Groovy, 153 + 10.697 = 10.850 253 + 9870 = 10.123 byte
Ho deciso che volevo una soluzione che coinvolgesse solo un file, quindi (all'ovvio costo dello spazio) ho codificato una versione CSV GZIP dei dati in caratteri Unicode 0x0020-0x007E (che immagino sarebbe una codifica 95 di base?). Il codice è di 253 caratteri, il contenuto della stringa è di 10123 caratteri.
import java.util.zip.*
t=0
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b=[]
while(t){b<<(byte)(t%256-128)
t=t.intdiv(256)}
println new GZIPInputStream(new ByteArrayInputStream((byte[])b)).readLines().collectEntries{(List)it.split(',')}[args[0]]
Per leggibilità, ecco la stessa cosa con il testo codificato escluso:
import java.util.zip.*
t=0
'''^/3...'%!'''.eachWithIndex{c,i->t+=95g**i*(((byte)c)-32g)}
b=[]
while(t){b<<(byte)(t%256-128)
t=t.intdiv(256)}
println new GZIPInputStream(new ByteArrayInputStream((byte[])b)).readLines().collectEntries{(List)it.split(',')}[args[0]]
La mia soluzione originale era una codifica Base 64 più semplice utilizzando l'encoder incorporato
import java.util.zip.*
print new GZIPInputStream(new ByteArrayInputStream(Base64.decoder.decode('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'))).readLines().collectEntries{(List)it.split(',')}[args[0]]
Per leggibilità, ecco la stessa cosa con il testo escluso:
new GZIPInputStream(new ByteArrayInputStream(Base64.decoder.decode(''))).readLines().collectEntries{(List)it.split(',')}[args[0]]