See also

@files_re

@files_re (tasks_or_file_names, matching_regex, [input_pattern], output_pattern, [extra_parameters,...])

Legacy design now deprecated. We suggest using @transform() instead

Purpose:

All singing, all dancing decorator which can do everything that @merge() and @transform() can do.

Applies the task function to transform data from input to output files.

Output file names are determined from tasks_or_file_names, i.e. from the output of specified tasks, or a list of file names, using regular expression pattern substitutions.

Only out of date tasks (comparing input and output files) will be run.

Example:
from ruffus import *
#
#   convert all files ending in ".1" into files ending in ".2"
#
@files_re('*.1', '(.*).1', r'\1.2')
def transform_func(infile, outfile):
    open(outfile, "w").write(open(infile).read() + "\nconverted\n")

pipeline_run([task_re])
If the following files are present a.1, b.1, c.1, this will result in the following function calls:
transform_func("a.1", "a.2")
transform_func("b.1", "b.2")
transform_func("c.1", "c.2")

Parameters:

  • tasks_or_file_names

    can be a:

    1. Task / list of tasks (as in the example above).

      File names are taken from the output of the specified task(s)

    2. (Nested) list of file name strings.
      File names containing *[]? will be expanded as a glob .

      E.g.:"a.*" => "a.1", "a.2"

  • matching_regex

    a python regular expression string.

    See python regular expression (re) documentation for details of regular expression syntax
    Each output file name is created using regular expression substitution with output_pattern
  • input_pattern

    Optionally specifies the resulting input file name(s).

  • output_pattern

    Specifies the resulting output file name(s).

  • [extra_parameters, ...]

    Any extra parameters are passed to the task function.

    Regular expression substitution is first applied to (even nested) string parameters.
    Other data types are passed verbatim.
    For example:
    from ruffus import *
#
#   convert all files ending in ".1" into files ending in ".2"
#
@files_re('*.1', '(.*).1', r'\1.2', [r'\1', 55], 17)
def transform_func(infile, outfile, extras, extra3):
    extra1, extra2 = extras
    open(outfile, "w").write(open(infile).read() + "\nconverted%s\n" % (extra1, extra2, extra3))

pipeline_run([transform_func])
    If the following files are present a.1, b.1, c.1, this will result in the following function calls:
    transform_func("a.1", "a.2", ["a", 55], 17)
transform_func("b.1", "b.2", ["b", 55], 17)
transform_func("c.1", "c.2", ["c", 55], 17)