# EasySubmit
A Python library for simplified job scheduling and management on SLURM clusters.
[](https://python.org)
[](https://opensource.org/licenses/MIT)
## Overview
EasySubmit is a Python-based job scheduling and management system designed to seamlessly integrate with SLURM, a popular cluster management and job scheduling platform. This project aims to simplify the process of submitting, monitoring, and managing jobs on cluster environments through an intuitive Python API.
## Key Features
- **Simple API**: Easy-to-use Python interface for SLURM job submission
- **Task Management**: Define and configure tasks with type-safe configuration classes
- **Batch Scheduling**: Submit multiple experiments or jobs with different parameters
- **Profiling Support**: Optional integration with Scalene for performance profiling
- **Flexible Configuration**: Comprehensive SLURM configuration options
- **Type Safety**: Built with modern Python type hints for better development experience
## Installation
### From PyPI (Recommended)
```bash
pip install easysubmit
```
### From Source
```bash
# Clone the repository
git clone https://github.com/ysenarath/easysubmit.git
cd easysubmit
# Install in development mode
pip install -e .
```
### Optional Dependencies
For profiling support:
```bash
pip install easysubmit[scalene]
```
## Quick Start
Here's a simple example of how to use EasySubmit:
```python
from easysubmit import SLURMCluster, SLURMConfig, Task, TaskConfig
from easysubmit.base import schedule
# Define your task configuration
class ExperimentConfig(TaskConfig):
name: str = "MyExperiment"
learning_rate: float = 0.001
batch_size: int = 32
# Define your task
class Experiment(Task):
config: ExperimentConfig
def run(self):
print(f"Running experiment with lr={self.config.learning_rate}")
# Your experiment code here
# Configure SLURM settings
config = SLURMConfig(
partition="gpu",
nodes=1,
ntasks_per_node=1,
gres="gpu:1",
mem="16G"
)
# Create cluster and schedule jobs
cluster = SLURMCluster(config)
experiments = [
{"name": "MyExperiment", "learning_rate": 0.001, "batch_size": 32},
{"name": "MyExperiment", "learning_rate": 0.01, "batch_size": 64},
]
schedule(cluster, experiments)
```
## Core Components
### Task and TaskConfig
- `TaskConfig`: Define configuration parameters for your tasks with type safety
- `Task`: Base class for implementing your computational tasks
### SLURM Integration
- `SLURMCluster`: Interface to SLURM cluster management
- `SLURMConfig`: Comprehensive SLURM job configuration options
### Job Management
- `Job`: Represents individual jobs in the cluster
- `AutoTask`: Advanced task automation features
## Prerequisites
- Python 3.9 or higher
- Access to a SLURM cluster environment
- SLURM commands (`sbatch`, `squeue`, etc.) available in PATH
## Examples
Check out the `examples/` directory for more comprehensive usage examples:
- `examples/slurm_scheduler.py`: Basic SLURM job scheduling
- `examples/slurm_scheduler_with_profile.py`: Job scheduling with profiling
- `examples/tasks.py`: Task definition examples
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
## Support
- **Issues**: [GitHub Issues](https://github.com/ysenarath/easysubmit/issues)
- **Documentation**: [GitHub README](https://github.com/ysenarath/easysubmit#readme)
- **Source Code**: [GitHub Repository](https://github.com/ysenarath/easysubmit)
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