exceljet-client 0.1.6

Client library for the ExcelJet API

ExcelJet API Client

A Python client for the ExcelJet API. This client library provides convenient access to the ExcelJet API from Python applications.

Installation

# Install the package
pip install exceljet-client

# For developers: Install with development dependencies
pip install "exceljet-client[dev]"

# For local development from source
git clone https://github.com/exceljet2/exceljet-client.git
cd exceljet-client
pip install -e ".[dev]"

Usage

from exceljet_client import ExceljetClient
from exceljet_client.models import ContentType

# Initialize the client
client = ExceljetClient(api_key="your_api_key")

# List nodes with optional filtering
nodes = client.list_nodes(content_type=ContentType.FUNCTION, limit=10)
print(f"Found {nodes.count} nodes")

# Get a specific node
node = client.get_node(node_id=123)
print(f"Node title: {node.title}")

# Get node as markdown
markdown = client.get_node_markdown(node_id=123)
print(markdown)

# Create a new node
from exceljet_client.models import BackdropNode

new_node = BackdropNode(
    nid=456,
    title="New Function Example",
    type="function",
    path="functions/new-example",
    created=int(time.time()),
    changed=int(time.time()),
    status=True,
    body="Example function body"
)

created_node = client.create_node(new_node)
print(f"Created node: {created_node.nid}")

# Update an existing node
updated_node = client.update_node(node_id=456, node=new_node)

# Delete a node
client.delete_node(node_id=456)

Bulk Operations

The client supports bulk operations for creating, updating, and deleting multiple nodes:

# Bulk create nodes
nodes_to_create = [node1, node2, node3]
result = client.create_nodes_bulk(nodes_to_create)
print(f"Created {result.created} nodes")

# Bulk update nodes
result = client.update_nodes_bulk(nodes_to_update)
print(f"Updated {result.updated} nodes")

# Bulk delete nodes
result = client.delete_nodes_bulk([123, 456, 789])
print(f"Deleted {result.deleted} nodes")

Semantic Search

The client provides semantic search capabilities using vector similarity:

# Perform semantic search
results = client.search_semantic(q="how to use VLOOKUP", limit=10)
for result in results.results:
    print(f"{result.title} ({result.path}) - Score: {result.score:.3f}")
    print(f"  Text: {result.text[:100]}...")

# Search with content type filter
function_results = client.search_semantic(
    q="lookup functions",
    type="function",
    limit=5
)

# Get search index statistics
stats = client.search_stats()
print(f"Pending: {stats.pending_count}, Chunks: {stats.chunk_count}, Cache: {stats.cache_count}")

# List indexed chunks
index = client.search_index(limit=50)
for item in index.items:
    print(f"Node {item.nid}: {item.title} - Chunk {item.chunk_index}")

# Manage search index
# Rebuild index in background (non-blocking)
client.search_rebuild(background=True)

# Or rebuild synchronously (blocking, returns stats)
rebuild_result = client.search_rebuild(background=False)
print(f"Processed {rebuild_result.chunks_processed} chunks")

Error Handling

The client raises typed exceptions for different error cases:

from exceljet_client.exceptions import ExceljetApiError, NodeNotFoundError

try:
    node = client.get_node(node_id=999999)
except NodeNotFoundError:
    print("Node not found")
except ExceljetApiError as e:
    print(f"API error: {e.status_code} - {e.detail}")

API Reference

See the full API reference for detailed documentation.

License

MIT