Job

nimbus_splash.job.parse_input_contents(input_file: str | Path, instance_name: str, skip_xyz: bool = False) → dict[str, Path]

Checks contents of input file and returns file dependencies

Parameters:

• input_file (str | pathlib.Path) – Full path to orca input file

• instance_name (str) – Name of Nimbus instance e.g. spot-fsv2-32

• skip_xyz (bool, default False) – If True, skips checking of xyz file formatting

Returns:

Relative paths of files required by this this input file

Key is identifier (xyz, gbw, hess), Value is file name as Path object

Return type:

dict[str, pathlib.Path]

Raises:

• ValueError – If errors encountered in input file format or xyz file format

• FileNotFound – If xyz, gbw, or hessian file cannot be found

• Warning – If specified per-core memory exceeds instance limit

nimbus_splash.job.write_file(input_file: str | Path, instance_name: str, time: str, dependencies: dict[str, str | Path], orca_version: str, research_allocation_id: str, verbose: bool = False, email: str = '', job_name: str = None) → str

Writes slurm jobscript to file for ORCA calculation on nimbus

Output file name is input_file with .slm extension

Parameters:

• input_file (str | pathlib.Path) – Full path to input file, including extension

• instance_name (str) – Name of Nimbus instance to use e.g. spot-hc-44

• time (str) – Job time limit formatted as HH:MM:SS

• verbose (bool, default=False) – If True, prints job file name to screen

• dependencies (dict[str | pathlib.Path]) – Files required by job - e.g. xyz, gbw, hess

• orca_version (str) – string name of orca version e.g. 5.0.4

• research_allocation_id (str) – Research allocation ID

• email (str, optional) –

  If provided, adds the specified email to the jobscript.

  Users recieve an email for all changes in job status

• job_name (str, optional) – Name of job. If not provided, then job name defaults to stem of input file

Returns:

Name of jobscript file

Return type:

str

Raises:

ValueError – If ORCA version not available on instance