Implements a data structure similar to hashes in Perl and dictionaries in Python but with a purposefully R flavor. For objects of appreciable size, access using hashes outperforms native named lists and vectors.
Version: | 2.2.6.1 |
Depends: | R (≥ 2.12.0), methods, utils |
Suggests: | testthat |
Published: | 2019-03-04 |
Author: | Christopher Brown |
Maintainer: | Christopher Brown <chris.brown at decisionpatterns.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] (see file LICENSE) |
NeedsCompilation: | no |
Materials: | README NEWS |
CRAN checks: | hash results |
Reference manual: | hash.pdf |
Package source: | hash_2.2.6.1.tar.gz |
Windows binaries: | r-devel: hash_2.2.6.1.zip, r-release: hash_2.2.6.1.zip, r-oldrel: hash_2.2.6.1.zip |
macOS binaries: | r-release: hash_2.2.6.1.tgz, r-oldrel: hash_2.2.6.1.tgz |
Old sources: | hash archive |
Reverse depends: | BOG, CellNOptR, GABi, GeneGA, neuroim, orderbook, rpartitions |
Reverse imports: | CITAN, coMET, CRISPRseek, crisprseekplus, dataone, datapack, epos, GUIDEseq, GWASinspector, Maaslin2, medicalrisk, nanotatoR, rankdist, ReinforcementLearning, rFSA, rgsepd, ribor, RITAN, sBIC, scfind, scPipe, scsR, sklarsomega, STRINGdb, tictactoe, TSDT |
Reverse suggests: | hadron |
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