Peleg Michaeli pelegm

## beamer-slides-with-notes.pdf

      
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                andrejbauer
                / beamer-slides-with-notes.pdf
            
            
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## clockface
#!/usr/bin/python
# -*- coding: utf-8 -*-

from sys import argv
from time import strftime

clocks = {'12:00': '🕛', '12:30': '🕧',  '1:00': '🕐',  '1:30': '🕜',
           '2:00': '🕑',  '2:30': '🕝',  '3:00': '🕒',  '3:30': '🕞',
           '4:00': '🕓',  '4:30': '🕟',  '5:00': '🕔',  '5:30': '🕠',
           '6:00': '🕕',  '6:30': '🕡',  '7:00': '🕖',  '7:30': '🕢',

## upgrade-install-ruby-2-1-2-ubuntu-12-04.md

      
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                scmx
                / upgrade-install-ruby-2-1-2-ubuntu-12-04.md
            
            
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              November 6, 2019 15:31
            
              
                Upgrade/Install ruby 2.1.2 #ubuntu #12.04 #14.04
              
          
    Upgrade/Install ruby 2.1.2

ubuntu 12.04 14.04
Reference http://stackoverflow.com/a/18490935/2037928
Login as root
Install needed packages
apt-get -y install build-essential zlib1g-dev libssl-dev libreadline6-dev libyaml-dev

  
## gist:173482
"""
Would this make a better random.sample() function for the Python
standard library? Robert Floyd's algorithm as presented in Jon
Bentley, "A Sample of Brilliance".

Answer: no, it's slower; somewhat slower even if you tune it.
I tried a few different test cases -- both small and large
result lists. I'd expect it to use much less memory in some cases,
but my flailings turned up no case where that seemed to matter.
	#!/usr/bin/python
	# -- coding: utf-8 --

	from sys import argv
	from time import strftime

	clocks = {'12:00': '🕛', '12:30': '🕧', '1:00': '🕐', '1:30': '🕜',
	'2:00': '🕑', '2:30': '🕝', '3:00': '🕒', '3:30': '🕞',
	'4:00': '🕓', '4:30': '🕟', '5:00': '🕔', '5:30': '🕠',
	'6:00': '🕕', '6:30': '🕡', '7:00': '🕖', '7:30': '🕢',
	"""
	Would this make a better random.sample() function for the Python
	standard library? Robert Floyd's algorithm as presented in Jon
	Bentley, "A Sample of Brilliance".

	Answer: no, it's slower; somewhat slower even if you tune it.
	I tried a few different test cases -- both small and large
	result lists. I'd expect it to use much less memory in some cases,
	but my flailings turned up no case where that seemed to matter.