Skip to main content

Sparkkflow

ARPES workflow engine with SPR-KKR, OSCARpes ingestion and ML polarization calibration.

Install

pip install -e .              # core
pip install -e ".[ml]"        # + torch / scikit-learn
pip install -e ".[oscarpes]"  # + OSCARpes ingestion
pip install -e ".[dev]"       # + pytest / ruff / mypy

CLI

sparkkflow doctor                                   # check tooling
sparkkflow scan --energy-range 20 50 --dicho        # run an ARPES scan
sparkkflow generate --energy-range 20 100 --fine-grid
sparkkflow train --model-path pol.pth
sparkkflow predict --model-path pol.pth --energy 30
sparkkflow monitor --job-ids 12,34 --continuous

Library

from sparkkflow.config import manager
from sparkkflow.scans import scans
from sparkkflow.jobs import submitter
from sparkkflow.ml import pipeline, train, predict
from sparkkflow.monitor import watch, status

cfg = manager("config.yaml").config
runner = scans(scheduler_type=cfg.scheduler.default_type, ml_mode=False)
runner.run(energy_range=(20, 50), dicho=True)

Layout

sparkkflow/
  __init__.py       # public API surface
  cli.py            # `sparkkflow` console entry point
  config.py         # YAML loader, env overrides, validation
  log.py            # structured logging
  jobs.py           # SLURM / SGE submitter (`submitter`, `slurm`, `sge`)
  scans.py          # ARPES parameter scans (`scans`)
  ml.py             # PyTorch pipeline + train / predict
  monitor.py        # status polling and resubmission
  plot.py           # dichroism plotting
  trcdad*.py        # TR+CDAD utilities
  calc_*.py         # SPR-KKR calculators
  atom_*.py         # atomic-position scans
config.yaml         # configuration template
examples/           # runnable demos
tests/              # pytest suite

Naming conventions

  • All modules and public classes are lowercase, snake_case, ASCII.
  • No +, -, spaces, or version words like enhanced in filenames.
  • One short responsibility per module name (config, jobs, ml, scans).

Development

pytest -q
ruff check sparkkflow tests
mypy sparkkflow

Metadata

Release files for sparkkflow 2.0.0

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for sparkkflow 2.0.0
File Size Uploaded Provenance Actions
sparkkflow-2.0.0.tar.gz 58.5 kB Without provenance Details for sparkkflow-2.0.0.tar.gz

Built distribution (wheel)

Table of built distributions (wheels) for sparkkflow 2.0.0
File Interpreter ABI Platform Actions
sparkkflow-2.0.0-py3-none-any.whl Python 3 none any Details for sparkkflow-2.0.0-py3-none-any.whl

Total release size: 103.6 kB

Release files / sparkkflow-2.0.0.tar.gz

Download URL sparkkflow-2.0.0.tar.gz
Size 58.5 kB
Tags Source
SHA-256 checksum
How to use checksums
8c624b8b65c579d1b910a1497d231aeda0203ca891a551244fdd3ae32d335b85
BLAKE2b-256 checksum
How to use checksums
002b948ffb8ad79183ac3a59d315727f49378d700223d32608c74b825e31b43c
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.3

Release files / sparkkflow-2.0.0-py3-none-any.whl

Download URL sparkkflow-2.0.0-py3-none-any.whl
Size 45.2 kB
Tags Python 3
SHA-256 checksum
How to use checksums
23a1cf66a5ad2988451915a77416da52a9abb6807d315488f8db95c9812c27c9
BLAKE2b-256 checksum
How to use checksums
e615f7763543198866d96edad4888a32d8ff424d1cf72c4eadcb5b9c0c758387
Upload date
Uploaded using Trusted Publishing?
What is trusted publishing?
No
Uploaded via twine/6.2.0 CPython/3.12.3

Security for sparkkflow 2.0.0

Provenance

Provenance describes where a file came from. On PyPI, provenance is shared via attestations, which provide a verifiable record of the build or publishing details. View details, limitations and caveats.

No provenance found

None of the files in this release were uploaded with provenance metadata.

A note on package security

PyPI is a repository for distributing packages, not a service for auditing them. While third-party security researchers and our staff do their best to detect and remove malicious packages, PyPI cannot guarantee the quality, security or suitability of any given package.

To learn more about protecting yourself from malicious actors, visit our package security documentation.

Release history Release notifications | RSS feed

This release

2.0.0 This release

2 release files No provenance

Anthropic, PBC Visionary sponsor Bloomberg Visionary sponsor Hudson River Trading Visionary sponsor Meta Visionary sponsor NVIDIA Visionary sponsor Microsoft Sustainability sponsor Depot Continuous Integration AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Sentry Error logging StatusPage Status page