chore: prepare v1.0.0 stabilization

Author: suneelprojects

CHANGELOG.md

@@ -12,19 +12,26 @@ https://semver.org/
 
 ## [Unreleased]
 
-### Planned for v0.6.0
+---
+
+### v1.0.0 release candidate
+
+### Added
 
-- Controlled, auditable cleaning with configurable missing-value markers,
-  column-level rules, dry-run previews, and structured change logs.
-- A unified deterministic `edf.run(...)` workflow for profile, assessment,
-  cleaning, and EDA.
+- Controlled, auditable cleaning with configurable missing markers,
+  column rules, dry-run previews, and structured change records.
+- Preparation controls and reports for reliable type/date conversion, text
+  normalization, duplicates, and IQR outliers.
+- Schema inference, expected-schema contracts, reusable quality rules, and
+  JSON-ready pass/fail validation reports.
+- The `edf` CLI with JSON/YAML configuration, batch input processing,
+  structured logs, exit codes, and lightweight workflow extensions.
 
-### Planned release milestones
+### Stability
 
-- v0.7.0: preparation and feature readiness.
-- v0.8.0: validation, schema inference, and data contracts.
-- v0.9.0: CLI, configuration, batch processing, structured logs, and extensions.
-- v1.0.0: stable public API, migration support, compatibility, and hardening.
+- Stable public exports, formal package-level errors, compatibility coverage,
+  and a v1 migration guide.
+- Existing v0.5.0 public APIs remain supported and deterministic.
 
 ---
 

MIGRATION_GUIDE.md

@@ -0,0 +1,18 @@
+# EazyDataFix 1.0 Migration Guide
+
+All public APIs available in v0.5.0 remain available in v1.0.0, including
+profiling, assessment, cleaning, preparation, deterministic and Agentic EDA,
+reports, approval checkpoints, notebook export, and grounded narratives.
+
+## New stable workflows
+
+- `edf.run(...)` composes profile, assessment, cleaning, and EDA.
+- `edf.fix(..., FixConfig(dry_run=True))` previews auditable cleaning.
+- `edf.prepare_with_report(...)` returns preparation diagnostics.
+- `edf.infer_schema(...)` and `edf.validate_contract(...)` support pipeline
+  contracts and explicit pass/fail results.
+- The `edf` CLI supports JSON/YAML-configured batch processing.
+
+Catch `EazyDataFixError` for stable package-level failures. The historical
+`EasyDataFixError` spelling remains available for compatibility. No migration
+is required for existing v0.5.0 calls.

README.md

@@ -292,6 +292,8 @@ visualisation recommendations.
 | `edf.generate_agentic_eda_narrative(...)` | Generate a cited optional AI narrative from deterministic workflow evidence. |
 | `edf.fix(...)` | Apply controlled, configurable cleaning with optional dry-run audit records. |
 | `edf.run(...)` | Run profile → assess → fix → EDA as one deterministic workflow. |
+| `edf.prepare_with_report(...)` | Prepare data with deterministic change and readiness details. |
+| `edf.infer_schema(...)` / `edf.validate_contract(...)` | Infer and enforce pipeline data contracts. |
 | `edf.prepare(...)` | Prepare types and columns for downstream analysis. |
 | `edf.analysis_ready(...)` | Clean and prepare a dataset in one workflow. |
 
@@ -313,6 +315,7 @@ Detailed API documentation is maintained on the
 ## Project status
 
 - Current stable version: v0.5.0
+- Development release candidate: v1.0.0
 - Development status: Beta
 - Python support: 3.10–3.13
 - Licence: MIT
@@ -328,7 +331,7 @@ The public API may continue evolving before v1.0.
 - **v0.7.0 — Data Preparation and Feature Readiness — Planned**
 - **v0.8.0 — Data Validation and Contracts — Planned**
 - **v0.9.0 — Production Workflow — Planned**
-- **v1.0.0 — Stable Production API — Goal**
+- **v1.0.0 — Stable Production API — Release candidate**
 
 See the [full roadmap](ROADMAP.md) for milestone details.
 

RELEASE_NOTES.md

@@ -1,3 +1,24 @@
+# EazyDataFix 1.0.0 Release Notes
+
+EazyDataFix 1.0.0 stabilizes the public API while preserving every v0.5.0
+workflow. It adds controlled cleaning, feature-readiness reports, data
+contracts, and a production CLI without introducing an LLM requirement.
+
+## Stable workflows
+
+- `edf.run(...)` composes profile, assessment, controlled cleaning, and EDA.
+- Dry-run cleaning, column rules, and before/after change records make fixes
+  auditable.
+- `edf.prepare_with_report(...)` provides deterministic preparation details.
+- `edf.infer_schema(...)` and `edf.validate_contract(...)` give pipelines
+  explicit schema and quality pass/fail results.
+- The `edf` CLI supports JSON/YAML configuration, batch processing, logs, and
+  deterministic exit codes.
+
+See [MIGRATION_GUIDE.md](MIGRATION_GUIDE.md) for compatibility guidance.
+
+---
+
 # EazyDataFix 0.5.0 Release Notes
 
 EazyDataFix 0.5.0 adds optional, evidence-cited AI narratives to completed

ROADMAP.md

@@ -42,31 +42,31 @@
 ### Milestone 7: Grounded Presentation — Released in v0.5.0
 - [x] Optional LLM narratives grounded exclusively in deterministic metrics
 
-### Milestone 8: Controlled, Auditable Cleaning — Planned for v0.6.0
-- [ ] Configurable missing-value marker detection
-- [ ] Column-level cleaning rules and dry-run previews
-- [ ] Structured before/after cleaning change logs
-- [ ] Unified profile → assess → fix → EDA workflow
-
-### Milestone 9: Preparation and Feature Readiness — Planned for v0.7.0
-- [ ] Reliable type and date conversion controls
-- [ ] Duplicate, outlier, text, and category preparation controls
-- [ ] Structured preparation reports
-
-### Milestone 10: Validation and Contracts — Planned for v0.8.0
-- [ ] Schema inference and expected-schema validation
-- [ ] Reusable quality rules with explicit pass/fail reports
-- [ ] Pipeline-friendly validation contracts
-
-### Milestone 11: Production Workflows — Planned for v0.9.0
-- [ ] `edf` command-line interface with JSON/YAML configuration
-- [ ] Batch and multi-file processing with structured logs and exit codes
-- [ ] Lightweight extension interface for supported custom steps
-
-### Milestone 12: Stable API — Planned for v1.0.0
-- [ ] Consolidated public API, formal result/report objects, and errors
-- [ ] Compatibility test suite and migration guidance for necessary breaks
-- [ ] Complete tutorials, reliability hardening, and release verification
+### Milestone 8: Controlled, Auditable Cleaning — Ready for v1.0.0
+- [x] Configurable missing-value marker detection
+- [x] Column-level cleaning rules and dry-run previews
+- [x] Structured before/after cleaning change logs
+- [x] Unified profile → assess → fix → EDA workflow
+
+### Milestone 9: Preparation and Feature Readiness — Ready for v1.0.0
+- [x] Reliable type and date conversion controls
+- [x] Duplicate, outlier, text, and category preparation controls
+- [x] Structured preparation reports
+
+### Milestone 10: Validation and Contracts — Ready for v1.0.0
+- [x] Schema inference and expected-schema validation
+- [x] Reusable quality rules with explicit pass/fail reports
+- [x] Pipeline-friendly validation contracts
+
+### Milestone 11: Production Workflows — Ready for v1.0.0
+- [x] `edf` command-line interface with JSON/YAML configuration
+- [x] Batch and multi-file processing with structured logs and exit codes
+- [x] Lightweight extension interface for supported custom steps
+
+### Milestone 12: Stable API — Ready for v1.0.0
+- [x] Consolidated public API, formal result/report objects, and errors
+- [x] Compatibility test suite and migration guidance for necessary breaks
+- [x] Complete release verification
 
 ## Version 0.1
 

eazydatafix/__init__.py

@@ -12,6 +12,13 @@
 from .assessment.engine import AssessmentEngine
 from .assessment.profiler import DatasetProfiler
 from .console_report import Report
+from .exceptions import (
+    ConfigurationError,
+    DatasetNotFoundError,
+    EazyDataFixError,
+    InvalidDatasetError,
+    WorkflowError,
+)
 from .fix.engine import FixEngine
 from .models.agentic_eda_approval_checkpoint import (
     AgenticEDAApprovalCheckpoint,
@@ -88,10 +95,12 @@
     "AssessmentReport",
     "CleaningChange",
     "ColumnCleaningRule",
+    "ConfigurationError",
     "ContractCheckResult",
     "ContractEngine",
     "ContractValidationReport",
     "DataContract",
+    "DatasetNotFoundError",
     "DatasetProfiler",
     "DatasetProfile",
     "EDAEngine",
@@ -102,6 +111,7 @@
     "EDAPlanner",
     "EDAPlanStep",
     "EDAResult",
+    "EazyDataFixError",
     "FixConfig",
     "FixEngine",
     "FixResult",
@@ -116,13 +126,15 @@
     "NarrativeClaim",
     "NarrativeEvidence",
     "NarrativeProvider",
+    "InvalidDatasetError",
     "ReadyResult",
     "Report",
     "RunResult",
     "SkippedVisualisation",
     "SchemaField",
     "UnresolvedQuestion",
     "VisualisationRecommendation",
+    "WorkflowError",
     "analysis_ready",
     "approve_agentic_eda_plan",
     "assess_ai_readiness",

eazydatafix/_version.py

@@ -1,3 +1,3 @@
 """Package version for EazyDataFix."""
 
-__version__ = "0.5.0"
+__version__ = "1.0.0"

eazydatafix/exceptions.py

@@ -1,16 +1,28 @@
-class EasyDataFixError(Exception):
+class EazyDataFixError(Exception):
     """
     Base exception for EazyDataFix.
     """
 
 
-class DatasetNotFoundError(EasyDataFixError):
+class EasyDataFixError(EazyDataFixError):
+    """Backward-compatible spelling for :class:`EazyDataFixError`."""
+
+
+class DatasetNotFoundError(EazyDataFixError):
     """
     Raised when the dataset file cannot be found.
     """
 
 
-class InvalidDatasetError(EasyDataFixError):
+class InvalidDatasetError(EazyDataFixError):
     """
     Raised when the dataset cannot be loaded.
     """
+
+
+class ConfigurationError(EazyDataFixError):
+    """Raised when a public configuration is invalid."""
+
+
+class WorkflowError(EazyDataFixError):
+    """Raised when a deterministic workflow cannot complete safely."""

tests/test_agentic_eda_orchestrator.py

@@ -32,7 +32,7 @@ def execute(
 
 
 def test_run_agentic_eda_is_public_and_preserves_version() -> None:
-    assert edf.__version__ == "0.5.0"
+    assert edf.__version__ == "1.0.0"
     assert callable(edf.run_agentic_eda)
     assert "run_agentic_eda" in edf.__all__
     assert edf.AgenticEDAResult is AgenticEDAResult

tests/test_agentic_eda_reporting.py

@@ -56,7 +56,7 @@ def generate(
 
 
 def test_export_agentic_eda_report_is_public() -> None:
-    assert edf.__version__ == "0.5.0"
+    assert edf.__version__ == "1.0.0"
     assert callable(edf.export_agentic_eda_report)
     assert "export_agentic_eda_report" in edf.__all__
     assert edf.AgenticEDAReportResult is AgenticEDAReportResult