Software health reportschema 0.34.0 · metrics 2.10.0 · 2026-09-20 06:41 UTC

speediedan / finetuning-scheduler

A PyTorch Lightning extension that accelerates and enhances foundation model experimentation with flexible fine-tuning schedules.

PythonApache-2.0★ 69 stars⑂ 8 forkssince Feb 2022View on GitHub ↗

KindCommand-line toolLibraryhow this is determined

#machine-learning #transfer-learning #finetuning #fine-tuning #pytorch-lightning #pytorch #artificial-intelligence #neural-networks #superglue

speediedan/finetuning-scheduler holds a health index of 78 out of 100, placing it in the Good band. It scores highest on Engineering Quality (96/100) and lowest on Security (45/100). It was last updated 8 days ago. A single contributor accounts for most of its recent work.

overall / 100

Good

Software health index

Metrics are grouped into weighted categories on one standardized 1–100 scale. Overall starts as their weighted mean, calibrated against the distribution of the public record so bands carry percentile meaning; when public evidence triggers the High-Risk Jurisdiction Policy, the rating is adjusted and receives an At Risk ceiling of 34.

Exceptional93-100The record's top tier (≈ top 5%); essentially all checked criteria met

Excellent80-92Strong across the board; minor gaps

Good65-79Healthy; gaps are limited and manageable

Moderate50-64Acceptable with notable gaps; review recommended

Weak35-49Material weaknesses across several areas

At Risk20-34Significant weaknesses; adoption warrants caution

Critical1-19Severe problems (abandoned, single-maintainer, no hygiene)

Score profile

Each axis is a category. The shape matters more than the average — a healthy subject fills the whole shape, while a spike-and-crater profile means strength in one dimension is masking risk in another.

The weighted overall 67 is calibrated to 78 on the published index scale (record calibration 2026-08-02).

Ownership

Dan DalePersonal account

22 followers36 public repossince May 2014

This repository is owned by a personal account. A single-owner project carries more continuity risk than an organization-backed one.

Package ecosystems

Registry	Package	Version	Downloads / mo	Versions	Last publish	Tags
PyPI	finetuning-scheduler	2.13.0	3,946	46	55 days ago	deep-learning pytorch ai machine-learning pytorch-lightning lightning fine-tuning finetuning

Metrics by category

Vitality

Is the project alive — is code being written and are releases shipping?

70Good · 21% of overall

Development activity

62Moderate

How it's scored

28.8/36	Push recency — last push 8 days ago
7.6/36	Commit cadence — 11/52 weeks with commits
15.6/18	Commit volume — 53 commits in the last year
10/10	OpenSSF Scorecard: Maintained — 23 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10

Inputs used

commits_last_year	53
human_commit_share	1
days_since_last_push	8
active_weeks_last_year	11

Release discipline

83Excellent

How it's scored

27/27	Ships releases — 48 releases published
36/36	Release recency — latest release 55 days ago
19.8/27	Release cadence — a release every ~78.9 days
0/10	OpenSSF Scorecard: Signed-Releases — Project has not signed or included provenance with any releases.

Inputs used

releases_count	48
latest_release_tag	v2.13.0
releases_from_tags	no
days_since_latest_release	55
mean_days_between_releases	78.9

Community & Adoption

Does the project have users, downloads, attention, and a welcoming setup for contributors?

62Moderate · 17% of overall

Popularity & adoption

38Weak

How it's scored

29.7/60	Stars — 69 stars
7/25	Forks — 8 forks
1.7/15	Watchers — 3 watchers

Inputs used

forks	8
stars	69
watchers	3
growth_state	unverified
growth_factor_pct	100
growth_unverified_reason	no_history

Community health

92Excellent

How it's scored

22.5/22.5	README
22.5/22.5	License — recognized license (Apache-2.0)
18/18	CONTRIBUTING guide
13.5/13.5	Code of conduct
0/7.2	Issue template
6.3/6.3	PR template

Inputs used

has_readme	yes
has_license	yes
readme_badges	9
has_contributing	yes
has_issue_template	no
has_code_of_conduct	yes
readme_badge_services	badge.fury.io, codecov.io, dev.azure.com, github.com, readthedocs.org, shields.io
has_pull_request_template	yes

Ecosystem adoption (downloads)

60Moderate

How it's scored

48/80	Monthly downloads — 3,946 downloads/month across pypi
0/20	Registry dependents — not reported by this ecosystem

Inputs used

packages	finetuning-scheduler
dependents	—
ecosystems	pypi
total_downloads	—
monthly_downloads	3,946
unverified_packages_excluded	—

Excluded from scoring (no data or not applicable): Registry dependents. Remaining weights renormalized.

Sustainability & Governance

Will the project survive its people — bus factor, responsiveness, who backs it, and package upkeep?

59Moderate · 23% of overall

Maintainer resilience (bus factor)

19Critical

How it's scored

9/54	Bus factor — 1 contributor(s) cover half of all commits
0.4/22.5	Commit distribution — top contributor authored 98% of commits
6.8/13.5	Contributor breadth — 5 contributors
3/10	OpenSSF Scorecard: Contributors — project has 1 contributing companies or organizations -- score normalized to 3

Inputs used

bus_factor	1
contributors_sampled	5
top_contributor_share	0.981

Issue & PR responsiveness

80Excellent

How it's scored

39.8/42	Issue resolution — 95% of issues closed
30/30	PR acceptance — 22/22 decided PRs merged
0/13	Newcomer PR acceptance — no first-time contributor's PR decided in 30d
0/15	OpenSSF Scorecard: Code-Review — Found 0/27 approved changesets -- score normalized to 0

Inputs used

merged_prs	22
open_issues	1
closed_issues	18
prs_merged_7d	0
prs_decided_7d	0
prs_merged_30d	9
prs_decided_30d	9
issue_closed_ratio	0.947
closed_unmerged_prs	0
first_time_authors_30d	0
first_time_prs_merged_30d	0
first_time_prs_decided_30d	0

Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.

Ownership & stewardship

54Moderate

How it's scored

10/30	Ownership backing — personal (user) account
0/20	Verified domain — not applicable to user accounts
9.8/25	Owner reach — 22 followers of speediedan
23.4/25	Track record — 36 public repos, account ~12 yr old

Inputs used

followers	22
owner_type	User
is_verified	—
owner_login	speediedan
public_repos	36
account_age_days	4,524

Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Package maintenance

100Exceptional

How it's scored

25/25	Published & resolvable — 1 package(s) on pypi
35/35	Publish recency — latest publish 55 days ago
20/20	Version history — 46 published versions
20/20	Not deprecated — active, not deprecated or yanked

Inputs used

packages	finetuning-scheduler
ecosystems	pypi
any_deprecated	no
min_days_since_publish	55

Engineering Quality

Are baseline engineering and documentation practices in place?

96Exceptional · 19% of overall

Engineering practices

94Exceptional

How it's scored

24/24	CI workflows — 10 workflow(s)
24/24	Tests present
16/16	Linter config — pyproject.toml ([tool.ruff])
9.6/9.6	Pre-commit hooks
0/6.4	.editorconfig
20/20	OpenSSF Scorecard: CI-Tests — 12 out of 12 merged PRs checked by a CI test -- score normalized to 10

Inputs used

has_ci	yes
has_tests	yes
has_editorconfig	no
has_linter_config	yes
has_precommit_config	yes

Documentation

100Exceptional

How it's scored

30/30	README
25/25	Documentation directory
15/15	Documentation / homepage site — https://finetuning-scheduler.readthedocs.io
10/10	Repository description
10/10	Topics — 9 topics
10/10	Wiki

Inputs used

topics	machine-learning, transfer-learning, finetuning, fine-tuning, pytorch-lightning, pytorch, artificial-intelligence, neural-networks, superglue
has_wiki	yes
homepage	https://finetuning-scheduler.readthedocs.io
docs_site	https://finetuning-scheduler.readthedocs.io
has_readme	yes
has_docs_dir	yes
has_description	yes

Security

Are visible security and supply-chain practices strong, without unresolved high-risk jurisdiction exposure?

45Weak · 16% of overall

Security posture

37Weak

How it's scored

7.5/7.5	Binary-Artifacts — no binaries found in the repo
0/7.5	Branch-Protection — branch protection not enabled on development/release branches
2.5/2.5	CI-Tests — 12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0/2.5	CII-Best-Practices — no effort to earn an OpenSSF best practices badge detected
0/7.5	Code-Review — Found 0/27 approved changesets -- score normalized to 0
0.8/2.5	Contributors — project has 1 contributing companies or organizations -- score normalized to 3
10/10	Dangerous-Workflow — no dangerous workflow patterns detected
0/7.5	Dependency-Update-Tool — no update tool detected
0/5	Fuzzing — project is not fuzzed
2.5/2.5	License — license file detected
7.5/7.5	Maintained — 23 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
5/5	Packaging — packaging workflow detected
0/5	Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0
0/5	SAST — SAST tool is not run on all commits -- score normalized to 0
3/5	Security-Policy — security policy file detected
0/7.5	Signed-Releases — Project has not signed or included provenance with any releases.
0/7.5	Token-Permissions — detected GitHub workflow tokens with excessive permissions
0/7.5	Vulnerabilities — 129 existing vulnerabilities detected

Inputs used

source	openssf_scorecard
checks_evaluated	18
scorecard_version	v5.5.0
checks_inconclusive	0
scorecard_aggregate	3.7

Dependency advisories

78Good

How it's scored

13.2/35	Direct dependencies free of known advisories — 1 affected: lightning 2.6.6 (high 7.8)
25/25	Indirect dependencies free of known advisories — no indirect dependency carries a known advisory
40/40	No advisories left outstanding — no advisory has been public longer than 90 days

Inputs used

source	osv
advisories	1
affected_packages	1
assessed_packages	46
unassessed_packages	0
affected_by_severity	high 1
direct_affected_packages	1

Matched the pypi:finetuning-scheduler@2.13.0 runtime dependency closure — what installing the published package pulls in — 46 packages. Reachability is not analyzed.

AI Readiness

How well is the repo equipped to be developed and maintained with AI coding agents? Carries a deliberately small weight (4%): agent tooling is a real maintenance signal, but a repository with none can still reach 100/100.

72Good · 4% of overall

Agent context & guidance

64Moderate

How it's scored

45/45	Agent instructions — .github/copilot-instructions.md, AGENTS.md, CLAUDE.md
0/15	Machine-readable docs (llms.txt)
18.7/40	Legible commit history — 35 of 100 human commits state their intent (structured subject or explanatory body)

Inputs used

has_llms_txt	no
llms_txt_url	—
legible_history_share	0.35
agent_instruction_files	.github/copilot-instructions.md, AGENTS.md, CLAUDE.md
agent_instruction_max_bytes	17,426

Verify loop (build / test / typecheck)

74Good

How it's scored

18/18	One-command bootstrap — Makefile, docs/Makefile
22/22	Automated tests
11/11	Lint / format config — pyproject.toml ([tool.ruff])
11/11	Static type checking — src/finetuning_scheduler/py.typed
10/10	Reproducible environment — Dockerfile
2/10	Demonstrated agent practice — 1 of the last 100 commits agent-authored or agent-credited
0/8	Automated maintenance — no automated dependency updates observed
0/10	OpenSSF Scorecard: Pinned-Dependencies — dependency not pinned by hash detected -- score normalized to 0

Inputs used

has_nix	no
has_tests	yes
lockfiles	—
has_dockerfile	yes
typed_language	no
bootstrap_files	Makefile, docs/Makefile
has_devcontainer	no
has_linter_config	yes
typecheck_configs	src/finetuning_scheduler/py.typed
agent_commit_share	0.01
toolchain_manifests	—
dependency_bot_commit_share	0

Code legibility for models

80Excellent

How it's scored

27/45	Type-checkable code — Python with type-check config (src/finetuning_scheduler/py.typed)
53.3/55	Manageable file sizes — 2/63 source files over 60KB

Inputs used

primary_language	Python
largest_source_bytes	129,297
source_files_sampled	63
oversized_source_files	2

Key facts

69GitHub stars

5contributors

53commits, last 12 months

8days since last push

48releases

1bus factor

1open issues

PyPIpackage ecosystems

Data collection warnings

Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
Could not fetch pypi package 'setup_tools.py' from its registry

More detail

Star and fork history 0 ★ / 8 ⇿

0Stars

8Forks

43Releases

When each star and fork was added, collected from GitHub and bucketed by day. Cumulative growth sits directly above the daily additions it is made of, so the two read against each other: steady organic accretion looks nothing like an abrupt, short-lived burst. Where that difference is measurable, it is reported as growth authenticity.

Major 1Minor 9Patch 31

Each point covers 4 days.

OpenSSF Scorecard 3.7 / 10

3.7aggregate

Independent, tool-agnostic security assessment from the open-source OpenSSF Scorecard. Each check rewards a security practice, not a specific vendor's tool. Checks Scorecard could not determine are marked n/a and excluded from the security score (never counted as zero).Scorecard v5.5.0 · 2026-09-20 06:41 UTC

10	Binary-Artifacts	no binaries found in the repo
0	Branch-Protection	branch protection not enabled on development/release branches
10	CI-Tests	12 out of 12 merged PRs checked by a CI test -- score normalized to 10
0	CII-Best-Practices	no effort to earn an OpenSSF best practices badge detected
0	Code-Review	Found 0/27 approved changesets -- score normalized to 0
3	Contributors	project has 1 contributing companies or organizations -- score normalized to 3
10	Dangerous-Workflow	no dangerous workflow patterns detected
0	Dependency-Update-Tool	no update tool detected
0	Fuzzing	project is not fuzzed
10	License	license file detected
10	Maintained	23 commit(s) and 2 issue activity found in the last 90 days -- score normalized to 10
10	Packaging	packaging workflow detected
0	Pinned-Dependencies	dependency not pinned by hash detected -- score normalized to 0
0	SAST	SAST tool is not run on all commits -- score normalized to 0
6	Security-Policy	security policy file detected
0	Signed-Releases	Project has not signed or included provenance with any releases.
0	Token-Permissions	detected GitHub workflow tokens with excessive permissions
0	Vulnerabilities	129 existing vulnerabilities detected

All dependencies 355

Full resolved dependency set from the GitHub dependency graph: 0 direct and 355 indirect (transitive) packages. The transitive closure is complete when the repository commits a lockfile.

Registry	Package	Version	Relation
PyPI	2-14-0-dev20260724	`—`	indirect
PyPI	aiohappyeyeballs	`2.7.1`	indirect
PyPI	aiohttp	`3.14.3`	indirect
PyPI	aiosignal	`1.4.0`	indirect
PyPI	alembic	`1.18.5`	indirect
PyPI	annotated-doc	`0.0.5`	indirect
PyPI	annotated-types	`0.8.0`	indirect
PyPI	antlr4-python3-runtime	`4.9.3`	indirect
PyPI	anyio	`4.14.2`	indirect
PyPI	appnope	`0.1.4`	indirect
PyPI	argon2-cffi	`25.1.0`	indirect
PyPI	argon2-cffi-bindings	`25.1.0`	indirect
PyPI	arrow	`1.4.0`	indirect
PyPI	aspy-yaml	`1.3.0`	indirect
PyPI	asttokens	`3.0.2`	indirect
PyPI	async-generator	`1.10`	indirect
PyPI	async-lru	`2.3.0`	indirect
PyPI	atomicwrites	`1.4.1`	indirect
PyPI	attrs	`20.3.0`	indirect
PyPI	attrs	`26.1.0`	indirect
PyPI	babel	`2.18.0`	indirect
PyPI	backcall	`0.2.0`	indirect
PyPI	beautifulsoup4	`4.15.0`	indirect
PyPI	bleach	`6.4.0`	indirect
PyPI	blinker	`1.9.0`	indirect
PyPI	cachetools	`5.5.2`	indirect
PyPI	cachetools	`7.1.6`	indirect
PyPI	certifi	`2026.7.22`	indirect
PyPI	cffi	`2.1.0`	indirect
PyPI	cfgv	`3.5.0`	indirect
PyPI	charset-normalizer	`3.4.9`	indirect
PyPI	click	`8.4.2`	indirect
PyPI	cloudpickle	`3.1.2`	indirect
PyPI	colorama	`0.4.6`	indirect
PyPI	comm	`0.2.3`	indirect
PyPI	commonmark	`0.9.2`	indirect
PyPI	contourpy	`1.3.3`	indirect
PyPI	coverage	`—`	indirect
PyPI	coverage	`6.4`	indirect
PyPI	coverage	`7.15.2`	indirect
PyPI	cryptography	`48.0.1`	indirect
PyPI	cryptography	`49.0.0`	indirect
PyPI	cu130	`—`	indirect
PyPI	cycler	`0.12.1`	indirect
PyPI	databricks-sdk	`0.122.0`	indirect
PyPI	datasets	`—`	indirect
PyPI	datasets	`4.0.0`	indirect
PyPI	datasets	`5.0.1`	indirect
PyPI	debugpy	`1.8.21`	indirect
PyPI	decorator	`5.3.1`	indirect
PyPI	defusedxml	`0.7.1`	indirect
PyPI	dill	`0.3.8`	indirect
PyPI	dill	`0.4.1`	indirect
PyPI	distlib	`0.4.3`	indirect
PyPI	docker	`7.2.0`	indirect
PyPI	docstring-parser	`0.18.0`	indirect
PyPI	docutils	`—`	indirect
PyPI	docutils	`0.23`	indirect
PyPI	entrypoints	`0.4`	indirect
PyPI	evaluate	`—`	indirect
PyPI	evaluate	`0.3.0`	indirect
PyPI	evaluate	`0.4.6`	indirect
PyPI	executing	`2.2.1`	indirect
PyPI	fastapi	`0.140.13`	indirect
PyPI	fastjsonschema	`2.22.1`	indirect
PyPI	filelock	`3.32.0`	indirect
PyPI	flask	`3.1.3`	indirect
PyPI	flask-cors	`6.0.5`	indirect
PyPI	fonttools	`4.63.0`	indirect
PyPI	fqdn	`1.5.1`	indirect
PyPI	frozenlist	`1.8.0`	indirect
PyPI	fsspec	`2025.3.0`	indirect
PyPI	fsspec	`2026.6.0`	indirect
PyPI	gitdb	`4.0.12`	indirect
PyPI	gitpython	`3.1.57`	indirect
PyPI	google-auth	`2.56.2`	indirect
PyPI	graphene	`3.4.3`	indirect
PyPI	graphql-core	`3.2.11`	indirect
PyPI	graphql-relay	`3.2.0`	indirect
PyPI	greenlet	`3.5.4`	indirect
PyPI	gunicorn	`23.0.0`	indirect
PyPI	gunicorn	`26.0.0`	indirect
PyPI	h11	`0.16.0`	indirect
PyPI	hf-xet	`1.5.2`	indirect
PyPI	httpcore	`1.0.9`	indirect
PyPI	httpx	`0.28.1`	indirect
PyPI	huey	`3.3.0`	indirect
PyPI	huggingface-hub	`0.36.2`	indirect
PyPI	huggingface-hub	`1.25.1`	indirect
PyPI	hydra-core	`—`	indirect
PyPI	hydra-core	`1.2.0`	indirect
PyPI	hydra-core	`1.3.4`	indirect
PyPI	id	`1.6.1`	indirect
PyPI	identify	`2.6.19`	indirect
PyPI	idna	`3.18`	indirect
PyPI	importlib-metadata	`8.9.0`	indirect
PyPI	importlib-metadata	`9.0.0`	indirect
PyPI	importlib-resources	`7.1.0`	indirect
PyPI	iniconfig	`2.3.0`	indirect
PyPI	ipykernel	`—`	indirect
PyPI	ipykernel	`6.2.0`	indirect
PyPI	ipykernel	`7.3.0`	indirect
PyPI	ipython	`—`	indirect
PyPI	ipython	`7.23.1`	indirect
PyPI	ipython	`9.15.0`	indirect
PyPI	ipython-genutils	`0.2.0`	indirect
PyPI	ipython-pygments-lexers	`1.1.1`	indirect
PyPI	ipywidgets	`—`	indirect
PyPI	ipywidgets	`7.6.0`	indirect
PyPI	ipywidgets	`8.1.8`	indirect
PyPI	isoduration	`20.11.0`	indirect
PyPI	itsdangerous	`2.2.0`	indirect
PyPI	jaraco-classes	`3.4.0`	indirect
PyPI	jaraco-context	`6.1.2`	indirect
PyPI	jaraco-functools	`4.6.0`	indirect
PyPI	jedi	`0.20.0`	indirect
PyPI	jeepney	`0.9.0`	indirect
PyPI	jinja2	`—`	indirect
PyPI	jinja2	`3.1.6`	indirect
PyPI	joblib	`1.5.3`	indirect
PyPI	json5	`0.15.0`	indirect
PyPI	jsonargparse	`—`	indirect
PyPI	jsonargparse	`4.27.7`	indirect
PyPI	jsonargparse	`4.50.0`	indirect
PyPI	jsonpointer	`3.1.1`	indirect
PyPI	jsonschema	`4.17.3`	indirect
PyPI	jsonschema	`4.26.0`	indirect
PyPI	jsonschema-specifications	`2025.9.1`	indirect
PyPI	jupyter-builder	`1.1.1`	indirect
PyPI	jupyter-client	`—`	indirect
PyPI	jupyter-client	`7.0.0`	indirect
PyPI	jupyter-client	`8.9.1`	indirect
PyPI	jupyter-core	`—`	indirect
PyPI	jupyter-core	`4.8.0`	indirect
PyPI	jupyter-core	`5.9.1`	indirect
PyPI	jupyter-events	`0.12.1`	indirect
PyPI	jupyter-lsp	`2.3.1`	indirect
PyPI	jupyter-server	`2.20.0`	indirect
PyPI	jupyter-server-terminals	`0.5.4`	indirect
PyPI	jupyterlab	`4.6.2`	indirect
PyPI	jupyterlab-pygments	`0.3.0`	indirect
PyPI	jupyterlab-server	`2.28.0`	indirect
PyPI	jupyterlab-widgets	`3.0.16`	indirect
PyPI	jupytext	`—`	indirect
PyPI	jupytext	`1.10.0`	indirect
PyPI	jupytext	`1.19.5`	indirect
PyPI	keyring	`25.7.0`	indirect
PyPI	kiwisolver	`1.5.0`	indirect
PyPI	lark	`1.3.1`	indirect
PyPI	lightning	`2.6.0`	indirect
PyPI	lightning	`2.6.5`	indirect
PyPI	lightning-utilities	`0.15.3`	indirect
PyPI	mako	`1.3.12`	indirect
PyPI	markdown-it-py	`0.6.2`	indirect
PyPI	markdown-it-py	`4.2.0`	indirect
PyPI	markupsafe	`3.0.3`	indirect
PyPI	matplotlib	`3.11.1`	indirect
PyPI	matplotlib-inline	`0.1.7`	indirect
PyPI	matplotlib-inline	`0.2.2`	indirect
PyPI	mdit-py-plugins	`0.2.6`	indirect
PyPI	mdit-py-plugins	`0.6.1`	indirect
PyPI	mdurl	`0.1.2`	indirect
PyPI	mistune	`0.8.4`	indirect
PyPI	mistune	`3.3.4`	indirect
PyPI	mlflow	`—`	indirect
PyPI	mlflow	`3.0.0`	indirect
PyPI	mlflow	`3.14.0`	indirect
PyPI	mlflow-skinny	`3.0.0`	indirect
PyPI	mlflow-skinny	`3.14.0`	indirect
PyPI	mlflow-tracing	`3.14.0`	indirect
PyPI	more-itertools	`11.1.0`	indirect
PyPI	multidict	`6.7.1`	indirect
PyPI	multiprocess	`0.70.16`	indirect
PyPI	multiprocess	`0.70.19`	indirect
PyPI	myst-parser	`4.0.1`	indirect
PyPI	narwhals	`2.24.0`	indirect
PyPI	nbclient	`—`	indirect
PyPI	nbclient	`0.11.0`	indirect
PyPI	nbclient	`0.5.0`	indirect
PyPI	nbconvert	`—`	indirect
PyPI	nbconvert	`6.0.0`	indirect
PyPI	nbconvert	`7.17.1`	indirect
PyPI	nbformat	`—`	indirect
PyPI	nbformat	`5.0.2`	indirect
PyPI	nbformat	`5.10.4`	indirect
PyPI	nbsphinx	`—`	indirect
PyPI	nbval	`—`	indirect
PyPI	nbval	`0.11.0`	indirect
PyPI	nbval	`0.9.6`	indirect
PyPI	nest-asyncio	`1.6.0`	indirect
PyPI	nest-asyncio2	`1.7.2`	indirect
PyPI	nh3	`0.3.6`	indirect
PyPI	nightly	`—`	indirect
PyPI	nodeenv	`1.10.0`	indirect
PyPI	notebook	`—`	indirect
PyPI	notebook	`6.4.0`	indirect
PyPI	notebook	`7.6.1`	indirect
PyPI	notebook-shim	`0.2.4`	indirect
PyPI	numpy	`2.4.6`	indirect
PyPI	omegaconf	`—`	indirect
PyPI	omegaconf	`2.2.3`	indirect
PyPI	omegaconf	`2.3.1`	indirect
PyPI	opentelemetry-api	`1.44.0`	indirect
PyPI	opentelemetry-proto	`1.44.0`	indirect
PyPI	opentelemetry-sdk	`1.44.0`	indirect
PyPI	opentelemetry-semantic-conventions	`0.65b0`	indirect
PyPI	packaging	`25.0`	indirect
PyPI	packaging	`26.2`	indirect
PyPI	pandas	`2.3.3`	indirect
PyPI	pandoc	`—`	indirect
PyPI	pandocfilters	`1.5.1`	indirect
PyPI	parso	`0.8.7`	indirect
PyPI	pexpect	`4.9.0`	indirect
PyPI	pickleshare	`0.7.5`	indirect
PyPI	pillow	`12.3.0`	indirect
PyPI	pip	`—`	indirect
PyPI	pip	`21.0`	indirect
PyPI	pip	`26.1.2`	indirect
PyPI	pkginfo	`1.12.1.2`	indirect
PyPI	platformdirs	`4.11.0`	indirect
PyPI	pluggy	`1.6.0`	indirect
PyPI	pre-commit	`—`	indirect
PyPI	pre-commit	`2.0.0`	indirect
PyPI	pre-commit	`4.6.1`	indirect
PyPI	prettytable	`3.18.0`	indirect
PyPI	prometheus-client	`0.26.0`	indirect
PyPI	prompt-toolkit	`3.0.53`	indirect
PyPI	propcache	`0.5.2`	indirect
PyPI	protobuf	`6.33.6`	indirect
PyPI	psutil	`—`	indirect
PyPI	psutil	`5.9.0`	indirect
PyPI	psutil	`7.2.2`	indirect
PyPI	pt-lightning-sphinx-theme	`—`	indirect
PyPI	ptyprocess	`0.7.0`	indirect
PyPI	pure-eval	`0.2.3`	indirect
PyPI	py	`1.11.0`	indirect
PyPI	pyarrow	`20.0.0`	indirect
PyPI	pyarrow	`24.0.0`	indirect
PyPI	pyasn1	`0.6.4`	indirect
PyPI	pyasn1-modules	`0.4.2`	indirect
PyPI	pycparser	`3.0`	indirect
PyPI	pydantic	`2.13.4`	indirect
PyPI	pydantic-core	`2.46.4`	indirect
PyPI	pygments	`2.20.0`	indirect
PyPI	pyparsing	`3.3.2`	indirect
PyPI	pyright	`—`	indirect
PyPI	pyright	`1.1.390`	indirect
PyPI	pyright	`1.1.411`	indirect
PyPI	pyrsistent	`0.20.0`	indirect
PyPI	pytest	`—`	indirect
PyPI	pytest	`7.0.0`	indirect
PyPI	pytest	`9.1.1`	indirect
PyPI	pytest-rerunfailures	`—`	indirect
PyPI	pytest-rerunfailures	`11.0`	indirect
PyPI	pytest-rerunfailures	`16.4`	indirect
PyPI	python-dateutil	`2.9.0.post0`	indirect
PyPI	python-discovery	`1.5.0`	indirect
PyPI	python-dotenv	`1.2.2`	indirect
PyPI	python-json-logger	`4.1.0`	indirect
PyPI	pytorch-lightning	`2.6.5`	indirect
PyPI	pytz	`2026.3.post1`	indirect
PyPI	pywin32	`312`	indirect
PyPI	pywin32-ctypes	`0.2.3`	indirect
PyPI	pywinpty	`3.0.5`	indirect
PyPI	pyyaml	`6.0.3`	indirect
PyPI	pyzmq	`27.1.0`	indirect
PyPI	readme-renderer	`45.0`	indirect
PyPI	referencing	`0.37.0`	indirect
PyPI	regex	`2026.7.19`	indirect
PyPI	requests	`2.34.2`	indirect
PyPI	requests-toolbelt	`1.0.0`	indirect
PyPI	responses	`0.18.0`	indirect
PyPI	rfc3339-validator	`0.1.4`	indirect
PyPI	rfc3986	`2.0.0`	indirect
PyPI	rfc3986-validator	`0.1.1`	indirect
PyPI	rfc3987-syntax	`1.1.0`	indirect
PyPI	rich	`—`	indirect
PyPI	rich	`12.3.0`	indirect
PyPI	rich	`15.0.0`	indirect
PyPI	rpds-py	`2026.6.3`	indirect
PyPI	safetensors	`0.8.0`	indirect
PyPI	scikit-learn	`—`	indirect
PyPI	scikit-learn	`1.2.0`	indirect
PyPI	scikit-learn	`1.9.0`	indirect
PyPI	scipy	`1.17.1`	indirect
PyPI	secretstorage	`3.5.0`	indirect
PyPI	send2trash	`2.1.0`	indirect
PyPI	sentencepiece	`—`	indirect
PyPI	sentencepiece	`0.2.0`	indirect
PyPI	sentencepiece	`0.2.2`	indirect
PyPI	setuptools	`—`	indirect
PyPI	setuptools	`81.0.0`	indirect
PyPI	shellingham	`1.5.4`	indirect
PyPI	six	`1.17.0`	indirect
PyPI	skops	`0.14.0`	indirect
PyPI	smmap	`5.0.3`	indirect
PyPI	soupsieve	`2.9.1`	indirect
PyPI	sphinx	`7.3.7`	indirect
PyPI	sphinx-autodoc-typehints	`—`	indirect
PyPI	sphinx-copybutton	`—`	indirect
PyPI	sphinx-paramlinks	`—`	indirect
PyPI	sphinx-togglebutton	`—`	indirect
PyPI	sqlalchemy	`2.0.51`	indirect
PyPI	sqlparse	`0.5.5`	indirect
PyPI	stack-data	`0.6.3`	indirect
PyPI	starlette	`1.3.1`	indirect
PyPI	tabulate	`—`	indirect
PyPI	tabulate	`0.10.0`	indirect
PyPI	tabulate	`0.8.9`	indirect
PyPI	tensorboardx	`—`	indirect
PyPI	tensorboardx	`2.6.1`	indirect
PyPI	tensorboardx	`2.6.5`	indirect
PyPI	terminado	`0.18.1`	indirect
PyPI	testpath	`0.6.0`	indirect
PyPI	threadpoolctl	`3.6.0`	indirect
PyPI	tinycss2	`1.5.1`	indirect
PyPI	tokenizers	`0.13.3`	indirect
PyPI	tokenizers	`0.22.2`	indirect
PyPI	toml	`0.10.2`	indirect
PyPI	tomli	`2.4.1`	indirect
PyPI	torch	`2.11.0`	indirect
PyPI	torch	`2.14.0.dev20260724`	indirect
PyPI	torchmetrics	`1.9.0`	indirect
PyPI	tornado	`6.5.7`	indirect
PyPI	tqdm	`4.70.0`	indirect
PyPI	traitlets	`—`	indirect
PyPI	traitlets	`5.0.0`	indirect
PyPI	traitlets	`5.15.1`	indirect
PyPI	transformers	`—`	indirect
PyPI	transformers	`4.26.0`	indirect
PyPI	transformers	`5.14.1`	indirect
PyPI	twine	`—`	indirect
PyPI	twine	`3.2.0`	indirect
PyPI	twine	`7.0.0`	indirect
PyPI	typer	`0.27.0`	indirect
PyPI	typeshed-client	`2.12.0`	indirect
PyPI	typing-extensions	`—`	indirect
PyPI	typing-extensions	`4.16.0`	indirect
PyPI	typing-inspection	`0.4.2`	indirect
PyPI	tzdata	`2026.3`	indirect
PyPI	uri-template	`1.3.0`	indirect
PyPI	urllib3	`2.7.0`	indirect
PyPI	uvicorn	`0.51.0`	indirect
PyPI	virtualenv	`21.7.0`	indirect
PyPI	waitress	`3.0.2`	indirect
PyPI	wcwidth	`0.8.2`	indirect
PyPI	webcolors	`25.10.0`	indirect
PyPI	webencodings	`0.5.1`	indirect
PyPI	websocket-client	`1.9.0`	indirect
PyPI	werkzeug	`3.1.8`	indirect
PyPI	widgetsnbextension	`3.5.2`	indirect
PyPI	widgetsnbextension	`4.0.15`	indirect
PyPI	xxhash	`3.8.1`	indirect
PyPI	yarl	`1.24.5`	indirect
PyPI	zipp	`4.1.0`	indirect

Dependency advisories 1

Installing pypi:finetuning-scheduler@2.13.0 pulls in 46 packages, direct and transitive: 1 carry known advisories, of which 1 are direct dependencies.

Package	Version	Relation	Severity	Advisories	Fixed in
lightning	`2.6.6`	direct	high	1	`2022.6.15`

An advisory means the version recorded in the dependency graph falls inside an advisory’s affected range. Reachability is not analysed, and the graph includes development and test pins — a finding may concern tooling rather than shipped software.

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Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.34.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statistics — PyPI.

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