think-lang 0.1.9

Think - A language for learning computational thinking

Think

Think is an educational programming language designed to teach computational thinking through problem decomposition. It helps users break down complex problems into manageable parts while providing interactive feedback and explanations.

Features

• Structured Problem Solving: Break down problems into objectives, tasks, subtasks, and steps
• Interactive Execution: Run your code and see results in real-time
• Explain Mode: Get detailed explanations of what each part of your code does
• Jupyter Integration: Use ThinkPy directly in Jupyter notebooks
• Educational Focus: Learn computational thinking concepts through hands-on coding

Installation

# Clone the repository
git clone https://github.com/yourusername/think.git
cd think

# Install the package
pip install -e .

Quick Start

Here's a simple ThinkPy program that calculates student grades:

objective "Calculate student grades"

task "Data Collection":
    step "Get scores":
        scores = [85, 92, 78, 90, 88]

task "Analysis":
    subtask "Calculate Average":
        total = sum(scores)
        avg = total / len(scores)
        return avg
    
    step "Determine Grade":
        final_score = Calculate_Average()
        decide:
            if final_score >= 90 then:
                grade = "A"
            elif final_score >= 80 then:
                grade = "B"
            else:
                grade = "C"

run "Data Collection"
run "Analysis"

Language Structure

Core Concepts

1. Objective: The main goal of your program

   objective "Your goal here"
   

2. Task: Major components of your solution

   task "Task Name":
       # steps or subtasks
   

3. Subtask: Reusable pieces of code

   subtask "Subtask Name":
       # statements
       return result
   

4. Step: Specific actions

   step "Step Name":
       # statements
   

Control Flow

1. Decide (If/Else):

    decide:
        if condition then:
           # statements
        elif another_condition then:
           # statements
        else:
           # statements
   

2. Loopd:

    for num in numbers:
       # statements
    end
    for index, value in enumerate(items):
        print(index, value)
    end
    for _, value in enumerate(items):
        print(value)
    end
   

Data Types

• Numbers: 42, 3.14
• Strings: "Hello, World!"
• Lists: [1, 2, 3, 4, 5]
• Variables: score = 85
• Dictionaries `{'key': 'value'}

Jupyter Notebook Usage

1. Load the ThinkPy extension:

   %load_ext thinkpy.jupyter_magic
   

2. Write ThinkPy code in cells:

   %%thinkpy --explain
   
   objective "Your program objective"
   # ... rest of your code
   

Built-in Functions

• sum(list): Calculate the sum of a list
• len(list): Get the length of a list
• print(value): Display a value

Examples

Temperature Analysis

objective "Analyze temperature data"

task "Data Collection":
    step "Get readings":
        temps = [72, 75, 68, 70, 73]

task "Analysis":
    subtask "Calculate Average":
        total = sum(temps)
        avg = total / len(temps)
        return avg
    
    subtask "Find High":
        max_temp = temps[0]
        for index, value in enumerate(temps):
            decide:
                if temps[index] > max_temp then:
                    max_temp = temps[index]
        end
        return max_temp

run "Data Collection"
run "Analysis"

Grade Calculator

objective "Calculate final grades"

task "Setup":
    step "Initialize data":
        scores = [85, 92, 78]
        weights = [0.3, 0.4, 0.3]

task "Calculate":
    subtask "Weighted Average":
        total = 0
        for index in range(3):
            total = total + (scores[index] * weights[index])
        end
        return total

run "Setup"
run "Calculate"

Development

Running Tests

python -m pytest tests/

Contributing

1. Fork the repository
2. Create a feature branch (git checkout -b feature/AmazingFeature)
3. Commit your changes (git commit -m 'Add some AmazingFeature')
4. Push to the branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

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

Acknowledgments

• Thanks to all contributors to this project
• Inspired by Python and educational programming concepts
• Built with PLY (Python Lex-Yacc)

Support

For support, feature requests, or bug reports:

1. Check the documentation
2. Open an issue on GitHub
3. Contact the maintainers

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Made with ❤️ for teaching computational thinking