​
Overview

Update the properties and definitions of existing columns in an experiment dataset.

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Method Signature

# Synchronous
client.experiments.update_columns(
    experiment_id: str,
    column_updates: List[Dict[str, Any]]
) -> Dict[str, Any]

# Asynchronous
await client.experiments.update_columns(
    experiment_id: str,
    column_updates: List[Dict[str, Any]]
) -> Dict[str, Any]

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Parameters

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experiment_id
string
required
The unique identifier of the experiment
​
column_updates
List[Dict[str, Any]]
required
List of column updates with name and new properties

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Returns

Returns a dictionary containing the updated experiment information.

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Example

from keywordsai import KeywordsAI

client = KeywordsAI(api_key="your-api-key")

# Update column definitions
column_updates = [
    {
        "name": "score",
        "type": "float",
        "description": "Updated scoring metric (0-1)",
        "required": True
    },
    {
        "name": "category",
        "description": "Response classification category"
    }
]

result = client.experiments.update_columns(
    experiment_id="exp_123",
    column_updates=column_updates
)

print(f"Updated {len(column_updates)} columns in experiment")

​
Error Handling

try:
    result = client.experiments.update_columns(
        experiment_id="exp_123",
        column_updates=column_updates
    )
except Exception as e:
    print(f"Error updating columns: {e}")