Client
Arize class to begin logging predictions and actuals from a Pandas.DataFrame.
Import and initialize Arize Client from
arize.pandas.logger from arize.pandas.logger import Client
class Client(
api_key: str #from Arize platform
space_key: str
uri: Optional[str] = "https://api.arize.com/v1"
)
Argument | Data Type | Description |
|---|---|---|
api_key | str | (Required) Arize-provided api key associated with your service/space. Click "Show API Key" in the "Upload Data" page in the Arize UI to copy the key. |
space_key | str | (Required) Arize-provided identifier for relating records to spaces. Click "Show API Key" in the "Upload Data" page in the Arize UI to copy the key. |
uri | str | (Optional) URI endpoint required for on-prem customers. Defaults to "https://api.arize.com/v1" |
from arize.pandas.logger import Client, Schema
from arize.utils.types import ModelTypes, Environments, Schema, Metrics
import pandas as pd
SPACE_KEY = "SPACE_KEY" # update value here with your Space Key
API_KEY = "API_KEY" # update value here with your API key
arize_client = Client(space_key=SPACE_KEY, api_key=API_KEY)
if SPACE_KEY == "SPACE_KEY" or API_KEY == "API_KEY":
raise ValueError("❌ NEED TO CHANGE SPACE AND/OR API_KEY")
else:
print(
"✅ Import and Setup Arize Client Done! Now we can start using Arize!"
)
Last modified 2mo ago