Spam roomsnaps! WHAT'S NEW IN v1.2: • Anti-clear (BETA) UPCOMING FEATURES FOR v1.3 or higher: • Hide username! • Suggestion box! Got suggestions? 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soon...data:image/png;base64,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data:image/png;base64,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

errorclose modalhttps://snap.berkeley.edu/project?user=powerbox1000&project=Roomsnaps%20Spammerpowerbox1000,Roomsnaps%20Spammerhttps://snap.berkeley.edu/project?user=powerbox1000&project=Roomsnaps%20Spammererror

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 _ 501

de:Grad _ ca:graus de _ radians pt:_ radianos em graus 0.5

de: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 _ 501linear linear 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 } elastic

de:animiere _ um _ in _ Sek. beschleunigt: _ ca:modifica _ amb _ en _ segons de forma _ pt:anima _ de _ em _ s de forma _ x position x 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 balance501linear linear 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 positiondirectionsizetempovolumebalance1

de:Beschleunigung _ ca:de forma _ pt:a forma _ linear linear 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-outelastic

unknown easing function ""

de:für _ = _ bis _ _ in _ Sek. beschleunigt: _ _ ca:per _ = _ fins _ _ en _ segons de forma _ _ pt:para _ de _ a _ _ em _ s de forma _ _ 01001linear linear 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 } elastic

pt:a resposta a _ de _ enviando _ e cabeçalhos _ GET GET POST PUT DELETEhttps://snap.berkeley.edu

pt:um par (chave: _ , valor: _ )

Reports a three-item list containing the latitude and longitude of the user, and the precision of the measurements. Works only if the user allows snap.berkeley.edu access to location data. Some browsers also require an HTTPS connection to Snap!.

pt:a localização actual do dispositivo

*empty*

de:sprich _ mit _ Aussprache _ und Höhe _ Geschwindigkeit _ pt:fala _ na língua _ _ com tom _ e velocidade _ Hello, World!en-US العربية=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-TW11

de:sprich _ mit _ Aussprache _ und Höhe _ Geschwindigkeit _ und warte pt:fala _ na língua _ _ com tom _ e velocidade _ , e espera Hello, World!en-US العربية=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-TW11

de:Kostüm aus Text _ Größe _ pt:um traje com o texto _ de tamanho _ A72

Takes 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 resulti2

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 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 resulti1

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 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 11111

pt:a primeira palavra de _

Takes a text string as input, and reports the last character in the string.

pt:o último caractere de _

pt:a última palavra de _ 11

Takes 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 _ 121

de: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 word

de: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 it

de:Liste $arrowRight Wort _ ca:llista $arrowRight paraula _ es:lista $arrowRight palabra _ fr:liste $arrowRight mot _ pt:uma palavra com os caracteres em _

Catch errors. Runs the first script. If it succeeds, nothing else happens. But if it has an error (something that would otherwise result in a red halo around the block), then the second script is run, with the text of the error message that would have been shown in the variable ERROR.

pt:tenta executar _ e, em caso de erro _ , executa _ return

Throw an error. Makes a red halo appear around the script that runs it, with the input text shown in a speech balloon next to the script, just like any Snap! error. This is useful to put in the second script of SAFELY TRY after some other instructions to undo the partial work of the first script.

pt:lança o erro _

LET (FOO) BE (5) is equivalent to SCRIPT VARIABLES (FOO) SET (FOO) TO (5)

pt:cria a variável de guião _ com valor _

Catch errors in a reporter. Evaluates its first input. If that expression successfully reports a value, this block reports that value. If the expression causes a Snap! error, then the final input slot is evaluated with the text of what would have been the error message in variable ERROR. SAFELY TRY then reports the value of that final expression. Sometimes you'll want to throw an error in the final expression. You can put an ERROR block inside a CALL block to do that.

err

pt: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 _

meRO!Rdood,RO!Rdood1,RO!Rdood2,RO!Rdood3,RO!Rdood41Roomsnaps-hubfalse