CLI tool for generating DDD architecture in Python projects
Project description
PyConstructor ๐๏ธ
PyConstructor is a command-line tool that helps developers quickly create a project structure following Domain-Driven Design (DDD) principles. The tool generates architecture based on a YAML configuration that defines bounded contexts, entities, repositories, services, use cases, and other DDD elements.
๐ Quick Start
Installation
# Install via pip
pip install pyconstructor
# Install via uv
uv add pyconstructor
# Generate YAML file with example data
pyc init
# Edit the generated ddd-config.yaml file
# ...
# Generate structure
pyc run
Basic Usage
- Initialize a new project with a preset configuration:
pyc init --preset <PresetType(Optional argument, default to Standard)>
- Validate your configuration (Optional command):
pyc validate
- Preview the project structure (Optional command):
pyc preview --file <file_name> (Optional argument)
- Generate the project:
pyc run --file <file_name> (Optional argument)
๐ Available Commands
Core Commands
| Command | Description | Example |
|---|---|---|
init |
Initialize a new project with a preset configuration | pyc init --preset standard |
validate |
Validate your YAML configuration | pyc validate --file custom-config.yaml |
preview |
Preview the project structure without generating files | pyc preview --file custom-config.yaml |
run |
Generate the project structure | pyc run --file custom-config.yaml |
Command Options
init Command
# Create project with standard preset
pyc init --preset standard
# Force overwrite existing config
pyc init --preset standard --force
validate Command
# Validate default config (ddd-config.yaml)
pyc validate
# Validate specific config file
pyc validate --file custom-config.yaml
preview Command
# Preview default config
pyc preview
# Preview specific config
pyc preview --file custom-config.yaml
Output:
- Displays the project structure tree in the console
- Generates a
structure.mdfile with the same tree view for future reference
Example output:
app/
โโโ domain/
โ โโโ user/
โ โ โโโ entities/
โ โ โ โโโ user.py
โ โ โโโ value_objects/
โ โ โโโ email.py
โ โโโ catalog/
โ โโโ entities/
โ โโโ product.py
โโโ application/
โ โโโ user/
โ โโโ use_cases/
โ โโโ register_user.py
โโโ infrastructure/
โโโ repositories/
โโโ user_repository.py
run Command
# Generate from default config
pyc run
# Generate from specific config
pyc run --file custom-config.yaml
Architecture Presets
PyConstructor comes with three built-in presets:
Simple Preset
Basic DDD structure without bounded contexts:
pyc init --preset simple
Standard Preset
Default preset with bounded contexts:
pybuilder init --preset standard
Advanced Preset
Complex structure with nested contexts:
pyc init --preset advanced
Configuration
The tool uses YAML configuration files to define your project structure.
Example configurations are provided in the src/templates/config_templates directory.
Configuration Reference
Settings Section
settings:
preset: "standard" # One of: "simple", "standard", "advanced"
use_contexts: true # Whether to use bounded contexts
contexts_layout: "flat" # One of: "flat", "nested"
group_components: true # Group similar components in directories
init_imports: false # Initialize imports in __init__.py files
root_name: "src" # Root directory name
Simple Configuration Example
settings:
preset: "simple"
layers:
domain:
entities: User, Product
value_objects: Email, Price
Standard Configuration Example
settings:
preset: "standard"
layers:
domain:
contexts:
- name: user
entities: [User, Profile]
value_objects: [Email, Password]
- name: catalog
entities: [Product, Category]
Advanced Configuration Example (for microservice architecture)
settings:
preset: "advanced"
layers:
contexts:
- name: user_context
domain:
entities: User
value_objects: Email
application:
use_cases: CreateUser
infrastructure:
repositories: UserRepository
- name: payment_context
domain:
entities: Payment
application:
use_cases: ProcessPayment
infrastructure:
repositories: TransactionRepository
Complete Configuration Example
Here's a complete example showing all available options:
settings:
preset: "advanced"
use_contexts: true
contexts_layout: "nested"
group_components: true
init_imports: true
root_name: "src"
layers:
contexts:
- name: user_context
domain:
entities: User, Profile
value_objects: Email, Password, UserRole
aggregates: UserAggregate
repositories: UserRepository
services: UserService
application:
use_cases: CreateUser, UpdateUser, DeleteUser
commands: CreateUserCommand, UpdateUserCommand
queries: GetUserQuery, ListUsersQuery
events: UserCreatedEvent, UserUpdatedEvent
dtos: UserDTO, UserCreateDTO
mappers: UserMapper
infrastructure:
repositories: UserRepositoryImpl
services: UserServiceImpl
interface:
controllers: [UserController]
middleware: AuthMiddleware
- name: order_context
domain:
entities: Order, OrderItem
value_objects: Money, OrderStatus
aggregates: OrderAggregate
repositories: OrderRepository
services: OrderService
application:
use_cases: CreateOrder, UpdateOrder
commands: CreateOrderCommand
queries: GetOrderQuery
events: OrderCreatedEvent
dtos: OrderDTO
mappers: OrderMapper
infrastructure:
repositories: OrderRepositoryImpl
interface:
controllers: OrderController
Generated Structure
When using the advanced configuration above, the tool will generate a structure like this:
src/
โโโ user_context/
โ โโโ domain/
โ โ โโโ entities/
โ โ โ โโโ user.py
โ โ โ โโโ profile.py
โ โ โโโ value_objects/
โ โ โ โโโ email.py
โ โ โ โโโ password.py
โ โ โ โโโ user_role.py
โ โ โโโ aggregates/
โ โ โ โโโ user_aggregate.py
โ โ โโโ repositories/
โ โ โ โโโ user_repository.py
โ โ โโโ services/
โ โ โโโ user_service.py
โ โโโ application/
โ โ โโโ use_cases/
โ โ โ โโโ create_user.py
โ โ โ โโโ update_user.py
โ โ โ โโโ delete_user.py
โ โ โโโ commands/
โ โ โ โโโ create_user_command.py
โ โ โ โโโ update_user_command.py
โ โ โโโ queries/
โ โ โ โโโ get_user_query.py
โ โ โ โโโ list_users_query.py
โ โ โโโ events/
โ โ โ โโโ user_created_event.py
โ โ โ โโโ user_updated_event.py
โ โ โโโ dtos/
โ โ โ โโโ user_dto.py
โ โ โ โโโ user_create_dto.py
โ โ โโโ mappers/
โ โ โโโ user_mapper.py
โ โโโ infrastructure/
โ โ โโโ repositories/
โ โ โ โโโ user_repository_impl.py
โ โ โโโ services/
โ โ โโโ user_service_impl.py
โ โโโ interface/
โ โโโ controllers/
โ โ โโโ user_controller.py
โ โโโ middleware/
โ โโโ auth_middleware.py
โโโ order_context/
โโโ ... (similar structure)
Customizing Templates
You can customize the generated files by modifying the templates in the src/templates directory. Each component type has its own template file that you can modify to suit your needs.
General Questions
Q: Which preset should I choose? A: Start with the "simple" preset for small projects, "standard" for medium-sized applications, and "advanced" for complex microservices.
Q: Can I modify the generated structure after creation? A: Yes, you can modify the configuration and regenerate the structure, but be careful with existing files.
Q: How do I handle shared components between contexts? A: Create a separate "shared" context for common components, or use the infrastructure layer for shared implementations.
Configuration Questions
Q: What's the difference between flat and nested contexts? A: Flat contexts are organized by layers first, then contexts. Nested contexts are organized by contexts first, then layers.
Q: How do I add new component types?
A: You can extend the configuration schema and add new templates in the src/templates directory.
Q: Can I customize the generated file templates?
A: Yes, all templates are located in the src/templates directory and can be modified to match your needs.
Technical Questions
Q: How do I handle dependencies between contexts? A: Use interfaces in the domain layer and implementations in the infrastructure layer to maintain loose coupling.
Q: What's the recommended way to handle database access? A: Use repositories in the domain layer for interfaces and implement them in the infrastructure layer.
Q: How do I implement event handling between contexts? A: Define events in the domain layer and implement handlers in the application layer.
๐ค Contributing
Contributions are welcome. Please feel free to submit a Pull Request.
- Fork the repository
- Create your feature branch (
git switch -c feature/amazing-feature) - Run tests (
pytest) - Commit your changes (
git commit -m 'Add amazing feature') - Push to the branch (
git push origin feature/amazing-feature) - Open a Pull Request
๐ License
This project is licensed under the MIT Licenseโsee the LICENSE file for details.
๐ค Author
Grigoriy Sokolov (Sokolov_Gr@proton.me)
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