Add architectural plan document for PSD extraction refactoring
Documents the complete analysis, implementation, and results of the PSD extraction refactoring from the architecture advisor's recommendations. Includes: - Problem statement and key insights - Architecture analysis (data-oriented approach) - Implementation phases and results - Testing outcomes and metrics - 227 files migrated, ~40 lines reduced, 220+ → 1-4 requests 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude <noreply@anthropic.com>
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# PSD Extraction Refactoring Plan
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**Status:** ✅ Completed
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**Branch:** `refactor/psd-extraction-r2`
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**Date:** 2025-10-20
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## Problem Statement
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The original PSD extraction implementation downloaded 220+ historical monthly archives from August 2006 to present, storing them in a nested `{year}/{month}/{etag}.zip` directory structure. This approach was overengineered because:
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1. **ETags already provide deduplication** - Each unique data snapshot has a unique ETag
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2. **Historical year/month structure was redundant** - The publication date (year/month) is metadata, not data identity
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3. **No R2 support** - Files could only be stored locally, not in production R2 bucket
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4. **Unnecessary complexity** - Downloading 220+ URLs hoping to find unique ETags when we only need the latest
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## Architecture Analysis
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### Key Insight
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**What does each file represent?**
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USDA publishes monthly snapshots, but most months they re-publish the same data. The ETag tells you when the *actual data* has changed, not when USDA published it. The year/month structure is publication metadata, not data identity.
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### The Data-Oriented Question
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**What do we actually need?**
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We need to capture every unique data snapshot. The ETag already identifies unique snapshots. The current approach downloads 220+ URLs to find unique ETags. The direct approach: check 1 URL (current month), download if new ETag, done.
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## Proposed Solution
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### 1. Simplify to Current-Month-Only Extraction
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**Old approach:**
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```python
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for year in range(2006, today.year+1):
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for month in range(1, 13):
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download(year, month) # 220+ downloads
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```
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**New approach:**
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```python
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# Try current month, fallback 3 months (handles publication lag)
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for months_back in range(4):
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if download_if_exists(today.year, today.month - months_back):
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break
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```
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**Why this works:**
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- ETags naturally deduplicate
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- Historical snapshots already captured from previous runs
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- Only need to check for latest data
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- Same result, 220x less work
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### 2. Flatten Storage Structure
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**Old:** `data/{year}/{month}/{etag}.zip`
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**New:** `data/{etag}.zip` (local) or `landing/psd/{etag}.zip` (R2)
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**Benefits:**
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- ETag is the natural identifier
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- Simpler to manage
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- No nested directory traversal
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- Works identically for local and R2
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### 3. Dual Storage Modes
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**Local Mode (Development):**
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- No R2 credentials → downloads to local directory
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- ETag-based deduplication via file existence check
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- Use case: Local development and testing
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**R2 Mode (Production):**
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- R2 credentials present → uploads to R2 only (no local storage)
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- ETag-based deduplication via S3 HEAD request
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- Use case: Production pipelines on ephemeral workers
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**Mode Detection:**
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```python
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use_r2 = all([R2_ENDPOINT, R2_BUCKET, R2_ACCESS_KEY, R2_SECRET_KEY])
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```
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### 4. R2 Integration
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**Configuration:**
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- Bucket: `beanflows-data-prod`
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- Path: `landing/psd/{etag}.zip`
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- Credentials: Via Pulumi ESC (`beanflows/prod`)
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- Library: boto3 with S3-compatible API
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**Pulumi ESC Environment Variables:**
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- `R2_ENDPOINT`: Account URL (without bucket path)
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- `R2_BUCKET`: `beanflows-data-prod`
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- `R2_ADMIN_ACCESS_KEY_ID`: Access key (fallback from R2_ACCESS_KEY)
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- `R2_ADMIN_SECRET_ACCESS_KEY`: Secret key (fallback from R2_SECRET_KEY)
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## Implementation Summary
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### Phase 1: Simplify Extraction ✅
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- Changed loop from 220+ historical downloads to current month check
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- Added fallback logic (tries 4 months back for publication lag)
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- Flattened storage to `{etag}.zip`
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- Updated raw SQLMesh model pattern to `*.zip`
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### Phase 2: Add R2 Support ✅
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- Added boto3 dependency
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- Implemented R2 upload with ETag deduplication
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- Added support for ESC variable names
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- Updated Pulumi ESC environment with R2_BUCKET and fixed R2_ENDPOINT
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### Phase 3: Historical Migration ✅
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- Created temporary script to upload 227 existing files to R2
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- All files now in `landing/psd/*.zip`
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- Verified deduplication works on both local and R2
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### Phase 4: Documentation ✅
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- Updated CLAUDE.md with Pulumi ESC usage guide
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- Fixed supervisor bootstrap documentation (automatic in CI/CD)
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- Added examples for running commands with ESC secrets
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## Benefits Achieved
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1. **Simplicity:** Single file check instead of 220+ URL attempts
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2. **Efficiency:** ETag-based deduplication works naturally
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3. **Flexibility:** Supports both local dev and production R2 storage
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4. **Maintainability:** Removed unnecessary complexity
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5. **Cost Optimization:** Ephemeral workers don't need local storage
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6. **Data Consistency:** All historical data now in R2 landing bucket
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## Testing Results
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✅ Local extraction works and respects ETags
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✅ R2 upload works (tested with Sept 2025 data)
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✅ R2 deduplication works (skips existing files)
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✅ Fallback logic works (tries current month, falls back to Sept)
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✅ Historical migration completed (227 files uploaded)
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✅ All linting passes
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## Metrics
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- **Code reduction:** ~40 lines removed, ~80 lines added (net +40 for R2 support)
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- **Download efficiency:** 220+ requests → 1-4 requests
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- **Storage structure:** Nested 3-level → Flat 1-level
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- **Files migrated:** 227 historical files to R2
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- **Time to migrate:** ~2 minutes for 227 files (~2.3 GB)
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## Next Steps
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1. Update SQLMesh raw model to support reading from R2 (future work)
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2. Merge branch to master
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3. Deploy to production
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4. Monitor daily extraction runs
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## References
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- Architecture pattern: Data-oriented design (identify data by content, not metadata)
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- Inspiration: ETag-based caching patterns
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- Storage: Cloudflare R2 (S3-compatible object storage)
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