# Moose / Workflows / Schedule Workflow Documentation – Python

## Included Files
1. moose/workflows/schedule-workflow/schedule-workflow.mdx

## Schedule Workflows

Source: moose/workflows/schedule-workflow/schedule-workflow.mdx

Set up recurring and scheduled workflow execution

# Schedule Workflows

## Overview

Moose workflows can be configured to run automatically on a schedule using cron expressions or interval-based scheduling. This enables you to automate recurring tasks, data processing jobs, and maintenance operations.

## Scheduling Workflows

Workflows can be configured to run on a schedule using the `schedule` field in `Workflow`. This field is optional and blank by default.

### Cron Expressions

```python filename="app/scheduled_workflow.py" copy
from moose_lib import Task, TaskConfig, Workflow, WorkflowConfig

myworkflow = Workflow(
  name="myworkflow",
  config=WorkflowConfig(starting_task=task1, schedule="0 12 * * *") # Runs at 12:00 PM every day
)
```

#### Cron Expression Format

```text
|------------------------------- Minute (0-59)
|     |------------------------- Hour (0-23)
|     |     |------------------- Day of the month (1-31)
|     |     |     |------------- Month (1-12; or JAN to DEC)
|     |     |     |     |------- Day of the week (0-6; or SUN to SAT; or 7 for Sunday)
|     |     |     |     |
|     |     |     |     |
*     *     *     *     *
```

#### Common Cron Examples

| Cron Expression | Description |
|-----------------|-------------|
| <code>0 12 * * *</code> | Runs at 12:00 PM every day |
| <code>0 0 * * 0</code> | Runs at 12:00 AM every Sunday |
| <code>0 8 * * 1-5</code> | Runs at 8:00 AM on weekdays (Monday to Friday) |
| <code>* * * * *</code> | Runs every minute |
| <code>0 */6 * * *</code> | Runs every 6 hours |
| <code>0 9 1 * *</code> | Runs at 9:00 AM on the first day of every month |
| <code>0 0 1 1 *</code> | Runs at midnight on January 1st every year |

Use an online cron expression visualizer like [crontab.guru](https://crontab.guru/) to help you understand how the cron expression will schedule your workflow.

### Interval Schedules

Interval schedules can be specified as a string `"@every <interval>"`. The interval follows standard duration format:

```python filename="app/interval_workflow.py" copy
from moose_lib import Task, TaskConfig, Workflow, WorkflowConfig

myworkflow = Workflow(
  name="myworkflow",
  config=WorkflowConfig(starting_task=task1, schedule="@every 1h") # Runs every hour
)
```

#### Interval Examples

| Interval | Description |
|----------|-------------|
| `@every 30s` | Every 30 seconds |
| `@every 5m` | Every 5 minutes |
| `@every 1h` | Every hour |
| `@every 12h` | Every 12 hours |
| `@every 24h` | Every 24 hours |
| `@every 7d` | Every 7 days |

## Practical Scheduling Examples

### Daily Data Processing

```python filename="app/daily_etl.py" copy
from moose_lib import Workflow, WorkflowConfig

daily_data_processing = Workflow(
  name="daily-data-processing",
  config=WorkflowConfig(
    starting_task=extract_data_task,
    schedule="0 2 * * *",  # Run at 2 AM every day
    retries=2,
    timeout="2h"
  )
)
```

### Weekly Reports

```python filename="app/weekly_reports.py" copy
weekly_reports = Workflow(
  name="weekly-reports",
  config=WorkflowConfig(
    starting_task=generate_report_task,
    schedule="0 9 * * 1",  # Run at 9 AM every Monday
    retries=1,
    timeout="1h"
  )
)
```

### High-Frequency Monitoring

```python filename="app/monitoring.py" copy
system_monitoring = Workflow(
  name="system-monitoring",
  config=WorkflowConfig(
    starting_task=check_system_health_task,
    schedule="@every 5m",  # Check every 5 minutes
    retries=0,  # Don't retry monitoring checks
    timeout="30s"
  )
)
```

## Monitoring Scheduled Workflows

### Development Environment

If your dev server is running, you should see logs in the terminal when your scheduled workflow is executed:

```bash filename="Terminal" copy
moose dev
```

```txt filename="Terminal"
[2024-01-15 12:00:00] Scheduled workflow 'daily-data-processing' started
[2024-01-15 12:00:01] Task 'extract' completed successfully
[2024-01-15 12:00:15] Task 'transform' completed successfully
[2024-01-15 12:00:30] Task 'load' completed successfully
[2024-01-15 12:00:30] Workflow 'daily-data-processing' completed successfully
```

### Checking Workflow Status

You can check the status of scheduled workflows using the CLI:

```bash filename="Terminal" copy
# List all workflows defined in your project
moose workflow list

# Alternative command to list all workflows
moose ls --type workflows

# View workflow execution history
moose workflow history

# Check specific workflow status
moose workflow status daily-data-processing

# Get detailed execution history
moose workflow status daily-data-processing --verbose
```

### Temporal Dashboard

Access the Temporal dashboard to view scheduled workflow executions:

```bash filename="Terminal" copy
# Open Temporal dashboard (typically at http://localhost:8080)
open http://localhost:8080
```

The dashboard shows:
- Scheduled workflow definitions
- Execution history and timing
- Success/failure rates
- Retry attempts and errors

## Best Practices for Scheduled Workflows

### Timeout and Retry Configuration

Configure appropriate timeouts and retries for scheduled workflows:

```python filename="app/robust_scheduled_workflow.py" copy
def run_main_task() -> None:
    # Long-running task logic
    pass

main_task = Task[None, None](
  name="main",
  config=TaskConfig(
    run=run_main_task,
    retries=3,  # Retry individual tasks
    timeout="1h"  # Task-level timeout
  )
)

robust_scheduled_workflow = Workflow(
  name="robust-scheduled",
  config=WorkflowConfig(
    starting_task=main_task,
    schedule="0 3 * * *",  # Run at 3 AM daily
    retries=2,  # Retry failed workflows
    timeout="4h"  # Allow sufficient time
  )
)
```

## Troubleshooting Scheduled Workflows

### Common Issues

- **Timezone considerations**: Cron schedules use UTC by default
- **Resource conflicts**: Ensure scheduled workflows don't compete for resources
- **Long-running tasks**: Set appropriate timeouts for lengthy operations
- **Error handling**: Implement proper error handling and logging