name: powerplatform-dataverseclient-python description: Guidance for using the PowerPlatform Dataverse Client Python SDK. Use when calling the SDK like creating CRUD operations, SQL queries, table metadata management, and upload files.

PowerPlatform Dataverse SDK Guide

Name: powerplatform-dataverseclient-python
Rating: 65
Author: microsoft

Overview

Use the PowerPlatform Dataverse Client Python SDK to interact with Microsoft Dataverse.

Key Concepts

Schema Names vs Display Names

Standard tables: lowercase (e.g., "account", "contact")
Custom tables: include customization prefix (e.g., "new_Product", "cr123_Invoice")
Custom columns: include customization prefix (e.g., "new_Price", "cr123_Status")
ALWAYS use schema names (logical names), NOT display names

Bulk Operations

The SDK supports Dataverse's native bulk operations: Pass lists to create(), update() for automatic bulk processing, for delete(), set use_bulk_delete when passing lists to use bulk operation

Paging

Control page size with page_size parameter
Use top parameter to limit total records returned

Common Operations

Import

from azure.identity import (
    InteractiveBrowserCredential, 
    ClientSecretCredential,
    ClientCertificateCredential,
    AzureCliCredential
)
from PowerPlatform.Dataverse.client import DataverseClient

Client Initialization

# Development options
credential = InteractiveBrowserCredential()
credential = AzureCliCredential()

# Production options
credential = ClientSecretCredential(tenant_id, client_id, client_secret)
credential = ClientCertificateCredential(tenant_id, client_id, cert_path)

# Create client (no trailing slash on URL!)
client = DataverseClient("https://yourorg.crm.dynamics.com", credential)

CRUD Operations

Create Records

# Single record
account_ids = client.create("account", {"name": "Contoso Ltd", "telephone1": "555-0100"})
account_id = account_ids[0]

# Bulk create (uses CreateMultiple API automatically)
contacts = [
    {"firstname": "John", "lastname": "Doe"},
    {"firstname": "Jane", "lastname": "Smith"}
]
contact_ids = client.create("contact", contacts)

Read Records

# Get single record by ID
account = client.get("account", account_id, select=["name", "telephone1"])

# Query with filter
pages = client.get(
    "account",
    select=["accountid", "name"],      # select is case-insensitive (automatically lowercased)
    filter="statecode eq 0",           # filter must use lowercase logical names (not transformed)
    top=100
)
for page in pages:
    for record in page:
        print(record["name"])

# Query with navigation property expansion (case-sensitive!)
pages = client.get(
    "account",
    select=["name"],
    expand=["primarycontactid"],  # Navigation properties are case-sensitive!
    filter="statecode eq 0"       # Column names must be lowercase logical names
)
for page in pages:
    for account in page:
        contact = account.get("primarycontactid", {})
        print(f"{account['name']} - {contact.get('fullname', 'N/A')}")

Update Records

# Single update
client.update("account", account_id, {"telephone1": "555-0200"})

# Bulk update (broadcast same change to multiple records)
client.update("account", [id1, id2, id3], {"industry": "Technology"})

Delete Records

# Single delete
client.delete("account", account_id)

# Bulk delete (uses BulkDelete API)
client.delete("account", [id1, id2, id3], use_bulk_delete=True)

SQL Queries

SQL queries are read-only and support limited SQL syntax. A single SELECT statement with optional WHERE, TOP (integer literal), ORDER BY (column names only), and a simple table alias after FROM is supported. But JOIN and subqueries may not be. Refer to the Dataverse documentation for the current feature set.

# Basic SQL query
results = client.query_sql(
    "SELECT TOP 10 accountid, name FROM account WHERE statecode = 0"
)
for record in results:
    print(record["name"])

Table Management

Create Custom Tables

# Create table with columns (include customization prefix!)
table_info = client.create_table(
    table_schema_name="new_Product",
    columns={
        "new_Code": "string",
        "new_Price": "decimal",
        "new_Active": "bool",
        "new_Quantity": "int"
    }
)

# With solution assignment and custom primary column
table_info = client.create_table(
    table_schema_name="new_Product",
    columns={"new_Code": "string", "new_Price": "decimal"},
    solution_unique_name="MyPublisher",
    primary_column_schema_name="new_ProductCode"
)

Supported Column Types

Types on the same line map to the same exact format under the hood

"string" or "text" - Single line of text
"int" or "integer" - Whole number
"decimal" or "money" - Decimal number
"float" or "double" - Floating point number
"bool" or "boolean" - Yes/No
"datetime" or "date" - Date
Enum subclass - Local option set (picklist)

Manage Columns

# Add columns to existing table (must include customization prefix!)
client.create_columns("new_Product", {
    "new_Category": "string",
    "new_InStock": "bool"
})

# Remove columns
client.delete_columns("new_Product", ["new_Category"])

Inspect Tables

# Get single table information
table_info = client.get_table_info("new_Product")
print(f"Logical name: {table_info['table_logical_name']}")
print(f"Entity set: {table_info['entity_set_name']}")

# List all tables
tables = client.list_tables()
for table in tables:
    print(table)

Delete Tables

# Delete custom table
client.delete_table("new_Product")

File Operations

# Upload file to a file column
client.upload_file(
    table_schema_name="account",
    record_id=account_id,
    file_name_attribute="new_document",
    path="/path/to/document.pdf"
)

Error Handling

The SDK provides structured exceptions with detailed error information:

from PowerPlatform.Dataverse.core.errors import (
    DataverseError,
    HttpError,
    ValidationError,
    MetadataError,
    SQLParseError
)
from PowerPlatform.Dataverse.client import DataverseClient

try:
    client.get("account", "invalid-id")
except HttpError as e:
    print(f"HTTP {e.status_code}: {e.message}")
    print(f"Error code: {e.code}")
    print(f"Subcode: {e.subcode}")
    if e.is_transient:
        print("This error may be retryable")
except ValidationError as e:
    print(f"Validation error: {e.message}")

Common Error Patterns

Authentication failures:

Check environment URL format (no trailing slash)
Verify credentials have Dataverse permissions
Ensure app registration is properly configured

404 Not Found:

Verify table schema name is correct (lowercase for standard tables)
Check record ID exists
Ensure using schema names, not display names
Cache issue could happen, so retry might help, especially for metadata creation

400 Bad Request:

Check filter/expand parameters use correct case
Verify column names exist and are spelled correctly
Ensure custom columns include customization prefix

Best Practices

Performance Optimization

Use bulk operations - Pass lists to create/update/delete for automatic optimization
Specify select fields - Limit returned columns to reduce payload size
Control page size - Use top and page_size parameters appropriately
Reuse client instances - Don't create new clients for each operation
Use production credentials - ClientSecretCredential or ClientCertificateCredential for unattended operations
Error handling - Implement retry logic for transient errors (e.is_transient)
Always include customization prefix for custom tables/columns
Use lowercase - Generally using lowercase input won't go wrong, except for custom table/column naming
Test in non-production environments first

Additional Resources

Load these resources as needed during development:

Key Reminders

Schema names are required - Never use display names
Custom tables need prefixes - Include customization prefix (e.g., "new_")
Filter is case-sensitive - Use lowercase logical names
Bulk operations are encouraged - Pass lists for optimization
No trailing slashes in URLs - Format: https://org.crm.dynamics.com
Structured errors - Check is_transient for retry logic

powerplatform-dataverseclient-python

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