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11/02/2022, 7:00 PMZouhair Mahboubi
11/02/2022, 7:00 PM@config.when(cfg_val='0')
@extract_columns('x','y','z')
def concat_v0(
X_e1: pd.Series, Y_e1: pd.Series, Z_e1: pd.Series,
X_e2: pd.Series, Y_e2: pd.Series, Z_e2: pd.Series,
X_e3: pd.Series, Y_e3: pd.Series, Z_e3: pd.Series,
X_e4: pd.Series, Y_e4: pd.Series, Z_e4: pd.Series) -> pd.DataFrame:
output = pd.DataFrame({'x': [X_e1, X_e2, X_e3, X_e4],
'y': [Y_e1, Y_e2, Y_e3, Y_e4],
'z': [Z_e1, Z_e2, Z_e3, Z_e4],})
return output
@config.when(cfg_val='1')
@extract_columns('x','y','z')
def concat_v1(
X_e1: pd.Series, Y_e1: pd.Series, Z_e1: pd.Series,
X_e2: pd.Series, Y_e2: pd.Series, Z_e2: pd.Series,
X_e3: pd.Series, Y_e3: pd.Series, Z_e3: pd.Series ) -> pd.DataFrame:
output = pd.DataFrame({'x': [X_e1, X_e2, X_e3],
'y': [Y_e1, Y_e2, Y_e3],
'z': [Z_e1, Z_e2, Z_e3]})
return output
Stefan Krawczyk
11/02/2022, 7:06 PMStefan Krawczyk
11/02/2022, 7:07 PM@config.when(cfg_val='0')
@extract_columns('x','y','z')
def concact__v0(...):
@config.when(cfg_val='1')
@extract_columns('x','y','z')
def concact__v1(...):
Zouhair Mahboubi
11/02/2022, 7:09 PMZouhair Mahboubi
11/02/2022, 7:09 PMStefan Krawczyk
11/02/2022, 7:10 PMconcat
node in the graph.Stefan Krawczyk
11/02/2022, 7:12 PMthanks, I meant is there a less verbose way of doing the above 😛
for example defining the inputs as **kwargs and telling the driver what kwargs to use depending on the config?what would that help with? Part of the value of hamilton is it’s pretty explicit what depends on what 🙂 — so a new person coming to own/use the code can know easily.
Stefan Krawczyk
11/02/2022, 7:13 PMZouhair Mahboubi
11/02/2022, 7:15 PMElijah Ben Izzy
11/02/2022, 7:17 PM