safe-ds-runner

Execute Safe-DS programs that were compiled to Python.

https://github.com/safe-ds/runner

Science Score: 44.0%

This score indicates how likely this project is to be science-related based on various indicators:

✓
CITATION.cff file
Found CITATION.cff file
✓
codemeta.json file
Found codemeta.json file
✓
.zenodo.json file
Found .zenodo.json file
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DOI references
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Academic publication links
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Committers with academic emails
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Institutional organization owner
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JOSS paper metadata
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Scientific vocabulary similarity
Low similarity (10.6%) to scientific vocabulary

Keywords from Contributors

usability dsl learnability safety static-analysis interactive mesh interpretability transformers sequences

Last synced: 7 months ago · JSON representation ·

Repository

Execute Safe-DS programs that were compiled to Python.

Basic Info

Host: GitHub
Owner: Safe-DS
License: mit
Language: Python
Default Branch: main
Homepage:
Size: 2.22 MB

Statistics

Stars: 2
Watchers: 1
Forks: 0
Open Issues: 10
Releases: 26

Created over 2 years ago · Last pushed 8 months ago

Metadata Files

Readme License Citation Codeowners

docs/README.md

Safe-DS Runner

Execute Safe-DS programs that were compiled to Python.

Installation

Get the latest version from PyPI:

shell pip install safe-ds-runner

On a Windows PC with an NVIDIA graphics card, you may also want to install the CUDA versions of torch and torchvision:

shell pip install --upgrade torch torchvision --index-url https://download.pytorch.org/whl/cu121

Usage

Start the runner server:

shell safe-ds-runner start

Documentation

You can find the full documentation here.

Contributing

We welcome contributions from everyone. As a starting point, check the following resources:

If you need further help, please use our discussion forum.

Owner

Name: Safe-DS
Login: Safe-DS
Kind: organization

Repositories: 1
Profile: https://github.com/Safe-DS

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
message: >-
  Please cite this software using the metadata from
  'preferred-citation'.
type: software
title: Safe-DS Runner
repository-code: https://github.com/Safe-DS/Runner
license: MIT
preferred-citation:
  type: conference-paper
  year: 2023
  conference:
    name: >-
      2023 IEEE/ACM 45th International Conference on
      Software Engineering: New Ideas and Emerging Results
  collection-title: >-
    2023 IEEE/ACM 45th International Conference on
    Software Engineering: New Ideas and Emerging Results
  title: >-
    An Alternative to Cells for Selective Execution of Data Science Pipelines
  authors:
    - given-names: Lars
      family-names: Reimann
      email: "reimann@cs.uni-bonn.de"
      affiliation: >-
        Institute for Computer Science III, University
        of Bonn, Germany
      orcid: "https://orcid.org/0000-0002-5129-3902"
    - affiliation: >-
        Institute for Computer Science III, University
        of Bonn, Germany
      given-names: Günter
      family-names: Kniesel-Wünsche
  abstract: >-
    Data Scientists often use notebooks to develop Data Science (DS) pipelines,
    particularly since they allow to selectively execute parts of the pipeline.
    However, notebooks for DS have many well-known flaws. We focus on the
    following ones in this paper: (1) Notebooks can become littered with code
    cells that are not part of the main DS pipeline but exist solely to make
    decisions (e.g. listing the columns of a tabular dataset). (2) While users
    are allowed to execute cells in any order, not every ordering is correct,
    because a cell can depend on declarations from other cells. (3) After making
    changes to a cell, this cell and all cells that depend on changed
    declarations must be rerun. (4) Changes to external values necessitate
    partial re-execution of the notebook. (5) Since cells are the smallest unit
    of execution, code that is unaffected by changes, can inadvertently be
    re-executed. To solve these issues, we propose to replace cells as the basis
    for the selective execution of DS pipelines. Instead, we suggest populating
    a context-menu for variables with actions fitting their type (like listing
    columns if the variable is a tabular dataset). These actions are executed
    based on a data-flow analysis to ensure dependencies between variables are
    respected and results are updated properly after changes. Our solution
    separates pipeline code from decision making code and automates dependency
    management, thus reducing clutter and the risk of making errors.
  keywords:
    - "notebook"
    - "usability"
    - "data science"
    - "machine learning"
  doi: "10.1109/ICSE-NIER58687.2023.00029"
  identifiers:
    - type: doi
      value: "10.1109/ICSE-NIER58687.2023.00029"
      description: "IEEE Xplore"
    - type: doi
      value: "10.48550/arXiv.2302.14556"
      description: "arXiv (preprint)"

GitHub Events

Total

Create event: 63
Issues event: 2
Release event: 3
Delete event: 60
Issue comment event: 106
Push event: 89
Pull request review event: 2
Pull request event: 116

Last Year

Create event: 63
Issues event: 2
Release event: 3
Delete event: 60
Issue comment event: 106
Push event: 89
Pull request review event: 2
Pull request event: 116

Committers

Last synced: 10 months ago

All Time

Total Commits: 206
Total Committers: 4
Avg Commits per committer: 51.5
Development Distribution Score (DDS): 0.476

Past Year

Commits: 70
Committers: 3
Avg Commits per committer: 23.333
Development Distribution Score (DDS): 0.214

Top Committers

Name	Email	Commits
dependabot[bot]	4****]	108
Lars Reimann	m**l@l**m	55
semantic-release-bot	s**t@m**t	25
WinPlay02	w**h@w**e	18

Committer Domains (Top 20 + Academic)

woberlaender.de: 1 martynus.net: 1 larsreimann.com: 1

Issues and Pull Requests

Last synced: 7 months ago

All Time

Total issues: 17
Total pull requests: 240
Average time to close issues: 17 days
Average time to close pull requests: 4 days
Total issue authors: 4
Total pull request authors: 3
Average comments per issue: 0.82
Average comments per pull request: 1.43
Merged pull requests: 172
Bot issues: 2
Bot pull requests: 195

Past Year

Issues: 4
Pull requests: 118
Average time to close issues: 22 days
Average time to close pull requests: 4 days
Issue authors: 2
Pull request authors: 2
Average comments per issue: 0.5
Average comments per pull request: 1.44
Merged pull requests: 78
Bot issues: 2
Bot pull requests: 111

View more stats

Top Authors

Issue Authors

lars-reimann (12)
dependabot[bot] (2)
SmiteDeluxe (2)
WinPlay02 (1)

Pull Request Authors

dependabot[bot] (195)
lars-reimann (34)
WinPlay02 (11)

Top Labels

Issue Labels

enhancement :bulb: (6) bug :beetle: (4) performance :runner: (3) dependencies (2) python (1) javascript (1)

Pull Request Labels

dependencies (195) python (161) released (67) javascript (29) github_actions (5)

Packages

Total packages: 1
Total downloads:
- pypi 102 last-month

Total dependent packages: 0
Total dependent repositories: 0
Total versions: 25
Total maintainers: 1

pypi.org: safe-ds-runner

Execute Safe-DS programs that were compiled to Python.

Homepage: https://github.com/Safe-DS/Runner
Documentation: https://safe-ds-runner.readthedocs.io
License: MIT
Latest release: 0.20.0
published 11 months ago

Versions: 25
Dependent Packages: 0
Dependent Repositories: 0
Downloads: 102 Last month

Rankings

Dependent packages count: 10.1%

Average: 38.7%

Dependent repos count: 67.4%

Maintainers (1)

lars-reimann

Last synced: 8 months ago

Dependencies

.github/workflows/dependency-review.yml actions

.github/workflows/issue.yml actions

actions/add-to-project v0.5.0 composite

.github/workflows/main.yml actions

.github/workflows/megalinter.yml actions

.github/workflows/pr-format.yml actions

.github/workflows/pr.yml actions

.github/workflows/release.yml actions

package-lock.json npm

509 dependencies

package.json npm

@lars-reimann/prettier-config ^5.0.0 development
@semantic-release/changelog ^6.0.3 development
@semantic-release/exec ^6.0.3 development
@semantic-release/git ^10.0.1 development
conventional-changelog-conventionalcommits ^6.1.0 development
semantic-release ^21.0.7 development

poetry.lock pypi

appnope 0.1.3
asttokens 2.2.1
backcall 0.2.0
certifi 2023.7.22
charset-normalizer 3.2.0
click 8.1.6
colorama 0.4.6
contourpy 1.1.0
coverage 7.2.7
cycler 0.11.0
decorator 5.1.1
et-xmlfile 1.1.0
exceptiongroup 1.1.2
executing 1.2.0
fonttools 4.42.0
ghp-import 2.1.0
idna 3.4
iniconfig 2.0.0
ipython 8.14.0
jedi 0.19.0
jinja2 3.1.2
joblib 1.3.2
kiwisolver 1.4.4
markdown 3.4.4
markupsafe 2.1.3
matplotlib 3.7.2
matplotlib-inline 0.1.6
mergedeep 1.3.4
mkdocs 1.5.2
mkdocs-glightbox 0.3.4
mkdocs-material 9.1.21
mkdocs-material-extensions 1.1.1
numpy 1.25.2
openpyxl 3.1.2
packaging 23.1
pandas 2.0.3
parso 0.8.3
pathspec 0.11.2
pexpect 4.8.0
pickleshare 0.7.5
pillow 9.5.0
platformdirs 3.10.0
pluggy 1.2.0
prompt-toolkit 3.0.39
ptyprocess 0.7.0
pure-eval 0.2.2
pygments 2.16.1
pymdown-extensions 10.1
pyparsing 3.0.9
pytest 7.4.0
pytest-cov 4.1.0
python-dateutil 2.8.2
pytz 2023.3
pyyaml 6.0.1
pyyaml-env-tag 0.1
regex 2023.8.8
requests 2.31.0
safe-ds 0.14.0
scikit-learn 1.3.0
scipy 1.9.3
seaborn 0.12.2
six 1.16.0
stack-data 0.6.2
threadpoolctl 3.2.0
tomli 2.0.1
traitlets 5.9.0
tzdata 2023.3
urllib3 2.0.4
watchdog 3.0.0
wcwidth 0.2.6

pyproject.toml pypi

pytest ^7.4.0 develop
pytest-cov ^4.1.0 develop
python ^3.10
safe-ds ^0.14.0