freshdata-cleaner 1.1.1

What's Changed

• fix: absolute README links/logo for PyPI rendering (1.1.1) by @JohnnyWilson16 in #111

Full Changelog: v1.1.0...v1.1.1

freshdata-cleaner 1.1.0

What's Changed

• Add repair plan artifacts by @JohnnyWilson16 in #1
• docs: add ydata-profiling comparison recipe by @WilliamK112 in #14
• docs: add README terminal demo GIF by @WilliamK112 in #15
• docs: add community label guide by @WilliamK112 in #12
• docs: expand CleanReport docstrings with usage examples by @WilliamK112 in #23
• test: report normalize_sentinels for blank-string cleanup by @WilliamK112 in #24
• feat: treat backslash N as a missing-value sentinel by @WilliamK112 in #25
• feat: treat backslash N as missing sentinel by @JohnnyWilson16 in #27
• Add P1 repair-layer feature modules by @Rohith27216 in #28
• Fix DeprecationWarning in _json_value by handling array-like values; … by @JohnnyWilson16 in #29
• feat: repair limits, snapshot control, deterministic outliers, CI quality lanes by @kevincostner17 in #37
• refactor: move _has_outliers into shared engine/utils.py by @kevincostner17 in #38
• Cut to lean core: drop unshipped enterprise-surface modules by @JohnnyWilson16 in #39
• Domain validator packs: finance (v0.1 vertical slice) by @JohnnyWilson16 in #40
• Lean core by @JohnnyWilson16 in #41
• Domain packs: retail (GS1) + transport (GTFS) — complete v0.1 set by @JohnnyWilson16 in #42
• fix: harden domain validator packs by @JohnnyWilson16 in #43
• feat: healthcare, education, agriculture, and media domain packs by @JohnnyWilson16 in #44
• test: end-to-end conformance suite for all seven domain packs by @JohnnyWilson16 in #45
• [codex] Fix PR #45 Ruff import placement by @Rohith27216 in #46
• refactor: cut speculative enterprise features and redundant registration by @JohnnyWilson16 in #47
• feat(compliance): regulatory compliance report generators by @JohnnyWilson16 in #48
• feat(integrations): orchestration hooks for Dagster, Airflow, and dbt by @JohnnyWilson16 in #49
• Add clean_csv helper for one-line CSV cleanup by @jeevesh47 in #50
• feat(execution): out-of-core Polars/DuckDB execution engine + benchmarks by @JohnnyWilson16 in #51
• feat(streaming): stateful streaming / micro-batch cleaning mode by @JohnnyWilson16 in #55
• feat(domains): energy (SCADA / Modbus) domain pack by @JohnnyWilson16 in #57
• Fix repository-wide Ruff violations by @jeevesh47 in #56
• feat: format parsers, finance tick mode, and a centralized reference layer by @JohnnyWilson16 in #58
• feat(healthcare): FHIR R4 JSON ingest + Condition/MedicationRequest validators by @JohnnyWilson16 in #59
• CodeRabbit Generated Unit Tests: Add unit tests for PR changes by @coderabbitai[bot] in #60
• feat(enterprise): schema drift, PII privacy, and probabilistic entity resolution by @JohnnyWilson16 in #61
• Quality-Ops interoperability: dbt / Great Expectations / exception tables / lineage exporters by @JohnnyWilson16 in #62
• Feat/enterprise drift privacy er by @JohnnyWilson16 in #63
• feat(enterprise): jurisdiction-aware privacy policy engine (HIPAA/FERPA/PCI/GDPR) by @JohnnyWilson16 in #64
• feat(execution): production-grade Spark backend + shared audit contract across engines by @JohnnyWilson16 in #65
• Add time-series and streaming-aware cleaning modes by @JohnnyWilson16 in #66
• Probabilistic dedupe subsystem: review queue, clerical feedback, golden records by @JohnnyWilson16 in #67
• feat: MaskingRule token alias, retention_days/policy_id, auditable policy_provenance by @JohnnyWilson16 in #71
• Pr 67 by @JohnnyWilson16 in #74
• feat: ergonomic fd.link wrapper for cross-source entity resolution by @JohnnyWilson16 in #70
• feat: profile_sample/max_columns/lazy_report perf controls on fd.profile by @JohnnyWilson16 in #73
• feat: contract gate on fd.clean/suggest_plan with ContractViolation and schema diff by @JohnnyWilson16 in #68
• Pr 67 by @JohnnyWilson16 in #75
• feat: source_provenance= on fd.clean for OCR/document-extracted table auditing by @JohnnyWilson16 in #72
• feat: CDC event-time quality gate (fd.cdc_profile, CDCReport, CDCDefect) by @JohnnyWilson16 in #69
• Benchmark Release: reproducible harness + enterprise fixtures by @JohnnyWilson16 in #76
• Explainable cleaning layer: honest out-of-core, interactive output, and decision-preserving workflow by @JohnnyWilson16 in #84
• feat(semantic): offline Semantic Cleaning Layer by @JohnnyWilson16 in #85
• feat(semantic): add DatePhraseExpert and retrieval-backed semantic memory by @JohnnyWilson16 in #86
• feat(context): Phase 1 — deterministic NL context policy compiler by @JohnnyWilson16 in #87
• chore: remove dead code found by whole-repo audit by @JohnnyWilson16 in #88
• [codex] refactor minimal public API surface by @Rohith27216 in #89
• Phase 2: deterministic semantic experts, executable repair plans, hard safety gates by @JohnnyWilson16 in #90
• [codex] add optional FreshCore backend by @Rohith27216 in #91
• feat(semantic): Phase 3 — optional local semantic model backend by @JohnnyWilson16 in #92
• [codex] Add MissForest imputation by @Rohith27216 in #93
• [codex] Add FreshData insight reports by @Rohith27216 in #94
• Phase 4: learning profiles — paired-data cleaning rules from messy/clean examples by @JohnnyWilson16 in #95
• feat(semantic): native distinct-value semantic path for Polars/DuckDB (Phase 6) by @JohnnyWilson16 in #97
• [codex] Align package install and imputation UX by @Rohith27216 in #96
• feat(cleanbench): public release package, baseline harness, reproducibility gates (Phase 6) by @JohnnyWilson16 in #98
• feat(plugins): entry-point + explicit plugin system for experts, backends, validators (Phase 6) by @JohnnyWilson16 in #99
• docs: rewrite README as a concise project overview by @JohnnyWilson16 in #100
• Launch readiness: streaming policies, release hardening, docs by @JohnnyWilson16 in #101
• docs: add logo asset and fix broken README image reference by @JohnnyWilson16 in #102
• Add freshdata-benchmarks suite by @JohnnyWilson16 in #103
• Add minimal function-first Core API by @JohnnyWilson16 in #104
• fix: restore publishable PyPI name and MissForest indicator correctness by @JohnnyWilson16 in #105
• Feature/freshdata vs pandas benchmark pr by @JohnnyWilson16 in #106
• docs: README refresh + ASV group-agg benchmark update by @JohnnyWilson16 in #107
• ci(release): scheduled PyPI Trusted Publishing release for 2026-07-06 00:00 IST by @JohnnyWilson16 in #108
• release: bump version to 1.1.0 by @JohnnyWilson16 in #109
• fix(release): resolve job crashed importing freshdata without deps by @JohnnyWilson16 in #110

New Contributors

• @JohnnyWilson16 made their first contribution in #1
• @W...

v1.0.0 — first stable release

freshdata-cleaner 1.0.0 — first stable release 🎉

pip install freshdata-cleaner · import freshdata as fd

The public API is now stable under Semantic Versioning — breaking changes will require a 2.0. No behavioral changes versus 0.5.0; the package is promoted to Production/Stable.

Stable surface: fd.clean, fd.profile, fd.suggest_plan, fd.compare_plans, fd.compare_clean, fd.explain_clean, fd.infer_roles, fd.Cleaner, fd.CleanConfig, fd.CleanReport/fd.Action, fd.Profile, and the lazy freshdata.enterprise layer.

Docs: https://freshcode-org.github.io/freshdata/ · Full changelog: https://github.com/FreshCode-Org/freshdata/blob/main/CHANGELOG.md

v0.5.0 — discoverability & docs release

freshdata-cleaner 0.5.0 — discoverability & docs release

Install: pip install freshdata-cleaner · Import: import freshdata as fd

Added

• Documentation site (MkDocs Material) at https://freshcode-org.github.io/freshdata/ — installation, quickstart, cleaning engine, profiling, auto-generated API reference, benchmarks, FAQ, contributing; search, dark/light, OpenGraph, sitemap, robots.
• 8 runnable examples/ + 3 reproducible notebooks/.
• Packaging governance: MANIFEST.in, SECURITY.md, RELEASE.md, .pre-commit-config.yaml, tag-triggered release workflow, docs-deploy workflow, issue-template chooser.
• Expanded PyPI keywords/classifiers + Documentation URL for discoverability.

Notes

• The PyPI distribution name remains freshdata-cleaner (the bare name freshdata is unavailable on PyPI); the import name is freshdata.

Full changelog: https://github.com/FreshCode-Org/freshdata/blob/main/CHANGELOG.md

Release v0.4.0

Release Notes — freshdata-cleaner v0.4.0 (Enterprise)

We are thrilled to announce the official release of freshdata-cleaner version 0.4.0! This release introduces the new Enterprise Layer, designed to extend our rule-based data cleaning engine to larger enterprise data-science workloads, data quality checking, and lineage tracking.

What's New in v0.4.0

1. Enterprise Cleaning Layer (freshdata.enterprise)

• enterprise.Cleaner: Orchestrates large-scale data cleaning pipelines across heterogeneous source types with high-performance execution.
• Lineage Tracking (lineage.py): Automatically maps and tracks the flow and modifications of your columns and values as they pass through the cleaning steps.
• Data Quality Metrics (metrics.py): Calculates statistical profiles, compares distributions, and exports machine-learning-ready data-quality dashboards.

2. Command-Line Interface (CLI)

• A new CLI tool freshdata is now registered on your PATH.
• Supported subcommands:
  • freshdata clean — Clean datasets directly from your terminal.
  • freshdata profile — Profile datasets and print formatting issues.
  • freshdata trust — Run sanity checks and verify schema configurations.

3. CI and Robustness Upgrades

• Upgraded the test coverage threshold constraint to 93% (currently reaching 95.26% coverage over 824 unit tests).
• Adjusted warning filters to cleanly isolate third-party deprecations, ensuring a zero-warning bar for freshdata internal code.
• Relaxed local performance/benchmark baseline check tolerances to ensure test runner stability.

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Installation

pip install freshdata-cleaner==0.4.0