APM

>Agent Skill

@microsoft/dataverse-sdk-use

skilldata

Guidance for using the PowerPlatform Dataverse Client Python SDK. Use when calling the SDK like creating CRUD operations, SQL queries, table metadata management, relationships, and upload files.

pythondocumentation
apm::install
$apm install @microsoft/dataverse-sdk-use
apm::skill.md
---
name: dataverse-sdk-use
description: Guidance for using the PowerPlatform Dataverse Client Python SDK. Use when calling the SDK like creating CRUD operations, SQL queries, table metadata management, relationships, and upload files.
---

# PowerPlatform Dataverse SDK Guide

## 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

### Operation Namespaces
- `client.records` -- CRUD and OData queries
- `client.query` -- query and search operations
- `client.tables` -- table metadata, columns, and relationships
- `client.files` -- file upload operations

### 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
```python
from azure.identity import (
    InteractiveBrowserCredential,
    ClientSecretCredential,
    CertificateCredential,
    AzureCliCredential
)
from PowerPlatform.Dataverse.client import DataverseClient
```

### Client Initialization
```python
# Development options
credential = InteractiveBrowserCredential()
credential = AzureCliCredential()

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

# Create client with context manager (recommended -- enables HTTP connection pooling)
# No trailing slash on URL!
with DataverseClient("https://yourorg.crm.dynamics.com", credential) as client:
    ...  # all operations here
# Session closed, caches cleared automatically

# Or without context manager:
client = DataverseClient("https://yourorg.crm.dynamics.com", credential)
```

### CRUD Operations

#### Create Records
```python
# Single record
account_id = client.records.create("account", {"name": "Contoso Ltd", "telephone1": "555-0100"})

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

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

# Query with filter (paginated)
for page in client.records.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 record in page:
        print(record["name"])

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

#### Create Records with Lookup Bindings (@odata.bind)
```python
# Set lookup fields using @odata.bind with PascalCase navigation property names
# CORRECT: use the navigation property name (case-sensitive, must match $metadata)
guid = client.records.create("new_ticket", {
    "new_name": "TKT-001",
    "new_CustomerId@odata.bind": f"/new_customers({customer_id})",
    "new_AgentId@odata.bind": f"/new_agents({agent_id})",
})

# WRONG: lowercase navigation property causes 400 error
# "new_customerid@odata.bind" -> ODataException: undeclared property 'new_customerid'
```

#### Update Records
```python
# Single update
client.records.update("account", account_id, {"telephone1": "555-0200"})

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

#### Upsert Records
Creates or updates records identified by alternate keys. Single item → PATCH; multiple items → `UpsertMultiple` bulk action.
> **Prerequisite**: The table must have an alternate key configured in Dataverse for the columns used in `alternate_key`. Without it, Dataverse will reject the request with a 400 error.
```python
from PowerPlatform.Dataverse.models.upsert import UpsertItem

# Single upsert
client.records.upsert("account", [
    UpsertItem(
        alternate_key={"accountnumber": "ACC-001"},
        record={"name": "Contoso Ltd", "telephone1": "555-0100"},
    )
])

# Bulk upsert (uses UpsertMultiple API automatically)
client.records.upsert("account", [
    UpsertItem(alternate_key={"accountnumber": "ACC-001"}, record={"name": "Contoso Ltd"}),
    UpsertItem(alternate_key={"accountnumber": "ACC-002"}, record={"name": "Fabrikam Inc"}),
])

# Composite alternate key
client.records.upsert("account", [
    UpsertItem(
        alternate_key={"accountnumber": "ACC-001", "address1_postalcode": "98052"},
        record={"name": "Contoso Ltd"},
    )
])

# Plain dict syntax (no import needed)
client.records.upsert("account", [
    {"alternate_key": {"accountnumber": "ACC-001"}, "record": {"name": "Contoso Ltd"}}
])
```

#### Delete Records
```python
# Single delete
client.records.delete("account", account_id)

# Bulk delete (uses BulkDelete API)
client.records.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.

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

# With solution assignment and custom primary column
table_info = client.tables.create(
    "new_Product",
    {"new_Code": "string", "new_Price": "decimal"},
    solution="MyPublisher",
    primary_column="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
- `"file"` - File column
- Enum subclass - Local option set (picklist)

#### Manage Columns
```python
# Add columns to existing table (must include customization prefix!)
client.tables.add_columns("new_Product", {
    "new_Category": "string",
    "new_InStock": "bool",
})

# Remove columns
client.tables.remove_columns("new_Product", ["new_Category"])
```

#### Inspect Tables
```python
# Get single table information
table_info = client.tables.get("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.tables.list()
for table in tables:
    print(table)
```

#### Delete Tables
```python
client.tables.delete("new_Product")
```

### Relationship Management

#### Create One-to-Many Relationship
```python
from PowerPlatform.Dataverse.models.relationship import (
    LookupAttributeMetadata,
    OneToManyRelationshipMetadata,
    Label,
    LocalizedLabel,
    CascadeConfiguration,
)
from PowerPlatform.Dataverse.common.constants import CASCADE_BEHAVIOR_REMOVE_LINK

lookup = LookupAttributeMetadata(
    schema_name="new_DepartmentId",
    display_name=Label(
        localized_labels=[LocalizedLabel(label="Department", language_code=1033)]
    ),
)

relationship = OneToManyRelationshipMetadata(
    schema_name="new_Department_Employee",
    referenced_entity="new_department",
    referencing_entity="new_employee",
    referenced_attribute="new_departmentid",
    cascade_configuration=CascadeConfiguration(
        delete=CASCADE_BEHAVIOR_REMOVE_LINK,
    ),
)

result = client.tables.create_one_to_many_relationship(lookup, relationship)
print(f"Created lookup field: {result['lookup_schema_name']}")
```

#### Create Many-to-Many Relationship
```python
from PowerPlatform.Dataverse.models.relationship import ManyToManyRelationshipMetadata

relationship = ManyToManyRelationshipMetadata(
    schema_name="new_employee_project",
    entity1_logical_name="new_employee",
    entity2_logical_name="new_project",
)

result = client.tables.create_many_to_many_relationship(relationship)
print(f"Created: {result['relationship_schema_name']}")
```

#### Convenience Method for Lookup Fields
```python
result = client.tables.create_lookup_field(
    referencing_table="new_order",
    lookup_field_name="new_AccountId",
    referenced_table="account",
    display_name="Account",
    required=True,
)
```

#### Query and Delete Relationships
```python
# Get relationship metadata
rel = client.tables.get_relationship("new_Department_Employee")
if rel:
    print(f"Found: {rel['SchemaName']}")

# Delete relationship
client.tables.delete_relationship(result["relationship_id"])
```

### File Operations

```python
# Upload file to a file column
client.files.upload(
    table="account",
    record_id=account_id,
    file_column="new_Document",  # If the file column doesn't exist, it will be created automatically
    path="/path/to/document.pdf",
)
```

## Error Handling

The SDK provides structured exceptions with detailed error information:

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

try:
    client.records.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
- For `@odata.bind` errors ("undeclared property"): the navigation property name before `@odata.bind` is case-sensitive and must match the entity's `$metadata` exactly (e.g., `new_CustomerId@odata.bind` for custom lookups, `parentaccountid@odata.bind` for system lookups). The SDK preserves `@odata.bind` key casing.

## Best Practices

### Performance Optimization

1. **Use bulk operations** - Pass lists to create/update/delete for automatic optimization
2. **Specify select fields** - Limit returned columns to reduce payload size
3. **Control page size** - Use `top` and `page_size` parameters appropriately
4. **Reuse client instances** - Don't create new clients for each operation
5. **Use production credentials** - ClientSecretCredential or CertificateCredential for unattended operations
6. **Error handling** - Implement retry logic for transient errors (`e.is_transient`)
7. **Always include customization prefix** for custom tables/columns
8. **Use lowercase for column names, match `$metadata` for navigation properties** - Column names in `$select`/`$filter`/record payloads use lowercase LogicalNames. Navigation properties in `$expand` and `@odata.bind` keys are case-sensitive and must match the entity's `$metadata` (PascalCase for custom lookups like `new_CustomerId`, lowercase for system lookups like `parentaccountid`)
9. **Test in non-production environments** first
10. **Use named constants** - Import cascade behavior constants from `PowerPlatform.Dataverse.common.constants`

## Additional Resources

Load these resources as needed during development:

- [API Reference](https://learn.microsoft.com/python/api/dataverse-sdk-docs-python/dataverse-overview)
- [Product Documentation](https://learn.microsoft.com/power-apps/developer/data-platform/sdk-python/)
- [Dataverse Web API](https://learn.microsoft.com/power-apps/developer/data-platform/webapi/)
- [Azure Identity](https://learn.microsoft.com/python/api/overview/azure/identity-readme)

## Key Reminders

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