Update: Project Complete

Author: imann128

.github/workflows/ci.yml

@@ -0,0 +1,45 @@
+name: CI
+
+on:
+  push:
+    branches: [main]
+  pull_request:
+    branches: [main]
+
+jobs:
+  test:
+    name: Test (Python ${{ matrix.python-version }}, ${{ matrix.os }})
+    runs-on: ${{ matrix.os }}
+    strategy:
+      fail-fast: false
+      matrix:
+        os: [ubuntu-latest, windows-latest, macos-latest]
+        python-version: ["3.9", "3.10", "3.11", "3.12", "3.13", "3.14"]
+
+    steps:
+      - name: Check out repository
+        uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install package and dev dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -e ".[dev]"
+
+      - name: Run tests with coverage
+        run: |
+          pytest --cov=tsauditor --cov-report=xml --cov-report=term-missing -v
+
+      - name: Upload coverage to Codecov
+        # Only upload once per matrix run to avoid duplicate/conflicting reports.
+        # ubuntu + the lowest supported Python version is the canonical run.
+        if: matrix.os == 'ubuntu-latest' && matrix.python-version == '3.9'
+        uses: codecov/codecov-action@v4
+        with:
+          file: ./coverage.xml
+          fail_ci_if_error: false
+          token: ${{ secrets.CODECOV_TOKEN }}

.github/workflows/dependabot.yml

@@ -0,0 +1,19 @@
+version: 2
+updates:
+  # Python package dependencies (pandas, numpy, scipy, statsmodels, rich, pytest, etc.)
+  - package-ecosystem: "pip"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+    open-pull-requests-limit: 5
+    labels:
+      - "dependencies"
+
+  # Keep the GitHub Actions themselves (checkout, setup-python, codecov-action) up to date
+  - package-ecosystem: "github-actions"
+    directory: "/"
+    schedule:
+      interval: "weekly"
+    labels:
+      - "dependencies"
+      - "github-actions"

.gitignore

@@ -0,0 +1,29 @@
+# Changelog
+
+All notable changes to this project are documented here. The format is based on
+[Keep a Changelog](https://keepachangelog.com/), and the project adheres to
+[Semantic Versioning](https://semver.org/).
+
+## [Unreleased]
+
+### Added
+- `leakage` module fully implemented: LEK001 (rank-based target equivalence —
+  Spearman for continuous targets, AUC separation for binary), LEK002 (positive-lag
+  cross-correlation), LEK003 (rolling-window lookahead via excess-over-persistence).
+- Test suites for the leakage module: `test_equivalence.py`, `test_correlation.py`,
+  `test_temporal.py`, covering clean/leak/edge cases.
+- Standard repository files: `README.md`, `LICENSE`, `CHANGELOG.md`, CI workflow.
+
+### Fixed
+- ANO003 contextual spike detection no longer self-masks: rolling statistics exclude
+  the current observation, use a wider window, and handle zero-variance context.
+- `scan()` runs end-to-end now that all non-stub modules are implemented; stale
+  scaffold tests updated to assert real behavior.
+- `.gitignore` re-encoded from UTF-16 to UTF-8 so its patterns take effect.
+
+## [0.1.0]
+
+### Added
+- Initial architecture: `profiler`, `anomaly`, `leakage` modules behind a single
+  `tsa.scan()` entry point returning a `GuardReport`.
+- Profiler checks (PRF001–PRF006), point anomalies (ANO002), CLI/JSON report output.

CHANGELOG.md

@@ -0,0 +1,21 @@
+MIT License
+
+Copyright (c) 2026 Iman
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

LICENSE

@@ -0,0 +1,100 @@
+# tsauditor
+
+A data-quality auditing library for **time-series tabular data**, with a focus on
+financial and sensor domains. `tsauditor` scans a `DataFrame` and returns a
+structured report of structural problems, anomalies, and — its core contribution —
+**data-leakage** between features and the prediction target.
+
+The project grew out of a real bug: a same-day percentage-change feature (`ChangeP`)
+was used to predict a direction label derived from the same price, inflating accuracy
+to ~99% until the leaky column was removed and it collapsed to ~52–58%. `tsauditor`
+exists to catch that class of mistake automatically.
+
+## Installation
+
+```bash
+git clone <repo-url>
+cd tsauditor
+pip install -e ".[dev]"
+```
+
+Requires Python ≥ 3.9. Core dependencies: `pandas`, `numpy`, `scipy`, `statsmodels`, `rich`.
+
+## Quickstart
+
+```python
+import tsauditor as tsa
+
+report = tsa.scan(df, target="Direction", domain="finance")
+
+report.summary()                 # rich-formatted CLI table
+report.critical                  # list[Issue] that block modeling
+report.filter(module="leakage")  # programmatic filtering
+report.to_json("report.json")    # structured export
+```
+
+`scan()` returns a `GuardReport` holding `Issue` dataclasses bucketed by severity
+(`critical`, `warnings`, `info`) plus dataset metadata.
+
+## What it checks
+
+| Module | Code | Severity | Detects |
+|--------|------|----------|---------|
+| profiler | PRF001 | warning | Irregular timestamp frequency |
+| profiler | PRF002 | warning | Clustered missing values |
+| profiler | PRF003 | info | Non-stationarity (Augmented Dickey-Fuller) |
+| profiler | PRF004 | warning | Duplicate timestamps |
+| profiler | PRF005 | warning | Clustered gaps |
+| profiler | PRF006 | warning | High overall missing rate |
+| anomaly | ANO001 | warning | Stuck / repeated constant values |
+| anomaly | ANO002 | warning | Point outliers (z-score + IQR) |
+| anomaly | ANO003 | warning | Contextual spikes (local rolling z-score) |
+| leakage | LEK001 | critical | Target equivalence (feature reproduces the target) |
+| leakage | LEK002 | warning | Positive-lag cross-correlation peak (future info) |
+| leakage | LEK003 | warning | Rolling-window lookahead (excess over persistence) |
+
+### Leakage detection (the research core)
+
+Leakage checks are **rank-based**, chosen by target type:
+
+- **LEK001 — equivalence.** Continuous targets use `|Spearman ρ|`; binary targets use
+  **AUC separation** (`max(AUC, 1−AUC)`). This is deliberate: Pearson against a binary
+  0/1 target is point-biserial correlation, which is capped near `√(2/π) ≈ 0.798`, so a
+  feature whose sign *defines* the target scores only ~0.80 and slips under a naive
+  threshold. AUC scores it 1.0.
+- **LEK002 — cross-correlation.** Flags features whose peak association with the target
+  falls at a *positive* lag (the feature aligns with the target's future).
+- **LEK003 — temporal lookahead.** Flags features that correlate with the future target
+  *beyond* what the target's own autocorrelation can explain — the signature of a
+  forward-looking or centered window. The persistence baseline is what keeps a
+  legitimate trailing feature from being false-flagged.
+
+LEK002/LEK003 are WARNING-level *suspicions*: in pure cross-correlation a genuine strong
+predictor and a leak are distinguishable only by magnitude. LEK001 is CRITICAL because
+equivalence is near-deterministic.
+
+## Architecture
+
+```
+tsauditor/
+├── scanner.py          # scan() — orchestrates all modules into a GuardReport
+├── profiler/           # structural checks: frequency, missing, stationarity
+├── anomaly/            # point.py, contextual.py
+├── leakage/            # equivalence.py, correlation.py, temporal.py
+├── report/summary.py   # GuardReport + Issue dataclasses, rich/JSON output
+└── utils/validation.py # input validation & DataFrame normalization
+```
+
+## Testing
+
+```bash
+pytest -q
+```
+
+## Status
+
+Alpha (`0.1.0`). Profiler, anomaly, and leakage modules are implemented and tested.
+
+## License
+
+MIT — see [LICENSE](LICENSE).

README.md

@@ -24,11 +24,11 @@ classifiers = [
     "Topic :: Scientific/Engineering :: Information Analysis",
 ]
 dependencies = [
-    "pandas>=1.5",
-    "numpy>=1.23",
-    "scipy>=1.9",
-    "statsmodels>=0.13",
-    "rich>=13.0",
+    "pandas>=1.5,<3",
+    "numpy>=1.23,<3",
+    "scipy>=1.9,<2",
+    "statsmodels>=0.13,<1",
+    "rich>=13.0,<15",
 ]
 
 [project.optional-dependencies]
@@ -43,3 +43,17 @@ include = ["tsauditor*"]
 
 [tool.pytest.ini_options]
 testpaths = ["tests"]
+
+[tool.coverage.run]
+source = ["tsauditor"]
+omit = [
+    "tsauditor/__pycache__/*",
+]
+
+[tool.coverage.report]
+exclude_lines = [
+    "pragma: no cover",
+    "raise NotImplementedError",
+    "if __name__ == .__main__.:",
+]
+show_missing = true