aiida-shell 0.4.0

AiiDA plugin that makes running shell commands easy.

aiida-shell

AiiDA plugin that makes running shell commands easy. Run any shell executable without writing a dedicated plugin or parser.

Installation

The recommended method of installation is through pip:

pip install aiida-shell

Requirements

To use aiida-shell a configured AiiDA profile is required. Please refer to the documentation of aiida-core for detailed instructions.

Examples

Running a shell command

The most simple example is to run a shell command without any arguments:

from aiida_shell import launch_shell_job
results, node = launch_shell_job('date')
print(results['stdout'].get_content())

Which should print something like Thu 17 Mar 2022 10:49:52 PM CET.

Running a shell command with arguments

To pass arguments to the shell command, pass them as a list to the arguments keyword:

from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'date',
    arguments=['--iso-8601']
)
print(results['stdout'].get_content())

which should print something like 2022-03-17.

Running a shell command with files as arguments

For commands that take arguments that refer to files, pass those files using the nodes keyword. The keyword takes a dictionary of SinglefileData nodes. To specify where on the command line the files should be passed, use placeholder strings in the arguments keyword.

from io import StringIO
from aiida.orm import SinglefileData
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'cat',
    arguments=['{file_a}', '{file_b}'],
    nodes={
        'file_a': SinglefileData(StringIO('string a')),
        'file_b': SinglefileData(StringIO('string b')),
    }
)
print(results['stdout'].get_content())

which prints string astring b.

Running a shell command with files as arguments with specific filenames

The keys in the nodes dictionary can only use alphanumeric characters and underscores. The keys will be used as the link label of the file in the provenance graph, and as the filename in the temporary directory in which the shell command will be executed. Certain commands may require specific filenames, for example including a file extension, e.g., filename.txt, but this cannot be used in the nodes arguments. To specify explicit filenames that should be used in the running directory, make sure that the filename of the SinglefileData node is defined. If the SinglefileData.filename was explicitly set when creating the node, that is the filename used to write the input file to the working directory:

from io import StringIO
from aiida.orm import SinglefileData
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'cat',
    arguments=['{file_a}'],
    nodes={
        'file_a': SinglefileData(StringIO('string a'), filename='filename.txt'),
    }
)
print(results['stdout'].get_content())

which prints string a.

If the filename of the SinglefileData cannot be controlled, alternatively explicit filenames can be defined using the filenames argument:

from io import StringIO
from aiida.orm import SinglefileData
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'cat',
    arguments=['{file_a}'],
    nodes={
        'file_a': SinglefileData(StringIO('string a')),
    },
    filenames={
        'file_a': 'filename.txt'
    }
)
print(results['stdout'].get_content())

which prints string a. Filenames specified in the filenames input will override the filename of the SinglefileData nodes. Any parent directories in the filepath, for example some/nested/path in the filename some/nested/path/file.txt, will be automatically created.

The output filename can be anything except for stdout, stderr and status, which are reserved filenames.

Passing other Data types as input

The nodes keyword does not only accept SinglefileData nodes, but it accepts also other Data types. For these node types, the content returned by the value property is directly cast to str, which is used to replace the corresponding placeholder in the arguments. So as long as the Data type implements this value property it should be supported. Of course, whether it makes sense for the value of the node to be used directly as a command line argument for the shell job, is up to the user. Typical useful examples, are the base types that ship with AiiDA, such as the Float, Int and Str types:

from aiida.orm import Float, Int, Str
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'echo',
    arguments=['{float}', '{int}', '{string}'],
    nodes={
        'float': Float(1.0),
        'int': Int(2),
        'string': Str('string'),
    },
)
print(results['stdout'].get_content())

which prints 1.0 2 string. This example is of course contrived, but when combining it with other components of AiiDA, which typically return outputs of these form, they can be used directly as inputs for launch_shell_job without having to convert the values. This ensures that provenance is kept.

Redirecting input file through stdin

Certain shell commands require input to be passed through the stdin file descriptor. This is normally accomplished as follows:

cat < input.txt

To reproduce this behaviour, the file that should be redirected through stdin can be defined using the metadata.option.filename_stdin input:

from io import StringIO
from aiida.orm import SinglefileData
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'cat',
    nodes={
        'input': SinglefileData(StringIO('string a'))
    },
    metadata={'options': {'filename_stdin': 'input'}}
)
print(results['stdout'].get_content())

which prints string a.

N.B.: one might be tempted to simply define the arguments as ['<', '{input}'], but this won't work as the < symbol will be quoted and will be read as a literal command line argument, not as the redirection symbol. This is why passing the < in the arguments input will result in a validation error.

Defining outputs

When the shell command is executed, AiiDA captures by default the content written to the stdout and stderr file descriptors. The content is wrapped in a SinglefileData node and attached to the ShellJob with the stdout and stderr link labels, respectively. Any other output files that need to be captured can be defined using the outputs keyword argument.

from io import StringIO
from aiida.orm import SinglefileData
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'sort',
    arguments=['{input}', '--output', 'sorted'],
    nodes={
        'input': SinglefileData(StringIO('2\n5\n3')),
    },
    outputs=['sorted']
)
print(results['sorted'].get_content())

which prints 2\n3\n5.

Defining output files with globbing

When the exact output files that will be generated and need to be captured are not known in advance, one can use globbing. Take for example the split command, which split a file into multiple files of a certain number of lines. By default, each output file will follow the sequence xa, xb, xc etc. augmenting the last character alphabetically. These output files can be captured by specifying the outputs as ['x*']:

from io import StringIO
from aiida.orm import SinglefileData
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'split',
    arguments=['-l', '1', '{single_file}'],
    nodes={
        'single_file': SinglefileData(StringIO('line 0\nline 1\nline 2\n')),
    },
    outputs=['x*']
)
print(results.keys())

which prints dict_keys(['xab', 'xaa', 'xac', 'stderr', 'stdout']).

Defining output folders

When the command produces a folder with multiple output files, it is also possible to parse this as a single output node, instead of individual outputs for each file. If a filepath specified in the outputs corresponds to a directory, it is attached as a FolderData that contains all its contents, instead of individual SinglefileData nodes. For example, imagine a compressed tarball /some/path/archive.tar.gz that contains the folder sub_folder with a number of files in it. The following example uncompresses the tarball and captures the uncompressed files in the sub_folder directory in the sub_folder output node:

from io import StringIO
from aiida.orm import SinglefileData
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'tar',
    arguments=['-zxvf', '{archive}'],
    nodes={
        'archive': SinglefileData('/some/path/archive.tar.gz'),
    },
    outputs=['sub_folder']
)
print(results.keys())

which prints dict_keys(['sub_folder', 'stderr', 'stdout']). The contents of the folder can be retrieved from the node as follows:

for filename in results['sub_folder'].list_object_names():
    content = results['sub_folder'].get_object_content(filename)
    # or, if a file-like object is preferred to stream the content
    with results['sub_folder'].open(filename) as handle:
        content = handle.read()

Defining a specific computer

By default the shell command ran by launch_shell_job will be executed on the localhost, i.e., the computer where AiiDA is running. However, AiiDA also supports running commands on remote computers. See the documentation of aiida-core for instructions to setting up and configuring a remote computer. To specify what computer to use for a shell command, pass it as an option to the metadata keyword:

from aiida.orm import load_computer
from aiida_shell import launch_shell_job
results, node = launch_shell_job(
    'date',
    metadata={'options': {'computer': load_computer('some-computer')}}
)
print(results['stdout'].get_content())

Here you can use aiida.orm.load_computer to load the Computer instance from its label, PK or UUID.

Running many shell jobs in parallel

By default the shell command ran by launch_shell_job is run blockingly; meaning that the Python interpreter is blocked from doing anything else until the shell command finishes. This becomes inefficient if you need to run many shell commands. If the shell commands are independent and can be run in parallel, it is possible to submit the jobs to AiiDA's daemon by setting submit=True:

from aiida.engine.daemon.client import get_daemon_client
from aiida_shell import launch_shell_job

# Make sure the daemon is running
get_daemon_client().start_daemon()

nodes = []

for string in ['string_one', 'string_two']:
    node = launch_shell_job(
        'echo',
        arguments=[string],
        submit=True,
    )
    nodes.append(node)
    print(f'Submitted {node}')

Instead of returning a tuple of the results and the node, launch_shell_job now only returns the node. The reason is because the function returns immediately after submitting the job to the daemon at which point it isn't necessarily finished yet. To check on the status of the submitted jobs, you can use the verdi process list command of the CLI that ships with AiiDA. Or you can do it programmatically:

import time

while True:
    if all(node.is_terminated for node in nodes):
        break
    time.sleep(1)

for node in nodes:
    if node.is_finished_ok:
        print(f'{node} finished successfully')
    else:
        print(f'{node} failed')

Custom parsing

By default, all outputs will be parsed into SinglefileData nodes. While convenient not having to define a parser manually, it can also be quite restrictive. One of AiiDA's strong points is that it can store data in JSON form in a relational database, making it queryable, but the content of SinglefileData nodes is excluded from this functionality.

The parser keyword allows to define a "custom" parser, which is a function with the following signature:

def parser(self, dirpath: pathlib.Path) -> dict[str, Data]:
    """Parse any output file generated by the shell command and return it as any `Data` node."""

The following example shows how a custom parser can be implemented:

from aiida_shell import launch_shell_job

def parser(self, dirpath):
    from aiida.orm import Str
    return {'string': Str((dirpath / 'stdout').read_text().strip())}

results, node = launch_shell_job(
    'echo',
    arguments=['some output'],
    parser=parser
)
print(results['string'].value)

which prints some output.

Important: if the output file that is parsed by the custom parser is not any of the files that are retrieved by default, i.e., stdout, stderr, status and the filenames specified in the outputs input, it has to be specified in the metadata.options.additional_retrieve input:

from io import StringIO
from json import dumps
from aiida_shell import launch_shell_job
from aiida.orm import SinglefileData

def parser(self, dirpath):
    """Parse the content of the ``results.json`` file and return as a ``Dict`` node."""
    import json
    from aiida.orm import Dict
    return {'json': Dict(json.load((dirpath / 'results.json').open()))}

results, node = launch_shell_job(
    'cat',
    arguments=['{json}'],
    nodes={'json': SinglefileData(StringIO(dumps({'a': 1})))},
    parser=parser,
    metadata={
        'options': {
            'output_filename': 'results.json',
            'additional_retrieve': ['results.json']
        }
    }
)
print(results['json'].get_dict())

which prints {'a': 1}.