Slide 87
Slide 87 text
87
Asset実装例
from dagster import asset
from typing import Dict
import pandas as pd
from sklearn.linear_model import LinearRegression
@asset
def iris_dataset() -> pd.DataFrame:
return pd.read_csv(
"https://docs.dagster.io/assets/iris.csv",
names=["sepal_length_cm","sepal_width_cm","petal_length_cm","petal_width_cm","species"]
)
@asset
def logistic_regression_model(iris_dataset: pd.DataFrame) -> LinearRegression:
x = iris_dataset[["sepal_length_cm", "sepal_width_cm", "petal_length_cm", "petal_width_cm"]]
y = iris_dataset["species"].map({"Iris-setosa": 0, "Iris-versicolor": 1, "Iris-virginica": 2})
return LinearRegression().fit(x, y)
@asset
def accuracy(logistic_regression_model: LinearRegression) -> Dict:
return {
"intercept": logistic_regression_model.intercept_,
"coef": logistic_regression_model.coef_,
}
@assetデコレータでAssetを
作成
関数引数がAssetの依存関係
を表す