Batch scoring
This example demonstrates how to use the eScorer Python client for batch scoring. You can download the complete example here.
Prerequisites
Import the H2O eScorer client
import h2o_escorer
import asyncio
Async function main to authenticate and score
async def main():
# Init the eScorer client
client = h2o_escorer.Client()
# Authenticate the client
await client.authenticate()
# Score model
response = await client.batch_scorer(
model_name='pipeline191.mojo',
properties_filepath='artifacts/s3.properties'
)
return response
Asynchronously call score
response = await main()
Running H2O eScorer: Batch. Model: pipeline191.mojo
Get the predictions
response['result']
'Scoring Starting
****** AWS *******
AWS Region US_EAST_1
AWS List Bucket US_EAST_1
Total selected rows 38999 Total Read time (ms) 7058
Thread-1 Rows Read 2473 Scored 2473 Error 0 Queue Empty false
...
Saving results to S3
Upload of file S3/predictions-2022-10-03-14-44-33.csv to S3 completed'
Get the scoring latency
f'{response["time_elapsed"]}s'
'12.829s'
Feedback
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