| Name | trainwave-cli JSON |
| Version |
0.2.8
JSON |
| download |
| home_page | None |
| Summary | Trainwave CLI - A command-line interface for managing Trainwave resources |
| upload_time | 2025-04-29 02:43:42 |
| maintainer | Johan Backman |
| docs_url | None |
| author | Johan Backman |
| requires_python | <4.0,>=3.10 |
| license | MIT |
| keywords |
cli
trainwave
ai
machine-learning
|
| VCS |
|
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# Trainwave CLI
A command-line interface for interacting with Trainwave's machine learning platform. This CLI tool provides functionality for managing training jobs, handling authentication, managing secrets, and configuring your Trainwave environment.
## Features
- Job Management: Create, monitor, and manage training jobs
- Authentication: Secure authentication with Trainwave's platform
- Secrets Management: Handle sensitive information for your jobs
- Configuration: Set up and manage your Trainwave environment
## Installation
### Using pip
```bash
pip install trainwave-cli
```
### From Source
1. Clone the repository
2. Install using Poetry:
```bash
poetry install
```
## Usage
The CLI provides several main commands:
```bash
wave jobs # Manage training jobs
wave auth # Authenticate with Trainwave
wave config # Configure your Trainwave environment
wave secrets # Manage job secrets
```
For detailed help on any command:
```bash
wave --help
wave <command> --help
```
## Development
This project uses Poetry for dependency management and packaging. Here's how to set up your development environment:
### Prerequisites
- Python 3.10 or higher
- Poetry
- Make (for development commands)
### Setting Up Development Environment
1. Clone the repository
2. Install development dependencies:
```bash
make install-dev
```
### Development Commands
The project includes several Make targets to help with development:
- `make install`: Install production dependencies
- `make install-dev`: Install development dependencies
- `make clean`: Remove temporary files and build artifacts
- `make ruff`: Run Ruff linter
- `make format`: Format code using Black and Ruff
- `make check`: Run all code quality checks
- `make test`: Run the test suite
- `make help`: Show available make commands
### Code Style
The project uses:
- Ruff for linting
- Black for code formatting
- Type hints are required for all functions
### Running Tests
```bash
make test
```
Or directly with pytest:
```bash
pytest tests/
```
## Project Structure
```
trainwave-cli/
├── trainwave_cli/ # Main package directory
├── tests/ # Test files
├── example/ # Example configurations and usage
├── pyproject.toml # Project metadata and dependencies
└── Makefile # Development automation
```
## Contributing
1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Run tests and linting: `make check`
5. Submit a pull request
## License
[License information here]
Raw data
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