Overview
Update the properties and definitions of existing columns in an experiment dataset.
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]
Parameters
The unique identifier of the experiment
column_updates
List[Dict[str, Any]]
required
List of column updates with name and new properties
Returns
Returns a dictionary containing the updated experiment information.
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}")
