiomatic syntax for prepending to a short python list?
...f a list, python has to move all the other items one space forwards, lists can't "make space at the front". collections.deque (double ended queue) has support for "making space at the front" and is much faster in this case.
– fejfo
Mar 18 at 14:49
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How does IPython's magic %paste work?
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You can't copy to IPython directly. This are the steps:
Copy the lines you want to copy into IPython into the clipboard
Enter %paste into IPython
Press enter
Profit!
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How do you create nested dict in Python?
...innerkey'] = 'value'
>>> d
{'dict1': {'innerkey': 'value'}}
You can also use a defaultdict from the collections package to facilitate creating nested dictionaries.
>>> import collections
>>> d = collections.defaultdict(dict)
>>> d['dict1']['innerkey'] = 'value'...
What is the best way to count “find” results?
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Note that you can shave off a few more nanoseconds by not quoting the dot in -printf '.'
– Jens
Mar 27 '13 at 16:42
6
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u'\ufeff' in Python string
...n).
When opening a file, Python 3 supports the encoding keyword to automatically handle the encoding.
Without it, the BOM is included in the read result:
>>> f = open('file', mode='r')
>>> f.read()
'\ufefftest'
Giving the correct encoding, the BOM is omitted in the result:
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How to loop through all but the last item of a list?
... I think I did. Author said he would like to do X, then asked how he can do Y. I answered how he can do Y. That he accepted my answer would indicate I answered the question he asked, if not the question he really wanted to ask. Asker is welcome to demote this answer.
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Python: fastest way to create a list of n lists
... iteration and is about 15 % faster on my machine.
Edit: Using NumPy, you can avoid the Python loop using
d = numpy.empty((n, 0)).tolist()
but this is actually 2.5 times slower than the list comprehension.
share
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Is volatile expensive?
...fectively no-ops on X86 CPUs. Does this mean that volatile read operations can be done without a explicit cache invalidation on x86, and is as fast as a normal variable read (disregarding the reordering constraints of volatile)?
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