data:image/png;base64,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what's your name?Alert!choose!title§_objectsMenuoptionleftleft
righthey!open my definition to look at examples how to use the menu blocksde:sprich _ mit _ Aussprache _ und Höhe _ Geschwindigkeit _
pt:fala _ na língua _ _ com tom _ e velocidade _
ca:digues _ amb accent _ _ to _ i velocitat _
Hello, World!en-USالعربية=ar
Български=bg
বাংলা=bn
Català=ca
Català - Valencià=ca-VA
Česky=cs
Deutsch=de
Dansk=dk
Ελληνικά=el
English-American=en-US
English-British=en-GB
Esperanto=eo
Español=es
Eesti=et
Euskara=eu
suomi=fi
Français=fr
Galego=gl
Hrvatski=hr
Magyar=hu
Interlingua=ia
Bahasa Indonesia=id
Italiano=it
日本語=ja
にほんご=ja-HIRA
ಕನ್ನಡ=kn
한국어=ko
Malayalam=ml
Nederlands=nl
Norsk=no
Polski=pl
Português=pt
Português do Brasil=pt-BR
Român=ro
Русский=ru
Slovenščina=si
svenska=sv
Tamil=ta
Telagu=te
Türkçe=tr
Українська=ua
简体中文=zh-CN
繁體中文=zh-TW11de:sprich _ mit _ Aussprache _ und Höhe _ Geschwindigkeit _ und warte
pt:fala _ na língua _ _ com tom _ e velocidade _ , e espera
ca:digues _ amb accent _ _ to _ velocitat _ i espera
Hello, World!en-USالعربية=ar
Български=bg
বাংলা=bn
Català=ca
Català - Valencià=ca-VA
Česky=cs
Deutsch=de
Dansk=dk
Ελληνικά=el
English-American=en-US
English-British=en-GB
Esperanto=eo
Español=es
Eesti=et
Euskara=eu
suomi=fi
Français=fr
Galego=gl
Hrvatski=hr
Magyar=hu
Interlingua=ia
Bahasa Indonesia=id
Italiano=it
日本語=ja
にほんご=ja-HIRA
ಕನ್ನಡ=kn
한국어=ko
Malayalam=ml
Nederlands=nl
Norsk=no
Polski=pl
Português=pt
Português do Brasil=pt-BR
Român=ro
Русский=ru
Slovenščina=si
svenska=sv
Tamil=ta
Telagu=te
Türkçe=tr
Українська=ua
简体中文=zh-CN
繁體中文=zh-TW11This block allows you to set the pen's color, transparency (on a scale from 0=opaque to 100=invisible), or size (in pixels). The color can be set in many ways, including RGB values, HSV values, HSL values, fair HSV or HSL (based on a modified spectrum that gives each spectral color equal space and promotes brown to a color), color number, crayon, or X11/W3C color name.
See Appendix A in the Snap! Reference Manual for details.ca:$brush fixa el _ del llapis a _ _
color
color number
crayon
fair hue
~1
size
transparency
X11/W3C name
~2
(3D color spaces)={
fair HSL={
fair hue
fair saturation (HSL)
fair lightness
fair HSL vector
}
fair HSV={
fair hue
fair saturation (HSV)
fair value (brightness)
fair HSV vector
}
HSL={
hue
saturation (HSL)
lightness
HSL vector
}
HSV={
hue
saturation (HSV)
value (brightness)
HSV vector
}
RGB (0-255)={
red
green
blue
RGB(A) vector
RGB(A) hex
}
}§_ext_clr_numbersNote to myself: When the user sets a fair dimension, say fair HSL, variable HSL contains the corresponding "unfair" values, and "raw HSL" contains the numbers the user actually gave. It has to be this way because in the case of HSV, there is no "HSV" variable; rather, we use the pen's actual remembered-by-Javascript color's HSV coordinates. So our HSL variable has to be analogous to that. In both cases "raw" means the numbers the user gave us.1HSV✐ raw HSL100HSV100The identity function reports its input.This block reports the pen size, color, or transparency, in all the same ways that the SET PEN block allows you to set those pen properties. (It will also report the current crayon number, if the pen color was most recently set with SET PEN TO CRAYON.)
See Appendix A of the Snap! Reference Manual for details. ca:$brush _ del llapis
color
color number
crayon
fair hue
~1
size
transparency
X11/W3C name
~2
(3D color spaces)={
fair HSL={
fair hue
fair saturation (HSL)
fair lightness
fair HSL vector
}
fair HSV={
fair hue
fair saturation (HSV)
fair value (brightness)
fair HSV vector
}
HSL={
hue
saturation (HSL)
lightness
HSL vector
}
HSV={
hue
saturation (HSV)
value (brightness)
HSV vector
}
RGB (0-255)={
red
green
blue
RGB vector
RGBA vector
RGB(A) hex
}
}huesaturation (HSV)value (brightness)transparencyRGB vectorRGBA vectorredgreenblueRGB(A) hex1616HSV vectorHSL vectorsaturation (HSL)lightnesscolor numbercolorfair huenot setfair saturation (HSL)not setfair lightnessnot setfair HSL vectornot setfair saturation (HSV)2not setfair value (brightness)3not setfair HSV vectornot setcrayonX11/W3C nameChanges any pen property by the specified amount. Some color scales can't be adjusted this way unless the color was first SET using that scale.
Vectors (e.g., RGB color as a list of three numbers) can be incremented
by a vector as the amount. X11/W3C names can't be incremented.ca:$brush augmenta _ del llapis en _
color number
crayon
fair hue
~1
size
transparency
~2
(3D color spaces)={
fair HSL={
fair hue
fair saturation (HSL)
fair lightness
fair HSL vector
}
fair HSV={
fair hue
fair saturation (HSV)
fair value (brightness)
fair HSV vector
}
HSL={
hue
saturation (HSL)
lightness
HSL vector
}
HSV={
hue
saturation (HSV)
value (brightness)
HSV vector
}
RGB (0-255)={
red
green
blue
RGB vector
RGBA vector
}
}crayonRGB hexI don't know how to handle pt:lança o erro _
combines any number of colors, reporting the result of mixing them, either additively (like colored light beams) or subtractively (like paints). If the result is too bright (additive) or too dark (subtractive), try the "averaged" versions, which will make the brightness more like the brightnesses of the input colors.ca:$brush barreja colors _ amb criteri _
additive (light)
additive (averaged)
subtractive (ideal)
subtractive (averaged)
simulated paint
paint (sRGB corrected)waveformssum of weightscombined waveformweighted geometric mean of waveformssum of weightscombined waveformTback to RGBT5.47813E-05 0.000184722 0.000935514 0.003096265 0.009507714 0.017351596 0.022073595 0.016353161 0.002002407 -0.016177731 -0.033929391 -0.046158952 -0.06381706 -0.083911194 -0.091832385 -0.08258148 -0.052950086 -0.012727224 0.037413037 0.091701812 0.147964686 0.181542886 0.210684154 0.210058081 0.181312094 0.132064724 0.093723787 0.057159281 0.033469657 0.018235464 0.009298756 0.004023687 0.002068643 0.00109484 0.000454231 0.000255925-4.65552E-05 -0.000157894 -0.000806935 -0.002707449 -0.008477628 -0.016058258 -0.02200529 -0.020027434 -0.011137726 0.003784809 0.022138944 0.038965605 0.063361718 0.095981626 0.126280277 0.148575844 0.149044804 0.14239936 0.122084916 0.09544734 0.067421931 0.035691251 0.01313278 -0.002384996 -0.009409573 -0.009888983 -0.008379513 -0.005606153 -0.003444663 -0.001921041 -0.000995333 -0.000435322 -0.000224537 -0.000118838 -4.93038E-05 -2.77789E-050.00032594 0.001107914 0.005677477 0.01918448 0.060978641 0.121348231 0.184875618 0.208804428 0.197318551 0.147233899 0.091819086 0.046485543 0.022982618 0.00665036 -0.005816014 -0.012450334 -0.015524259 -0.016712927 -0.01570093 -0.013647887 -0.011317812 -0.008077223 -0.005863171 -0.003943485 -0.002490472 -0.001440876 -0.000852895 -0.000458929 -0.000248389 -0.000129773 -6.41985E-05 -2.71982E-05 -1.38913E-05 -7.35203E-06 -3.05024E-06 -1.71858E-06newsRGBRGB vector255addmax255RGB vectorThis block reports a color. The color can be set in many ways, including RGB values, HSV values, HSL values, fair HSV or HSL (based on a modified spectrum that gives each spectral color equal space and promotes brown to a color), color number, crayon, or X11/W3C color name.
See Appendix A in the Snap! Reference Manual for details.ca:$brush color amb _ _ _
color
color number
crayon
fair hue
X11/W3C name
~
fair HSL=fair HSL vector
fair HSV=fair HSV vector
HSL=HSL vector
HSV=HSV vector
RGB (0-255)=RGB vector
RGB hex§_ext_clr_numberscolor numbercolor300index15scale1515255fromto122crayon132X11/W3C nameRGB hexcolorRGB vectorHSV vectorHSL vectorfair HSV vectorindex-1scale1index1color100fair HSL vectorindex-1scale1index1color110050ca:$brush _ del color _
nearest color number
crayon number
fair hue
~1
transparency
X11/W3C name
~2
(3D color spaces)={
fair HSL={
fair hue
fair saturation (HSL)
fair lightness
fair HSL vector
}
fair HSV={
fair hue
fair saturation (HSV)
fair value (brightness)
fair HSV vector
}
HSL={
hue
saturation (HSL)
lightness
HSL vector
}
HSV={
hue
saturation (HSV)
value (brightness)
HSV vector
}
RGB (0-255)={
red
green
blue
RGB vector
RGBA vector
RGB hex
}
}X11/W3C namenearest color numberrgbhslhsvrgbtransparencytransparencyRGB vectorRGBA vectorRGB hexredgreenbluehsvfalseHSV vectorhuesaturation (HSV)value (brightness)hsltrueHSL vectorsaturation (HSL)lightnessHSLlightnessfair lightness310030.9833.333333330.986.9444444516.944444451.96100fair lightnessfair saturation (HSL)210075.9493610075.949366.9444444516.944444451.96100fair saturation (HSL)fair HSL vectorfair lightness310030.9833.333333330.986.9444444516.944444458.823529100fair lightnessfair saturation (HSL)210075.9493610075.949366.9444444516.944444458.823529100fair saturation (HSL)fair HSL vectorfair hue11111111fair huefair saturation (HSL)fair lightnessfair HSL vectorbrownfair value (brightness)310054.5166.66666666754.516.9444444516.944444451.96100fair value (brightness)fair saturation (HSV)210086.3310086.336.9444444516.944444451.96100fair saturation (HSV)fair HSV vectorfair value (brightness)310054.5166.66666666754.516.9444444516.944444451.96100fair value (brightness)fair saturation (HSV)210086.3310086.336.9444444516.944444451.96100fair saturation (HSV)fair HSV vectorfair hue11111111fair huefair saturation (HSV)fair value (brightness)fair HSV vectorbrownfair somethingCan't get here -- please post project and screenshot to forum.This block reports the pen color
(as a color, not as a list of numbers).ca:✐ color de llapis actual
de:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
pt:captura _ _
contSets the pen color
to one of 100 preselected colors, like a box of 100 crayons.
The colors have names that are meant to be evocative.
They are organized in families, more or less corresponding
to spectral (rainbow) colors; the input slot has a two-level menu
in which you can hover over a family name to see the colors
of that family, each including a crayon number and an RGB value.
See Appendix A of the Snap! Reference Manual for more details.ca:✐ fixa el llapis de color _ _
grays={
0 black #000000=0
1 gray7 #121212=1
2 gray14 #242424=2
3 gray21 #363636=3
4 gray28 #484848=4
5 gray36 #5c5c5c=5
6 gray43 #6d6d6d=6
7 gray50 #7f7f7f=7
8 gray57 #919191=8
9 gray64 #a3a3a3=9
10 gray71 #b5b5b5=10
11 gray78 #c8c8c8=11
12 gray85 #dadada=12
13 gray92 #ececec=13
14 white #ffffff=14
}
pinks={
15 deep pink #ff1493=15
16 hot pink #ff69b4=16
17 bright pink #ff007f=17
18 raspberry #e30b5d=18
19 amaranth #e52b50=19
}
reds={
20 red #ff0000=20
21 burgundy #900020=21
22 cherry #990000=22
23 dark candy apple red #a40000=23
24 sanguine #c00000=24
25 maroon #800000=25
26 crimson #c90016=26
27 Lists #d94d11=27
28 candy apple red #ff0800=28
29 coquelicot #ff3800=29
}
browns={
30 saddle brown #8b4513=30
31 chocolate #7b3f00=31
32 kobicha #6b4423=32
33 sepia #704214=33
34 chestnut #954535=34
35 dark brown #654321=35
36 brown #964b00=36
37 golden brown #996515=37
38 cinnamon #b87333=38
39 copper #d2691e=39
}
oranges={
40 orange #ff7f00=40
41 Pantone orange #ff5800=41
42 pumpkin #ff7518=42
43 Variables #f3761d=43
44 Spanish orange #e86100=44
45 burnt orange #cc5500=45
46 sinopia #cb410b=46
47 ochre #cc7722=47
48 carrot #ed9121=48
49 tangerine #f28500=49
}
yellows={
50 yellow #ffff00=50
51 Control #e6a822=51
52 dark goldenrod #b8860b=52
53 goldenrod #daa520=53
54 saffron #f4c430=54
55 sandstorm #ecd540=55
56 mustard #ffdb58=56
57 gold #ffd700=57
58 egg yolk #fee33e=58
59 rubber duck #fbe108=59
}
greens={
60 lime #00ff00=60
61 apple green #8db600=61
62 Operators #62c213=62
63 forest green #228b22=63
64 green #008000=64
65 dark green #006400=65
66 dark pastel green #03c03c=66
67 emerald #50c878=67
68 mint #3eb489=68
69 Pen #00a178=69
}
cyans={
70 aqua (cyan) #00ffff=70
71 dark cyan #008b8b=71
72 cerulean #007ba7=72
73 iceberg #71a6d2=73
74 Sensing #0494dc=74
75 teal #008080=75
76 light sky blue #87cefa=76
77 deep sky blue #00bfff=77
78 dodger blue #1e90ff=78
79 azure #007fff=79
}
blues={
80 blue #0000ff=80
81 midnight blue #191970=81
82 dark powder blue #003399=82
83 cobalt #0047ab=83
84 denim #1560bd=84
85 navy blue #000080=85
86 steel blue #4682b4=86
87 Motion #4a6cd4=87
88 cornflower #6495ed=88
89 slate blue #6a5acd=89
}
purples={
90 violet #8000ff=90
91 Looks #8f56e3=91
92 grape #6f2da8=92
93 indigo #4b0082=93
94 x11 purple #a020f0=94
95 magenta (fuchia) #ff00ff=95
96 dark orchid #9932cc=96
97 Sound #cf4ad9=97
98 purple #7f007f=98
99 dark magenta #8b008b=99
}✐ last set ascrayon✐ fair?false1231Takes three inputs for red, green, and blue
values, each between 0 and 255. 0,0,0 is black; 255,255,255 is white. 255,255,0 is yellow, and so on.
The SET PEN block in this library lets you set individual red, green, or blue without changing the others, lets you provide a list of three RGB color components, and lets you provide a six-digit hexadecimal number, the form in which RGB color values are usually found online.
See Appendix A of the Snap! Reference Manual for details.pt:altera a cor da tua caneta para vermelho _ , verde _ e azul _ (0 a 255)
ca:fixa el llapis al color r: _ g: _ b: _
25500Takes three inputs for hue, saturation, and value ("brightness")
values, each between 0 and 1. 0,0,0 is black; 0,0,1 is white. 0.15,1,1 is yellow, and so on.
The SET PEN block in this library lets you set individual hue, saturation, or value without changing the others, lets you provide a list of three HSV color components, and lets you
use the very much superior HSL (hue, saturation, lightness)
color space.
See Appendix A of the Snap! Reference Manual for details.pt:altera a cor da caneta para matiz _ , saturação _ e brilho _ (0 a 1)
ca:fixa el llapis al color h: _ s: _ v: _
0.30.70.6Reports the current pen color as a list of three RGB values in the range 0-255. The PEN block in this library provides a large set of ways to examine the color.
See Appendix A in the Snap! Reference Manual for details.pt:a cor da caneta em RGB (vermelho, verde e azul; 0 a 255)
Reports the current pen color as a list of three HSV values
in the range 0-1.
See Appendix A in the Snap! Reference Manual for details.pt:a cor da caneta em HSV (matiz, saturação e brilho, 0 a 1)
Takes a value from 0 to 15 and reports
the corresponding hexadecimal digit.
For internal use of the color library.Don't ask.
Only for internal use by the SET PEN block.truetrueCreates a bunch of global variables.
For internal use by Color library.global✐ last set as✐ fair?✐ color scale✐ HSL✐ last crayon✐ last X11✐ raw HSL✐ raw HSV✐ X11✐ crayon colors✐ fair hue table✐ colors✐ brights✐ pivots✐ HSV brights✐ HSL brights✐ HSV colors✐ HSL colors✐ X11 catch✐ dimension names✐ dimension dispatch✐ last set asRGB✐ fair?false✐ raw HSV0100100✐ HSL010050✐ raw HSL010050not a crayonnot an X11 color11000hues1fair hues00hue101100021000✐ fair hue table10111smallest componentrgb255smallest component2rgb2552Red family8.7Brown/orange family17yellow501427.7522.334green52cyan67blue83.33333333purple9550505left of blackfalsehue603.61001003.6100100hue mod 100, other components cut off at [0, 100]value100color3.6index1index-1scale1255fromto1newHSVHSL✐ fair?truecolor300index15scale15grayscale15255fromto121✐ last set ascolor number✐ fair?true✐ raw HSL10050✐ raw HSV100100015866161216341656✐ last set asRGB✐ fair?false144partial matchestrue4matchhead matchestrueSUBSET throws here if it handles a unique match144partial matchesfalse4matchhead matchesfalseSUBSET throws here if it handles a unique match2015866161216341656fair hue
transparency
~2
(3D color spaces)={
fair HSL={
fair hue
fair saturation (HSL)
fair lightness
}
fair HSV={
fair hue
fair saturation (HSV)
fair value (brightness)
}
HSL={
hue
saturation (HSL)
lightness
}
HSV={
hue
saturation (HSV)
value (brightness)
}
RGB (0-255)={
red
green
blue
}
}255100We have to do this last test to rule out the vector options, which aren't numbers; their code makes three recursive calls and we catch range issues then.huesaturation (HSV)value (brightness)saturation (HSL)lightnesstransparencyredgreenbluefair huefair saturation (HSV)fair value (brightness)fair saturation (HSL)fair lightness✐ last set asHSL33✐ fair?false1✐ last set asRGB✐ fair?false✐ last set asRGB✐ fair?false✐ last set asRGB✐ fair?false✐ last set asRGB✐ fair?false04value0255131✐ last set asRGB✐ fair?false✐ last set asHSL22✐ fair?false1✐ last set asHSL✐ HSL11000100✐ raw HSL✐ fair?false1✐ last set asHSV✐ fair?false✐ raw HSV1310031100if USED TO BE fairHSL✐ fair?false1✐ last set asHSL2222✐ fair?true1✐ last set asHSL3333✐ fair?true1231322✐ last set asHSV✐ fair?true133✐ last set asHSV✐ fair?true123131pt:o texto multilinha _
Reports the part of the first string up to the first instance of the second string inside it. If the second string isn't found, reports the entire first string.pt:o texto de _ antes de _
Reports the portion of the first input string starting after the first occurrence of the second string. If the second string isn't found in the first string, reports an empty string.pt:o texto de _ depois de _
Reports the character position (starting from 1) of the beginning of the first input string inside the second input string.
If it's not found, reports 0.pt:a posição de _ em _
If input is TRUE, comparisons made by functions in the string library will be case-independent (so "FOO" = "foo"). This is the default.
If input is FALSE, comparisons will be exact.pt:altera comparações ignorando distinção minúsculas/maiúsculas para _
Reports the portion of the first input (string) starting at the position given by the second input (counting from 1, like LETTER n OF) and ending at the position given by the third input (also counting from 1). If the third input is empty, reports the portion from the first position to the end of the string.
If a position number is negative, counts from the end backward, so -1 is the last character, -2 is the next to last, etc.pt:o texto de _ entre as posições _ e _ , inclusive
Reports True if the first input string contains the second input string, otherwise false.
Comparison is case-independent by default; use USE CASE-INDEPENDENT COMPARISONS to change that.pt:o texto de _ antes de _
Reports the input text with lower case letters instead of capital letters in the input. Uses the user's locale's rules for case conversion.pt:em minúsculas _
err_resetThis block creates new variables on the selected scope: global (for all sprites), sprite (for this sprite only) or script (only for that blocks stack) with the names given (in 'names' list).
If there is already a variable with that name in that scope, it does nothing: no errors and no overwrites.pt:cria as variáveis _ _
ca:crea les _ variables _
es:crear las _ variables _
de:erstellen _ var _
globalglobal
sprite
scriptThis block reports "true" if there is a variable with this given name (input slot) in that context.
It can be a global, sprite or script variable.
Otherwise it reports "false".pt:a variável _ existe
ca:existeix la variable _ ?
es:existe la variable _ ?
de:existiert var _ ?
err_resetde:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
pt:captura _ _
contde:wirf _
ca:llança _
es:lanzar _
fr:lance _
pt:lança _
catchtagde:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
pt:captura _ _
contde:wirf _ _
ca:llança _ _
es:lanzar _ _
fr:lance _ _
pt:lança _ _
catchtagThis is a breakpoint block, to be used in debugging.
The Boolean input specifies the condition under which
the program should pause. (Use True for an unconditional breakpoint.) The intent is that the script should have
SHOW VARIABLE blocks for the process's local variables.
After the pause, this block automatically hides all temporary variables.de:falls _ dann _ und pause $pause-1-255-220-0
ca:si _ fes _ i atura-ho tot $pause-1-255-220-0
es:si _ haz _ y páralo todo $pause-1-255-220-0
fr:si _ faire _ et mettre tout en pause $pause-1-255-220-0
pt:se _ , então _ e faz pausa em tudo $pause-1-255-220-0
This block does nothing.
Use it when you are calling a reporter
for its side effect and don't care about
its return value.de:ignoriere _
ca:ignora _
es:ignorar _
fr:ignore _
pt:ignora _
Call f(f(f(...(f(x))))) n times where the three input slots are n, f, and x from left to right. The # variable can be used inside f to represent how many times f has been called.pt:o resultado de _ invocações em cascata de _ com argumento inicial _ _
ca:en cascada _ vegades _ _ _
Call f(f(f(...(f(x))))) until condition is true, where the three input slots are condition, f, and x from left to right. The # variable can be used inside f or condition to indicate how many times f has been called.pt:o resultado da invocação em cascata até que _ de _ com argumento inicial _ _
ca:en cascada fins _ _ _ _
Returns the function x↦f(g(x)) where f and g are the two inputs.pt:a composição de _ com _
ca:composa _ _
Like the built-in REPEAT UNTIL block, except that the ending condition is not tested until the script has been run the first time. So the script is run at least once.pt:repete _ até que _ $loop-0.7
ca:repeteix _ fins _
Run the script repeatedly, as long as the given condition is true. Runs the script at least once before testing the condition.pt:repete _ enquanto _ $loop-0.7
ca:repeteix _ mentre _
Runs the script repeatedly, as long as the condition is true. Tests the condition before the first time the script is run. Like the built in REPEAT UNTIL except that in this block the condition must be true, not false.pt:enquanto _ , repete _ $loop-0.7
Runs the script the specified number of times, like the built-in REPEAT block, but this one provides the # variable that can be used inside the script. Try
REPEAT (200)
MOVE (#) STEPS
RIGHT 92
with the pen down.pt:repete _ vezes _ _ $loop-0.7
ca:repeteix _ _ _
The primitive FOR block uses an implicit step of ±1 depending on which of the starting and ending values is larger. This version allows you to provide an explicit step value. If the sign of the step input is incompatible with the ordering of the starting and ending values, the script will not be run at all.pt:para _ de _ com passo _ a _ _ $loop-0.7
ca:per _ = _ incrementant _ fins _ _
1110Provides LOOP as a function of one input that runs
the body of the LET with A set to the function input,
so the body can run itself recursively.
See COPY block in Variables for an example of use.pt:tendo _ o valor inicial _ , executa _ definido como _
ca:fes que _ sigui _ al _ _
new 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pink,15255,105,180,hot pink,16255,0,127,bright pink,17227,11,93,raspberry,18229,43,80,amaranth,19255,0,0,red,20144,0,32,burgundy,21153,0,0,cherry,22164,0,0,dark candy apple red,23192,0,0,sanguine,24128,0,0,maroon,25201,0,22,crimson,26217,77,17,Lists,27255,8,0,candy apple red,28255,56,0,coquelicot,29139,69,19,saddle brown,30123,63,0,chocolate,31107,68,35,kobicha,32112,66,20,sepia,33149,69,53,chestnut,34101,67,33,dark brown,35150,75,0,brown,36153,101,21,golden brown,37184,115,51,cinnamon,38210,105,30,copper,39255,127,0,orange,40255,88,0,Pantone orange,41255,117,24,pumpkin,42243,118,29,Variables,43232,97,0,Spanish orange,44204,85,0,burnt orange,45203,65,11,sinopia,46204,119,34,ochre,47237,145,33,carrot,48242,133,0,tangerine,49255,255,0,yellow,50230,168,34,Control,51184,134,11,dark goldenrod,52218,165,32,goldenrod,53244,196,48,saffron,54236,213,64,sandstorm,55255,219,88,mustard,56255,215,0,gold,57254,227,62,egg yolk,58251,225,8,rubber duck,590,255,0,lime,60141,182,0,apple green,6198,194,19,Operators,6234,139,34,forest green,630,128,0,green,640,100,0,dark green,653,192,60,dark pastel green,6680,200,120,emerald,6762,180,137,mint,680,161,120,Pen,690,255,255,aqua,700,139,139,dark cyan,710,123,167,cerulean,72113,166,210,iceberg,734,148,220,Sensing,740,128,128,teal,75135,206,250,light sky blue,760,191,255,deep sky blue,7730,144,255,dodger blue,780,127,255,azure,790,0,255,blue,8025,25,112,midnight blue,810,51,153,dark powder blue,820,71,171,cobalt,8321,96,189,denim,840,0,128,navy blue,8570,130,180,steel blue,8674,108,212,Motion,87100,149,237,cornflower,88106,90,205,slate blue,89128,0,255,violet,90143,86,227,Looks,91111,45,168,grape,9275,0,130,indigo,93160,32,240,x11 purple,94255,0,255,magenta,95153,50,204,dark orchid,96207,74,217,Sound,97127,0,127,purple,98139,0,139,dark 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number,crayon,fair hue,size,transparency,X11/W3C name,fair saturation (HSL),fair lightness,fair HSL vector,fair saturation (HSV),fair value (brightness),fair HSV vector,hue,saturation (HSL),lightness,HSL vector,saturation (HSV),value (brightness),HSV vector,red,green,blue,RGB(A) vector,RGB(A) hexFried Calamari,Seared Scallops,Steamed Loster,Grilled Squid,Raw Oysters,Steamed Crawfish,Fried Shrimp,Fried Catfish,Crab Cakes,Spicy WingsBlue Cheese Stuffed Shrimp,Coconut Shrimp,Hot Crab Dip,Crab Wontons,Marinated Shrimp Cups,Sesame Tuna Bites,Cucumber Rolls,Spicy Shrimp SalsaCoke,Dr. Pepper,Sprite,Water,Sparkling Ocean Water,Lemonade,Milk,Margarita,Martini,MimosaCajun Fries,Cauliflower Gnocchi,Burrata Salad,Panzella Salad,Potatoe Salad,Portobello Mushrooms,Parmesan Brussel Sprouts,Avocado Rice,Greek Salad,Grilled CornStrawberry Shortcake,Heaven on Earth Cake,Raspberry Sorbet,Citrus Fruit Salad,Fruit Kebabs