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Quick Reference: Template | How To Use | Documentation
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🔗 Quick Links:
- GitHub Template - Click "Use this template"
- How To Use Guide - usage guide from basic to advanced
- Documentation - project overview
- Architecture Guide - System design details
- Workflow Guide - Development process
- GitHub Template: A research project template with test-driven development, automated PDF generation, and professional documentation structure.
- Research Workflow: template for academic papers with test coverage, automated figure generation, and LaTeX/PDF output.
- Academic Template: Professional research project structure with thin orchestrator pattern, automated testing, and publication-ready PDF generation.
- Science Template: Test-driven development template for research projects with automated documentation, figure generation, and LaTeX compilation.
- Automated Research: Template that automatically generates PDFs from markdown with integrated figures, cross-references, and professional formatting.
- Test-Driven Science: Research template enforcing test coverage with thin orchestrator pattern for maintainable scientific code.
- Publication Ready: Academic template that generates publication-ready PDFs with proper LaTeX formatting, figure integration, and cross-referencing.
This GitHub template implements a thin orchestrator pattern with test coverage requirements. The template automatically generates publication-ready PDFs from markdown sources, includes automated figure generation from Python scripts, and maintains coherence between source code, tests, and documentation. It's for academic papers, scientific documentation, technical reports, and any project requiring professional output with automated quality assurance. The architecture ensures maintainable, testable code while keeping scripts lightweight and focused.
A revolutionary research project template that transforms how scientists and researchers approach documentation. It provides a standardized structure with test-driven development, automated PDF generation from markdown, and professional LaTeX formatting. The template includes cross-referencing systems, automated glossary generation from source code, and ensures all figures and data are properly integrated. for thesis projects, research papers, and scientific documentation. The markdown guide shows how to create publication-ready content with proper equations and references.
Built for developers who need professional research output, this template enforces clean architecture through the thin orchestrator pattern where scripts import and use tested methods from source modules. It includes testing with coverage requirements, automated build pipelines, and generates multiple output formats including PDF, LaTeX, and HTML. The template maintains synchronization between code, tests, and documentation. The workflow guide shows the development process from tests to publication.
Get started immediately with this research project template that provides everything you need: project structure, test-driven development setup, automated PDF generation, and professional documentation workflows. Simply click "Use this template" on GitHub, customize your project details, and start building. The template includes examples, automated testing, and generates publication-ready outputs with minimal configuration. Check the how to use guide for step-by-step instructions and the examples showcase for real-world usage patterns.
# Clean all outputs and regenerate everything
uv run python scripts/execute_pipeline.py --project {name} --core-only# Run tests with coverage
uv run pytest tests/ --cov=src --cov-report=term-missing# Option 1: Edit config.yaml (recommended)
cp projects/{name}/manuscript/config.yaml.example projects/{name}/manuscript/config.yaml
vim projects/{name}/manuscript/config.yaml
# Option 2: Use environment variables
export AUTHOR_NAME="Your Name"
export PROJECT_TITLE="Your Project Title"# Install dependencies
uv sync
# Run pipeline
uv run python scripts/execute_pipeline.py --project {name} --core-only
# Run pipeline (includes cleanup)
uv run python scripts/execute_pipeline.py --project {name} --core-only# 1. Make changes to src/ code
# 2. Run tests to ensure coverage requirements met
uv run pytest tests/ --cov=src --cov-report=term-missing
# 3. Generate figures and validate
uv run python projects/templates/template_code_project/scripts/optimization_analysis.py
uv run python -m infrastructure.validation.cli markdown projects/{name}/manuscript/
# 4. Build pipeline
uv run python scripts/execute_pipeline.py --project {name} --core-only🚀 New research project template! Test-driven development + automated PDF generation + professional LaTeX output. for academic papers, thesis projects, and scientific documentation. test coverage enforced. #Research #Academic #OpenSource
Excited to share this research project template I've been working on! It provides a standardized structure for research projects with test-driven development, automated PDF generation from markdown, and professional documentation workflows. for academics, researchers, and developers who need publication-ready outputs. The template enforces clean architecture through the thin orchestrator pattern and includes testing with coverage requirements. Check it out and let me know what you think!
[GitHub Template] Research Project Template with Test-Driven Development, Automated PDF Generation, and Professional Documentation Structure
I've created a GitHub template for research projects that I think could be really useful for the community. It includes:
✅ Test-driven development with coverage requirements ✅ Automated PDF generation from markdown with LaTeX ✅ Thin orchestrator pattern for maintainable code ✅ Professional documentation structure ✅ Automated figure generation from Python scripts ✅ Cross-referencing system for complex documents
The template is designed for academic papers, scientific documentation, thesis projects, and any research requiring professional output. It automatically validates code quality, generates figures, and creates publication-ready PDFs. Check out the examples showcase for real-world usage patterns.
Would love feedback from researchers and developers who might use this!
Here's a research project template that handles exactly what you're looking for:
🚀 Key Features: ✅ Test-driven development with coverage ✅ Automated PDF generation from markdown ✅ Professional LaTeX output with cross-referencing ✅ Automated figure generation from Python scripts ✅ Thin orchestrator pattern for maintainable code
⚡ Quick Start:
# Clone and setup
git clone https://github.com/docxology/template.git
cd template
uv sync
# Generate everything
uv run python scripts/execute_pipeline.py --project {name} --core-onlyThe template automatically handles LaTeX compilation, figure integration, and generates publication-ready PDFs. for academic papers and research documentation. Check the how to use guide for step-by-step instructions and the architecture guide for detailed system design.
This template solves exactly the problem you're describing! It provides:
🔧 1. Standardized Structure: Clear separation between source code, tests, scripts, and documentation 🧪 2. Automated Quality: test coverage and automated validation 📚 3. Professional Output: Publication-ready PDFs with proper LaTeX formatting 🖼️ 4. Figure Integration: Automated generation and integration of figures from Python scripts 🔗 5. Cross-Referencing: Built-in system for equations, figures, and sections
The thin orchestrator pattern ensures your scripts use tested methods from source modules, making the codebase maintainable and reliable. for research projects where accuracy and reproducibility matter. The how to use guide provides step-by-step instructions, and the workflow guide shows the development process.
I've developed a research project template that addresses many of the workflow issues we discuss here. It implements:
🔬 Core Principles: ✅ Test-driven development with enforced coverage requirements ✅ Automated documentation generation from source code ✅ Professional PDF output with LaTeX compilation ✅ Integrated figure and data generation ✅ Cross-referencing and glossary systems
🎯 Benefits for Researchers: ✅ Consistent project structure across teams ✅ Automated quality assurance ✅ Publication-ready outputs ✅ Reproducible research workflows ✅ Integration with existing Python ecosystems
The template is designed for academic papers, thesis projects, and scientific documentation. It automatically validates code quality and generates professional outputs, saving significant time on formatting and quality assurance. The how to use guide provides step-by-step instructions, and the examples showcase demonstrates real-world applications across different research domains.
Subject: Research Project Template - Automated Quality Assurance and Professional Output
Hi [Name],
I wanted to share a research project template I've developed that I think could be valuable for your team. It provides:
- Automated Quality Assurance: test coverage enforcement
- Professional Documentation: Publication-ready PDFs with LaTeX
- Standardized Workflow: Consistent project structure and processes
- Figure Integration: Automated generation and integration of research figures
- Cross-Referencing: Built-in systems for equations, figures, and sections
The template is designed for research projects requiring professional output and maintains synchronization between code, tests, and documentation.
You can find it at: GitHub Template
The how to use guide provides step-by-step instructions for getting started at any level of complexity.
Would be happy to discuss how this might fit into your research workflow.
Best regards, [Your Name]
Subject: Feedback Request - Research Project Template
Hi [Name],
I've developed a research project template and would value your feedback as someone working in [field/area]. The template includes:
- Test-driven development with automated quality assurance
- Professional PDF generation from markdown sources
- Automated figure generation and integration
- Cross-referencing and glossary systems
- Standardized project structure
It's designed for academic papers and research documentation, with a focus on reproducibility and professional output.
The how to use guide shows how it can be used at different levels of complexity, from basic document creation to advanced test-driven development.
Could you take a look and let me know what you think? Any suggestions for improvements would be greatly appreciated.
Template: GitHub Link
Thanks! [Your Name]
🚀 "Transform Your Research Workflow with Automated Quality Assurance" ⚡ "Professional Research Outputs with Zero Configuration" 🧪 "Test-Driven Development Meets Academic Publishing" 📚 "Automated PDF Generation for Research Projects" ✅ "Research Template with Test Coverage"
⏰ Save Time: Automated PDF generation eliminates manual formatting 🔒 Ensure Quality: test coverage enforced automatically 📖 Professional Output: Publication-ready LaTeX and PDF generation 🔄 Maintain Consistency: Standardized structure across all projects 🤝 Enable Collaboration: Clear workflows for team research projects
🚀 "Click 'Use this template' and start building in minutes" ⚡ "Transform your research workflow today" 🤝 "Join the community of researchers using this template" 📚 "Get started with professional research outputs" 🔮 "Experience the future of research project management"
graph TB
subgraph "Research Project Template"
SRC[📁 src<br/>Core business logic<br/>Tested]
TESTS[🧪 tests<br/>Test suite<br/>coverage]
SCRIPTS[📜 scripts<br/>Thin orchestrators<br/>Use src/ methods]
MANUSCRIPT[📚 manuscript<br/>Research manuscript<br/>Cross-referenced]
SCRIPTS[📊 scripts/<br/><br/>Build pipeline<br/>Stage scripts]
OUTPUT[📤 output<br/>Generated files<br/>PDFs, figures, data]
end
subgraph "Thin Orchestrator Pattern"
SRC -->|"provides tested methods"| SCRIPTS
SCRIPTS -->|"import & use"| SRC
SCRIPTS -->|"generate"| OUTPUT
TESTS -->|"validate"| SRC
end
subgraph "Build Pipeline"
RENDER[🚀 execute_pipeline.py<br/>Pipeline Orchestrator]
RENDER -->|"runs tests"| TESTS
RENDER -->|"executes scripts"| SCRIPTS
RENDER -->|"builds PDFs"| OUTPUT
end
classDef core fill:#e1f5fe,stroke:#01579b,stroke-width:2px
classDef pattern fill:#f3e5f5,stroke:#4a148c,stroke-width:2px
classDef pipeline fill:#e8f5e8,stroke:#1b5e20,stroke-width:2px
classDef output fill:#fff3e0,stroke:#e65100,stroke-width:2px
class SRC,TESTS,SCRIPTS,MANUSCRIPT,REPO_UTILS core
class SRC,SCRIPTS pattern
class RENDER pipeline
class OUTPUT output
flowchart TD
START([🚀 Start Development]) --> TESTS[🧪 Write Tests First]
TESTS --> IMPLEMENT[💻 Implement Functionality]
IMPLEMENT --> VALIDATE[✅ Run Tests & Check Coverage]
VALIDATE -->|Coverage below requirements| ADD_TESTS[➕ Add Missing Tests]
ADD_TESTS --> VALIDATE
VALIDATE -->|Coverage requirements met| INTEGRATION[🔗 Test Script Integration]
INTEGRATION --> DOCS[📚 Update Documentation]
DOCS --> PIPELINE[🚀 Run Pipeline]
PIPELINE --> SUCCESS[🎉 Development]
classDef process fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
classDef decision fill:#fff3e0,stroke:#e65100,stroke-width:2px
classDef success fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px
class TESTS,IMPLEMENT,VALIDATE,ADD_TESTS,INTEGRATION,DOCS,PIPELINE process
class START,SUCCESS success
graph LR
subgraph "Input Sources"
SRC[📁 src/ modules]
MD[📚 Markdown files]
PREAMBLE[📝 LaTeX preamble]
end
subgraph "Processing Pipeline"
TESTS[🧪 Test validation]
SCRIPTS[📜 Script execution]
VALIDATION[✅ Markdown validation]
GLOSSARY[📖 Glossary generation]
end
subgraph "Generated Outputs"
FIGS[🖼️ Figures]
DATA[📊 Data files]
PDFS[📄 PDFs]
TEX[🔤 LaTeX exports]
end
SRC --> TESTS
SRC --> SCRIPTS
MD --> VALIDATION
SRC --> GLOSSARY
SCRIPTS --> FIGS
SCRIPTS --> DATA
MD --> PDFS
MD --> TEX
classDef input fill:#e8f5e8,stroke:#2e7d32,stroke-width:2px
classDef process fill:#e3f2fd,stroke:#1565c0,stroke-width:2px
classDef output fill:#fff3e0,stroke:#e65100,stroke-width:2px
class SRC,MD,PREAMBLE input
class TESTS,SCRIPTS,VALIDATION,GLOSSARY process
class FIGS,DATA,PDFS,TEX output
🔗 GitHub Template - Click "Use this template" 📚 Documentation - project overview 🐛 Issues - Report bugs & request features 💬 Discussions - Join the community
✅ Test-driven development with coverage ✅ Automated PDF generation from markdown ✅ Professional LaTeX output with cross-referencing ✅ Automated figure generation from Python scripts ✅ Cross-referencing system for equations & figures ✅ Standardized project structure for consistency ✅ Thin orchestrator pattern for maintainability ✅ Publication-ready outputs for academic use
🚀 How To Use Guide - usage guide from basic to advanced 🏗️ Architecture Guide - System design overview ⚡ Workflow Guide - Development process 📝 Markdown Guide - Writing & formatting 🎯 Examples Showcase - Real-world usage 🔧 Thin Orchestrator Summary - Pattern implementation 🗺️ Development Roadmap - Future plans 🤝 Contributing Guide - How to contribute ❓ FAQ - Common questions
| Feature | Traditional Approach | This Template | Benefit |
|---|---|---|---|
| Project Structure | Manual organization | 🏗️ Standardized structure | Consistency across projects |
| Testing | Optional coverage | 🧪 Coverage requirements enforced | Reliable, bug-free code |
| Documentation | Manual updates | 📚 Auto-synchronized | Code-doc always in sync |
| PDF Generation | Manual LaTeX editing | 🚀 Automated from markdown | Save hours of formatting |
| Figure Integration | Manual file management | 🖼️ Automated generation | Seamless figure inclusion |
| Cross-referencing | Manual numbering | 🔗 Automatic system | Professional academic output |
| Quality Assurance | Manual review | ✅ Automated validation | Consistent high quality |
| Collaboration | Ad-hoc workflows | 🤝 Standardized processes | Team efficiency |
- Thesis & Dissertation Projects - Professional formatting with automated quality
- Research Papers - Publication-ready outputs with proper citations
- Lab Reports - Consistent structure with integrated data visualization
- Grant Proposals - Professional appearance with automated validation
- Technical Documentation - Professional reports with code integration
- Research & Development - Reproducible workflows with quality assurance
- Data Analysis Projects - Automated figure generation with statistical rigor
- Software Documentation - Code-doc synchronization with automated testing
- Numerical Analysis - Tested algorithms with reproducible results
- Machine Learning - Validated models with automated documentation
- Statistical Research - Rigorous testing with professional output
- Computational Science - Quality-assured code with publication-ready results
- Click Use this template on GitHub
- Clone your new repository
- Run
uv syncto install dependencies - Execute
uv run python scripts/execute_pipeline.py --project {name} --core-onlyto test the pipeline
- Update
config.yamlor.envwith your project details - Update manuscript files with your content
- Add your business logic to
projects/{name}/src/modules - Add your business logic to
src/modules - Create tests in
tests/directory (coverage requirements apply)
📖 Need guidance? See ../core/how-to-use.md for step-by-step instructions at your experience level.
- Read ../core/how-to-use.md for usage guide
- Read README.md for overview
- Study ../core/architecture.md for system design
- Follow ../core/workflow.md for development process
- Check examples-showcase.md for real-world usage
🎉 Ready to Transform Your Research Workflow?
All content in this file is ready for copy-paste use. Customize as needed for your specific context and audience. The Research Project Template is available at: https://github.com/docxology/template
🔗 Quick Start: Click "Use this template" and start building in minutes! 📚 Documentation: guides for every aspect of the system 🤝 Community: Join discussions and contribute to the project ⭐ Support: Star the repository if you find it useful!