> ## Documentation Index
> Fetch the complete documentation index at: https://splinter.mintlify.site/llms.txt
> Use this file to discover all available pages before exploring further.

# Checkpointing

> Save progress and resume from failures

Save workflow state. Resume from failures without losing progress.

## Basic Usage

```python theme={null}
from splinter.coordination import CheckpointManager

manager = CheckpointManager()

# Create checkpoint
manager.create_checkpoint(
    workflow_id="wf-123",
    step=5,
    agent_id="researcher",
    status=AgentStatus.COMPLETED,
    state=current_state,
    metrics=current_metrics,
)

# Get latest checkpoint
checkpoint = manager.get_latest_checkpoint("wf-123")
```

## File Storage

Persist checkpoints across restarts:

```python theme={null}
from splinter.coordination import FileCheckpointStorage

manager = CheckpointManager(
    storage=FileCheckpointStorage("./checkpoints"),
    max_checkpoints=10,  # Keep last 10
)
```

## Resume from Failure

```python theme={null}
# Get resume point
resume_point = manager.get_resume_point("wf-123")

if resume_point:
    resume_step, state_snapshot, metrics = resume_point
    print(f"Resuming from step {resume_step}")

    # Restore state
    state = SharedState(initial_data=state_snapshot.data)
```

## Resumable Workflow

```python theme={null}
from splinter.coordination import ResumableWorkflow

resumable = ResumableWorkflow(
    workflow_id="wf-123",
    checkpoint_manager=manager,
)

# Try to resume
resume_step = resumable.try_resume()

if resumable.is_resumed:
    print(f"Resumed from step {resume_step}")
else:
    print("Starting fresh")

# Create checkpoints during execution
resumable.checkpoint(
    step=current_step,
    agent_id=current_agent,
    status=AgentStatus.COMPLETED,
)
```

## List Checkpoints

```python theme={null}
checkpoints = manager.list_checkpoints("wf-123")

for cp in checkpoints:
    print(f"Step {cp.step}: {cp.agent_id} - {cp.status}")
```

## Delete Checkpoints

```python theme={null}
# Delete specific step
manager.delete_checkpoints("wf-123", step=5)

# Delete all for workflow
manager.delete_checkpoints("wf-123")
```

## Checkpoint Contents

Each checkpoint contains:

* `workflow_id`: Workflow identifier
* `step`: Step number
* `agent_id`: Agent that completed
* `status`: Completion status
* `state_snapshot`: Full state snapshot
* `metrics`: Execution metrics
* `timestamp`: When created