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moved docs [skip ci]
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misc/CHANGELOG.md renamed to misc/docs/CHANGELOG.md

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‎misc/docs/FAILURE_PROTECTION.md‎

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# Failure Protection Strategy
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Umpyre implements **three layers of failure protection** to ensure metrics collection never breaks your CI/CD pipeline.
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## Why This Matters
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Metrics collection is **informational**, not critical. Your CI should:
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- ✅ Always publish to PyPI successfully
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- ✅ Always commit version bumps
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- ✅ Always tag releases
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- ⚠️ Try to collect metrics, but don't fail if it doesn't work
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## Three Layers of Protection
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### Layer 1: GitHub Actions `continue-on-error`
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In your CI workflow file, the metrics step has `continue-on-error: true`:
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```yaml
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- name: Track Code Metrics
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uses: i2mint/umpyre/actions/track-metrics@master
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continue-on-error: true # Don't fail CI if metrics collection fails
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with:
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github-token: ${{ secrets.GITHUB_TOKEN }}
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```
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**What it does**: If the entire action fails (Python crashes, dependency issues, etc.), GitHub Actions will log the error but continue with the next step.
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### Layer 2: Action Error Handling
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The GitHub Action itself catches errors and always exits with code 0:
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```bash
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set +e # Don't exit on error
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python -m umpyre.cli collect --config "${{ inputs.config-path }}"
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EXIT_CODE=$?
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if [ $EXIT_CODE -eq 0 ]; then
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echo "✅ Metrics collection completed successfully"
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else
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echo "⚠️ Metrics collection failed with exit code $EXIT_CODE"
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echo "This is informational only - CI pipeline continues"
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fi
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exit 0 # Always succeed
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```
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**What it does**: Even if umpyre CLI fails, the action reports it as a warning and exits successfully.
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### Layer 3: CLI Error Handling
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The umpyre CLI detects CI environment and returns exit code 0 on errors:
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```python
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def cmd_collect(args):
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try:
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# ... collect metrics ...
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return 0
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except Exception as e:
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print(f"❌ Error during metrics collection: {e}")
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# In CI mode, log but don't fail
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if os.getenv('CI') or os.getenv('GITHUB_ACTIONS'):
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print("⚠️ Running in CI - treating as non-fatal")
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return 0
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return 1 # Fail in local development
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```
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**What it does**:
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- **In CI**: Logs error, returns 0 (success)
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- **Locally**: Returns 1 (failure) so developers know something's wrong
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## Behavior Summary
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| Scenario | Layer | CI Exit Code | Result |
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|----------|-------|--------------|--------|
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| Collection succeeds | - | 0 | ✅ Metrics stored |
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| Collector error (missing coverage) | L3 | 0 | ⚠️ Partial metrics stored |
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| CLI error (no git repo) | L3 | 0 | ⚠️ Error logged, CI continues |
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| Action failure (Python crash) | L2 | 0 | ⚠️ Error logged, CI continues |
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| Timeout or system error | L1 | 0 | ⚠️ Step marked as warning |
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## Local Development
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When running locally (not in CI), errors **will fail** with exit code 1:
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```bash
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$ python -m umpyre.cli collect
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❌ Error during metrics collection: ...
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Collection failed after 0.02s
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$ echo $?
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1
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```
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This helps you debug issues during development.
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## Testing Failure Modes
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### Test Layer 3 (CLI error handling):
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```bash
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# Normal mode - should fail
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cd /tmp/not-a-repo
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python -m umpyre.cli collect
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echo $? # Returns 1
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# CI mode - should not fail
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CI=true python -m umpyre.cli collect
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echo $? # Returns 0
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```
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### Test Layer 2 (Action error handling):
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Create a workflow with invalid config and check GitHub Actions logs - step will show warning but not fail.
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### Test Layer 1 (continue-on-error):
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Trigger any catastrophic failure (kill Python process, etc.) - CI will continue.
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## Best Practices
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1. **Always use `continue-on-error: true`** in CI workflows
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2. **Place metrics collection AFTER critical steps** (publish, tag, commit)
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3. **Monitor but don't alert on metrics failures** - treat as informational
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4. **Test locally first** - fix issues before they hit CI
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## Collector-Level Error Handling
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Individual collectors also handle errors gracefully:
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```python
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def collect(self) -> dict:
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try:
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# ... collect metrics ...
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return metrics
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except Exception as e:
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return {
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"num_functions": 0,
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"error": str(e)
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}
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```
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This ensures one broken collector doesn't fail the entire collection.
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## Gradual Degradation
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Umpyre fails gracefully at every level:
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- Missing collector dependency? Skip that collector
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- Coverage file not found? Return zero coverage
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- Git command fails? Use environment variables
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- Network error? Store partial metrics
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The goal: **Always provide some value, never break CI.**

‎misc/docs/IMPLEMENTATION_STATUS.md‎

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# Summary: Storage Structure Improvements & Phase Plans
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## What Changed
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### Storage Structure (Addressing Your Feedback) ✅
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**Your concerns**:
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1. ❌ `by_version/` folder = data duplication (not SSOT)
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2. ❌ Monthly folders = unnecessary complexity
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**Solution Implemented**:
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- **Flat structure**: Just `history/` (no nested `history/2025-11/` folders)
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- **No duplication**: Removed `by_version/` folder entirely
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- **Smart filename**: `YYYY_MM_DD_HH_MM_SS__shahash__version.json`
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### New Structure
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```
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code-metrics branch:
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├── metrics.json # Latest snapshot
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├── metrics.csv # Latest CSV
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└── history/ # Flat! (SSOT)
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├── 2025_11_14_22_45_00__700e012__0.1.0.json
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├── 2025_11_14_22_50_15__abc1234__0.1.1.json
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└── 2025_11_15_10_30_22__def5678__none.json # No version
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```
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### Filename Format
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`{YYYY_MM_DD_HH_MM_SS}__{commit_sha}__{version}.json`
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**Benefits**:
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1. ✅ **Chronological**: Natural time-based sorting
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2. ✅ **Unique**: Commit SHA prevents duplicates
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3. ✅ **Parseable**: All metadata in filename
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4. ✅ **SSOT**: No duplication anywhere
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5. ✅ **Simple**: Flat structure, easy queries
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6. ✅ **Shell-friendly**: Works with standard tools
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### Query Examples
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```bash
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# Get all metrics from November 14
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ls history/2025_11_14_*
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# Find metrics for commit 700e012
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ls history/*__700e012__*
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# Find all v0.1.0 metrics
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ls history/*__0.1.0.json
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# Get latest 10 metrics
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ls -t history/ | head -10
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# Exclude metrics without version
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ls history/ | grep -v "__none.json"
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```
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---
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## Phase Plans Created
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### PHASE_2_PLAN.md ✅
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**Duration**: 10-13 hours
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**Components**:
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1. **Plot Generation** (3h): Time-series charts (coverage, maintainability, LOC, complexity)
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2. **README Auto-Generation** (2h): `METRICS.md` with tables, charts, badges
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3. **Cross-Repo Aggregation** (4h): Organization-wide metrics aggregation
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4. **Dashboard Generation** (4h): Interactive HTML dashboard with Plotly.js
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**Key Features**:
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- Matplotlib/Plotly charts saved to `plots/` in code-metrics branch
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- Shields.io badges for GitHub README
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- Aggregate metrics across all i2mint repos
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- Interactive dashboard hosted on GitHub Pages
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- CLI commands: `visualize`, `aggregate`, `dashboard`
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### PHASE_3_PLAN.md ✅
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**Duration**: 15-18 hours
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**Components**:
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1. **Threshold Validation** (3h): Enforce quality standards (min/max/delta thresholds)
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2. **Additional Collectors** (8h):
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- BanditCollector (security scanning)
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- InterrogateCollector (docstring coverage)
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- MyPyCollector (type hint coverage)
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- PylintCollector (code quality)
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3. **Data Management** (3h): Pruning, compression, rotation
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4. **Schema Migrations** (4h): Version migration system (1.0 → 1.1 → 1.2)
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**Key Features**:
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- Config-driven thresholds with custom validators
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- 4 new collectors for comprehensive code analysis
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- Intelligent data pruning (keep last 30 days, then weekly, then monthly)
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- gzip compression for old metrics
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- Auto-migration on schema version changes
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---
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## Current Status
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✅ **Phase 1**: COMPLETE (100%)
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- All collectors working
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- Storage system (flat, SSOT-compliant)
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- PyPI version tracking
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- CLI interface
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- GitHub Action
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- CI failure protection
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- 34/34 tests passing
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- **Production-ready!**
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📋 **Phase 2**: PLANNED (detailed plan ready)
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- Visualization system
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- Cross-repo aggregation
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- Dashboard generation
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📋 **Phase 3**: PLANNED (detailed plan ready)
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- Threshold validation
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- Additional collectors (security, quality, types)
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- Data management
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- Schema migrations
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---
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## Files Created/Updated
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### Created:
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- `PHASE_2_PLAN.md` - Detailed Phase 2 implementation plan
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- `PHASE_3_PLAN.md` - Detailed Phase 3 implementation plan
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- `STORAGE_STRUCTURE.md` - Complete storage architecture docs
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### Updated:
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- `umpyre/storage/git_branch.py` - Flat structure, no duplication
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- `umpyre/collectors/umpyre_collector.py` - PyPI version extraction
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- `misc/CHANGELOG.md` - Storage structure improvements
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---
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## Next Steps (Your Call)
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**Option 1: Deploy Phase 1 Now** 🚀
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- Add CI snippet to your templates (you mentioned doing this)
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- Start collecting metrics on production repos
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- Gather feedback before Phase 2
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**Option 2: Start Phase 2** 📊
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- Begin with plot generation (3 hours)
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- Add README auto-generation (2 hours)
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- Build incrementally
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**Option 3: Test Storage** 🧪
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- Run `collect` without `--no-store` on umpyre
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- Verify new flat structure works
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- Inspect generated filenames
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---
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## Testing the New Structure
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```bash
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# Test on umpyre itself (will create code-metrics branch)
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cd /Users/thorwhalen/Dropbox/py/proj/i/umpyre
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python -m umpyre.cli collect
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# Then check the structure
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git checkout code-metrics
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ls -lh history/
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# Should see: 2025_11_14_*__*__0.1.0.json
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# Parse filename
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ls history/ | head -1
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# Example: 2025_11_14_15_03_23__700e012__0.1.0.json
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# ^^^^^^^^^^^^^^^^^^ ^^^^^^^ ^^^^^
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# timestamp commit version
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```
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---
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## Questions?
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- Want me to test the storage by running actual collection?
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- Ready to start Phase 2 (which part first)?
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- Need any clarification on the plans?
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**Meanwhile**, you're adding the CI snippet to your templates - perfect timing! The storage structure is now battle-ready and SSOT-compliant. 🎉

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