Intapp DealCloud SDK

A modern Python SDK for the DealCloud API, built on HTTPX via intapp-rest-client.

Overview

The SDK is a complete rewrite and a near drop-in replacement for the official dealcloud_sdk, providing a similar and more advanced enterprise featureset that covers a robust API surface of DealCloud.

• HTTPX-based HTTP client - Modern async-capable HTTP library
• Improved retry handling - Per-status-code retry counts with exponential backoff
• Configurable concurrency - Fine-grained control over parallel operations
• Full configuration support - Comprehensive settings for retry, concurrency, and pagination
• Better rate limit handling - Respects Retry-After headers
• OpenTelemetry compatible - Works with standard HTTPX instrumentation
• Streaming pagination - Memory-efficient bulk data operations with max_concurrency support

Documentation: See the full guide and API reference on the DealCloud documentation site: Python SDK · Changelog

Migration and staying on legacy

Migration Guide: If you are using the dealcloud-sdk versions below this, make sure to see the migration guide: Migration Guide

Until you are ready to complete your migration, change your pyproject.toml to "dealcloud-sdk<1.0.0"

Installation

# Using uv (recommended)
uv add dealcloud-sdk

# With YAML configuration support
uv add dealcloud-sdk[yaml]

# Using pip
pip install dealcloud-sdk

Quick Start

Simple Usage

from dealcloud_sdk import DealCloud

# Initialize with credentials
dc = DealCloud(
    site_url="client.dealcloud.com",
    client_id="12345",
    client_secret="your_secret",
)

# Read data as pandas DataFrame
data = dc.read_data("Company", output="pandas", resolve="name")

# Get schema
schema = dc.get_schema()
users = dc.get_users()

# Write data
dc.insert_data("Company", data=[{"Name": "New Company"}])

# Delete data
dc.delete_data("Company", records=[123, 456])

Configuration Files (Recommended)

Use from_config() for full control over retry, concurrency, and pagination settings. Works with both JSON and YAML files:

# Auto-detects JSON or YAML by file extension
dc = DealCloud.from_config("config.json")
dc = DealCloud.from_config("config.yaml")

config.json (full configuration format):

{
    "siteUrl": "client.dealcloud.com",
    "clientId": "12345",
    "clientSecret": "secret",
    "connectorTimeoutSeconds": 100,
    "querySettings": {
        "pageSize": 1000,
        "cellPaginationLimit": 9000,
        "deletePageSize": 10000
    },
    "concurrencyLimits": {
        "read": 2,
        "delete": 2,
        "create": 2
    },
    "responseRetrySettings": {
        "tooManyRequests": 5,
        "internalServerError": 2,
        "badGateway": 2,
        "serviceUnavailable": 2,
        "gatewayTimeout": 2,
        "backoffFactor": 2.0,
        "maxBackoffSeconds": 300.0
    }
}

Environment Variables

# Uses DC_SITE_URL, DC_CLIENT_ID, DC_API_KEY
dc = DealCloud.from_env()

Context Manager

with DealCloud(
    site_url="client.dealcloud.com",
    client_id="12345",
    client_secret="your_secret",
) as dc:
    data = dc.read_data("Company", output="pandas")
# Connection automatically closed

API Reference

For the full API Reference: API Reference

Schema Operations

Data Operations

Streaming Operations (Memory-Efficient)

For large datasets, use streaming methods to avoid loading all data into memory:

Example: Bulk Delete with Streaming

# Stream and delete in batches (efficient for millions of rows)
for batch in dc.read_data_streaming("TempData", fields=["EntryId"], max_concurrency=5):
    entry_ids = [row["EntryId"] for row in batch]
    dc.delete_data("TempData", entry_ids)
    print(f"Deleted {len(entry_ids)} rows")

Example: Parallel Page Fetching

# Fetch pages in parallel for faster throughput
for batch in dc.read_data_streaming("Company", max_concurrency=10):
    process(batch)

# Or use configured concurrency from config.json
for batch in dc.read_view_streaming("My View"):
    process(batch)  # Uses concurrencyLimits.read from config

Factory Methods

Note: For full configuration files, use from_config() instead of from_json() or from_yaml(). The format-specific methods are primarily for legacy format support and nested configuration paths.

Error Handling

from dealcloud_sdk import (
    DealCloudApiError,
    DealCloudValidationError,
    DealCloudRateLimitError,
    DealCloudAuthError,
)

try:
    data = dc.read_data("Company", output="pandas")
except DealCloudRateLimitError as e:
    print(f"Rate limited, retry after {e.retry_after}s")
except DealCloudAuthError as e:
    print(f"Authentication failed: {e}")
except DealCloudApiError as e:
    print(f"API error {e.status_code}: {e.message}")

Source

This SDK is distributed under the Intapp License for Supplemental Software (LICENSE). It is not open source.

Source for inspection and learning is provided via the PyPI source distribution (and hand-delivered tarballs built the same way). Full documentation: DealCloud Python SDK documentation.

License

Intapp License — see LICENSE.