Skip to main content

ORCA high-throughput pipeline orchestrator

Project description

orcastrator

chain orca calculations together to build complex quantum chemistry pipelines.

Usage

from pathlib import Path
import logging

from logger import configure_logging

from orcastrator import Calculation

configure_logging(level=logging.DEBUG)

opt = Calculation(
    name="opt",
    root_dir=Path("test/scratch"),
    level_of_theory="! OPT D4 TPSS def2-SVP",
    charge=0,
    mult=1,
    xyz_string=Path("test/h2.xyz").read_text(),
    overwrite=True,
)
opt_result = opt.run()
print(opt_result.directory)

sp = Calculation(
    name="sp",
    root_dir=opt.root_dir,
    level_of_theory="! D4 TPSSh def2-TZVP",
    charge=opt.charge,
    mult=opt.mult,
    xyz_string=opt_result.geometry,
    overwrite=True,
)
sp.run()

Design

A single executable that runs all calculations itself. This means that the orcastrator run has to be submitted to SLURM by itself.

Calculation objects compose with an instance of a QCEngine class, which implements a run() method takes consumes a Calculation object and return its results (or smth).

What does a Calculation need? I'll focus on pure ORCA calculations, because I don't really use anything else anyway. The QCEngine is still a good idea because e.g. there are different ORCA versions etc. Alternatively, the Calculation is just a directory, containing at least an input file.

How can i represent the directory tree of the calculations? I think the orcastrator should probably consume its own toml input file.

How might that look?

xyz_file = "guess.xyz"
charge = 0
mult = 1

[opt_freq]
input = """
! OPT FREQ
! D4 TPSS def2/TZVP

* XYZFILE $charge $mult $xyz_file
"""

[tddft]
input = """
! D4 TPSSh def2/TZVP

%TDDFT
    NROOTS 16
END

* XYZFILE $charge $mult $opt_freq.xyz_file
"""

hmm.. maybe it's better to create everything programmatically.

opt_freq_template = """
! OPT FREQ ...

* XYZFILE $charge $mult $xyz_file
"""
tddft_template = """
! D4 TPSSh ...

* XYZFILE $charge $mult $xyz_file
"""

settings = dict(
    charge=0,
    mult=1,
    xyz_file="guess.xyz"
    engine=OrcaEngine(version="6.0.1", scratch="/scratch")
)

opt_freq = Calculation(input_template=opt_freq_template, settings)
tddft = Calculation(input_template=tddft_template, settings)

opt_freq.run()

tddft.xyz_file = opt_freq.files.optimized_xyz_file
tddft.run()

Project details


Release history Release notifications | RSS feed

This version

0.5.0

Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

orcastrator-0.5.0.tar.gz (53.9 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

orcastrator-0.5.0-py3-none-any.whl (8.5 kB view details)

Uploaded Python 3

File details

Details for the file orcastrator-0.5.0.tar.gz.

File metadata

  • Download URL: orcastrator-0.5.0.tar.gz
  • Upload date:
  • Size: 53.9 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.5.20

File hashes

Hashes for orcastrator-0.5.0.tar.gz
Algorithm Hash digest
SHA256 2247be0e4876433ede3c0a7662a6df194fad3423578da5bc46a72578632443fc
MD5 1fd77fae90b50deb8562cf2117d0f248
BLAKE2b-256 e7aef9c8b04361fa42ad52c0ca8ddabe645af7f613496ec456f095c943a6d5fe

See more details on using hashes here.

File details

Details for the file orcastrator-0.5.0-py3-none-any.whl.

File metadata

File hashes

Hashes for orcastrator-0.5.0-py3-none-any.whl
Algorithm Hash digest
SHA256 3a2c8f668890925cf16ce47351590bf2791fe64bc6e988e68d514b9377d27a25
MD5 3ecd74f5a81334ce92f8889d777b3ae2
BLAKE2b-256 ffd31b9d32864f682566744f66003334085af673a97a4187d7e970ff16525330

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page