add version 4.0.4 to r-ff (#20942)

var/spack/repos/builtin/packages/r-ff/package.py

@@ -7,17 +7,60 @@
 
 
 class RFf(RPackage):
-    """memory-efficient storage of large data on disk and
+    """Memory-Efficient Storage of Large Data on Disk and Fast Access Functions
-    fast access functions."""
+
+    The ff package provides data structures that are stored on disk but behave
+    (almost) as if they were in RAM by transparently  mapping only a section
+    (pagesize) in main memory - the effective  virtual memory consumption per
+    ff object. ff supports R's standard  atomic data types 'double', 'logical',
+    'raw' and 'integer' and  non-standard atomic types boolean (1 bit), quad (2
+    bit unsigned),  nibble (4 bit unsigned), byte (1 byte signed with NAs),
+    ubyte (1 byte  unsigned), short (2 byte signed with NAs), ushort (2 byte
+    unsigned),  single (4 byte float with NAs). For example 'quad' allows
+    efficient  storage of genomic data as an 'A','T','G','C' factor. The
+    unsigned  types support 'circular' arithmetic. There is also support for
+    close-to-atomic types 'factor', 'ordered', 'POSIXct', 'Date' and  custom
+    close-to-atomic types.  ff not only has native C-support for vectors,
+    matrices and arrays  with flexible dimorder (major column-order, major
+    row-order and  generalizations for arrays). There is also a ffdf class not
+    unlike  data.frames and import/export filters for csv files. ff objects
+    store raw data in binary flat files in native encoding, and complement this
+    with metadata stored in R as physical and virtual attributes. ff objects
+    have well-defined hybrid copying semantics,  which gives rise to certain
+    performance improvements through  virtualization. ff objects can be stored
+    and reopened across R  sessions. ff files can be shared by multiple ff R
+    objects  (using different data en/de-coding schemes) in the same process
+    or from multiple R processes to exploit parallelism. A wide choice of
+    finalizer options allows to work with 'permanent' files as well as
+    creating/removing 'temporary' ff files completely transparent to the  user.
+    On certain OS/Filesystem combinations, creating the ff files works without
+    notable delay thanks to using sparse file allocation. Several access
+    optimization techniques such as Hybrid Index  Preprocessing and
+    Virtualization are implemented to achieve good  performance even with large
+    datasets, for example virtual matrix  transpose without touching a single
+    byte on disk. Further, to reduce  disk I/O, 'logicals' and non-standard
+    data types get stored native and  compact on binary flat files i.e.
+    logicals take up exactly 2 bits to  represent TRUE, FALSE and NA.  Beyond
+    basic access functions, the ff package also provides  compatibility
+    functions that facilitate writing code for ff and ram  objects and support
+    for batch processing on ff objects (e.g. as.ram,  as.ff, ffapply). ff
+    interfaces closely with functionality from package  'bit': chunked looping,
+    fast bit operations and coercions between  different objects that can store
+    subscript information ('bit',  'bitwhich', ff 'boolean', ri range index, hi
+    hybrid index). This allows to work interactively with selections of large
+    datasets and quickly  modify selection criteria.  Further high-performance
+    enhancements can be made available upon request.x """
 
     homepage = "http://ff.r-forge.r-project.org/"
     url      = "https://cloud.r-project.org/src/contrib/ff_2.2-13.tar.gz"
     list_url = "https://cloud.r-project.org/src/contrib/Archive/ff"
 
+    version('4.0.4', sha256='22ecf1811263f27c9fd9f7e13e77f97dcbc0b8ae6f59b76dbaed77569c13d2e5')
     version('2.2-14', sha256='1c6307847275b1b8ad9e2ffdce3f4df3c9d955dc2e8a45e3fd7bfd2b0926e2f0')
     version('2.2-13', sha256='8bfb08afe0651ef3c23aaad49208146d5f929af5af12a25262fe7743fa346ddb')
 
     depends_on('r@2.10.1:', type=('build', 'run'))
     depends_on('r-bit@1.1-13:', type=('build', 'run'))
+    depends_on('r-bit@4.0.0:', when='@4.0.4:', type=('build', 'run'))
 
     patch('utk_platform_macros.hpp.patch', when='target=aarch64:')