workspace-hub-compliance

name	workspace-hub-compliance
version	1.0.0
category	archive
description	Systematic verification checklist for ensuring repositories comply with workspace-hub standards covering UV, Plotly, file organization, and modern Python practices.

Workspace-Hub Standards Compliance Skill

Version: 1.0.0 Created: 2026-01-08 Category: Standards, Compliance, Code Quality

Overview

This skill provides a systematic verification checklist for ensuring repositories comply with workspace-hub standards. It covers UV package management, Plotly visualization requirements, file organization standards, and modern Python development practices.

When to Use

Use this skill when:

• Setting up new repositories in workspace-hub
• Reviewing existing repositories for standards violations
• Modernizing tech stacks to workspace-hub requirements
• Preparing repositories for compliance propagation
• Auditing codebase for deprecated tools and practices
• Implementing best practices across multiple repositories

Skill Components

1. UV Package Manager Compliance

Standard: All Python projects MUST use UV package manager (not Conda, Poetry, or pip)

Verification Checklist:

• pyproject.toml exists with proper configuration
• No conda.yaml, environment.yml, or requirements.txt files
• No Poetry configuration (poetry.lock, pyproject.toml with [tool.poetry])
• README documentation mentions UV, not Conda/Poetry
• Setup instructions use uv venv and uv pip install
• Python version specified as requires-python = ">=3.11"

Compliance Commands:

# ✅ Correct UV usage
uv venv
source .venv/bin/activate  # Linux/Mac
.venv\Scripts\activate     # Windows
uv pip install -e .

# ❌ Wrong - Conda
conda create -n myenv python=3.11
conda activate myenv

# ❌ Wrong - Poetry
poetry install
poetry shell

# ❌ Wrong - pip
python -m venv venv
pip install -r requirements.txt

Migration Steps:

1. Install UV: curl -LsSf https://astral.sh/uv/install.sh | sh
2. Create pyproject.toml from existing requirements.txt or pyproject.toml (Poetry)
3. Remove Conda/Poetry configuration files
4. Update README with UV instructions
5. Test installation: uv pip install -e .

pyproject.toml Template:

[project]
name = "project-name"
version = "1.0.0"
description = "Brief description"
requires-python = ">=3.11"
dependencies = [
    "pandas>=2.0.0",
    "numpy>=1.24.0",
    # Add other dependencies
]

[project.optional-dependencies]
dev = [
    "pytest>=7.4.0",
    "pytest-cov>=4.1.0",
    "ruff>=0.1.0",
]

[project.scripts]
main-command = "package.module:main"

2. Plotly Interactive Visualization Compliance

Standard: ALL visualizations MUST be interactive using Plotly (no static matplotlib/seaborn)

Verification Checklist:

• No matplotlib, seaborn, or pyplot imports in codebase
• All plotting uses plotly.express or plotly.graph_objects
• Dependencies include plotly>=5.14.0 and kaleido>=0.2.1
• No .png, .jpg, .svg static plot exports
• HTML reports with interactive plots (.html files)
• Explicit note in docs: "All visualizations MUST be interactive (Plotly)"

Compliance Commands:

# ✅ Correct - Plotly interactive
import plotly.express as px
import pandas as pd

df = pd.read_csv('../data/processed/results.csv')
fig = px.scatter(df, x='time', y='value', title='Interactive Plot')
fig.write_html('../reports/analysis.html')

# ❌ Wrong - Matplotlib static
import matplotlib.pyplot as plt
plt.scatter(df['time'], df['value'])
plt.savefig('plot.png')  # Static image export

# ❌ Wrong - Seaborn static
import seaborn as sns
sns.scatterplot(data=df, x='time', y='value')
plt.savefig('plot.png')

Migration Steps:

1. Search codebase for matplotlib, seaborn, pyplot imports
2. Replace with plotly.express or plotly.graph_objects
3. Convert static plots to interactive equivalents
4. Update dependencies: Remove matplotlib/seaborn, add Plotly/Kaleido
5. Change output from .png/.jpg to .html
6. Test all visualizations in browser

Plotly Equivalents:

Matplotlib/Seaborn	Plotly Equivalent
plt.plot()	px.line()
plt.scatter()	px.scatter()
plt.bar()	px.bar()
plt.hist()	px.histogram()
sns.heatmap()	px.imshow() or go.Heatmap()
plt.pie()	px.pie()
sns.boxplot()	px.box()
sns.violinplot()	px.violin()

3. File Organization Standards Compliance

Standard: Consistent file organization across all repositories

Verification Checklist:

• Reports saved to /reports/ directory (NOT root)
• Data files in /data/ with subdirectories: raw/, processed/, results/
• Source code in /src/ with module-based organization
• Tests in /tests/ mirroring /src/ structure
• Configuration in /config/ directory
• Documentation in /docs/ directory
• No files saved to repository root (except standard files: README, LICENSE, pyproject.toml, .gitignore)

Standard Directory Structure:

repository/
├── src/                    # Source code
│   └── modules/
│       ├── module_1/
│       └── module_2/
├── tests/                  # Test files
│   ├── unit/
│   └── integration/
├── docs/                   # Documentation
├── config/                 # Configuration files
├── scripts/                # Utility scripts
├── data/                   # Data files
│   ├── raw/               # Raw input data
│   ├── processed/         # Processed data
│   └── results/           # Output results
├── reports/               # Generated reports (HTML, PDF)
└── pyproject.toml        # Project configuration

Migration Steps:

1. Create standard directories if missing: mkdir -p {src,tests,docs,config,scripts,data/{raw,processed,results},reports}
2. Move misplaced files to correct directories
3. Update import paths in code
4. Update file paths in scripts and documentation
5. Add .gitignore entries for generated files in /reports/ and /data/results/

4. CSV Data Import Standards Compliance

Standard: CSV data MUST use relative paths from report location

Verification Checklist:

• No hardcoded absolute paths (e.g., /mnt/github/..., C:\Users\...)
• All CSV imports use relative paths (e.g., ../data/processed/file.csv)
• CSV files stored in standardized locations (/data/raw/, /data/processed/, /data/results/)
• Path resolution utilities for cross-platform compatibility
• Documentation specifies data directory structure

Compliance Commands:

# ✅ Correct - Relative path from report location
import pandas as pd
df = pd.read_csv('../data/processed/results.csv')

# ✅ Correct - Path utility
from pathlib import Path

def get_data_path(filename, data_type='processed'):
    """Get data file path relative to project root."""
    project_root = Path(__file__).parent.parent.parent
    return project_root / 'data' / data_type / filename

df = pd.read_csv(get_data_path('results.csv'))

# ❌ Wrong - Absolute path (not portable)
df = pd.read_csv('/mnt/github/workspace-hub/repo/data/results.csv')

# ❌ Wrong - Windows-specific absolute path
df = pd.read_csv('C:/Users/user/Documents/repo/data/results.csv')

Migration Steps:

1. Search codebase for absolute paths: grep -r "/mnt/" . or grep -r "C:\\" .
2. Replace with relative paths or path utilities
3. Test on different platforms (Linux, macOS, Windows)
4. Document data directory structure in README

5. Modern Python Standards Compliance

Standard: Python 3.11+ with modern type hints and current dependency versions

Verification Checklist:

• Python version >=3.11 in pyproject.toml
• Modern type hints used (from __future__ import annotations)
• Current major versions for dependencies (Pandas 2.0+, NumPy 1.24+)
• Deprecated packages replaced (e.g., pypdf instead of PyPDF2)
• Modern linter: Ruff (not Black + isort + flake8)
• Type checking with mypy enabled

Compliance Dependencies:

[project]
requires-python = ">=3.11"
dependencies = [
    "pandas>=2.0.0",        # Not pandas 1.x
    "numpy>=1.24.0",        # Not numpy 1.x
    "pypdf>=3.0.0",         # Not PyPDF2
    "plotly>=5.14.0",       # Interactive viz
    "python-dotenv>=1.0.0", # Modern version
]

[project.optional-dependencies]
dev = [
    "ruff>=0.1.0",          # Modern linter (replaces Black, isort, flake8)
    "mypy>=1.5.0",          # Type checking
    "pytest>=7.4.0",        # Testing
]

Migration Steps:

1. Update requires-python to >=3.11
2. Update all dependencies to current major versions
3. Replace deprecated packages (PyPDF2 → pypdf, etc.)
4. Replace Black + isort + flake8 with Ruff
5. Add type hints to functions
6. Run mypy to validate types

6. Module Organization Standards Compliance

Standard: Modular architecture with clear module boundaries and CLI commands

Verification Checklist:

• Modules organized under /src/modules/ with domain-driven names
• Each module has __init__.py with clear exports
• Module-specific CLI commands defined in [project.scripts]
• Shared utilities in /src/modules/shared/ or /src/utils/
• Module boundaries clearly documented (DEC-XXX decisions)
• No circular dependencies between modules

Compliance Structure:

src/
└── modules/
    ├── module_1/
    │   ├── __init__.py
    │   ├── core.py
    │   ├── utils.py
    │   └── config.py
    ├── module_2/
    │   ├── __init__.py
    │   └── processor.py
    └── shared/
        ├── __init__.py
        └── helpers.py

CLI Configuration:

[project.scripts]
module1-command = "package.modules.module_1:main"
module2-command = "package.modules.module_2:main"

Migration Steps:

1. Identify logical module boundaries based on functionality
2. Create module directories under /src/modules/
3. Move related files into appropriate modules
4. Update imports to reflect new structure
5. Define CLI entry points for each module
6. Document module architecture in decisions.md

Compliance Verification Process

Step 1: Run Automated Checks

UV Compliance:

# Check for Conda/Poetry files
find . -name "conda.yaml" -o -name "environment.yml" -o -name "poetry.lock"
# Should return nothing

# Check for pyproject.toml with UV
grep -q "requires-python" pyproject.toml && echo "✓ UV compliant" || echo "✗ Missing UV config"

Plotly Compliance:

# Check for matplotlib/seaborn imports
grep -r "import matplotlib" src/ && echo "✗ Matplotlib found" || echo "✓ No matplotlib"
grep -r "import seaborn" src/ && echo "✗ Seaborn found" || echo "✓ No seaborn"
grep -r "import plotly" src/ && echo "✓ Plotly found" || echo "✗ Missing Plotly"

File Organization:

# Check for files in root that should be elsewhere
ls *.html *.csv *.png 2>/dev/null && echo "✗ Files in root" || echo "✓ Clean root"

# Check for standard directories
for dir in src tests docs config scripts data reports; do
    [ -d "$dir" ] && echo "✓ $dir exists" || echo "✗ $dir missing"
done

Step 2: Manual Review

Checklist:

• README documentation reflects UV usage
• All visualizations are interactive (test HTML reports in browser)
• CSV paths are relative (no absolute paths)
• Dependencies are current versions (check pyproject.toml)
• Modules have clear boundaries (check /src/modules/ structure)
• CLI commands work (python -m package.module)

Step 3: Test Compliance

UV Installation Test:

# Clean environment
rm -rf .venv

# Test UV setup
uv venv
source .venv/bin/activate
uv pip install -e .

# Verify installation
python -c "import [package]"

Visualization Test:

# Generate report
python scripts/generate_report.py

# Open in browser
open reports/report.html  # macOS
xdg-open reports/report.html  # Linux
start reports/report.html  # Windows

# Verify interactivity: hover, zoom, pan should work

Compliance Templates

UV Migration Template

#!/bin/bash
# migrate_to_uv.sh - Migrate repository to UV package manager

echo "🔄 Migrating to UV package manager..."

# Step 1: Install UV (if not installed)
if ! command -v uv &> /dev/null; then
    echo "Installing UV..."
    curl -LsSf https://astral.sh/uv/install.sh | sh
fi

# Step 2: Create pyproject.toml from requirements.txt
if [ -f "requirements.txt" ]; then
    echo "Creating pyproject.toml from requirements.txt..."
    # Manual conversion needed - see template
fi

# Step 3: Remove old configuration
echo "Removing Conda/Poetry files..."
rm -f conda.yaml environment.yml poetry.lock

# Step 4: Create UV environment
echo "Creating UV environment..."
uv venv
source .venv/bin/activate

# Step 5: Install dependencies
echo "Installing dependencies with UV..."
uv pip install -e .

# Step 6: Update README
echo "Update README with UV instructions (manual step)"
echo "✅ UV migration complete!"

Plotly Migration Template

# migrate_to_plotly.py - Convert matplotlib plots to Plotly

import re
from pathlib import Path

def convert_matplotlib_to_plotly(file_path):
    """Convert matplotlib code to Plotly equivalents."""

    conversions = {
        r'import matplotlib\.pyplot as plt': 'import plotly.express as px',
        r'plt\.scatter\((.*?)\)': r'px.scatter(df, x=\1)',
        r'plt\.plot\((.*?)\)': r'px.line(df, x=\1)',
        r'plt\.bar\((.*?)\)': r'px.bar(df, x=\1)',
        r'plt\.savefig\(["\'](.+?)\.png["\']\)': r'fig.write_html("\1.html")',
    }

    content = file_path.read_text()

    for old_pattern, new_pattern in conversions.items():
        content = re.sub(old_pattern, new_pattern, content)

    file_path.write_text(content)
    print(f"✅ Converted: {file_path}")

# Usage
for py_file in Path('src').rglob('*.py'):
    if 'matplotlib' in py_file.read_text():
        convert_matplotlib_to_plotly(py_file)

File Organization Template

#!/bin/bash
# organize_files.sh - Reorganize files to workspace-hub standards

echo "📁 Organizing files to workspace-hub standards..."

# Create standard directories
mkdir -p src/{modules,utils} tests/{unit,integration} docs config scripts
mkdir -p data/{raw,processed,results} reports

# Move misplaced files
echo "Moving files to correct directories..."

# Move Python files to src/
find . -maxdepth 1 -name "*.py" ! -name "setup.py" -exec mv {} src/ \;

# Move test files to tests/
find . -name "test_*.py" -exec mv {} tests/unit/ \;

# Move data files
find . -maxdepth 1 -name "*.csv" -exec mv {} data/raw/ \;

# Move reports
find . -maxdepth 1 -name "*.html" -exec mv {} reports/ \;

# Update .gitignore
cat >> .gitignore <<EOF

# Generated files
reports/*.html
data/results/
*.log
EOF

echo "✅ File organization complete!"
echo "⚠️  Update import paths in code manually"

Compliance Enforcement

Pre-Commit Hook

#!/bin/bash
# .git/hooks/pre-commit - Workspace-hub standards enforcement

echo "🔍 Checking workspace-hub standards compliance..."

# Check 1: UV compliance
if [ -f "conda.yaml" ] || [ -f "environment.yml" ]; then
    echo "❌ ERROR: Conda configuration found. Use UV package manager."
    exit 1
fi

# Check 2: Plotly compliance
if grep -r "import matplotlib" src/ 2>/dev/null; then
    echo "❌ ERROR: Matplotlib imports found. Use Plotly for interactive visualizations."
    exit 1
fi

# Check 3: File organization
if ls *.html 2>/dev/null || ls *.csv 2>/dev/null; then
    echo "❌ ERROR: Files in root directory. Move to /reports/ or /data/"
    exit 1
fi

# Check 4: Absolute paths
if grep -r "/mnt/github" src/ 2>/dev/null || grep -r "C:\\\\" src/ 2>/dev/null; then
    echo "❌ ERROR: Absolute paths found. Use relative paths."
    exit 1
fi

echo "✅ Compliance checks passed!"

CI/CD Validation

# .github/workflows/compliance.yml
name: Workspace-Hub Compliance

on: [push, pull_request]

jobs:
  compliance:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3

      - name: Check UV Configuration
        run: |
          test -f pyproject.toml || (echo "Missing pyproject.toml" && exit 1)
          grep -q "requires-python" pyproject.toml || (echo "Missing Python version" && exit 1)

      - name: Check for Conda/Poetry
        run: |
          ! test -f conda.yaml && ! test -f environment.yml && ! test -f poetry.lock

      - name: Check Plotly Usage
        run: |
          ! grep -r "import matplotlib" src/
          ! grep -r "import seaborn" src/
          grep -r "import plotly" src/ || (echo "Missing Plotly" && exit 1)

      - name: Check File Organization
        run: |
          test -d src && test -d tests && test -d docs && test -d data && test -d reports
          ! ls *.html *.csv 2>/dev/null

Best Practices

Do's

✅ Use UV for all Python projects - Faster, more reliable than Conda/Poetry ✅ Interactive visualizations only - Plotly for all charts and graphs ✅ Relative paths for data - Portable across environments ✅ Organized directory structure - Files in appropriate subdirectories ✅ Modern Python (3.11+) - Latest features and performance ✅ Current dependency versions - Major versions (Pandas 2.0+, etc.)

Don'ts

❌ Don't use Conda or Poetry - UV is the workspace-hub standard ❌ Don't use matplotlib/seaborn - Static plots violate standards ❌ Don't use absolute paths - Breaks portability ❌ Don't save to root directory - Use /reports/, /data/, etc. ❌ Don't use outdated dependencies - Keep major versions current ❌ Don't use deprecated packages - Replace PyPDF2 with pypdf, etc.

Related Skills

• Product Documentation Modernization - Documenting compliance requirements
• Technology Stack Modernization - Updating to compliant tech stack
• File Organization - Implementing standard directory structure
• Quantification & Metrics - Measuring compliance impact

References

• Workspace-Hub Standards: /mnt/github/workspace-hub/docs/modules/standards/
• UV Package Manager: https://github.com/astral-sh/uv
• Plotly Documentation: https://plotly.com/python/
• HTML Reporting Standards: docs/modules/standards/HTML_REPORTING_STANDARDS.md
• File Organization Standards: docs/modules/standards/FILE_ORGANIZATION_STANDARDS.md

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Version History

• 1.0.0 (2026-01-08): Initial skill creation based on aceengineer-admin tech-stack.md modernization work