annotate paste/paste.29925 @ 3903:0f6dc05fb0d4
<boily> echo -e "#!/usr/bin/env python\\n# -*- encoding: utf-8 -*-\\nimport sys\\nimport unicodedata\\ntry:\\n print u\'\'.join(map(unicodedata.lookup, sys.argv[1:])).encode(\'utf-8\')\\nexcept KeyError:\\n print u\'\xc3\x9a\xc5\x84\xe1\xb8\xb1\xc5\x84\xc3\xb3\xe1\xba\x83\xc5\x84 \xc4\x87h\xcc\x81\xc3\xa1\xc5\x95\xc3\xa1\xc4\x87t\xcc\x81\xc3\xa9\xc5\x95.\'" >bin/unicode
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HackBot |
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Fri, 11 Oct 2013 15:24:35 +0000 |
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bdb161c7f923 |
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398
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1 Usage: words [-dhNo] [DATASETS...] [NUMBER_OF_WORDS]
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2
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3 options:
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4 -l, --list list valid datasets
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5 -d, --debug debugging output
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6 -N, --dont-normalize don't normalize frequencies when combining
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7 multiple Markov models; this has the effect
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8 of making larger datasets more influential
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9 -o, --target-offset change the target length offset used in the
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10 word generation algorithm; use negative integers
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11 for best results
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