data:image/png;base64,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data:image/png;base64,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heightde:$globe zeige aktuellen Standort
pt:mostra a localização corrente do dispositivo no $globe
ca:$globe centra a la meva ubicació
de:$globe Zoom
pt:o zoom do $globe
ca:$globe zoom
de:setze $globe Zoom auf _
pt:altera o zoom do $globe para _
ca:$globe fixa el zoom a _
10de:$globe Längengrad von x _
pt:a longitude no $globe da coordenada x _
ca:$globe longitud per a x _
0de:$globe Breitengrad von y _
pt:a latitude no $globe da coordenada y _
ca:$globe latitud per a y _
0de:setze $globe auf Länge: _ Breite: _
pt:altera a posição no $globe para (longitude: _ , latitude: _ )
ca:$globe centra a longitud: _ latitud: _
-122.25785237.872099de:y von $globe Breitengrad _
pt:a coordenada y da latitude _ no $globe
ca:$globe y per a latitud _
de:x von $globe Längengrad _
pt:a coordenada x da longidude _ no $globe
ca:$globe x per a longitud _
de:ändere $globe um x: _ y: _ Pixel
pt:desloca a posição do mapa de (x: _ , y: _ )
ca:$globe canvia la ubicació en x: _ y: _ píxels
1010de:$globe Entfernung in km zu _
pt:a tua distância em km a _ no $globo
ca:$globe distància en km fins a _
§_objectsMenustagelat1lng1lat2lng2return stage.worldMap.distanceInKm(lat1, lng1, lat2, lng2)de:$globe aktuelle Position
pt:a localização corrente do dispositivo no $globe
ca:$globe ubicació actual
de:$globe aktueller Breitengrad
pt:a latitude corrente do dispositivo no $globe
ca:$globe latitud actual
de:$globe aktueller Längengrad
pt:a longitude corrente do dispositivo no $globe
ca:$globe longitud actual
de:aktualisiere $globe
pt:actualiza o $globe
ca:$globe força refresc
de:$globe als Kostüm
pt:a parte visível do $globe na forma de traje
ca:$globe vestit del mapa actual
de:setze $globe Stil auf _
pt:altera o estilo do $globe para _
ca:$globe fixa l'estil de mapa a _
WikimediaOpenStreetMap
Wikimedia
Watercolor
Toner
Terrain
Topographic
Satellite
Streets
Shading
Mapbox (experimental)de:sprich _ mit _ Aussprache _ und Höhe _ Geschwindigkeit _
pt:fala _ na língua _ _ com tom _ e velocidade _
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suomi=fi
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Interlingua=ia
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にほんご=ja-HIRA
ಕನ್ನಡ=kn
한국어=ko
Malayalam=ml
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Português do Brasil=pt-BR
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svenska=sv
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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
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-TW11Takes a text string as input, and reports a new text string containing all but the first character of the input.pt:_ sem o primeiro caractere
resulti2Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the first word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)pt:_ sem a primeira palavra
Takes a text string as input, and reports a new text string containing all but the last letter of the input.pt:_ sem o último caractere
resulti1Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing all but the last word, with one space between words and no spaces at the beginning or end. (Note: consider using SENTENCE->LIST and processing the resulting list instead of doing recursion on sentences in text string form. List operations are faster.)pt:_ sem a última palavra
11111Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing only the first word, with no spaces before or after it.pt:a primeira palavra de _
Takes a text string as input, and reports the last character in the string.pt:o último caractere de _
Takes a text string as input, divides it into words treating one or more spaces as a word separator (only spaces count; punctuation is part of the word) and reports a text string containing only the last word of the input, with no spaces before or after it.pt:a última palavra de _
11Takes a text string as input, and reports TRUE if the string has no characters in it of any kind, otherwise false.pt:a palavra _ está vazia
Takes a text string as input, and reports TRUE if the input contains no characters other than spaces (therefore, no words when the string is considered as a sentence), otherwise FALSE.pt:a frase _ está vazia
de:füge Wörter zusammen _
ca:uneix les paraules _
es:unir las palabras _
fr:fusionne les mots _
pt:uma frase com as palavras _
121de:Liste $arrowRight Satz _
ca:llista $arrowRight frase _
es:lista $arrowRight frase _
fr:liste $arrowRight phrase _
pt:uma frase com as palavras em _
de:Satz $arrowRight Liste _
ca:frase $arrowRight llista _
es:frase $arrowRight lista _
fr:phrase $arrowRight liste _
pt:uma lista com as palavras da frase _
report a list in which each item is one letter from the input wordde:Wort $arrowRight Liste _
ca:paraula $arrowRight llista _
es:palabra $arrowRight lista _
fr:mot $arrowRight liste _
pt:uma lista com os caracteres da palavra _
join all the items of the input list
into a single word, and report itde:Liste $arrowRight Wort _
ca:llista $arrowRight paraula _
es:lista $arrowRight palabra _
fr:liste $arrowRight mot _
pt:uma palavra com os caracteres em _
de:Kostüm aus Text _ Größe _
pt:um traje com o texto _ de tamanho _
A72de:fange _ _
ca:agafa _ _
es:atrapar _ _
fr:attrape _ _
pt:captura _ _
contde:wirf _ _
ca:llança _ _
es:lanzar _ _
fr:lance _ _
pt:lança _ _
catchtagde: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
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 _ _
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 _ _
Returns the function f(g(x)) where f and g are the two inputs.pt:a composição de _ com _
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
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
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
pt:para _ de _ com passo _ a _ _ $loop-0.7
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 _
new valuept:se _ , então _ _
testpt:captura _ _
contpt:lança _
catchtagpt:senão, se _ , então _
pt:senão, _
de:animiere Setter _ Getter _ Delta _ über _ Sek. beschleunigt _
ca:modifica setter _ i getter _ amb delta _ en _ segons de forma _
pt:anima com modificador _ e inspector _ de _ em _ s de forma _
501de:Grad _
ca:graus de _ radians
pt:_ radianos em graus
0.5de:Fehler _
pt:assinala o erro _
de:gleite _ in _ Sek. beschleunigt: _
ca:llisca _ en _ segons de forma _
fr:glisser _ en _ sec. accélérer _
pt:desliza _ em _ s de forma _
501linearlinear
quadratic={
quadratic-in
quadratic-out
quadratic-in-out
}
cubic={
cubic-in
cubic-out
cubic-in-out
}
quart={
quart-in
quart-out
quart-in-out
}
sinusoidal={
sine-in
sine-out
sine-in-out
}
elasticde:animiere _ um _ in _ Sek. beschleunigt: _
ca:modifica _ amb _ en _ segons de forma _
pt:anima _ de _ em _ s de forma _
x positionx position
y position
direction
size
ghost effect
color effect
saturation effect
brightness effect
fisheye effect
whirl effect
pixelate effect
mosaic effect
negative effect
tempo
volume
balance501linearlinear
quadratic={
quadratic-in
quadratic-out
quadratic-in-out
}
cubic={
cubic-in
cubic-out
cubic-in-out
}
quart={
quart-in
quart-out
quart-in-out
}
sinusoidal={
sine-in
sine-out
sine-in-out
}
elasticy positiondirectionsizetempovolumebalance112de:Beschleunigung _
ca:de forma _
pt:a forma _
linearlinear
quadratic={
quadratic-in
quadratic-out
quadratic-in-out
}
cubic={
cubic-in
cubic-out
cubic-in-out
}
quart={
quart-in
quart-out
quart-in-out
}
sinusoidal={
sine-in
sine-out
sine-in-out
}
elasticquadratic-inquadratic-outquadratic-in-outcubic-incubic-outcubic-in-outquart-inquart-outquart-in-outsine-insine-outsine-in-outelasticunknown easing function ""de:für _ = _ bis _ _ in _ Sek. beschleunigt: _ _
ca:per _ = _ fins _ _ en _ segons de forma _ _
pt:para _ de _ a _ _ em _ s de forma _ _
01001linearlinear
quadratic={
quadratic-in
quadratic-out
quadratic-in-out
}
cubic={
cubic-in
cubic-out
cubic-in-out
}
quart={
quart-in
quart-out
quart-in-out
}
sinusoidal={
sine-in
sine-out
sine-in-out
}
elastic0002102501000210239truetrue60