schinken

Keybase proof

I hereby claim:

• I am schinken on github.
• I am schinken (https://keybase.io/schinken) on keybase.
• I have a public key whose fingerprint is FFB7 E40D B2DD D24C C9B7 B5C5 703C F8B8 882C 871E

To claim this, I am signing this object:

schinken

function fuck() {
    killall -9 $2;
    if [ $? == 0 ]
      then
        echo
        echo " (╯°□°）╯︵$(echo $2|flip &2>/dev/null)"
        echo
    fi
}

schinken

Ft_ccc-bamberg-2015-04-28.jpg
Ft_ankuendigung-repaircafe-2015-04-25.jpg
Ft_SaferInternetDay.pdf
Ft_ankuendigung-tdot-2015.jpg
Feki.de_Der_backspace_-_Bamberger_Hacker_laden_ein.pdf

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myproject
  - directoryX
     - beautifulClass.py
  - directoryY
     - scriptThatNeedsBeautifulClass.py

schinken

import sys
(s,c,m,w,k,z,b)=("Easterhegg",0,int(sys.argv[1]),sys.stdout.write,0,lambda p:s[p%len(s)],[])
for v in [g for g in list(bin(0x471000)[2:].zfill(30)) for _ in range(m*2)]:
	if not k%(5*m*2):b+=["\n"];w(''.join(b*m));b=[]
	if int(v):b+=[" "]
	else:b+=[z(c)];c+=1
	k+=1

schinken

.
 \_ server.py
 \_ track
    \_ __init__.py
    \_ history.py (class history)
    \_ downloader.py (class downloader)


server.py:

schinken

try:
    im = Image.open( infile )
except IOError:
    print "Cant load", infile
    sys.exit(1)


curW, curH = size = im.size

schinken

def mapRange( val, min1, max1, min2, max2 ):
    return (val-min1)/(max1-min1) * (max2-min2) + min2

def toGrayscale( rgb, steps = 3.0 ):

    r, g, b = rgb

    value = float( r + g + b ) / 3.0
    value = mapRange( value, 0.0, 255.0, 0.0, steps )

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works:
{'background': 255, 'extension': ('NETSCAPE2.0', 795), 'version': 'GIF89a', 'transparency': 255, 'duration': 70, 'loop': 0}
{'background': 0, 'extension': ('NETSCAPE2.0', 75), 'version': 'GIF89a', 'transparency': 14, 'duration': 70, 'loop': 0}

doesnt work:
{'background': 0, 'extension': ('NETSCAPE2.0', 123), 'version': 'GIF89a', 'transparency': 31, 'duration': 1500, 'loop': 0}

schinken

Mode
The mode of an image defines the type and depth of a pixel in the image. The current
release supports the following standard modes:
1 (1-bit pixels, black and white, stored as 8-bit pixels)
•
L (8-bit pixels, black and white)
•
P (8-bit pixels, mapped to any other mode using a colour palette)
•
RGB (3x8-bit pixels, true colour)