Add comprehensive benchmark tests with quality validation

.github/copilot-instructions.md

@@ -1,46 +1,48 @@
 # Useful Optimizer - GitHub Copilot Instructions
 
-Useful Optimizer is a Python optimization library containing 58 optimization algorithms for numeric problems. The library uses Poetry for dependency management and provides a comprehensive collection of metaheuristic, gradient-based, and nature-inspired optimization techniques.
+Useful Optimizer is a Python optimization library containing 58 optimization algorithms for numeric problems. The project uses **uv** for dependency management, virtual environments, and packaging while providing a comprehensive collection of metaheuristic, gradient-based, and nature-inspired optimization techniques.
 
-**Always reference these instructions first and fallback to search or bash commands only when you encounter unexpected information that does not match the info here.**
+**Always reference these instructions first and fall back to search or shell commands only when you encounter unexpected information that does not match the info here.** All commands are written as **single-line Fish-shell commands** so they can be copied directly into the terminal.
 
 ## Working Effectively
 
 ### Initial Setup and Installation
-- Install Poetry package manager:
-  ```bash
-  pip3 install poetry
-  export PATH="$HOME/.local/bin:$PATH"
+- Install uv (recommended via installer script):
+  ```fish
+  curl -LsSf https://astral.sh/uv/install.sh | sh
   ```
-  **Alternative if PATH export doesn't work:** Use `~/.local/bin/poetry` instead of `poetry`
-- Install project dependencies:
-  ```bash
-  poetry install
+- Ensure `$HOME/.local/bin` is on your Fish PATH (replace with your actual install dir if different):
+  ```fish
+  set -Ux PATH $HOME/.local/bin $PATH
+  ```
+- Install project dependencies and create the managed virtual environment:
+  ```fish
+  uv sync
   ```
   **NEVER CANCEL: Takes 2-3 minutes to complete. Set timeout to 5+ minutes.**
 
 ### Core Development Commands
 - Run any Python command in the project environment:
-  ```bash
-  poetry run python [your_command]
+  ```fish
+  uv run python [your_command]
   ```
 - Test basic functionality:
-  ```bash
-  poetry run python -c "import opt; print('Import successful')"
+  ```fish
+  uv run python -c "import opt; print('Import successful')"
   ```
 - Run linting (finds code quality issues):
-  ```bash
-  poetry run ruff check opt/
+  ```fish
+  uv run ruff check opt/
   ```
   **Takes 5-10 seconds. Common to find existing issues in codebase.**
 - Auto-format code:
-  ```bash
-  poetry run ruff format opt/
+  ```fish
+  uv run ruff format opt/
   ```
   **Takes less than 1 second.**
 - Build the package:
-  ```bash
-  poetry build
+  ```fish
+  uv build
   ```
   **Takes less than 1 second. Creates wheel and sdist in dist/ directory.**
 
@@ -49,56 +51,26 @@ Useful Optimizer is a Python optimization library containing 58 optimization alg
 **ALWAYS test your changes with these scenarios after making modifications:**
 
 ### Scenario 1: Basic Import and Functionality Test
-```bash
-poetry run python -c "
-from opt.benchmark.functions import shifted_ackley, rosenbrock, sphere
-from opt.particle_swarm import ParticleSwarm
-print('Testing basic import and optimizer creation...')
-pso = ParticleSwarm(func=shifted_ackley, lower_bound=-2.768, upper_bound=2.768, dim=2, max_iter=50)
-best_solution, best_fitness = pso.search()
-print(f'PSO completed successfully. Fitness: {best_fitness:.6f}')
-print('Basic functionality test PASSED')
-"
+```fish
+uv run python -c "from opt.benchmark.functions import shifted_ackley, rosenbrock, sphere; from opt.particle_swarm import ParticleSwarm; print('Testing basic import and optimizer creation...'); pso = ParticleSwarm(func=shifted_ackley, lower_bound=-2.768, upper_bound=2.768, dim=2, max_iter=50); best_solution, best_fitness = pso.search(); print(f'PSO completed successfully. Fitness: {best_fitness:.6f}'); print('Basic functionality test PASSED')"
 ```
 **Expected: Completes in < 1 second, prints fitness value around 0.001-1.0**
 
 ### Scenario 2: Multiple Optimizer Test
-```bash
-poetry run python -c "
-from opt.benchmark.functions import shifted_ackley, rosenbrock
-from opt.harmony_search import HarmonySearch
-from opt.ant_colony import AntColony
-print('Testing multiple optimizers...')
-
-# Test HarmonySearch
-hs = HarmonySearch(func=rosenbrock, lower_bound=-5, upper_bound=5, dim=2, max_iter=50)
-_, fitness1 = hs.search()
-
-# Test AntColony
-ac = AntColony(func=shifted_ackley, lower_bound=-2.768, upper_bound=2.768, dim=2, max_iter=50)
-_, fitness2 = ac.search()
-
-print(f'HS fitness: {fitness1:.6f}, ACO fitness: {fitness2:.6f}')
-print('Multiple optimizer test PASSED')
-"
+```fish
+uv run python -c "from opt.benchmark.functions import shifted_ackley, rosenbrock; from opt.harmony_search import HarmonySearch; from opt.ant_colony import AntColony; print('Testing multiple optimizers...'); hs = HarmonySearch(func=rosenbrock, lower_bound=-5, upper_bound=5, dim=2, max_iter=50); _, fitness1 = hs.search(); ac = AntColony(func=shifted_ackley, lower_bound=-2.768, upper_bound=2.768, dim=2, max_iter=50); _, fitness2 = ac.search(); print(f'HS fitness: {fitness1:.6f}, ACO fitness: {fitness2:.6f}'); print('Multiple optimizer test PASSED')"
 ```
 **Expected: Completes in < 1 second, prints two fitness values**
 
 ### Scenario 3: Direct Script Execution Test
-```bash
-poetry run python opt/harmony_search.py
+```fish
+uv run python opt/harmony_search.py
 ```
 **Expected: Prints "Best solution found:" and "Best fitness found:" with numerical values**
 
 ### Scenario 4: Advanced Import Test
-```bash
-poetry run python -c "
-from opt.abstract_optimizer import AbstractOptimizer
-from opt.benchmark.functions import shifted_ackley, sphere, rosenbrock, ackley
-from opt.sgd_momentum import SGDMomentum
-from opt.adamw import AdamW
-print('Advanced imports successful - gradient-based and base classes work')
-"
+```fish
+uv run python -c "from opt.abstract_optimizer import AbstractOptimizer; from opt.benchmark.functions import shifted_ackley, sphere, rosenbrock, ackley; from opt.sgd_momentum import SGDMomentum; from opt.adamw import AdamW; print('Advanced imports successful - gradient-based and base classes work')"
 ```
 
 ## Project Structure
@@ -142,9 +114,15 @@ print('Advanced imports successful - gradient-based and base classes work')
 
 ### Code Quality and Linting
 - **ALWAYS run linting before committing:**
-  ```bash
-  poetry run ruff check opt/
-  poetry run ruff format opt/
+  ```fish
+  uv run ruff check opt/ && uv run ruff format opt/
+  ```
+- Or run them separately:
+  ```fish
+  uv run ruff check opt/
+  ```
+  ```fish
+  uv run ruff format opt/
   ```
 - The project uses extensive ruff rules - expect to find existing linting issues
 - Ruff configuration is in `pyproject.toml` with Google docstring convention
@@ -158,16 +136,67 @@ print('Advanced imports successful - gradient-based and base classes work')
 - Use benchmark functions from `opt.benchmark.functions` for testing
 
 ### Testing Changes
-- No formal test suite exists - use the validation scenarios above
+- Run the test suite:
+  ```fish
+  uv run pytest opt/test/ -v
+  ```
+- Run specific test files:
+  ```fish
+  uv run pytest opt/test/test_benchmarks.py -v
+  ```
 - Test with multiple benchmark functions: `shifted_ackley`, `rosenbrock`, `sphere`
 - Test with different parameter combinations
 - Ensure optimizers complete within reasonable time (< 1 second for small max_iter)
 
 ### Common Issues to Avoid
-- Don't modify `poetry.lock` manually - use `poetry add/remove` commands
+- Don't modify `uv.lock` manually - use `uv add`, `uv remove`, or `uv sync` to change dependencies
 - Ruff linting will fail on many existing files - focus on new/modified code
 - Some algorithms use legacy `np.random.rand` calls - documented in README
-- Always use `poetry run` prefix for Python commands to use project environment
+- Always use `uv run` (or activate `.venv`) so commands execute inside the project environment
+
+### CRITICAL: Fish Shell and Terminal Rules
+**All commands MUST be single-line.** Multiline commands crash the terminal in Fish shell.
+
+**Git commit messages:** Always use single-line format with conventional commits:
+```fish
+git commit -m "feat: add new optimizer algorithm"
+```
+
+**Conventional commit types:**
+- `feat:` - New feature
+- `fix:` - Bug fix
+- `docs:` - Documentation changes
+- `test:` - Adding or updating tests
+- `refactor:` - Code refactoring
+- `chore:` - Maintenance tasks
+
+**NEVER use multiline commit messages like this (WILL CRASH):**
+```fish
+# BAD - DO NOT USE
+git commit -m "Title
+
+Multiline body"
+```
+
+**For commit messages with title and body**, use multiple `-m` flags on one line:
+```fish
+git commit -m "Title" -m "Body paragraph 1" -m "Body paragraph 2"
+```
+
+**For longer commit messages**, use the editor:
+```fish
+git commit
+```
+
+**Chaining commands:** Use `&&` to chain multiple commands:
+```fish
+git add . && git commit -m "message" && git push
+```
+
+**Python -c commands:** Keep on single line with semicolons:
+```fish
+uv run python -c "import x; print(x.value); do_something()"
+```
 
 ## Project Information
 - **Version:** 0.1.2
@@ -178,16 +207,16 @@ print('Advanced imports successful - gradient-based and base classes work')
 - **License:** MIT
 
 ## Build and Distribution
-- Build package: `poetry build` (< 1 second)
+- Build package: `uv build` (< 1 second)
 - Built artifacts appear in `dist/` directory
 - CI/CD publishes to PyPI on tag pushes via GitHub Actions
 - Test PyPI publishing is also configured
 
 ## Performance Expectations
-- **Poetry install:** 2-3 minutes (NEVER CANCEL)
+- **uv sync:** 2-3 minutes (NEVER CANCEL)
 - **Ruff linting:** 5-10 seconds
 - **Ruff formatting:** < 1 second
-- **Package build:** < 1 second
+- **Package build (uv build):** < 1 second
 - **Small optimization runs:** < 1 second (max_iter=50-100)
 - **Import operations:** Nearly instantaneous
 

.github/workflows/python-publish.yaml

@@ -69,7 +69,7 @@ jobs:
           name: python-package-distributions
           path: dist/
       - name: Sign the dists with Sigstore
-        uses: sigstore/gh-action-sigstore-python@v3.1.0
+        uses: sigstore/gh-action-sigstore-python@v3.2.0
         with:
           inputs: >-
             ./dist/*.tar.gz