def read(nml_path, row_major=None, strict_logical=None):
"""Parse a Fortran 90 namelist file ``nml_file`` or file path ``nml_path``
and return its contents as a ``Namelist``.
File object usage:
>>> with open(nml_path) as nml_file:
>>> nml = f90nml.read(nml_file)
File path usage:
>>> nml = f90nml.read(nml_path)
This function is equivalent to the ``read`` function of the ``Parser``
object.
>>> parser = f90nml.Parser()
>>> nml = parser.read(nml_file)
Multidimensional array data contiguity is preserved by default, so that
column-major Fortran data is represented as row-major Python list of
lists.
The ``row_major`` flag will reorder the data to preserve the index rules
between Fortran to Python, but the data will be converted to row-major form
(with respect to Fortran).
The ``strict_logical`` flag will limit the parsing of non-delimited logical
strings as logical values. The default value is ``True``.
When ``strict_logical`` is enabled, only ``.true.``, ``.t.``, ``true``, and
``t`` are interpreted as ``True``, and only ``.false.``, ``.f.``,
``false``, and ``.false.`` are interpreted as false.
When ``strict_logical`` is disabled, any value starting with ``.t`` or
``t`` are interpreted as ``True``, while any string starting with ``.f`` or
``f`` is interpreted as ``False``."""
parser = Parser()
parser.row_major = row_major
parser.strict_logical = strict_logical
return parser.read(nml_path)
def read(nml_path, row_major=None, strict_logical=None):
"""Parse a Fortran 90 namelist file ``nml_file`` or file path ``nml_path``
and return its contents as a ``Namelist``.
File object usage:
>>> with open(nml_path) as nml_file:
>>> nml = f90nml.read(nml_file)
File path usage:
>>> nml = f90nml.read(nml_path)
This function is equivalent to the ``read`` function of the ``Parser``
object.
>>> parser = f90nml.Parser()
>>> nml = parser.read(nml_file)
Multidimensional array data contiguity is preserved by default, so that
column-major Fortran data is represented as row-major Python list of
lists.
The ``row_major`` flag will reorder the data to preserve the index rules
between Fortran to Python, but the data will be converted to row-major form
(with respect to Fortran).
The ``strict_logical`` flag will limit the parsing of non-delimited logical
strings as logical values. The default value is ``True``.
When ``strict_logical`` is enabled, only ``.true.``, ``.t.``, ``true``, and
``t`` are interpreted as ``True``, and only ``.false.``, ``.f.``,
``false``, and ``.false.`` are interpreted as false.
When ``strict_logical`` is disabled, any value starting with ``.t`` or
``t`` are interpreted as ``True``, while any string starting with ``.f`` or
``f`` is interpreted as ``False``."""
parser = Parser()
parser.row_major = row_major
parser.strict_logical = strict_logical
return parser.read(nml_path)
def patch(nml_path, nml_patch, out_path=None, row_major=None,
strict_logical=None):
"""Create a new namelist based on an input namelist and reference dict.
>>> f90nml.patch('data.nml', nml_patch, 'patched_data.nml')
This function is equivalent to the ``read`` function of the ``Parser``
object with the patch output arguments.
>>> parser = f90nml.Parser()
>>> nml = parser.read('data.nml', nml_patch, 'patched_data.nml')
A patched namelist file will retain any formatting or comments from the
original namelist file. Any modified values will be formatted based on the
settings of the ``Namelist`` object.
"""
parser = Parser()
parser.row_major = row_major
parser.strict_logical = strict_logical
return parser.read(nml_path, nml_patch, out_path)