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

# Merging Examples

> Examples of merging extracted data into knowledge graphs with Graphora

# Merging Examples

This page provides practical examples of merging extracted data into knowledge graphs using the Graphora client library.

## Basic Merging Operation

After transforming documents, you can merge the extracted data into a knowledge graph:

```python theme={null}
import os
from graphora import GraphoraClient

client = GraphoraClient(
    auth_token=os.environ["GRAPHORA_AUTH_TOKEN"],
)

# Use a previously completed transformation
session_id = "ont_123456789"  # Ontology ID
transform_id = "transform_123456789"

# Start the merging process
merge = client.start_merge(session_id, transform_id)
print(f"Merge started with ID: {merge.merge_id}")

state = client.get_merge_status(merge.merge_id)
print("Merge state:", state)
```

## Monitoring Merge Progress

For large datasets, merging can take some time. Here's how to monitor the progress:

```python theme={null}
import os
import time
from graphora import GraphoraClient, MergeState

client = GraphoraClient(
    auth_token=os.environ["GRAPHORA_AUTH_TOKEN"],
)

# Start a merge (assuming you have already completed a transformation)
session_id = "ont_123456789"  # Ontology ID
transform_id = "transform_123456789"
merge_response = client.start_merge(session_id, transform_id)
merge_id = merge_response.merge_id

# Monitor the merge progress
completed = False
while not completed:
    state = client.get_merge_status(merge_id)
    print(f"Merge state: {state}")

    if state in (MergeState.COMPLETED, MergeState.FAILED):
        completed = True
    else:
        time.sleep(5)

if state == MergeState.COMPLETED:
    graph = client.get_merged_graph(merge_id, transform_id)
    print(f"Retrieved graph with {len(graph.nodes)} nodes and {len(graph.edges)} edges")
```

## Handling Merge Conflicts

When merging data, conflicts may arise. Here's how to handle them:

```python theme={null}
import os
from graphora import GraphoraClient, ResolutionStrategy

client = GraphoraClient(
    auth_token=os.environ["GRAPHORA_AUTH_TOKEN"],
)

# Get conflicts for a merge that has detected conflicts
merge_id = "merge_123456789"
conflicts = client.get_conflicts(merge_id)

print(f"Found {len(conflicts)} conflicts")

# Resolve each conflict
for conflict in conflicts:
    print(f"Conflict ID: {conflict.id}")
    print(f"Staging props: {conflict.staging_node.properties}")
    print(f"Production props: {conflict.prod_node.properties}")

    client.resolve_conflict(
        merge_id,
        conflict.id,
        changed_props={},
        resolution=ResolutionStrategy.KEEP_STAGING,
        learning_comment="Prefer staging record",
    )
```

## Getting Merge Statistics

You can get detailed statistics about a merge operation:

```python theme={null}
from graphora import GraphoraClient

# Initialize the client with user ID (required)
client = GraphoraClient(
    base_url="https://api.graphora.io",
    user_id="your-user-id",  # Required for all API calls
    api_key="your-api-key"
)

# Get merge statistics
merge_id = "merge_123456789"
stats = client.get_merge_statistics(merge_id)

print("Merge Statistics:")
print(f"Total entities processed: {stats.get('total_entities', 0)}")
print(f"Entities merged: {stats.get('merged_entities', 0)}")
print(f"New entities created: {stats.get('new_entities', 0)}")
print(f"Conflicts detected: {stats.get('conflicts_detected', 0)}")
print(f"Conflicts resolved: {stats.get('conflicts_resolved', 0)}")
```

## Retrieving and Using the Merged Graph

Once a merge is complete, you can retrieve and use the graph data:

```python theme={null}
from graphora import GraphoraClient

# Initialize the client with user ID (required)
client = GraphoraClient(
    base_url="https://api.graphora.io",
    user_id="your-user-id",  # Required for all API calls
    api_key="your-api-key"
)

# Get the merged graph
merge_id = "merge_123456789"
transform_id = "transform_123456789"
graph_response = client.get_merged_graph(merge_id, transform_id)

# Print some statistics
print(f"Graph contains {len(graph_response.nodes)} nodes and {len(graph_response.edges)} edges")

# Examine nodes
for node in graph_response.nodes[:5]:  # First 5 nodes
    print(f"Node {node.id}: {node.labels} - {node.properties}")

# Examine edges
for edge in graph_response.edges[:5]:  # First 5 edges
    print(f"Edge {edge.id}: {edge.source} -> {edge.target} ({edge.type})")
```

These examples demonstrate the basic operations for merging data with the Graphora client library. For more detailed information about merging concepts and options, see the [Merging Concepts](/client/concepts/merging) page.