hjvogel / structured-code-commodity-layer

Structured Code Commodity Layer (SCCL) is an innovative framework that transforms Web3 code into modular, tokenized commodities, enabling dynamic composability, co-competition, and seamless integration for developing and optimizing virtual assets.

Structured Code Commodity Layer (SCCL)

Welcome to the Structured Code Commodity Layer (SCCL) repository! This project leverages cutting-edge Web3 technologies, composable architectures, Finite State Machines (FSM), and DSPy / DSPyGEN CLI controlled AI-LLMs to create a robust, flexible, and scalable system for developing and optimizing tokenized digital static or dynamic assets - of algorithms and data structures. SCCL transforms and code into modular, tokenized WEB3 commodities, enabling dynamic composability, co-competition, and seamless integration for developing and optimizing virtual assets.

Key Features

1. Composable Architecture

SCCL is built around modular, independently deployable components that can be dynamically selected and optimized based on performance metrics. This ensures high modularity, maintainability, and scalability.

2. Web3 and Tokenization

Every contribution to SCCL is tokenized, providing clear ownership and economic incentives for contributors. Our blockchain-backed infrastructure ensures transparency and fairness, enabling contributors to benefit directly from their optimizations.

3. Open Co-Competition and Value Co-Creation

We foster a competitive environment where the top-performing workflows and composables are dynamically selected based on real-time performance and sustainable economical metrics. This drives continuous improvement and open innovation.

4. Extensive Experimentation and Sandbox Environments

SCCL supports large-scale experiments and sandbox environments, allowing developers to test and refine their ideas in isolated conditions before deployment.

5. Legal Compliance and Product Stability

Our blockchain integrations prioritize legal compliance, product compliance, protocol stability and scalability. We might start with R3 Corda - SDX integration wrappers in Python, Hyperledger, and potentially Bitcoin (plain vanilla set in stone, restored op_codes, onchain scaled) to ensure a stable, regulation friendly and compliant environment.

6. Open Composables and Workflows Database

We provide an open database solution that cross-links all our and other open contributer's composables and workflows, making them easily accessible for other repository runners in the co-competition network. This openness ensures that anyone can join by forking our repository and contributes to the continuous evolution of next-generation composables. Pick a thing you can just improve or add and easy get started. Learn from the best - check the dashbords, they all should support Triple Entry Accounting.

Establishing a FAANG Standard Software Supply Chain

To establish a FAANG standard software supply chain for creating tokenizable digital commodity assets, following a strict workflow pipeline according to the Hoare Logic framework, we'll outline a process integrating elements like Physical Unclonable Functions (PUFs), semantic lifting, and strong consistency assertions. Here's how to approach this:

1. Establishing the Workflow Pipeline

Overview: The pipeline should consist of stages for asset creation, verification, validation, and deployment, ensuring each stage adheres to formal specifications derived from domain and state logic.

Stages:

1. Asset Creation:

   • Define the digital commodity assets using strict code-result pairs.
   • Implement Physical Unclonable Functions (PUFs) to provide unique, unclonable characteristics to each asset.

2. Verification:

   • Use Hoare Logic to verify the correctness of the assets concerning their specifications.
   • Employ two-tier assertions to integrate domain-specific requirements with state-specific logic.

3. Validation:

   • Ensure that the assets meet both the implementation and domain specifications.
   • Use semantic lifting to translate program states into domain-specific knowledge graphs for validation.

4. Deployment:

   • Deploy the validated assets to a blockchain or distributed ledger to enable tokenization and immutability.
   • Implement mechanisms for maintaining the integrity and uniqueness of the assets through PUFs and cryptographic proofs.

2. Implementing Physical Unclonable Functions (PUFs) in Python

Example:

import os
import hashlib

def generate_puf(seed: bytes) -> str:
    """Generate a PUF based on a seed."""
    # Use the seed to generate a unique, unclonable identifier
    puf = hashlib.sha256(seed).hexdigest()
    return puf

def verify_puf(puf: str, seed: bytes) -> bool:
    """Verify the PUF against the seed."""
    return puf == hashlib.sha256(seed).hexdigest()

# Example usage
seed = os.urandom(32)  # Generate a random seed
puf = generate_puf(seed)
print(f"PUF: {puf}")
assert verify_puf(puf, seed), "PUF verification failed!"

3. Integrating Hoare Logic for Verification

Example:

class HoareLogic:
    def __init__(self):
        self.preconditions = []
        self.postconditions = []

    def add_precondition(self, precondition):
        self.preconditions.append(precondition)

    def add_postcondition(self, postcondition):
        self.postconditions.append(postcondition)

    def verify(self):
        # Simplified verification logic
        for pre in self.preconditions:
            if not pre():
                return False
        for post in self.postconditions:
            if not post():
                return False
        return True

# Define the conditions
def precondition():
    return True  # Replace with actual condition

def postcondition():
    return True  # Replace with actual condition

# Usage
hoare_logic = HoareLogic()
hoare_logic.add_precondition(precondition)
hoare_logic.add_postcondition(postcondition)
assert hoare_logic.verify(), "Hoare Logic verification failed!"

4. Semantic Lifting and Two-Tier Assertions

Example:

class State:
    def __init__(self, variables):
        self.variables = variables

    def lift(self):
        # Lift state variables to domain-specific knowledge
        return {k: f"HasValue({v})" for k, v in self.variables.items()}

# Example state and lifting
state = State({'wheels': 4})
lifted_state = state.lift()
print(f"Lifted State: {lifted_state}")

5. Full Workflow Implementation

Putting it all together:

# Step 1: Asset Creation
seed = os.urandom(32)
puf = generate_puf(seed)

# Step 2: Verification
hoare_logic = HoareLogic()
hoare_logic.add_precondition(lambda: True)  # Replace with actual conditions
hoare_logic.add_postcondition(lambda: verify_puf(puf, seed))
assert hoare_logic.verify(), "Verification failed!"

# Step 3: Validation
state = State({'wheels': 4})
lifted_state = state.lift()
print(f"Lifted State: {lifted_state}")
# Add additional domain-specific validation

# Step 4: Deployment
# Deploy to blockchain or ledger
print(f"Deploying asset with PUF: {puf}")

This framework ensures that each digital commodity asset created is unique, verifiable, and compliant with both domain and implementation specifications, providing a secure and reliable supply chain for digital assets.

Directory Structure

dspygen-composable-architecture/
├── app/
│   ├── main.py
│   ├── agents/
│   │   ├── __init__.py
│   │   ├── base_agent.py
│   │   ├── financial_agent.py
│   │   ├── compliance_agent.py
│   ├── flows/
│   │   ├── __init__.py
│   │   ├── issue_currency_flow.py
│   │   ├── create_and_issue_asset_flow.py
│   │   ├── purchase_asset_flow.py
├── config/
│   ├── dapr_config.yaml
│   ├── sdx_config.json
│   ├── logging_config.yaml
├── data/
│   ├── db/
│   │   ├── transaction.db
│   ├── sample_data/
│   │   ├── sample_transactions.csv
├── docs/
│   ├── index.md
│   ├── architecture.md
│   ├── design_decisions.md
│   ├── api_documentation.md
│   ├── user_guide.md
│   ├── setup_guide.md
│   ├── api_reference.md
│   ├── compliance_manual.md
│   ├── changelog.md
│   ├── composables/
│   │   ├── overview.md
│   │   ├── composable1.md
│   │   ├── composable2.md
│   ├── legal/
│   │   ├── terms_and_conditions.md
│   │   ├── jurisdiction1.md
│   │   ├── jurisdiction2.md
│   ├── experiments/
│   │   ├── experiment1.md
│   │   ├── experiment2.md
├── logs/
│   ├── app.log
│   ├── error.log
├── scripts/
│   ├── deploy_nodes.sh
│   ├── start_agents.sh
│   ├── clean_data.sh
├── tests/
│   ├── unit/
│   │   ├── test_agents.py
│   │   ├── test_flows.py
│   ├── integration/
│   │   ├── test_dapr_integration.py
│   │   ├── test_sdx_integration.py
│   ├── e2e/
│   │   ├── test_full_flow.py
├── utils/
│   ├── logger.py
│   ├── db_helper.py
│   ├── api_client.py
├── db/
│   ├── composables.db
│   ├── workflows.db
├── Dockerfile
├── requirements.txt
├── README.md
├── LICENSE

Getting Started

Prerequisites

Ensure you have the following installed:

• Python 3.8 or higher
• Node.js

and npm

• Docker
• Docker Compose
• Dapr CLI
• Terraform (for infrastructure management)
• Vue CLI (for Vue/NUXT development)

Installation

1. Clone the repository:

   git clone https://github.com/hjvogel/Structured-Code-Commodity-Layer.git
   cd Structured-Code-Commodity-Layer

2. Install Python dependencies:

   pip install -r requirements.txt

3. Initialize Dapr:

   dapr init

4. Install Node.js dependencies (for the dashboard):

   cd src/dashboard
   npm install
   cd ../..

5. Build and run the Docker containers:

   docker-compose up --build

Running Experiments

You can run predefined experiments in the experiments directory. For example, to run the first experiment:

1. Navigate to the experiment directory:

   cd experiments/experiment1

2. Run the experiment:

   python main.py

3. View results:

   python results.py

Using the Sandbox

To use the sandbox environment for testing and experimentation:

1. Navigate to the sandbox directory:

   cd sandbox

2. Install the required dependencies:

   pip install -r requirements.txt

3. Run the sandbox application:

   python main.py

Developing the Dashboard

To develop and run the Vue3/NUXT3 dashboard:

1. Navigate to the dashboard directory:

   cd src/dashboard

2. Start the development server:

   npm run dev

3. Open your browser and go to http://localhost:3000 to view the dashboard.

Database for Open Composables and Workflows

We provide an open database to make all our composables and workflows easily accessible. This database allows cross-linking to other databases, enabling a network of reusable components.

• Database Files:
  • db/composables.db: Contains all composable units.
  • db/workflows.db: Contains all workflows.

CLI for the Advanced Financial Transaction System

Welcome to the CLI for the Advanced Financial Transaction System! This tool allows you to interact with the system, manage agents, execute financial transactions, and ensure compliance dynamically. Below you will find a guide to using the CLI commands.

General Usage

python main.py [COMMAND] [OPTIONS]

Commands

Agent Management

start-agent

Start a new agent to participate in financial transactions.

Usage:

python main.py start-agent --type [TYPE] --id [ID]

Options:

• --type [TYPE]: The type of agent to start (financial, compliance, etc.).
• --id [ID]: Unique identifier for the agent.

Example:

python main.py start-agent --type financial --id agent-123

stop-agent

Stop a running agent.

Usage:

python main.py stop-agent --id [ID]

Options:

• --id [ID]: Unique identifier for the agent.

Example:

python main.py stop-agent --id agent-123

Transaction Management

issue-currency

Issue fiat currency to an agent.

Usage:

python main.py issue-currency --currency [CURRENCY] --amount [AMOUNT] --recipient [RECIPIENT]

Options:

• --currency [CURRENCY]: The type of currency to issue (e.g., USD).
• --amount [AMOUNT]: The amount of currency to issue.
• --recipient [RECIPIENT]: The recipient agent's ID.

Example:

python main.py issue-currency --currency USD --amount 1000000 --recipient agent-456

create-asset

Create a new financial asset.

Usage:

python main.py create-asset --name [NAME] --type [TYPE] --value [VALUE] --owner [OWNER]

Options:

• --name [NAME]: Name of the asset.
• --type [TYPE]: Type of asset (CPU time, cloud storage, etc.).
• --value [VALUE]: Value of the asset.
• --owner [OWNER]: The owner agent's ID.

Example:

python main.py create-asset --name "High Performance CPU Time" --type "CPU time" --value 5000 --owner agent-123

purchase-asset

Purchase a financial asset from another agent.

Usage:

python main.py purchase-asset --asset-id [ASSET_ID] --buyer [BUYER]

Options:

• --asset-id [ASSET_ID]: The unique ID of the asset to purchase.
• --buyer [BUYER]: The buyer agent's ID.

Example:

python main.py purchase-asset --asset-id asset-789 --buyer agent-456

Compliance Management

check-compliance

Check the compliance status of a transaction or asset.

Usage:

python main.py check-compliance --transaction-id [TRANSACTION_ID]

Options:

• --transaction-id [TRANSACTION_ID]: The unique ID of the transaction to check.

Example:

python main.py check-compliance --transaction-id txn-321

System Management

deploy-nodes

Deploy the Dapr nodes required for the system.

Usage:

python main.py deploy-nodes

Options:

• None

Example:

python main.py deploy-nodes

start-services

Start all required services for the system.

Usage:

python main.py start-services

Options:

• None

Example:

python main.py start-services

Help

help

Display the help screen for the CLI or a specific command.

Usage:

python main.py help [COMMAND]

Options:

• [COMMAND]: (Optional) The command to display help for.

Example:

python main.py help
python main.py help start-agent

Disclaimer

The information provided here is for informational purposes only and does not constitute legal, financial, or investment advice. Users should conduct their own research and consult with a qualified professional before making any financial decisions or engaging in transactions involving digital assets. The authors and sources cited are not liable for any losses or damages arising from the use of this information.

For further details and advanced configurations, please refer to the documentation in the docs/ directory or visit our official documentation website.

Thank you for using the Advanced Financial Transaction System CLI! If you encounter any issues or have questions, please refer to the documentation or contact our support team.

Contributing

We welcome contributions from developers and business professionals alike. Whether you want to optimize existing workflows, create new composables, or improve our dashboard, your contributions are valued.

Steps to Contribute:

1. Fork the repository: Click the "Fork" button at the top right corner of this repository's GitHub page.

2. Clone your fork:

   git clone https://github.com/hjvogel/Structured-Code-Commodity-Layer.git
   cd Structured-Code-Commodity-Layer

3. Create a new branch:

   git checkout -b feature/your-feature-name

4. Make your changes and commit:

   git add .
   git commit -m "Add your message here"

5. Push to your fork:

   git push origin feature/your-feature-name

6. Open a pull request: Navigate to the original repository and click the "New pull request" button to submit your changes for review.

License

This project is licensed under the MIT License. See the LICENSE file for details.

Contact

For any questions or support, please reach out to us here on GitHub

Acknowledgements

We would like to thank all contributors and the open-source community for their invaluable support and contributions to this project.

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With this repository, we aim to provide a collaborative and innovative platform that not only meets the high standards of modern software development but also fosters a transparent and economically sustainable ecosystem for all participants. Join us in building the future of composable architectures and tokenized digital assets!