Source code for gmxapi.commandline

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Provide command line operation.

__all__ = ['commandline_operation']

import shutil
import subprocess

import gmxapi as gmx
from gmxapi import exceptions
from gmxapi import logger as root_logger
from gmxapi.datamodel import NDArray
from gmxapi.operation import OutputCollectionDescription

# Module-level logger
logger = root_logger.getChild('commandline')'Importing {}'.format(__name__))

# Create an Operation that consumes a list and a boolean to produce a string and an integer.
# Wrap the defined function using a decorator that
#    * strips the `output` parameter from the signature
#    * provides `output` publishing proxy to the inner function and
#    * produce a result with attributes for
#       * file: mapping of output flags to output filenames
#       * erroroutput: text results in case of error
#       * returncode: integer return code of wrapped command
# Note that the existence of the 'file' output map is expressed here, but
# the keys of the map are not implicit or set by the wrapped function.
# For the map to be non-empty, it must be defined before the resulting helper
# function is called.
# TODO: Operation returns the output object when called with the shorter signature.
@gmx.function_wrapper(output={'erroroutput': str, 'returncode': int})
def cli(command: NDArray, shell: bool, output: OutputCollectionDescription):
    """Execute a command line program in a subprocess.

    Configure an executable in a subprocess. Executes when run in an execution
    Context, as part of a work graph or via Runs in the current
    working directory.

    Shell processing is not enabled, but can be considered for a future version.
    This means that shell expansions such as environment variables, globbing (`*`),
    and other special symbols (like `~` for home directory) are not available.
    This allows a simpler and more robust implementation, as well as a better
    ability to uniquely identify the effects of a command line operation. If you
    think this disallows important use cases, please let us know.

         command : a tuple (or list) to be the subprocess arguments, including `executable`
         output : mapping of command line flags to output filename arguments
         shell : unused (provides forward-compatibility)

    Arguments are iteratively added to the command line with standard Python
    iteration, so you should use a tuple or list even if you have only one parameter.
    I.e. If you provide a string with `arguments="asdf"` then it will be passed as
    `... "a" "s" "d" "f"`. To pass a single string argument, `arguments=("asdf")`
    or `arguments=["asdf"]`.

    `input` and `output` should be a dictionary with string keys, where the keys
    name command line "flags" or options.

        Execute a command named `exe` that takes a flagged option for file name
        (stored in a local Python variable `my_filename`) and an `origin` flag
        that uses the next three arguments to define a vector.

            >>> my_filename = "somefilename"
            >>> result = cli(('exe', '--origin', 1.0, 2.0, 3.0, '-f', my_filename), shell=False)
            >>> assert hasattr(result, 'file')
            >>> assert hasattr(result, 'erroroutput')
            >>> assert hasattr(result, 'returncode')

        A data structure with attributes for each of the results `file`, `erroroutput`, and `returncode`

    Result object attributes:
        * `file`: the mapping of CLI flags to filename strings resulting from the `output` kwarg
        * `erroroutput`: A string of error output (if any) if the process failed.
        * `returncode`: return code of the subprocess.

    # Note: we could make provisions for stdio filehandles in a future version. E.g.
    # * STDOUT is available if a consuming operation is bound to `output.stdout`.
    # * STDERR is available if a consuming operation is bound to `output.stderr`.
    # * Otherwise, STDOUT and/or STDERR is(are) closed when command is called.
    # Warning:
    #     Commands relying on STDIN cannot be used and is closed when command is called.

    # In the operation implementation, we expect the `shell` parameter to be intercepted by the
    # wrapper and set to False.
    if shell:
        raise exceptions.UsageError("Operation does not support shell processing.")

    if isinstance(command, (str, bytes)):
        command = [command]
    command = list([arg for arg in command])
        command[0] = shutil.which(command[0])
    except Exception:
        raise exceptions.ValueError('command argument could not be resolved to an executable file path.')

    # TODO: (FR9) Can OS input/output filehandles be a responsibility of
    #  the code providing 'resources'?

    erroroutput = ''
    logger.debug('executing subprocess')
        # TODO: If Python >=3.5 is required, switch to
        command_output = subprocess.check_output(command,
        returncode = 0
        # TODO: Resource management code should manage a safe data object for `output`.
        # WARNING: We have no reason to assume the output is utf-8 encoded text!!!
        for line in command_output.decode('utf-8').split('\n'):
    except subprocess.CalledProcessError as e:"commandline operation had non-zero return status when calling {}".format(e.cmd))
        erroroutput = e.output.decode('utf-8')
        returncode = e.returncode
    # resources.output.erroroutput.publish(erroroutput)
    # resources.output.returncode.publish(returncode)
    # `publish` is descriptive, but redundant. Access to the output data handler is
    # assumed to coincide with publishing, and we assume data is published when the
    # handler is released. A class with a single `publish` method is overly complex
    # since we can just use the assignment operator.
    output.erroroutput = erroroutput
    output.returncode = returncode
    # TODO: Handle the file output at the higher level wrapper.
    # output.file = None

# TODO: (FR4) Make this a formal operation to properly handle gmxapi data dependencies.
#  The consumer of this operation has an NDArray input. filemap may contain gmxapi data flow
#  aspects that we want the framework to handle for us.
def filemap_to_flag_list(filemap: dict = None):
    """Convert a map of command line flags and filenames to a list of command line arguments.

    Used to map inputs and outputs of command line tools to and from gmxapi data handles.
    User provides mappings of flags and filenames so that gmxapi can construct an
    executable command line.

    Primary use case is implicit. commandline_operation() instantiates this operation based on
    user input, and sends the output to cli()

        filemap : key-value map of command line flags and filename arguments

        list of strings and/or gmxapi data references
    result = []
    if filemap is not None:
        for key, value in filemap.items():
            # Note that the value may be a string, a list, an ndarray, or a future
            if not isinstance(value, (list, tuple, NDArray)):
                if hasattr(value, 'result') and value.dtype == NDArray:
                elif hasattr(value, 'result') and value.dtype != NDArray:
                    # TODO: Fix this ugly hack when we have proper Future slicing and can make NDArray futures.
                    result_function = value.result
                    value.result = lambda function=result_function: [function()]
                    value = [value]
            result = gmx.join_arrays(front=result, back=gmx.join_arrays(front=[key], back=value))
    return result

# TODO: (FR4) Use generating function or decorator that can validate kwargs?
# TODO: (FR4) Outputs need to be fully formed and typed in the object returned
#  from the helper (decorated function).
[docs]def commandline_operation(executable=None, arguments=(), input_files: dict = None, output_files: dict = None, **kwargs): """Helper function to define a new operation that executes a subprocess in gmxapi data flow. Define a new Operation for a particular executable and input/output parameter set. Generate a chain of operations to process the named key word arguments and handle input/output data dependencies. Arguments: executable : name of an executable on the path arguments : list of positional arguments to insert at ``argv[1]`` input_files : mapping of command-line flags to input file names output_files : mapping of command-line flags to output file names Output: The output node of the resulting operation handle contains * ``file``: the mapping of CLI flags to filename strings resulting from the ``output_files`` kwarg * ``erroroutput``: A string of error output (if any) if the process failed. * ``returncode``: return code of the subprocess. """ # Implementation details: When used in a script, this function returns an # instance of an operation. However, because of the dynamic specification of # inputs and outputs, each invocation may have the overhead of defining new # types to express the data flow topology, regardless of the executable. # If this overhead is problematic, consider exposing the intermediate step # at which the Operation is fully specified to facilitate reuse. ## # 1. Define a new operation with outputs from `cli()` plus `file` from `output_files` # output_files is essentially passed through, but we need assurance that results # will not be published until the rest of the operation has run (i.e. the cli() executable.) # Warning: decorating a local function like this is counter to the notion of Operations # as portable (importable, serializable/deserializable). The big picture here needs # some more consideration. # TODO: (NOW) Distinguish portable Operations from relocatable Futures. # There is nothing antithetical about objects implementing gmxapi data interfaces # that are only resolvable by a certain Context as long as that Context can convey # the results to another Context upon request. Re-instantiating Operations is # only one way of relocating Futures. In this case, though, the dynamic creation of # merged_ops doesn't seem right, and commandline_operation should probably be # a proper Operation. # # TODO: (FR4+) Characterize the `file` dictionary key type: # explicitly sequences rather than maybe-string/maybe-sequence-of-strings @gmx.function_wrapper(output={'erroroutput': str, 'returncode': int, 'file': dict}) def merged_ops(erroroutput: str = None, returncode: int = None, file: dict = None, output: OutputCollectionDescription = None): assert erroroutput is not None assert returncode is not None assert file is not None assert output is not None output.file = file output.returncode = returncode output.erroroutput = erroroutput ## # 2. Prepare data flow. if input_files is None: input_files = {} if output_files is None: output_files = {} if isinstance(arguments, (str, bytes)): arguments = [arguments] command = gmx.concatenate_lists([[executable], arguments, filemap_to_flag_list(input_files), filemap_to_flag_list(output_files)]) shell = gmx.make_constant(False) cli_args = {'command': command, 'shell': shell} cli_args.update(**kwargs) ## # 3. Merge operations # # Note: Without a `label` argument, repeated calls to cli(**cli_args) should # produce references to the same unique resource. Creating this handle # separately should not be necessary, but we've got a way to go until we have the # fingerprinting and Context resource management we need for that. # TODO: ``label`` kwarg # TODO: input fingerprinting cli_result = cli(**cli_args) merged_result = merged_ops(erroroutput=cli_result.output.erroroutput, returncode=cli_result.output.returncode, file=output_files, **kwargs) # Return an object with an OutputCollection granting access to outputs of # cli() and of output_files (as "file") return merged_result