atomate.utils package

Submodules

atomate.utils.database module

atomate.utils.fileio module

class atomate.utils.fileio.FileClient(filesystem=None, private_key='~/.ssh/id_rsa')

Bases: object

A client for performing many file operations while being agnostic of whether those operations are happening locally or via SSH

__init__(filesystem=None, private_key='~/.ssh/id_rsa')
Args:
filesystem (str): remote filesystem, e.g. username@remote_host.

If None, use local

private_key (str): path to the private key file (for remote

connections only). Note: passwordless ssh login must be setup

abspath(path)

return the absolute path

Args:

path (str): path to get absolute string of

copy(src, dest)

Copy from source to destination.

Args:

src (str): source full path dest (str): destination file full path

static exists(sftp, path)

os.path.exists() for paramiko’s SCP object

Args:

sftp (SFTPClient): path (str): path to check existence of

static get_ssh_connection(username, host, private_key)

Connect to the remote host via paramiko using the private key. If the host key is not present it will be added automatically.

Args:

username (str): host (str):

private_key (str): path to private key file

Returns:

SSHClient

glob(path)

return the glob

Args:

path (str): path to glob

listdir(ldir)

Get the directory listing from either the local or remote filesystem.

Args:

ldir (str): full path to the directory

Returns:

iterator of filenames

atomate.utils.testing module

class atomate.utils.testing.AtomateTest(methodName='runTest')

Bases: unittest.case.TestCase

get_task_collection(coll_name=None)

Returns pymongo collection

get_task_database()

Returns pymongo db connection.

setUp(lpad=True)

Create scratch directory(removes the old one if there is one) and change to it. Also initialize launchpad.

tearDown()

Remove the scratch directory and teardown the test db.

atomate.utils.utils module

atomate.utils.utils.env_chk(val, fw_spec, strict=True, default=None)

env_chk() is a way to set different values for a property depending on the worker machine. For example, you might have slightly different executable names or scratch directories on different machines.

env_chk() works using the principles of the FWorker env in FireWorks.

This helper method translates string “val” that looks like this: “>>ENV_KEY<<” to the contents of: fw_spec[“_fw_env”][ENV_KEY]

Otherwise, the string “val” is interpreted literally and passed-through as is.

The fw_spec[“_fw_env”] is in turn set by the FWorker. For more details, see: https://materialsproject.github.io/fireworks/worker_tutorial.html

Since the fw_env can be set differently for each FireWorker, one can use this method to translate a single “val” into multiple possibilities, thus achieving different behavior on different machines.

Args:

val: any value, with “>><<” notation reserved for special env lookup values fw_spec: (dict) fw_spec where one can find the _fw_env keys strict (bool): if True, errors if env format (>><<) specified but cannot be found in fw_spec default: if val is None or env cannot be found in non-strict mode,

return default

atomate.utils.utils.get_a_unique_id()
atomate.utils.utils.get_database(config_file=None, settings=None, admin=False, **kwargs)
atomate.utils.utils.get_fws_and_tasks(workflow, fw_name_constraint=None, task_name_constraint=None)

Helper method: given a workflow, returns back the fw_ids and task_ids that match name constraints. Used in developing multiple powerups.

Args:

workflow (Workflow): Workflow fw_name_constraint (str): a constraint on the FW name task_name_constraint (str): a constraint on the task name

Returns:

a list of tuples of the form (fw_id, task_id) of the RunVasp-type tasks

atomate.utils.utils.get_logger(name, level=10, log_format='%(asctime)s %(levelname)s %(name)s %(message)s', stream=<_io.TextIOWrapper name='<stdout>' mode='w' encoding='UTF-8'>)
atomate.utils.utils.get_meta_from_structure(structure)
atomate.utils.utils.get_mongolike(d, key)

Retrieve a dict value using dot-notation like “a.b.c” from dict {“a”:{“b”:{“c”: 3}}} Args:

d (dict): the dictionary to search key (str): the key we want to retrieve with dot notation, e.g., “a.b.c”

Returns:

value from desired dict (whatever is stored at the desired key)

atomate.utils.utils.get_uri(dir_name)

Returns the URI path for a directory. This allows files hosted on different file servers to have distinct locations. Args:

dir_name:

A directory name.

Returns:

Full URI path, e.g., fileserver.host.com:/full/path/of/dir_name.

atomate.utils.utils.get_wf_from_spec_dict(structure, wfspec, common_param_updates=None)

Load a WF from a structure and a spec dict. This allows simple custom workflows to be constructed quickly via a YAML file.

Args:

structure (Structure): An input structure object. wfspec (dict): A dict specifying workflow. A sample of the dict in

YAML format for the usual MP workflow is given as follows:

``` fireworks: - fw: atomate.vasp.fireworks.core.OptimizeFW - fw: atomate.vasp.fireworks.core.StaticFW

params:

parents: 0

  • fw: atomate.vasp.fireworks.core.NonSCFUniformFW params:

    parents: 1

  • fw: atomate.vasp.fireworks.core.NonSCFLineFW params:

    parents: 1

common_params:

db_file: db.json $vasp_cmd: $HOME/opt/vasp

name: bandstructure metadata:

tag: testing_workflow

```

The fireworks key is a list of Fireworks; it is expected that all such Fireworks have “structure” as the first argument and other optional arguments following that. Each Firework is specified via “fw”: <explicit path>.

You can pass arguments into the constructor using the special keyword params, which is a dict. Any param starting with a $ will be expanded using environment variables.If multiple fireworks share the same params, you can use common_params to specify a common set of arguments that are passed to all fireworks. Local params take precedent over global params.

Another special keyword is parents, which provides the indices of the parents of that particular Firework in the list. This allows you to link the Fireworks into a logical workflow.

Finally, name is used to set the Workflow name (structure formula + name) which can be helpful in record keeping.

common_param_updates (dict): A dict specifying any user-specified updates to common_params

Returns:

Workflow

atomate.utils.utils.load_class(modulepath, classname)

Load and return the class from the given module.

Args:

modulepath (str): dotted path to the module. eg: “pymatgen.io.vasp.sets” classname (str): name of the class to be loaded.

Returns:

class

atomate.utils.utils.recursive_get_result(d, result)

Function that gets designated keys or values of d (i. e. those that start with “d>>” or “a>>”) from the corresponding entry in result_dict, similar to FireWorks recursive_deserialize.

Note that the plain “>>” notation will get a key from the result.as_dict() object and may use MongoDB dot notation, while “a>>” will get an attribute of the object.

Examples:

Getting a dict key from a VaspRun instance:

recursive_get_result({“stress”:”>>output.ionic_steps.-1.stress”}, vasprun) –> {“stress”:[[0.2, 0, 0], [0, 0.3, 0], [0, 0, 0.3]]}

Getting an attribute from a vasprun:

recursive_get_result({“epsilon”:”a>>epsilon_static”, vasprun} –> {“epsilon”:-3.4}

atomate.utils.utils.recursive_update(d, u)

Recursive updates d with values from u Args:

d (dict): dict to update u (dict): updates to propagate

Module contents