Updated algorithm to work with 5.0.0a23

Author: bartvanb

v6-session-basics/central.py

@@ -1,6 +1,6 @@
 from vantage6.common import info
 from vantage6.algorithm.decorator.action import central
-from vantage6.algorithm.decorator import algorithm_client
+from vantage6.algorithm.decorator.algorithm_client import algorithm_client
 from vantage6.algorithm.client import AlgorithmClient
 
 
@@ -21,7 +21,7 @@ def global_sum(client: AlgorithmClient, column: str) -> dict:
         description="subtask",
         method="sum",
         organizations=ids,
-        input_={"args": [column], "kwargs": {}},
+        arguments={"column": column},
     )
 
     info("Waiting for results...")
@@ -53,7 +53,7 @@ def global_sum_dev(client: AlgorithmClient, column: str) -> dict:
         description="subtask",
         method="sum_dev",
         organizations=ids,
-        input_={"args": [column], "kwargs": {}},
+        arguments={"column": column},
     )
 
     info("Waiting for results...")
@@ -85,7 +85,7 @@ def global_sum_dev_many(client: AlgorithmClient, column: str) -> dict:
         description="subtask",
         method="sum_many",
         organizations=ids,
-        input_={"args": [column], "kwargs": {}},
+        arguments={"column": column},
     )
 
     info("Waiting for results...")

v6-session-basics/partial.py

@@ -10,32 +10,30 @@
 import time
 import pandas as pd
 from vantage6.common import info, error
-from vantage6.algorithm.decorator import data, source_database
-from .tmp import dataframe, dataframes
+from vantage6.algorithm.decorator.data import dataframe, dataframes
 from vantage6.algorithm.decorator.action import (
     data_extraction,
-    pre_processing,
+    preprocessing,
     federated,
 )
 
 
 @data_extraction
-@source_database
 def read_csv(connection_details: dict) -> dict:
     info(f"Reading CSV file from {connection_details['uri']}")
     return pd.read_csv(connection_details["uri"])
 
 
-@pre_processing
-@data(1)
+@preprocessing
+@dataframe(1)
 def pre_process(df1: pd.DataFrame, column: str, dtype: str) -> pd.DataFrame:
     info(f"Pre-processing data for column {column} with dtype {dtype}")
     df1[column] = df1[column].astype(dtype)
     return df1
 
 
 @federated
-@data(1)
+@dataframe(1)
 def sum(df1: pd.DataFrame, column: str) -> dict:
     info(f"Summing column {column}")
     return {"sum": int(df1[column].sum())}