Track .codeflash/ data: unignore observability and add krrt7/odoo case study
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Kevin Turcios
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234
.codeflash/krrt7/odoo/HANDOFF.md
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234
.codeflash/krrt7/odoo/HANDOFF.md
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# Optimization Session Handoff
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**Session ID**: codeflash-20260413-01
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**Domain**: Deep (cross-domain analysis)
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**Branch**: codeflash/optimize
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**Start time**: 2026-04-13
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## Project Context
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**Project**: Odoo ERP Framework
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- Large Python-based ERP system
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- Uses Pillow for image processing
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- Performance-critical: image resizing, format conversion, thumbnail generation
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- Python 3.14.3, pip-based installation
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## Baseline Profile
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**Target**: Image processing operations (benchmark_image.py)
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- Operations: resize 2048x2048→512x512, thumbnail generation, format conversion (PNG→JPEG→PNG), base64 encoding
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- Iterations: 5x each operation
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### CPU Profile Results
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**Total runtime**: 5.481 seconds
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**Top hotspots by cumulative time:**
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1. `Image.resize()` - 3.27s (60%)
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- `ImagingCore.resize` (C extension) - 1.86s actual work
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2. `Image.save()` - 1.92s (35%)
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- `ImagingDecoder.decode` - 1.33s
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- `ImagingEncoder.encode` - 0.64s
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3. Module imports - 1.11s (20% - overlaps with above)
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- PIL module loading overhead
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**Top hotspots by self time:**
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1. `ImagingCore.resize` - 1.86s (C extension, not optimizable)
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2. `ImagingDecoder.decode` - 1.33s (C extension, not optimizable)
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3. `ImagingEncoder.encode` - 0.64s (C extension, not optimizable)
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4. `PngImagePlugin._save` - 0.067s
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5. `benchmark_image.create_test_image` - 0.060s
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6. `Image.load` - 0.052s (566 calls)
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### Memory Profile Results
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**Peak memory**: 3.1 MiB
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**Current memory**: 2.8 MiB
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**Top allocations:**
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1. importlib bootstrap - 939 KiB (module loading)
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2. PIL PngImagePlugin - 55.6 KiB
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3. PIL ImageFile - 41.3 KiB
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4. benchmark code - 21.0 KiB
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## Cross-Domain Analysis
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### CPU ↔ Memory Interactions
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**Import overhead (Structure × CPU × Memory)**
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- 1.11s CPU time in module imports
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- 939 KiB memory in importlib bootstrap
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- All PIL image format plugins are eagerly loaded even if not used
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- **Opportunity**: Defer imports of unused image formats
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**Image object creation (CPU × Memory)**
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- `create_test_image()` uses `putpixel()` in a loop (477 calls, 0.014s)
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- Each putpixel call crosses Python↔C boundary
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- **Opportunity**: Use array-based approaches or batch operations
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**Image load calls (CPU)**
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- 566 calls to `Image.load()` taking 0.052s total
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- Many redundant load checks
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- **Opportunity**: Cache loaded state or reduce redundant loads
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### I/O Bottlenecks
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**PIL I/O operations:**
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- Encoding/decoding happens in C extensions (not optimizable directly)
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- BUT: Multiple encode/decode cycles in format conversion
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- **Opportunity**: Avoid unnecessary format round-trips
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**Base64 operations:**
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- Not profiled separately in this run
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- Need deeper analysis
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## Optimization Targets
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### High-Priority (Cross-Domain)
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1. **Defer PIL plugin imports** (Structure + CPU + Memory)
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- Current: All image format plugins load eagerly
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- Target: `Image.preinit()` call and plugin loading
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- Expected: -1.1s CPU, -939 KiB memory
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- Domain: Structure (import time optimization)
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2. **Optimize test image creation** (CPU)
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- Current: 477 `putpixel()` calls, 0.060s total
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- Target: `create_test_image()` function
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- Use array/buffer approach instead of per-pixel calls
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- Expected: -0.040s CPU
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- Domain: CPU (algorithmic)
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3. **Reduce redundant Image.load() calls** (CPU)
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- Current: 566 calls, 0.052s
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- Target: Image loading logic
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- Expected: -0.030s CPU
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- Domain: CPU (caching/memoization)
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### Medium-Priority
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4. **Optimize format conversion pipeline** (CPU)
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- Current: PNG→JPEG→PNG involves multiple encode/decode cycles
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- Investigate if intermediate formats can be avoided
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- Expected: -0.2s CPU
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- Domain: CPU (algorithmic)
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5. **BytesIO buffer management** (Memory)
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- Multiple BytesIO objects created/destroyed
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- Investigate buffer reuse
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- Expected: Small memory win
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- Domain: Memory
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### Out of Scope
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- Core PIL C extensions (resize, encode, decode) - already optimized
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- PNG compression algorithm - external library
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## Next Steps
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1. **Experiment 1**: Defer PIL plugin imports
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- Modify `benchmark_image.py` to selectively import only needed formats
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- Remove `Image.preinit()` call
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- Re-profile and measure impact
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2. **Experiment 2**: Optimize image creation using numpy/array interface
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- Replace per-pixel `putpixel()` with array-based approach
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- Measure CPU improvement
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3. **Experiment 3**: Investigate Image.load() redundancy
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- Add caching or state tracking to reduce load calls
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## Key Discoveries
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1. **PIL is already well-optimized**: Core operations are in C extensions and perform well
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2. **Import overhead is significant**: 20% of runtime spent loading modules
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3. **Python↔C boundary costs**: Per-pixel operations (putpixel) are expensive due to call overhead
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4. **Low memory footprint**: PIL's C extensions keep memory usage minimal (3.1 MiB peak)
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## Constraints
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- Must maintain compatibility with PIL API
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- Cannot modify PIL internals (external library)
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- Must preserve image quality and correctness
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- No guard command specified - will verify with manual inspection
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## Experiment Log
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### Experiment 1: Replace putpixel with numpy arrays (DISCARDED)
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**Hypothesis**: Using numpy arrays for image creation would be faster than per-pixel PIL operations.
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**Implementation**: Replaced `img.putpixel()` loop with `np.full()` + `Image.fromarray()`.
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**Results**:
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- CPU: 5.481s → 6.075s (+0.594s, **11% SLOWER**)
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- Memory: 3.1 MiB → 13.5 MiB peak (**4.4x WORSE**)
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- New bottleneck: `numpy.full()` at 0.615s
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**Root cause**:
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- numpy creates large intermediate arrays (12.5 MB for 2048x2048x3)
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- PIL's native C-level operations are already optimal
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- The original putpixel loop only cost 0.014s (0.26% of runtime), not worth optimizing
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**Decision**: DISCARD - This is a regression, not an optimization.
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**Key learning**: "Obvious" optimizations can backfire. Always profile after changes. PIL's C extensions are highly optimized - avoid introducing Python/numpy overhead.
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## Current Status
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**Branch**: codeflash/optimize
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**Experiments**: 1 attempted, 1 discarded
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**Improvements**: None yet
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**Analysis**: The target workload (PIL image operations) is dominated by C extension calls that cannot be optimized from Python:
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- 60% of runtime: PIL C extension resize operation
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- 35% of runtime: PIL C extension encode/decode operations
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- Only 5% of runtime in Python code, mostly import overhead
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**Conclusion**: This specific workload (image processing with PIL) has limited optimization potential because:
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1. Core operations are already in optimized C extensions
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2. The Python wrapper code is minimal
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3. Import overhead could be reduced but requires structural changes to how PIL is loaded
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**Recommendation**: For meaningful performance gains on Odoo, we should target different subsystems:
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- Database query optimization (ORM operations)
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- Business logic computation
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- Template rendering
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- Cache management
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These areas have more Python code and optimization opportunities.
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## Session Resume - New Target Identified
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**Date**: 2026-04-13 (continued)
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**New Strategy**: Target actual Odoo Python code instead of C-extension-heavy PIL operations
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### Scan Results
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Identified cache key computation in `odoo/tools/cache.py` as HIGH PRIORITY target:
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**Benchmark Results** (.codeflash/benchmark_cache_keys.py):
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- Key function lookups: 0.42-1.33 µs per call (fast, not a bottleneck)
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- Key function creation: **1656 µs per call** (VERY SLOW - 16.5s for 10k creations)
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**Profile Results** (.codeflash/profile_cache_keys.py):
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- `eval()`: 13.8s (42% of runtime) - expensive dynamic compilation
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- `inspect.signature()`: 12.0s (37% of runtime) - heavyweight introspection
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- String operations: 5.0s (15% of runtime) - join/genexpr overhead
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**Root Cause**: `ormcache.determine_key()` uses:
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1. `inspect.signature()` to introspect method parameters (runs every time)
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2. String building to create lambda code
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3. `eval()` to compile the lambda from string
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**Optimization Opportunities**:
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1. Cache signature inspection results (avoid repeated introspection)
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2. Replace eval() with closure or pre-compiled approach
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3. Optimize string building or bypass it entirely
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This is **pure Python algorithmic work** with clear optimization potential.
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## Next Steps
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Profile the cache module in a real workload context and implement optimizations to:
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- Reduce `determine_key()` overhead
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- Test impact on actual Odoo operations that create many cached methods
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88
.codeflash/krrt7/odoo/benchmark_cache_keys.py
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88
.codeflash/krrt7/odoo/benchmark_cache_keys.py
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#!/usr/bin/env python3
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"""
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Benchmark for cache key computation in odoo/tools/cache.py
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Focuses on the determine_key() and key() methods which are pure Python.
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"""
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import time
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from inspect import signature, Parameter
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# Simulate the key computation logic from ormcache
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def build_cache_key_eval(method, cache_args):
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"""Current implementation using eval - generates lambda from string"""
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args = ', '.join(
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str(params.replace(annotation=Parameter.empty))
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for params in signature(method).parameters.values()
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)
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values = ['self._name', 'method', *cache_args]
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code = f"lambda {args}: ({''.join(a for arg in values for a in (arg, ','))})"
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return eval(code, {'method': method})
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# Test methods with various signatures
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class MockModel:
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_name = 'test.model'
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def simple_method(self, arg1, arg2):
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return arg1 + arg2
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def complex_method(self, model_name, mode="read", limit=None, offset=0):
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return f"{model_name}:{mode}:{limit}:{offset}"
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def many_args_method(self, a, b, c, d, e, f, g, h):
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return sum([a,b,c,d,e,f,g,h])
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def benchmark_key_computation():
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"""Benchmark the key computation overhead"""
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model = MockModel()
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print("=== Cache Key Computation Benchmark ===\n")
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# Scenario 1: Simple method, many lookups
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print("Scenario 1: Simple method (2 args), 100k lookups")
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key_func = build_cache_key_eval(MockModel.simple_method, ['arg1', 'arg2'])
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start = time.perf_counter()
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for i in range(100_000):
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_ = key_func(model, i, i*2)
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elapsed = time.perf_counter() - start
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print(f" Total: {elapsed:.3f}s")
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print(f" Per call: {elapsed/100_000*1e6:.2f} µs\n")
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# Scenario 2: Complex method with defaults, many lookups
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print("Scenario 2: Complex method (4 args with defaults), 100k lookups")
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key_func = build_cache_key_eval(
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MockModel.complex_method,
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['model_name', 'mode', 'limit', 'offset']
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)
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start = time.perf_counter()
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for i in range(100_000):
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_ = key_func(model, 'res.partner', 'read', 10, i)
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elapsed = time.perf_counter() - start
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print(f" Total: {elapsed:.3f}s")
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print(f" Per call: {elapsed/100_000*1e6:.2f} µs\n")
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# Scenario 3: Many args method
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print("Scenario 3: Many args method (8 args), 100k lookups")
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key_func = build_cache_key_eval(
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MockModel.many_args_method,
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['a', 'b', 'c', 'd', 'e', 'f', 'g', 'h']
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)
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start = time.perf_counter()
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for i in range(100_000):
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_ = key_func(model, 1, 2, 3, 4, 5, 6, 7, 8)
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elapsed = time.perf_counter() - start
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print(f" Total: {elapsed:.3f}s")
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print(f" Per call: {elapsed/100_000*1e6:.2f} µs\n")
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# Scenario 4: Key function creation overhead
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print("Scenario 4: Key function creation (determine_key), 10k methods")
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start = time.perf_counter()
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for i in range(10_000):
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_ = build_cache_key_eval(MockModel.simple_method, ['arg1', 'arg2'])
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elapsed = time.perf_counter() - start
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print(f" Total: {elapsed:.3f}s")
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print(f" Per call: {elapsed/10_000*1e6:.2f} µs\n")
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if __name__ == '__main__':
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benchmark_key_computation()
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154
.codeflash/krrt7/odoo/benchmark_image.py
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.codeflash/krrt7/odoo/benchmark_image.py
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#!/usr/bin/env python3
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"""
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Benchmark for Odoo image processing utilities.
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Tests resize, format conversion, and thumbnail generation.
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"""
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import sys
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import os
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import io
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import timeit
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from PIL import Image
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import base64
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# Add odoo to path
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sys.path.insert(0, '/Users/krrt7/Desktop/work/odoo_org/odoo')
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# Activating venv programmatically by modifying path
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venv_site_packages = '/Users/krrt7/Desktop/work/odoo_org/odoo/venv/lib/python3.14/site-packages'
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if os.path.exists(venv_site_packages):
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sys.path.insert(0, venv_site_packages)
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try:
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from odoo.tools import image
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except ImportError as e:
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print(f"Failed to import odoo.tools.image: {e}")
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print("This benchmark will run PIL operations directly.")
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image = None
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def create_test_image(width=2048, height=2048):
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"""Create a test image in memory."""
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img = Image.new('RGB', (width, height), color='red')
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# Add some complexity
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for i in range(0, width, 100):
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for j in range(0, height, 100):
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img.putpixel((i, j), (0, 255, 0))
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buffer = io.BytesIO()
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img.save(buffer, format='PNG')
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return buffer.getvalue()
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def benchmark_resize_pil(image_data, target_size=(512, 512)):
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"""Benchmark PIL resize operation."""
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img = Image.open(io.BytesIO(image_data))
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img_resized = img.resize(target_size, Image.Resampling.LANCZOS)
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buffer = io.BytesIO()
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img_resized.save(buffer, format='PNG')
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return buffer.getvalue()
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def benchmark_thumbnail_pil(image_data, max_size=(256, 256)):
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"""Benchmark PIL thumbnail operation."""
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img = Image.open(io.BytesIO(image_data))
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img.thumbnail(max_size, Image.Resampling.LANCZOS)
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buffer = io.BytesIO()
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img.save(buffer, format='PNG')
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return buffer.getvalue()
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def benchmark_format_conversion(image_data):
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"""Benchmark format conversion (PNG -> JPEG -> PNG)."""
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img = Image.open(io.BytesIO(image_data))
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# Convert to JPEG
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buffer_jpeg = io.BytesIO()
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img_rgb = img.convert('RGB')
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img_rgb.save(buffer_jpeg, format='JPEG', quality=85)
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# Convert back to PNG
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img2 = Image.open(io.BytesIO(buffer_jpeg.getvalue()))
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buffer_png = io.BytesIO()
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img2.save(buffer_png, format='PNG')
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return buffer_png.getvalue()
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def benchmark_base64_operations(image_data):
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"""Benchmark base64 encoding/decoding."""
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encoded = base64.b64encode(image_data)
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decoded = base64.b64decode(encoded)
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return decoded
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def run_benchmarks():
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"""Run all image benchmarks."""
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print("="*80)
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print("Image Processing Benchmark")
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print("="*80)
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# Create test images of different sizes
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test_sizes = [
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(512, 512, "Small (512x512)"),
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(2048, 2048, "Medium (2048x2048)"),
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(4096, 4096, "Large (4096x4096)"),
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]
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results = []
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for width, height, label in test_sizes:
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print(f"\n{label}:")
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print("-" * 40)
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image_data = create_test_image(width, height)
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size_mb = len(image_data) / 1024 / 1024
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print(f"Image size: {size_mb:.2f} MB")
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# Benchmark resize
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time_resize = timeit.timeit(
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lambda: benchmark_resize_pil(image_data, (512, 512)),
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number=10
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) / 10
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print(f"Resize to 512x512: {time_resize*1000:.2f} ms")
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# Benchmark thumbnail
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time_thumbnail = timeit.timeit(
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lambda: benchmark_thumbnail_pil(image_data, (256, 256)),
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number=10
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) / 10
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print(f"Thumbnail to 256x256: {time_thumbnail*1000:.2f} ms")
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# Benchmark format conversion
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time_format = timeit.timeit(
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lambda: benchmark_format_conversion(image_data),
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number=5
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) / 5
|
||||
print(f"Format conversion (PNG->JPEG->PNG): {time_format*1000:.2f} ms")
|
||||
|
||||
# Benchmark base64
|
||||
time_base64 = timeit.timeit(
|
||||
lambda: benchmark_base64_operations(image_data),
|
||||
number=100
|
||||
) / 100
|
||||
print(f"Base64 encode/decode: {time_base64*1000:.2f} ms")
|
||||
|
||||
results.append({
|
||||
'size': label,
|
||||
'image_mb': size_mb,
|
||||
'resize_ms': time_resize * 1000,
|
||||
'thumbnail_ms': time_thumbnail * 1000,
|
||||
'format_ms': time_format * 1000,
|
||||
'base64_ms': time_base64 * 1000,
|
||||
})
|
||||
|
||||
# Summary
|
||||
print("\n" + "="*80)
|
||||
print("SUMMARY")
|
||||
print("="*80)
|
||||
for r in results:
|
||||
print(f"\n{r['size']} ({r['image_mb']:.2f} MB):")
|
||||
print(f" Total processing time: {r['resize_ms'] + r['thumbnail_ms'] + r['format_ms']:.2f} ms")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
run_benchmarks()
|
||||
158
.codeflash/krrt7/odoo/benchmark_image_opt1.py
Normal file
158
.codeflash/krrt7/odoo/benchmark_image_opt1.py
Normal file
|
|
@ -0,0 +1,158 @@
|
|||
#!/usr/bin/env python3
|
||||
"""
|
||||
Benchmark for Odoo image processing utilities - Optimized version 1.
|
||||
Optimization: Use numpy array for efficient image creation instead of per-pixel operations.
|
||||
"""
|
||||
import sys
|
||||
import os
|
||||
import io
|
||||
import timeit
|
||||
from PIL import Image
|
||||
import base64
|
||||
import numpy as np
|
||||
|
||||
# Add odoo to path
|
||||
sys.path.insert(0, '/Users/krrt7/Desktop/work/odoo_org/odoo')
|
||||
|
||||
# Activating venv programmatically by modifying path
|
||||
venv_site_packages = '/Users/krrt7/Desktop/work/odoo_org/odoo/venv/lib/python3.14/site-packages'
|
||||
if os.path.exists(venv_site_packages):
|
||||
sys.path.insert(0, venv_site_packages)
|
||||
|
||||
try:
|
||||
from odoo.tools import image
|
||||
except ImportError as e:
|
||||
print(f"Failed to import odoo.tools.image: {e}")
|
||||
print("This benchmark will run PIL operations directly.")
|
||||
image = None
|
||||
|
||||
|
||||
def create_test_image(width=2048, height=2048):
|
||||
"""Create a test image in memory using numpy for efficiency."""
|
||||
# Create array with red background (RGB)
|
||||
arr = np.full((height, width, 3), [255, 0, 0], dtype=np.uint8)
|
||||
|
||||
# Add green pixels at intervals - use numpy slicing instead of loops
|
||||
arr[::100, ::100] = [0, 255, 0]
|
||||
|
||||
# Convert numpy array to PIL Image
|
||||
img = Image.fromarray(arr, 'RGB')
|
||||
|
||||
buffer = io.BytesIO()
|
||||
img.save(buffer, format='PNG')
|
||||
return buffer.getvalue()
|
||||
|
||||
|
||||
def benchmark_resize_pil(image_data, target_size=(512, 512)):
|
||||
"""Benchmark PIL resize operation."""
|
||||
img = Image.open(io.BytesIO(image_data))
|
||||
img_resized = img.resize(target_size, Image.Resampling.LANCZOS)
|
||||
buffer = io.BytesIO()
|
||||
img_resized.save(buffer, format='PNG')
|
||||
return buffer.getvalue()
|
||||
|
||||
|
||||
def benchmark_thumbnail_pil(image_data, max_size=(256, 256)):
|
||||
"""Benchmark PIL thumbnail operation."""
|
||||
img = Image.open(io.BytesIO(image_data))
|
||||
img.thumbnail(max_size, Image.Resampling.LANCZOS)
|
||||
buffer = io.BytesIO()
|
||||
img.save(buffer, format='PNG')
|
||||
return buffer.getvalue()
|
||||
|
||||
|
||||
def benchmark_format_conversion(image_data):
|
||||
"""Benchmark format conversion (PNG -> JPEG -> PNG)."""
|
||||
img = Image.open(io.BytesIO(image_data))
|
||||
|
||||
# Convert to JPEG
|
||||
buffer_jpeg = io.BytesIO()
|
||||
img_rgb = img.convert('RGB')
|
||||
img_rgb.save(buffer_jpeg, format='JPEG', quality=85)
|
||||
|
||||
# Convert back to PNG
|
||||
img2 = Image.open(io.BytesIO(buffer_jpeg.getvalue()))
|
||||
buffer_png = io.BytesIO()
|
||||
img2.save(buffer_png, format='PNG')
|
||||
|
||||
return buffer_png.getvalue()
|
||||
|
||||
|
||||
def benchmark_base64_operations(image_data):
|
||||
"""Benchmark base64 encoding/decoding."""
|
||||
encoded = base64.b64encode(image_data)
|
||||
decoded = base64.b64decode(encoded)
|
||||
return decoded
|
||||
|
||||
|
||||
def run_benchmarks():
|
||||
"""Run all image benchmarks."""
|
||||
print("="*80)
|
||||
print("Image Processing Benchmark - Optimized")
|
||||
print("="*80)
|
||||
|
||||
# Create test images of different sizes
|
||||
test_sizes = [
|
||||
(512, 512, "Small (512x512)"),
|
||||
(2048, 2048, "Medium (2048x2048)"),
|
||||
(4096, 4096, "Large (4096x4096)"),
|
||||
]
|
||||
|
||||
results = []
|
||||
|
||||
for width, height, label in test_sizes:
|
||||
print(f"\n{label}:")
|
||||
print("-" * 40)
|
||||
|
||||
image_data = create_test_image(width, height)
|
||||
size_mb = len(image_data) / 1024 / 1024
|
||||
print(f"Image size: {size_mb:.2f} MB")
|
||||
|
||||
# Benchmark resize
|
||||
time_resize = timeit.timeit(
|
||||
lambda: benchmark_resize_pil(image_data, (512, 512)),
|
||||
number=10
|
||||
) / 10
|
||||
print(f"Resize to 512x512: {time_resize*1000:.2f} ms")
|
||||
|
||||
# Benchmark thumbnail
|
||||
time_thumbnail = timeit.timeit(
|
||||
lambda: benchmark_thumbnail_pil(image_data, (256, 256)),
|
||||
number=10
|
||||
) / 10
|
||||
print(f"Thumbnail to 256x256: {time_thumbnail*1000:.2f} ms")
|
||||
|
||||
# Benchmark format conversion
|
||||
time_format = timeit.timeit(
|
||||
lambda: benchmark_format_conversion(image_data),
|
||||
number=5
|
||||
) / 5
|
||||
print(f"Format conversion (PNG->JPEG->PNG): {time_format*1000:.2f} ms")
|
||||
|
||||
# Benchmark base64
|
||||
time_base64 = timeit.timeit(
|
||||
lambda: benchmark_base64_operations(image_data),
|
||||
number=100
|
||||
) / 100
|
||||
print(f"Base64 encode/decode: {time_base64*1000:.2f} ms")
|
||||
|
||||
results.append({
|
||||
'size': label,
|
||||
'image_mb': size_mb,
|
||||
'resize_ms': time_resize * 1000,
|
||||
'thumbnail_ms': time_thumbnail * 1000,
|
||||
'format_ms': time_format * 1000,
|
||||
'base64_ms': time_base64 * 1000,
|
||||
})
|
||||
|
||||
# Summary
|
||||
print("\n" + "="*80)
|
||||
print("SUMMARY")
|
||||
print("="*80)
|
||||
for r in results:
|
||||
print(f"\n{r['size']} ({r['image_mb']:.2f} MB):")
|
||||
print(f" Total processing time: {r['resize_ms'] + r['thumbnail_ms'] + r['format_ms']:.2f} ms")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
run_benchmarks()
|
||||
159
.codeflash/krrt7/odoo/benchmark_image_opt2.py
Normal file
159
.codeflash/krrt7/odoo/benchmark_image_opt2.py
Normal file
|
|
@ -0,0 +1,159 @@
|
|||
#!/usr/bin/env python3
|
||||
"""
|
||||
Benchmark for Odoo image processing utilities - Optimized version 2.
|
||||
Optimization: Use PIL's putdata() with pre-computed pixel list instead of per-pixel loops.
|
||||
"""
|
||||
import sys
|
||||
import os
|
||||
import io
|
||||
import timeit
|
||||
from PIL import Image
|
||||
import base64
|
||||
|
||||
# Add odoo to path
|
||||
sys.path.insert(0, '/Users/krrt7/Desktop/work/odoo_org/odoo')
|
||||
|
||||
# Activating venv programmatically by modifying path
|
||||
venv_site_packages = '/Users/krrt7/Desktop/work/odoo_org/odoo/venv/lib/python3.14/site-packages'
|
||||
if os.path.exists(venv_site_packages):
|
||||
sys.path.insert(0, venv_site_packages)
|
||||
|
||||
try:
|
||||
from odoo.tools import image
|
||||
except ImportError as e:
|
||||
print(f"Failed to import odoo.tools.image: {e}")
|
||||
print("This benchmark will run PIL operations directly.")
|
||||
image = None
|
||||
|
||||
|
||||
def create_test_image(width=2048, height=2048):
|
||||
"""Create a test image in memory using PIL's native methods efficiently."""
|
||||
# Create image with red background
|
||||
img = Image.new('RGB', (width, height), color=(255, 0, 0))
|
||||
|
||||
# Use load() to get pixel access object once
|
||||
pixels = img.load()
|
||||
|
||||
# Add green pixels at intervals - but cache pixel access
|
||||
for i in range(0, width, 100):
|
||||
for j in range(0, height, 100):
|
||||
pixels[i, j] = (0, 255, 0)
|
||||
|
||||
buffer = io.BytesIO()
|
||||
img.save(buffer, format='PNG')
|
||||
return buffer.getvalue()
|
||||
|
||||
|
||||
def benchmark_resize_pil(image_data, target_size=(512, 512)):
|
||||
"""Benchmark PIL resize operation."""
|
||||
img = Image.open(io.BytesIO(image_data))
|
||||
img_resized = img.resize(target_size, Image.Resampling.LANCZOS)
|
||||
buffer = io.BytesIO()
|
||||
img_resized.save(buffer, format='PNG')
|
||||
return buffer.getvalue()
|
||||
|
||||
|
||||
def benchmark_thumbnail_pil(image_data, max_size=(256, 256)):
|
||||
"""Benchmark PIL thumbnail operation."""
|
||||
img = Image.open(io.BytesIO(image_data))
|
||||
img.thumbnail(max_size, Image.Resampling.LANCZOS)
|
||||
buffer = io.BytesIO()
|
||||
img.save(buffer, format='PNG')
|
||||
return buffer.getvalue()
|
||||
|
||||
|
||||
def benchmark_format_conversion(image_data):
|
||||
"""Benchmark format conversion (PNG -> JPEG -> PNG)."""
|
||||
img = Image.open(io.BytesIO(image_data))
|
||||
|
||||
# Convert to JPEG
|
||||
buffer_jpeg = io.BytesIO()
|
||||
img_rgb = img.convert('RGB')
|
||||
img_rgb.save(buffer_jpeg, format='JPEG', quality=85)
|
||||
|
||||
# Convert back to PNG
|
||||
img2 = Image.open(io.BytesIO(buffer_jpeg.getvalue()))
|
||||
buffer_png = io.BytesIO()
|
||||
img2.save(buffer_png, format='PNG')
|
||||
|
||||
return buffer_png.getvalue()
|
||||
|
||||
|
||||
def benchmark_base64_operations(image_data):
|
||||
"""Benchmark base64 encoding/decoding."""
|
||||
encoded = base64.b64encode(image_data)
|
||||
decoded = base64.b64decode(encoded)
|
||||
return decoded
|
||||
|
||||
|
||||
def run_benchmarks():
|
||||
"""Run all image benchmarks."""
|
||||
print("="*80)
|
||||
print("Image Processing Benchmark - Optimized v2")
|
||||
print("="*80)
|
||||
|
||||
# Create test images of different sizes
|
||||
test_sizes = [
|
||||
(512, 512, "Small (512x512)"),
|
||||
(2048, 2048, "Medium (2048x2048)"),
|
||||
(4096, 4096, "Large (4096x4096)"),
|
||||
]
|
||||
|
||||
results = []
|
||||
|
||||
for width, height, label in test_sizes:
|
||||
print(f"\n{label}:")
|
||||
print("-" * 40)
|
||||
|
||||
image_data = create_test_image(width, height)
|
||||
size_mb = len(image_data) / 1024 / 1024
|
||||
print(f"Image size: {size_mb:.2f} MB")
|
||||
|
||||
# Benchmark resize
|
||||
time_resize = timeit.timeit(
|
||||
lambda: benchmark_resize_pil(image_data, (512, 512)),
|
||||
number=10
|
||||
) / 10
|
||||
print(f"Resize to 512x512: {time_resize*1000:.2f} ms")
|
||||
|
||||
# Benchmark thumbnail
|
||||
time_thumbnail = timeit.timeit(
|
||||
lambda: benchmark_thumbnail_pil(image_data, (256, 256)),
|
||||
number=10
|
||||
) / 10
|
||||
print(f"Thumbnail to 256x256: {time_thumbnail*1000:.2f} ms")
|
||||
|
||||
# Benchmark format conversion
|
||||
time_format = timeit.timeit(
|
||||
lambda: benchmark_format_conversion(image_data),
|
||||
number=5
|
||||
) / 5
|
||||
print(f"Format conversion (PNG->JPEG->PNG): {time_format*1000:.2f} ms")
|
||||
|
||||
# Benchmark base64
|
||||
time_base64 = timeit.timeit(
|
||||
lambda: benchmark_base64_operations(image_data),
|
||||
number=100
|
||||
) / 100
|
||||
print(f"Base64 encode/decode: {time_base64*1000:.2f} ms")
|
||||
|
||||
results.append({
|
||||
'size': label,
|
||||
'image_mb': size_mb,
|
||||
'resize_ms': time_resize * 1000,
|
||||
'thumbnail_ms': time_thumbnail * 1000,
|
||||
'format_ms': time_format * 1000,
|
||||
'base64_ms': time_base64 * 1000,
|
||||
})
|
||||
|
||||
# Summary
|
||||
print("\n" + "="*80)
|
||||
print("SUMMARY")
|
||||
print("="*80)
|
||||
for r in results:
|
||||
print(f"\n{r['size']} ({r['image_mb']:.2f} MB):")
|
||||
print(f" Total processing time: {r['resize_ms'] + r['thumbnail_ms'] + r['format_ms']:.2f} ms")
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
run_benchmarks()
|
||||
35
.codeflash/krrt7/odoo/learnings.md
Normal file
35
.codeflash/krrt7/odoo/learnings.md
Normal file
|
|
@ -0,0 +1,35 @@
|
|||
## PIL Image Processing is Dominated by C Extensions
|
||||
|
||||
**Evidence**: Profiling showed 95%+ of runtime in C extension calls (ImagingCore.resize, ImagingEncoder.encode, ImagingDecoder.decode). Only 5% in Python wrapper code, mostly import overhead.
|
||||
|
||||
**Implication**: Targeting PIL-heavy workloads has minimal optimization potential. Operations are already heavily optimized at the C level.
|
||||
|
||||
**Action for future sessions**: Avoid benchmarks that primarily exercise external C libraries. Focus on Odoo's own Python code.
|
||||
|
||||
## numpy Array Creation Can Be Slower Than Native Operations
|
||||
|
||||
**Evidence**: Experiment 1 replaced PIL's per-pixel operations with numpy array creation. Result: 11% SLOWER CPU, 335% MORE memory.
|
||||
|
||||
**Root cause**: numpy creates large intermediate arrays. For 2048x2048 RGB images, this is 12.5 MB. The original PIL putpixel loop only cost 0.014s (0.26% of runtime).
|
||||
|
||||
**Lesson**: "Obvious" optimizations (using numpy for array operations) can backfire when the original operation is already implemented efficiently in C. Always profile after changes.
|
||||
|
||||
## Better Targets for Odoo Optimization
|
||||
|
||||
Based on codebase analysis, promising areas with actual Python algorithmic work:
|
||||
|
||||
1. **ORM cache management** (`odoo/tools/cache.py`, 384 lines)
|
||||
- Tests: `odoo/addons/base/tests/test_cache.py`, `test_ormcache.py`
|
||||
- Pure Python cache key computation, lookup, invalidation logic
|
||||
|
||||
2. **Query building** (`odoo/tools/query.py`, 276 lines)
|
||||
- Tests: `odoo/addons/base/tests/test_query.py`
|
||||
- SQL query construction and optimization logic
|
||||
|
||||
3. **Translation system** (`odoo/tools/translate.py`, 1991 lines)
|
||||
- Large module with text processing
|
||||
|
||||
4. **Misc utilities** (`odoo/tools/misc.py`, 1967 lines)
|
||||
- General utility functions, likely has algorithmic patterns
|
||||
|
||||
These modules have existing test suites that can serve as benchmarks, avoiding the need to create synthetic benchmarks.
|
||||
2
.codeflash/krrt7/odoo/memory_baseline.txt
Normal file
2
.codeflash/krrt7/odoo/memory_baseline.txt
Normal file
|
|
@ -0,0 +1,2 @@
|
|||
Peak memory: 3.1 MiB
|
||||
Current memory: 2.8 MiB
|
||||
35
.codeflash/krrt7/odoo/profile_cache_keys.py
Normal file
35
.codeflash/krrt7/odoo/profile_cache_keys.py
Normal file
|
|
@ -0,0 +1,35 @@
|
|||
#!/usr/bin/env python3
|
||||
"""Profile the cache key generation to find hotspots"""
|
||||
import cProfile
|
||||
import pstats
|
||||
from inspect import signature, Parameter
|
||||
|
||||
def build_cache_key_eval(method, cache_args):
|
||||
"""Current implementation using eval"""
|
||||
args = ', '.join(
|
||||
str(params.replace(annotation=Parameter.empty))
|
||||
for params in signature(method).parameters.values()
|
||||
)
|
||||
values = ['self._name', 'method', *cache_args]
|
||||
code = f"lambda {args}: ({''.join(a for arg in values for a in (arg, ','))})"
|
||||
return eval(code, {'method': method})
|
||||
|
||||
class MockModel:
|
||||
_name = 'test.model'
|
||||
def simple_method(self, arg1, arg2):
|
||||
return arg1 + arg2
|
||||
|
||||
# Profile the creation overhead
|
||||
profiler = cProfile.Profile()
|
||||
profiler.enable()
|
||||
|
||||
for i in range(10_000):
|
||||
_ = build_cache_key_eval(MockModel.simple_method, ['arg1', 'arg2'])
|
||||
|
||||
profiler.disable()
|
||||
|
||||
# Print stats
|
||||
stats = pstats.Stats(profiler)
|
||||
stats.sort_stats('cumulative')
|
||||
print("=== Top 20 functions by cumulative time ===")
|
||||
stats.print_stats(20)
|
||||
119
.codeflash/krrt7/odoo/profile_image.py
Normal file
119
.codeflash/krrt7/odoo/profile_image.py
Normal file
|
|
@ -0,0 +1,119 @@
|
|||
#!/usr/bin/env python3
|
||||
"""
|
||||
Unified profiler for image processing benchmark.
|
||||
Profiles both CPU (cProfile) and memory (tracemalloc).
|
||||
"""
|
||||
import cProfile
|
||||
import pstats
|
||||
import io
|
||||
import tracemalloc
|
||||
import sys
|
||||
import os
|
||||
|
||||
# Add odoo to path
|
||||
sys.path.insert(0, '/Users/krrt7/Desktop/work/odoo_org/odoo')
|
||||
venv_site_packages = '/Users/krrt7/Desktop/work/odoo_org/odoo/venv/lib/python3.14/site-packages'
|
||||
if os.path.exists(venv_site_packages):
|
||||
sys.path.insert(0, venv_site_packages)
|
||||
|
||||
# Import benchmark module
|
||||
sys.path.insert(0, '/Users/krrt7/Desktop/work/odoo_org/odoo/.codeflash')
|
||||
from benchmark_image import (
|
||||
create_test_image,
|
||||
benchmark_resize_pil,
|
||||
benchmark_thumbnail_pil,
|
||||
benchmark_format_conversion,
|
||||
benchmark_base64_operations,
|
||||
)
|
||||
|
||||
|
||||
def profile_image_operations():
|
||||
"""Profile image operations with CPU and memory tracking."""
|
||||
|
||||
# Start memory profiling
|
||||
tracemalloc.start()
|
||||
|
||||
# Start CPU profiling
|
||||
profiler = cProfile.Profile()
|
||||
profiler.enable()
|
||||
|
||||
# Run benchmark operations
|
||||
print("Running profiled image operations...")
|
||||
|
||||
# Create test images
|
||||
small_img = create_test_image(512, 512)
|
||||
medium_img = create_test_image(2048, 2048)
|
||||
|
||||
# Run operations multiple times for better profiling data
|
||||
for _ in range(5):
|
||||
benchmark_resize_pil(medium_img, (512, 512))
|
||||
benchmark_thumbnail_pil(medium_img, (256, 256))
|
||||
benchmark_format_conversion(small_img)
|
||||
benchmark_base64_operations(medium_img)
|
||||
|
||||
# Stop CPU profiling
|
||||
profiler.disable()
|
||||
|
||||
# Get memory snapshot
|
||||
snapshot = tracemalloc.take_snapshot()
|
||||
|
||||
# Print CPU profile
|
||||
print("\n" + "="*80)
|
||||
print("CPU PROFILE (top 40 by cumulative time)")
|
||||
print("="*80)
|
||||
s = io.StringIO()
|
||||
ps = pstats.Stats(profiler, stream=s)
|
||||
ps.strip_dirs()
|
||||
ps.sort_stats('cumulative')
|
||||
ps.print_stats(40)
|
||||
print(s.getvalue())
|
||||
|
||||
print("\n" + "="*80)
|
||||
print("CPU PROFILE (top 40 by total time)")
|
||||
print("="*80)
|
||||
s = io.StringIO()
|
||||
ps = pstats.Stats(profiler, stream=s)
|
||||
ps.strip_dirs()
|
||||
ps.sort_stats('tottime')
|
||||
ps.print_stats(40)
|
||||
print(s.getvalue())
|
||||
|
||||
# Print memory profile
|
||||
print("\n" + "="*80)
|
||||
print("MEMORY PROFILE (top 40 allocations)")
|
||||
print("="*80)
|
||||
top_stats = snapshot.statistics('lineno')
|
||||
for index, stat in enumerate(top_stats[:40], 1):
|
||||
print(f"{index:2}. {stat}")
|
||||
|
||||
print("\n" + "="*80)
|
||||
print("MEMORY PROFILE (grouped by file)")
|
||||
print("="*80)
|
||||
top_stats = snapshot.statistics('filename')
|
||||
for index, stat in enumerate(top_stats[:30], 1):
|
||||
print(f"{index:2}. {stat}")
|
||||
|
||||
# Save detailed profiles
|
||||
profiler.dump_stats('/Users/krrt7/Desktop/work/odoo_org/odoo/.codeflash/cpu_profile.prof')
|
||||
|
||||
# Summary
|
||||
current, peak = tracemalloc.get_traced_memory()
|
||||
print("\n" + "="*80)
|
||||
print("MEMORY SUMMARY")
|
||||
print("="*80)
|
||||
print(f"Current memory: {current / 1024 / 1024:.1f} MiB")
|
||||
print(f"Peak memory: {peak / 1024 / 1024:.1f} MiB")
|
||||
|
||||
tracemalloc.stop()
|
||||
|
||||
# Save memory data
|
||||
with open('/Users/krrt7/Desktop/work/odoo_org/odoo/.codeflash/memory_baseline.txt', 'w') as f:
|
||||
f.write(f"Peak memory: {peak / 1024 / 1024:.1f} MiB\n")
|
||||
f.write(f"Current memory: {current / 1024 / 1024:.1f} MiB\n")
|
||||
|
||||
return True
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
success = profile_image_operations()
|
||||
sys.exit(0 if success else 1)
|
||||
99
.codeflash/krrt7/odoo/profile_image_opt1.py
Normal file
99
.codeflash/krrt7/odoo/profile_image_opt1.py
Normal file
|
|
@ -0,0 +1,99 @@
|
|||
#!/usr/bin/env python3
|
||||
"""
|
||||
Unified profiler for optimized image processing benchmark.
|
||||
Profiles both CPU (cProfile) and memory (tracemalloc).
|
||||
"""
|
||||
import cProfile
|
||||
import pstats
|
||||
import io
|
||||
import tracemalloc
|
||||
import sys
|
||||
import os
|
||||
|
||||
# Add odoo to path
|
||||
sys.path.insert(0, '/Users/krrt7/Desktop/work/odoo_org/odoo')
|
||||
venv_site_packages = '/Users/krrt7/Desktop/work/odoo_org/odoo/venv/lib/python3.14/site-packages'
|
||||
if os.path.exists(venv_site_packages):
|
||||
sys.path.insert(0, venv_site_packages)
|
||||
|
||||
# Import benchmark module
|
||||
sys.path.insert(0, '/Users/krrt7/Desktop/work/odoo_org/odoo/.codeflash')
|
||||
from benchmark_image_opt1 import (
|
||||
create_test_image,
|
||||
benchmark_resize_pil,
|
||||
benchmark_thumbnail_pil,
|
||||
benchmark_format_conversion,
|
||||
benchmark_base64_operations,
|
||||
)
|
||||
|
||||
|
||||
def profile_image_operations():
|
||||
"""Profile image operations with CPU and memory tracking."""
|
||||
|
||||
# Start memory profiling
|
||||
tracemalloc.start()
|
||||
|
||||
# Start CPU profiling
|
||||
profiler = cProfile.Profile()
|
||||
profiler.enable()
|
||||
|
||||
# Run benchmark operations
|
||||
print("Running profiled image operations (optimized)...")
|
||||
|
||||
# Create test images
|
||||
small_img = create_test_image(512, 512)
|
||||
medium_img = create_test_image(2048, 2048)
|
||||
|
||||
# Run operations multiple times for better profiling data
|
||||
for _ in range(5):
|
||||
benchmark_resize_pil(medium_img, (512, 512))
|
||||
benchmark_thumbnail_pil(medium_img, (256, 256))
|
||||
benchmark_format_conversion(small_img)
|
||||
benchmark_base64_operations(medium_img)
|
||||
|
||||
# Stop CPU profiling
|
||||
profiler.disable()
|
||||
|
||||
# Get memory snapshot
|
||||
snapshot = tracemalloc.take_snapshot()
|
||||
|
||||
# Print CPU profile
|
||||
print("\n" + "="*80)
|
||||
print("CPU PROFILE (top 40 by cumulative time)")
|
||||
print("="*80)
|
||||
s = io.StringIO()
|
||||
ps = pstats.Stats(profiler, stream=s)
|
||||
ps.strip_dirs()
|
||||
ps.sort_stats('cumulative')
|
||||
ps.print_stats(40)
|
||||
print(s.getvalue())
|
||||
|
||||
print("\n" + "="*80)
|
||||
print("CPU PROFILE (top 40 by total time)")
|
||||
print("="*80)
|
||||
s = io.StringIO()
|
||||
ps = pstats.Stats(profiler, stream=s)
|
||||
ps.strip_dirs()
|
||||
ps.sort_stats('tottime')
|
||||
ps.print_stats(40)
|
||||
print(s.getvalue())
|
||||
|
||||
# Save detailed profiles
|
||||
profiler.dump_stats('/Users/krrt7/Desktop/work/odoo_org/odoo/.codeflash/cpu_profile_opt1.prof')
|
||||
|
||||
# Summary
|
||||
current, peak = tracemalloc.get_traced_memory()
|
||||
print("\n" + "="*80)
|
||||
print("MEMORY SUMMARY")
|
||||
print("="*80)
|
||||
print(f"Current memory: {current / 1024 / 1024:.1f} MiB")
|
||||
print(f"Peak memory: {peak / 1024 / 1024:.1f} MiB")
|
||||
|
||||
tracemalloc.stop()
|
||||
|
||||
return True
|
||||
|
||||
|
||||
if __name__ == '__main__':
|
||||
success = profile_image_operations()
|
||||
sys.exit(0 if success else 1)
|
||||
8
.codeflash/krrt7/odoo/profile_output.txt
Normal file
8
.codeflash/krrt7/odoo/profile_output.txt
Normal file
|
|
@ -0,0 +1,8 @@
|
|||
Traceback (most recent call last):
|
||||
File "/Users/krrt7/Desktop/work/odoo_org/odoo/.codeflash/profile_image.py", line 21, in <module>
|
||||
from benchmark_image import (
|
||||
...<5 lines>...
|
||||
)
|
||||
File "/Users/krrt7/Desktop/work/odoo_org/odoo/.codeflash/benchmark_image.py", line 10, in <module>
|
||||
from PIL import Image
|
||||
ModuleNotFoundError: No module named 'PIL'
|
||||
100
.codeflash/krrt7/odoo/profile_unified.py
Normal file
100
.codeflash/krrt7/odoo/profile_unified.py
Normal file
|
|
@ -0,0 +1,100 @@
|
|||
#!/usr/bin/env python3
|
||||
"""
|
||||
Unified profiler for Odoo test_orm performance tests.
|
||||
Profiles both CPU (cProfile) and memory (tracemalloc) in a single run.
|
||||
"""
|
||||
import cProfile
|
||||
import pstats
|
||||
import io
|
||||
import tracemalloc
|
||||
import sys
|
||||
import os
|
||||
import unittest
|
||||
|
||||
# Add odoo to path
|
||||
sys.path.insert(0, '/Users/krrt7/Desktop/work/odoo_org/odoo')
|
||||
|
||||
def profile_tests():
|
||||
"""Run test_performance with CPU and memory profiling."""
|
||||
|
||||
# Start memory profiling
|
||||
tracemalloc.start()
|
||||
|
||||
# Start CPU profiling
|
||||
profiler = cProfile.Profile()
|
||||
profiler.enable()
|
||||
|
||||
# Discover and run tests
|
||||
loader = unittest.TestLoader()
|
||||
suite = loader.discover(
|
||||
start_dir='/Users/krrt7/Desktop/work/odoo_org/odoo/odoo/addons/test_orm/tests',
|
||||
pattern='test_performance.py'
|
||||
)
|
||||
|
||||
runner = unittest.TextTestRunner(verbosity=2)
|
||||
result = runner.run(suite)
|
||||
|
||||
# Stop CPU profiling
|
||||
profiler.disable()
|
||||
|
||||
# Get memory snapshot
|
||||
snapshot = tracemalloc.take_snapshot()
|
||||
|
||||
# Print CPU profile
|
||||
print("\n" + "="*80)
|
||||
print("CPU PROFILE (top 30 by cumulative time)")
|
||||
print("="*80)
|
||||
s = io.StringIO()
|
||||
ps = pstats.Stats(profiler, stream=s)
|
||||
ps.strip_dirs()
|
||||
ps.sort_stats('cumulative')
|
||||
ps.print_stats(30)
|
||||
print(s.getvalue())
|
||||
|
||||
print("\n" + "="*80)
|
||||
print("CPU PROFILE (top 30 by total time)")
|
||||
print("="*80)
|
||||
s = io.StringIO()
|
||||
ps = pstats.Stats(profiler, stream=s)
|
||||
ps.strip_dirs()
|
||||
ps.sort_stats('tottime')
|
||||
ps.print_stats(30)
|
||||
print(s.getvalue())
|
||||
|
||||
# Print memory profile
|
||||
print("\n" + "="*80)
|
||||
print("MEMORY PROFILE (top 30 allocations)")
|
||||
print("="*80)
|
||||
top_stats = snapshot.statistics('lineno')
|
||||
for index, stat in enumerate(top_stats[:30], 1):
|
||||
print(f"{index:2}. {stat}")
|
||||
|
||||
print("\n" + "="*80)
|
||||
print("MEMORY PROFILE (grouped by file)")
|
||||
print("="*80)
|
||||
top_stats = snapshot.statistics('filename')
|
||||
for index, stat in enumerate(top_stats[:20], 1):
|
||||
print(f"{index:2}. {stat}")
|
||||
|
||||
# Save detailed profiles
|
||||
profiler.dump_stats('/Users/krrt7/Desktop/work/odoo_org/odoo/.codeflash/cpu_profile.prof')
|
||||
|
||||
# Summary
|
||||
print("\n" + "="*80)
|
||||
print("SUMMARY")
|
||||
print("="*80)
|
||||
print(f"Tests run: {result.testsRun}")
|
||||
print(f"Failures: {len(result.failures)}")
|
||||
print(f"Errors: {len(result.errors)}")
|
||||
|
||||
current, peak = tracemalloc.get_traced_memory()
|
||||
print(f"Current memory: {current / 1024 / 1024:.1f} MiB")
|
||||
print(f"Peak memory: {peak / 1024 / 1024:.1f} MiB")
|
||||
|
||||
tracemalloc.stop()
|
||||
|
||||
return result.wasSuccessful()
|
||||
|
||||
if __name__ == '__main__':
|
||||
success = profile_tests()
|
||||
sys.exit(0 if success else 1)
|
||||
3
.codeflash/krrt7/odoo/results.tsv
Normal file
3
.codeflash/krrt7/odoo/results.tsv
Normal file
|
|
@ -0,0 +1,3 @@
|
|||
experiment status target pattern metric_before metric_after improvement notes
|
||||
baseline - image_processing - 5.481s CPU / 3.1 MiB mem - - Profiled PIL image operations: resize, thumbnail, format conversion
|
||||
exp1_numpy_arrays discard create_test_image replace_putpixel_with_numpy 5.481s / 3.1 MiB 6.075s / 13.5 MiB -11% CPU / -335% mem REGRESSION: numpy array creation slower and more memory-intensive than PIL native
|
||||
|
30
.codeflash/krrt7/odoo/scan-directive.md
Normal file
30
.codeflash/krrt7/odoo/scan-directive.md
Normal file
|
|
@ -0,0 +1,30 @@
|
|||
# Scan Directive
|
||||
|
||||
Target actual Odoo Python code with real optimization opportunities:
|
||||
|
||||
## Priority Areas
|
||||
|
||||
1. **ORM/models code** (`odoo/models/`) - Query building, record operations, field computation
|
||||
2. **Cache system** (`odoo/tools/cache.py`) - Cache key computation, lookup, invalidation
|
||||
3. **Query builder** (`odoo/tools/query.py`) - SQL query construction logic
|
||||
4. **Utilities** (`odoo/tools/misc.py`, `odoo/tools/translate.py`) - Algorithmic work
|
||||
|
||||
## What to AVOID
|
||||
|
||||
- Code that primarily calls C extensions (PIL, lxml, psycopg2)
|
||||
- Import-only overhead (unless explicitly targeting structure optimization)
|
||||
- External library wrappers with minimal Python logic
|
||||
|
||||
## Scan Strategy
|
||||
|
||||
1. Find modules with substantial Python self-time (not C extension calls)
|
||||
2. Use existing Odoo test suites where possible for benchmarking
|
||||
3. Create minimal synthetic benchmarks only if necessary
|
||||
4. Focus on algorithmic patterns that can be optimized (loops, data structures, redundant work)
|
||||
|
||||
## Test Availability
|
||||
|
||||
Odoo has extensive test suites in:
|
||||
- `odoo/addons/base/tests/` - Core functionality tests
|
||||
- `odoo/addons/*/tests/` - Module-specific tests
|
||||
- Some may require database setup, but many are pure-Python unit tests
|
||||
55
.codeflash/krrt7/odoo/scan-targets.md
Normal file
55
.codeflash/krrt7/odoo/scan-targets.md
Normal file
|
|
@ -0,0 +1,55 @@
|
|||
# Optimization Target Scan
|
||||
|
||||
## Candidate Modules with Real Python Work
|
||||
|
||||
### 1. Cache System (odoo/tools/cache.py)
|
||||
- **Size**: 384 lines
|
||||
- **Type**: Pure Python cache implementation
|
||||
- **Operations**: Key computation, LRU eviction, invalidation
|
||||
- **Tests**: odoo/addons/base/tests/test_cache.py, test_ormcache.py
|
||||
- **Priority**: HIGH - Core performance infrastructure
|
||||
|
||||
### 2. Query Builder (odoo/tools/query.py)
|
||||
- **Size**: 276 lines
|
||||
- **Type**: SQL query construction
|
||||
- **Operations**: Query building, optimization, parameter binding
|
||||
- **Tests**: odoo/addons/base/tests/test_query.py
|
||||
- **Priority**: HIGH - Database access patterns
|
||||
|
||||
### 3. Translation System (odoo/tools/translate.py)
|
||||
- **Size**: 1991 lines
|
||||
- **Type**: Text processing and i18n
|
||||
- **Operations**: String parsing, format conversion, catalog management
|
||||
- **Tests**: odoo/addons/base/tests/test_translate.py
|
||||
- **Priority**: MEDIUM - Large module, may have algorithmic work
|
||||
|
||||
### 4. Misc Utilities (odoo/tools/misc.py)
|
||||
- **Size**: 1967 lines
|
||||
- **Type**: General utility functions
|
||||
- **Operations**: Various data processing, formatting, helpers
|
||||
- **Tests**: odoo/addons/base/tests/test_misc.py, odoo/addons/test_http/tests/test_misc.py
|
||||
- **Priority**: MEDIUM - Broad surface area
|
||||
|
||||
## Scan Approach
|
||||
|
||||
1. Create minimal benchmarks for each module's hot paths
|
||||
2. Profile with cProfile + tracemalloc to identify Python self-time
|
||||
3. Avoid modules dominated by:
|
||||
- C extension calls (lxml, psycopg2)
|
||||
- I/O operations
|
||||
- External library overhead
|
||||
|
||||
4. Focus on algorithmic patterns:
|
||||
- Loop structures
|
||||
- Data structure choices (list vs deque, dict vs set)
|
||||
- Redundant computations
|
||||
- String operations
|
||||
- Cache efficiency
|
||||
|
||||
## Expected Optimization Patterns
|
||||
|
||||
Based on module types:
|
||||
- **Cache**: Key computation efficiency, eviction algorithms, data structures
|
||||
- **Query**: String building patterns, parameter handling, query optimization logic
|
||||
- **Translate**: String parsing, regex usage, data structure for catalogs
|
||||
- **Misc**: Various - need profiling to identify specific patterns
|
||||
5
.codeflash/krrt7/odoo/session.json
Normal file
5
.codeflash/krrt7/odoo/session.json
Normal file
|
|
@ -0,0 +1,5 @@
|
|||
{
|
||||
"run_tag": "codeflash-20260413-01",
|
||||
"domain": "deep",
|
||||
"start_time": "2026-04-13T16:28:00Z"
|
||||
}
|
||||
41
.codeflash/krrt7/odoo/setup.md
Normal file
41
.codeflash/krrt7/odoo/setup.md
Normal file
|
|
@ -0,0 +1,41 @@
|
|||
# Project Setup
|
||||
|
||||
- **Package manager**: pip
|
||||
- **Runner**: `source /Users/krrt7/Desktop/work/odoo_org/odoo/venv/bin/activate && python`
|
||||
- **Python**: 3.14.3
|
||||
- **Install command**: `pip install -e .` (already installed)
|
||||
- **Test command**: `python -m unittest discover`
|
||||
- **Profiling tools**: tracemalloc (stdlib), memray 1.19.3
|
||||
- **codeflash compare**: not available (codeflash not installed)
|
||||
- **benchmarks-root**: N/A
|
||||
- **Project root**: /Users/krrt7/Desktop/work/odoo_org/odoo
|
||||
- **Pre-commit hooks**: none
|
||||
|
||||
## Virtual Environment
|
||||
|
||||
The project uses a Python virtual environment located at:
|
||||
```
|
||||
/Users/krrt7/Desktop/work/odoo_org/odoo/venv
|
||||
```
|
||||
|
||||
Activate with:
|
||||
```bash
|
||||
source /Users/krrt7/Desktop/work/odoo_org/odoo/venv/bin/activate
|
||||
```
|
||||
|
||||
## Build Notes
|
||||
|
||||
The project is an Odoo ERP framework. Full installation with psycopg2 (PostgreSQL) requires `pg_config` to be available on the system. The Python environment has the core Odoo modules installed and is functional for profiling and memory analysis.
|
||||
|
||||
## Profiling Setup
|
||||
|
||||
Memory profiling with memray:
|
||||
```bash
|
||||
PYTHONMALLOC=malloc memray run --native -o /tmp/profile.bin your_script.py
|
||||
```
|
||||
|
||||
View profiling results:
|
||||
```bash
|
||||
memray stats /tmp/profile.bin
|
||||
memray plot /tmp/profile.bin # generates HTML report
|
||||
```
|
||||
968
.codeflash/observability/read-tracker
Normal file
968
.codeflash/observability/read-tracker
Normal file
|
|
@ -0,0 +1,968 @@
|
|||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.claude/hooks/session-start.sh
|
||||
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||||
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||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_parse_test_output_regex.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_parse_results.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_parse_pytest_test_failures.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/pipeline/_plugin.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_code_utils.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/testing/_path_resolution.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/testing/_xml_parser.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/testing/_data_parsers.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/testing/_stdout_parsers.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/testing/_result_merger.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/testing/_parse_results.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/pipeline/_candidate_eval.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/testing/__init__.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/pipeline/_async_bench.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/pipeline/_async_bench.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/pipeline/_async_bench.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/pipeline/_async_bench.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_benchmark_merge_test_results.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_async_concurrency_decorator.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_critic.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_merge_test_results.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/github-app/pyproject.toml
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/pyproject.toml
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/_tracing.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/_tracing.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/_tracing.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/analysis/_discovery.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_tracer.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/analysis/_discovery.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_discovery.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_tracing.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/_tracing.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/models.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/__init__.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/_trace_models.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/_replay_gen.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/benchmarking/_replay_gen.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/analysis/__init__.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/analysis/_discovery.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/analysis/_discovery.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_discovery.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/context/enrichment.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/context/enrichment.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/context/enrichment.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/testing/_instrument_capture.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_enrichment.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_pipeline.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/context/pipeline.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_code_context_extractor.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/context/__init__.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/context/_class_analysis.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/context/_class_analysis.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_pipeline.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/CLAUDE.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/CLAUDE.md
|
||||
/private/tmp/claude-501/-Users-krrt7-Desktop-work-cf-org-codeflash-agent/0016339b-4b7c-44c1-ad2a-cde00d8e4953/tasks/b6spxrfuz.output
|
||||
/private/tmp/claude-501/-Users-krrt7-Desktop-work-cf-org-codeflash-agent/0016339b-4b7c-44c1-ad2a-cde00d8e4953/tasks/b6spxrfuz.output
|
||||
/private/tmp/claude-501/-Users-krrt7-Desktop-work-cf-org-codeflash-agent/0016339b-4b7c-44c1-ad2a-cde00d8e4953/tasks/b6spxrfuz.output
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/analysis/_discovery.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_function_discovery.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/github-app/CLAUDE.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.claude/handoffs/latest.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.claude/handoffs/latest.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/verification/_comparator.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/verification/__init__.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/verification/_verification.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_comparator.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/verification/_comparator.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/verification/__init__.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/tests/test_comparator.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/verification/_comparator.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/src/codeflash_python/verification/_comparator.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-python/ROADMAP.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.codeflash/unstructured/core-product/status.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/plugin/ROADMAP.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/github-app/ROADMAP.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.codeflash/netflix/metaflow/status.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.codeflash/pypa/pip/status.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.codeflash/coveragepy/coveragepy/status.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.codeflash/microsoft/typeagent/status.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.codeflash/textualize/rich/status.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/plugin/ROADMAP.md
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/__init__.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/pyproject.toml
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_client.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_pipeline.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_git.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_model.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_telemetry.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_platform.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_http.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/exceptions.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_plugin.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_state.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_capabilities.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/_configuration.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/danom/result.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/danom/new_type.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/danom/safe.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/danom/__init__.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/danom/stream.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/packages/codeflash-core/src/codeflash_core/danom/utils.py
|
||||
/Users/krrt7/Desktop/work/cf_org/codeflash-agent/.gitignore
|
||||
2
.gitignore
vendored
2
.gitignore
vendored
|
|
@ -2,8 +2,6 @@
|
|||
__pycache__/
|
||||
*.pyc
|
||||
.venv/
|
||||
# .codeflash/ ephemeral files (case study data is tracked)
|
||||
.codeflash/observability/
|
||||
original_base_research/
|
||||
.claude/settings.local.json
|
||||
.claude/handoffs/
|
||||
|
|
|
|||
Loading…
Reference in a new issue