Public record
Software health reportschema 0.31.0 · metrics 2.10.0 · 2026-08-13 00:16 UTC

nalepae / pandarallel

A simple and efficient tool to parallelize Pandas operations on all available CPUs

PythonBSD-3-Clause★ 3,801 stars⑂ 213 forkssince Mar 2019View on GitHub ↗

nalepae/pandarallel holds a health index of 30 out of 100, placing it in the At Risk band. It scores highest on Community & Adoption (69/100) and lowest on Vitality (21/100). It was last updated 764 days ago. A single contributor accounts for most of its recent work.

30
overall / 100
At Risk

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.

30
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)
VitalityCommunity &AdoptionSustainability &GovernanceEngineeringQualitySecurityAI Readiness

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 50 is calibrated to 50 on the published index scale (record calibration 2026-08-02).

Ownership

Manu NALEPAPersonal account
158 followers19 public repossince Jul 2013Offchain Labs

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

Package ecosystems

RegistryPackageVersionDownloads / moVersionsLast publish
PyPIpandarallelpoints to another repo — not scored1.6.5-411198 days ago

Metrics by category

Vitality

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

21At Risk · 21% of overall
How it's scored
0/36Push recencylast push 764 days ago
0/36Commit cadence0/52 weeks with commits
0/18Commit volume0 commits in the last year
0/10OpenSSF Scorecard: Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
Inputs used
commits_last_year0
human_commit_share1
days_since_last_push764
active_weeks_last_year0
How it's scored
27/27Ships releases41 releases published
0/36Release recencylatest release 1,198 days ago
19.8/27Release cadencea release every ~50 days
0/10OpenSSF Scorecard: Signed-Releasesno data
Inputs used
releases_count41
latest_release_tagv1.6.5
releases_from_tagsno
days_since_latest_release1,198
mean_days_between_releases50
Excluded from scoring (no data or not applicable): OpenSSF Scorecard: Signed-Releases. Remaining weights renormalized.

Community & Adoption

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

69Good · 17% of overall
How it's scored
58.1/60Stars3,801 stars
19.4/25Forks213 forks
7.9/15Watchers27 watchers
Inputs used
forks213
stars3,801
watchers27
growth_stateunverified
growth_factor_pct100
growth_unverified_reasonno_history
How it's scored
22.5/22.5README
22.5/22.5Licenserecognized license (BSD-3-Clause)
0/18CONTRIBUTING guide
0/13.5Code of conduct
0/7.2Issue template
0/6.3PR template
Inputs used
has_readmeyes
has_licenseyes
readme_badges3
has_contributingno
has_issue_templateno
has_code_of_conductno
readme_badge_servicesbadge.fury.io, shields.io
has_pull_request_templateno

Sustainability & Governance

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

52Moderate · 23% of overall
How it's scored
9/54Bus factor1 contributor(s) cover half of all commits
4.4/22.5Commit distributiontop contributor authored 80% of commits
13.5/13.5Contributor breadth26 contributors
10/10OpenSSF Scorecard: Contributorsproject has 4 contributing companies or organizations
Inputs used
bus_factor1
contributors_sampled26
top_contributor_share0.803
How it's scored
25.4/42Issue resolution60% of issues closed
23/30PR acceptance36/47 decided PRs merged
0/13Newcomer PR acceptanceno first-time contributor's PR decided in 30d
6/15OpenSSF Scorecard: Code-ReviewFound 10/22 approved changesets -- score normalized to 4
Inputs used
merged_prs36
open_issues88
closed_issues135
prs_merged_7d0
prs_decided_7d0
prs_merged_30d0
prs_decided_30d0
issue_closed_ratio0.605
closed_unmerged_prs11
first_time_authors_30d0
first_time_prs_merged_30d0
first_time_prs_decided_30d0
Excluded from scoring (no data or not applicable): Newcomer PR acceptance. Remaining weights renormalized.
How it's scored
10/30Ownership backingpersonal (user) account
0/20Verified domainnot applicable to user accounts
15.8/25Owner reach158 followers of nalepae
21.5/25Track record19 public repos, account ~13 yr old
Inputs used
followers158
owner_typeUser
is_verified
owner_loginnalepae
public_repos19
account_age_days4,787
Excluded from scoring (no data or not applicable): Verified domain. Remaining weights renormalized.

Engineering Quality

Are baseline engineering and documentation practices in place?

69Good · 19% of overall
How it's scored
24/24CI workflows1 workflow(s)
24/24Tests present
0/16Linter config
0/9.6Pre-commit hooks
0/6.4.editorconfig
0/20OpenSSF Scorecard: CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
Inputs used
has_ciyes
has_testsyes
has_editorconfigno
has_linter_configno
has_precommit_configno

Documentation

100Exceptional
How it's scored
30/30README
25/25Documentation directory
15/15Documentation / homepage sitehttps://nalepae.github.io/pandarallel
10/10Repository description
10/10Topics3 topics
10/10Wiki
Inputs used
topicspandas, python, parallel
has_wikiyes
homepagehttps://nalepae.github.io/pandarallel
docs_sitehttps://nalepae.github.io/pandarallel
has_readmeyes
has_docs_diryes
has_descriptionyes

Security

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

44Weak · 16% of overall
How it's scored
7.5/7.5Binary-Artifactsno binaries found in the repo
0/7.5Branch-Protectionbranch protection not enabled on development/release branches
0/2.5CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
0/2.5CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
3/7.5Code-ReviewFound 10/22 approved changesets -- score normalized to 4
2.5/2.5Contributorsproject has 4 contributing companies or organizations
10/10Dangerous-Workflowno dangerous workflow patterns detected
0/7.5Dependency-Update-Toolno update tool detected
0/5Fuzzingproject is not fuzzed
2.5/2.5Licenselicense file detected
0/7.5Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
0/5Packagingno data
0/5Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0/5SASTSAST tool is not run on all commits -- score normalized to 0
0/5Security-Policysecurity policy file not detected
0/7.5Signed-Releasesno data
7.5/7.5Token-PermissionsGitHub workflow tokens follow principle of least privilege
7.5/7.5Vulnerabilities0 existing vulnerabilities detected
Inputs used
sourceopenssf_scorecard
checks_evaluated16
scorecard_versionv5.5.0
checks_inconclusive2
scorecard_aggregate4.4
Excluded from scoring (no data or not applicable): Packaging, Signed-Releases. Remaining weights renormalized.

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.

37Weak · 4% of overall
How it's scored
0/45Agent instructionsno CLAUDE.md / AGENTS.md / editor rules
0/15Machine-readable docs (llms.txt)
16.5/40Legible commit history31 of 100 human commits state their intent (structured subject or explanatory body)
Inputs used
has_llms_txtno
llms_txt_url
legible_history_share0.31
agent_instruction_files
agent_instruction_max_bytes
How it's scored
0/18One-command bootstrap
22/22Automated tests
0/11Lint / format config
0/11Static type checking
0/10Reproducible environment
0/10Demonstrated agent practiceno agent-authored commits among the last 100
0/8Automated maintenanceno automated dependency updates observed
0/10OpenSSF Scorecard: Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
Inputs used
has_nixno
has_testsyes
lockfiles
has_dockerfileno
typed_languageno
bootstrap_files
has_devcontainerno
has_linter_configno
typecheck_configs
agent_commit_share0
toolchain_manifests
dependency_bot_commit_share0
How it's scored
0/45Type-checkable codePython without a type-check config
55/55Manageable file sizes0/14 source files over 60KB
Inputs used
primary_languagePython
largest_source_bytes19,173
source_files_sampled14
oversized_source_files0
How it's scored
0/40API schema (OpenAPI/GraphQL/proto)not applicable to this kind of software
0/20MCP servernot applicable to this kind of software
40/40Runnable examplesnotebooks
Inputs used
example_dirsnotebooks
has_mcp_signalno
api_schema_files
interfaces_expected_of
Excluded from scoring (no data or not applicable): API schema (OpenAPI/GraphQL/proto), MCP server. Remaining weights renormalized.

Key facts

3,801GitHub stars
26contributors
0commits, last 12 months
764days since last push
41releases
1bus factor
88open issues
PyPIpackage ecosystems

Data collection warnings

  • Star history unavailable: GitHub GraphQL error: Resource not accessible by personal access token
  • pypi package 'pandarallel' points at a different repository (https://nalepae.github.io/pandarallel); excluded from ecosystem scoring

More detail

Star and fork history 0 ★ / 213 ⇿
0Stars
213Forks
32Releases

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.

0408012016020024020982019-042022-112026-07
Major 0Minor 6Patch 26

Each point covers 7 days.

OpenSSF Scorecard 4.4 / 10
4.4aggregate

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 · 2026-08-13 00:16 UTC

10Binary-Artifactsno binaries found in the repo
0Branch-Protectionbranch protection not enabled on development/release branches
0CI-Tests0 out of 15 merged PRs checked by a CI test -- score normalized to 0
0CII-Best-Practicesno effort to earn an OpenSSF best practices badge detected
4Code-ReviewFound 10/22 approved changesets -- score normalized to 4
10Contributorsproject has 4 contributing companies or organizations
10Dangerous-Workflowno dangerous workflow patterns detected
0Dependency-Update-Toolno update tool detected
0Fuzzingproject is not fuzzed
10Licenselicense file detected
0Maintained0 commit(s) and 0 issue activity found in the last 90 days -- score normalized to 0
n/aPackagingpackaging workflow not detected
0Pinned-Dependenciesdependency not pinned by hash detected -- score normalized to 0
0SASTSAST tool is not run on all commits -- score normalized to 0
0Security-Policysecurity policy file not detected
n/aSigned-Releasesno releases found
10Token-PermissionsGitHub workflow tokens follow principle of least privilege
10Vulnerabilities0 existing vulnerabilities detected
Direct dependencies 3
RegistryPackageVersion constraintManifest
PyPIdill>= 0.3.1setup.cfg
PyPIpandas>= 1setup.cfg
PyPIpsutilsetup.cfg
All dependencies 0

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

RegistryPackageVersionRelation
Dependency advisories not assessed

Advisory matching could not run for this report: No resolved dependencies to assess

Raw JSON report machine-readable

Feedback

Spotted something off in this report, or have thoughts to share? Wrong measurements, missed tooling, ideas, questions — anything is welcome. Every message is read and gets a response.

The message is kept through sign-in.

Scores are signals, not warranties. They reflect publicly visible practices on GitHub — not a code audit, and not a security guarantee.

Missing data is excluded and weights renormalized, never scored as zero. Methodology is versioned and open: metrics v2.10.0, schema v0.31.0 — full methodology · metrics wiki.

How one result sits in the wider record: aggregate statisticsPyPI.