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feat: update plan
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‎.amazonq/plan/compare_template_files.py‎

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#!/usr/bin/env python3
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"""Reusable file comparison tool for template validation."""
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import difflib
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from pathlib import Path
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from typing import Literal
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import typer
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def compare_files(file1: Path, file2: Path, label1: str, label2: str) -> bool:
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"""Compare two files and show differences. Returns True if identical."""
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print(f"\n{'='*60}")
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print(f"COMPARING: {file1.name}")
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print(f"{label1}: {file1}")
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print(f"{label2}: {file2}")
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print(f"{'='*60}")
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if not file1.exists():
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print(f"❌ MISSING: {file1} does not exist")
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return False
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if not file2.exists():
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print(f"❌ MISSING: {file2} does not exist")
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return False
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content1 = file1.read_text().splitlines(keepends=True)
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content2 = file2.read_text().splitlines(keepends=True)
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diff = list(
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difflib.unified_diff(
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content1,
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content2,
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fromfile=f"{label1}/{file1.name}",
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tofile=f"{label2}/{file2.name}",
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lineterm="",
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)
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)
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if not diff:
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print("✅ FILES IDENTICAL")
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return True
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else:
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print("❌ DIFFERENCES FOUND:")
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for line in diff:
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print(line)
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return False
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def main(
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mode: Literal["template", "generated"] = typer.Argument(
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help="Compare template files or generated files"
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),
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question: str = typer.Option("invert_binary_tree", help="Question name for comparison"),
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):
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"""Compare files for template validation."""
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base_dir = Path(__file__).parent.parent.parent
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files_to_compare = ["solution.py", "tests.py", "README.md", "playground.ipynb", "__init__.py"]
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if mode == "template":
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# Compare reference vs template source
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dir1 = base_dir / "leetcode" / ".example" / question
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dir2 = base_dir / ".templates" / "leetcode" / ".example" / "{{cookiecutter.question_name}}"
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label1, label2 = "Reference", "Template"
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print("TEMPLATE SOURCE ANALYSIS")
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elif mode == "generated":
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# Compare reference vs currently generated
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dir1 = base_dir / "leetcode" / ".example" / question
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dir2 = base_dir / "leetcode" / question
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label1, label2 = "Reference", "Generated"
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print("GENERATED FILES VALIDATION")
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if not dir2.exists():
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print(f"\n❌ ERROR: Generated directory does not exist: {dir2}")
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print(f"Run: make q-gen QUESTION={question}")
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return
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print(f"{label1}: {dir1}")
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print(f"{label2}: {dir2}")
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identical_count = 0
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for filename in files_to_compare:
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file1 = dir1 / filename
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file2 = dir2 / filename
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if compare_files(file1, file2, label1, label2):
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identical_count += 1
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print(f"\n{'='*60}")
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print(f"SUMMARY: {identical_count}/{len(files_to_compare)} files identical")
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print("- ✅ = Files identical")
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print("- ❌ = Differences found or missing files")
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if __name__ == "__main__":
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typer.run(main)

‎.amazonq/plan/cookiecutter-template-plan.md‎

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# Cookiecutter Template Modernization Plan
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## Analysis Summary
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**Target Structure**: `leetcode/.example/` contains the reference implementation
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**Key Differences Found:**
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- `leetcode/.example/` has `__init__.py` files (missing in old template)
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- `leetcode/.example/` uses modern Python syntax (`TreeNode | None` vs `Optional[TreeNode]`)
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- `leetcode/.example/` follows project's coding standards more closely
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- Template must generate files identical to `leetcode/.example/` structure
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## Implementation Plan
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### 0. Explicit File Content Analysis
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- **Tool**: `.amazonq/plan/compare_template_files.py` (reusable comparison script)
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- **Usage**:
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- `python .amazonq/plan/compare_template_files.py template` - Compare reference vs template source
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- `python .amazonq/plan/compare_template_files.py generated` - Compare reference vs generated files
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- **Analysis**: Line-by-line diff of all file types
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- **Document**: Exact differences and required changes
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- **Verify**: Template variables handle all variations
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### 1. Incremental Template Updates (File-by-File Approach)
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#### Phase 1: Add `__init__.py`
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- **Add**: Empty `__init__.py` file to template
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- **Validate**: `make q-gen` → `make q-validate` → `make lint`
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#### Phase 2: Fix `solution.py`
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- **Update**: Modern syntax (`TreeNode | None`), clean template logic
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- **Validate**: `make q-gen` → `make q-validate` → `make lint`
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#### Phase 3: Fix `tests.py`
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- **Update**: Relative imports (`from .solution`), clean structure
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- **Validate**: `make q-gen` → `make q-validate` → `make lint`
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#### Phase 4: Fix `README.md`
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- **Update**: Clean formatting, proper markdown
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- **Validate**: `make q-gen` → `make q-validate` → `make lint`
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#### Phase 5: Fix `playground.ipynb`
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- **Update**: Clean cells without execution state
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- **Validate**: `make q-gen` → `make q-validate` → `make lint`
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**Benefits**: Isolated debugging, safer progression, easier rollback
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### 2. Multi-Problem Type Testing
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- **Test Cases**: Ensure template handles all problem types
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- Basic array: `two_sum` (return `list[int]`)
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- Tree: `invert_binary_tree` (return `TreeNode | None`)
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- String: problems returning `str`
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- Boolean: problems returning `bool`
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- No imports vs TreeNode/ListNode imports
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- **Validation**: Each type generates correctly
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### 3. Modernize cookiecutter.json Schema
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- **Base on**: Existing `.templates/leetcode/.example/examples/` JSON5 files
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- **Ensure**: All template variables are properly defined
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- **Add**: Missing fields found in real examples
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- **Note**: Variable mapping handled by `gen.py` `convert_arrays_to_nested()`
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### 4. Update Template Files
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#### solution.py
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- Use modern type hints (`TreeNode | None` not `Optional[TreeNode]`)
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- Match exact import patterns from real examples
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- Ensure proper TODO placeholder format
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#### tests.py
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- Follow `@logged_test` decorator pattern
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- Use parametrized pytest structure
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- Match logging format from real examples
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#### README.md
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- Follow exact format from real examples
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- Include proper problem description formatting
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#### playground.ipynb
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- Ensure notebook structure matches real examples
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### 5. Template Generation Logic
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- **File**: `.templates/leetcode/gen.py` (already handles variable mapping)
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- **Integration**: Works with `make q-gen QUESTION=name` (verified in Makefile)
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- **Update**: Handle new `__init__.py` file
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- **Process**: JSON → `gen.py` → cookiecutter → `leetcode/$(QUESTION)/`
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### 6. Automated Validation System
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- **Tool**: Reusable `.amazonq/plan/compare_template_files.py`
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- **Usage**:
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```bash
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# Validate current template generates correct files
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python .amazonq/plan/compare_template_files.py generated --question=invert_binary_tree
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```
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- **Makefile**: `make q-validate QUESTION=name` (implemented)
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- **Test**: Template regression testing
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- **Ensure**: `make q-gen` + `make lint` + `make q-test` all pass
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### 7. Testing & Validation
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- **Test**: Template generation with existing JSON files
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- **Verify**: Generated files match `leetcode/.example/` structure exactly
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- **Compare**: Automated diff against reference files
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- **Ensure**: `make q-gen` works seamlessly
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- **Test**: Recreation process from `.prompt/` files
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- **Validate**: Multi-problem type generation
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## Key Template Variables to Ensure
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```json
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{
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"question_name": "snake_case_name",
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"class_name": "PascalCaseName",
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"method_name": "snake_case_method",
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"problem_number": "226",
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"problem_title": "Display Title",
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"difficulty": "Easy|Medium|Hard",
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"topics": "Comma, Separated, Topics",
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"tags": ["grind-75", "blind-75"],
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"problem_description": "Full description",
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"examples": [{"input": "...", "output": "..."}],
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"constraints": "Formatted constraints",
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"parameters": "typed_params: list[int]",
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"return_type": "TreeNode | None",
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"imports": "from leetcode_py.tree_node import TreeNode",
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"test_cases": [{"args": [...], "expected": ...}]
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}
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```
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## Success Criteria
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### Phase-by-Phase Validation (File-by-File)
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1. ✅ **Phase 1**: `__init__.py` files generated correctly
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2. ✅ **Phase 2**: `solution.py` with modern syntax (`TreeNode | None`)
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3. ✅ **Phase 3**: `tests.py` with relative imports and clean structure
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4. ✅ **Phase 4**: `README.md` with clean formatting
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5. ✅ **Phase 5**: `playground.ipynb` with clean cells
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### Multi-Problem Type Validation
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5. ✅ Basic problems (array/string) generate correctly
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6. ✅ Tree problems generate correctly
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7. ✅ Different return types handled (`bool`, `int`, `str`, `list`, etc.)
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### Automated Validation
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8. ✅ Automated diff shows no differences vs `leetcode/.example/`
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9. ✅ `make q-validate` passes for all problem types
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10. ✅ Recreation from `.prompt/` works flawlessly
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11. ✅ All linting passes (`make lint`)
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12. ✅ Tests run successfully (`make q-test`)
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## Files to Modify
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### Template Files
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1. `.templates/leetcode/{{cookiecutter.question_name}}/`
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- **Add**: `__init__.py` (empty file)
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- **Update**: `solution.py` (modern syntax, imports)
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- **Update**: `tests.py` (match `leetcode/.example/` format)
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- **Update**: `README.md` (match `leetcode/.example/` format)
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- **Update**: `playground.ipynb` (match structure)
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### Configuration
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2. `.templates/leetcode/cookiecutter.json`
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- Align with JSON5 examples
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- Add missing variables
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### Generation Logic
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3. `.templates/leetcode/gen.py`
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- Handle `__init__.py` generation
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- Maintain existing variable mapping
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### Validation Tools
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4. **Reusable**: `.amazonq/plan/compare_template_files.py` (handles both template and generated comparisons)
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5. **New**: Makefile target `make q-validate`
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## Risk Mitigation
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- **Incremental phases** prevent all-or-nothing failures
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- **Automated validation** catches regressions immediately
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- **Multi-problem testing** ensures template generalization
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- **Explicit file comparison** documents exact requirements
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This plan ensures the template generates files that exactly match `leetcode/.example/` while maintaining the robust generation process described in the rules.

‎.amazonq/rules/development-rules.md‎

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## Testing
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- Test specific: `make test-question QUESTION=<name>`
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- Test specific: `make q-test QUESTION=<name>`
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- Test all: `make test`
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- Beautiful logging with loguru
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‎.templates/leetcode/cookiecutter.json‎ renamed to ‎.templates/leetcode/.example/cookiecutter.json‎

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]
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},
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"param_names": "nums, target, expected",
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"param_names_with_types": "nums: list[int], target: int, expected: list[int]",
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"input_description": "nums={nums}, target={target}",
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"input_params": "nums, target",
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"expected_param": "expected",

‎.templates/leetcode/examples/basic.json5‎ renamed to ‎.templates/leetcode/.example/examples/basic.json5‎

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// Test template variables (auto-generated, can be customized)
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param_names: "nums, target, expected",
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param_names_with_types: "nums: list[int], target: int, expected: list[int]",
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input_description: "nums={nums}, target={target}",
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input_params: "nums, target",
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expected_param: "expected",

‎.templates/leetcode/examples/tree.json5‎ renamed to ‎.templates/leetcode/.example/examples/tree.json5‎

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// Tree-specific test setup
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param_names: "root, expected",
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param_names_with_types: "root: list[int], expected: list[int]",
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input_description: "root={root}",
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input_params: "root",
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expected_param: "expected",

‎.templates/leetcode/json/invert_binary_tree.json‎ renamed to ‎.templates/leetcode/.example/json/invert_binary_tree.json‎

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"tags": ["grind-75"],
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"problem_description": "Given the root of a binary tree, invert the tree, and return its root.",
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"examples": [
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{
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"input": "root = [4,2,7,1,3,6,9]",
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"output": "[4,7,2,9,6,3,1]"
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},
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{
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"input": "root = [2,1,3]",
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"output": "[2,3,1]"
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},
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{
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"input": "root = []",
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"output": "[]"
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}
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{ "input": "root = [4,2,7,1,3,6,9]", "output": "[4,7,2,9,6,3,1]" },
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{ "input": "root = [2,1,3]", "output": "[2,3,1]" },
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{ "input": "root = []", "output": "[]" }
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],
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"constraints": "- The number of nodes in the tree is in the range [0, 100].\n- -100 <= Node.val <= 100",
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"parameters": "root: TreeNode | None",
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"return_type": "TreeNode | None",
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"imports": "from leetcode_py.tree_node import TreeNode",
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"test_cases": [
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{
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"args": [[4, 2, 7, 1, 3, 6, 9]],
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"expected": [4, 7, 2, 9, 6, 3, 1]
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},
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{
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"args": [[2, 1, 3]],
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"expected": [2, 3, 1]
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},
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{
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"args": [[]],
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"expected": []
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}
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{ "args": [[4, 2, 7, 1, 3, 6, 9]], "expected": [4, 7, 2, 9, 6, 3, 1] },
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{ "args": [[2, 1, 3]], "expected": [2, 3, 1] },
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{ "args": [[]], "expected": [] }
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],
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"param_names": "root, expected",
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"input_description": "root={root}",
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"param_names": "root_list, expected",
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"param_names_with_types": "root_list: list[int | None], expected: list[int | None]",
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"input_description": "root_list={root_list}",
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"input_params": "root",
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"expected_param": "expected",
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"method_args": "root",
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"test_setup": "root = TreeNode.from_list(root)",
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"test_setup": "root = TreeNode.from_list(root_list)",
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"test_logging": "logger.success(f\"Got result: {result.to_list() if result else []}\")",
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"assertion_code": "assert result == expected",
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"test_input_setup": "# Example test case\\nroot = TreeNode.from_list([4, 2, 7, 1, 3, 6, 9])",

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