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Bulk Operations

This guide covers how to perform bulk operations in Teable tables.

Batch Record Operations

Batch Creation

from teable import TeableClient, TeableConfig

# Initialize the client
client = TeableClient(TeableConfig(
    api_url="https://your-teable-instance.com/api",
    api_key="your-api-key"
))

# Prepare multiple records
records = [
    {
        "Name": f"User {i}",
        "Email": f"user{i}@example.com",
        "Department": "Engineering"
    }
    for i in range(1, 101)  # Create 100 records
]

# Batch create records
result = client.records.batch_create_records(
    table_id="table_id",
    records=records
)

print(f"Successfully created: {result.success_count}")
print(f"Failed to create: {result.failure_count}")
print(f"Success rate: {result.success_rate}%")

# Process successful records
for record in result.successful:
    print(f"Created record: {record.record_id}")

# Process failed records
for failure in result.failed:
    print(f"Failed record: {failure}")

Batch Updates

# Prepare updates for multiple records
records = [
    {
        "record_id": "rec123",
        "fields": {
            "Status": "Active",
            "Last Updated": "2023-01-15"
        }
    },
    {
        "record_id": "rec456",
        "fields": {
            "Status": "Inactive",
            "Last Updated": "2023-01-15"
        }
    }
]

# Batch update records
result = client.records.batch_update_records(
    table_id="table_id",
    records=records
)

print(f"Successfully updated: {result.success_count}")
print(f"Failed to update: {result.failure_count}")
print(f"Success rate: {result.success_rate}%")

Batch Deletion

# Delete multiple records
record_ids = ["rec123", "rec456", "rec789"]

success = client.records.batch_delete_records(
    table_id="table_id",
    record_ids=record_ids
)

if success:
    print(f"Successfully deleted {len(record_ids)} records")

Error Handling

Handling Batch Operations

from teable.exceptions import TeableError, ValidationError

def safe_batch_operation(client, table_id, records):
    """Safely perform batch operations with error handling."""
    try:
        # Get table for validation
        table = client.tables.get(table_id)

        # Validate records
        for record in records:
            table.validate_record_fields(record['fields'])

        # Perform batch creation
        result = client.records.batch_create_records(
            table_id=table_id,
            records=records
        )

        print(f"Successfully created: {result.success_count}")
        print(f"Failed to create: {result.failure_count}")
        print(f"Success rate: {result.success_rate}%")

        return result

    except ValidationError as e:
        print(f"Validation error: {e}")
        return None
    except TeableError as e:
        print(f"Batch operation failed: {e}")
        return None

Best Practices

  1. Batch Processing
  2. Use batch operations for multiple records
  3. Handle partial failures gracefully
  4. Monitor API rate limits

  5. Consider performance impact

  6. Data Preparation

  7. Clean data before processing
  8. Validate data structure
  9. Handle missing values

  10. Convert data types appropriately

  11. Error Handling

  12. Implement comprehensive error handling
  13. Log failures for review
  14. Provide meaningful error messages

  15. Consider recovery strategies

  16. Performance

  17. Monitor API usage
  18. Consider rate limits
  19. Track operation progress
  20. Handle failures appropriately

Next Steps

After mastering bulk operations, you can: