from sklearn import datasets
from sklearn.modelselection import traintestsplit
from sklearn.linearmodel import LogisticRegression

Load the iris dataset

iris = datasets.load_iris()
X, y = iris.data, iris.target

Split the dataset into training and testing sets

Xtrain, Xtest, ytrain, ytest = traintestsplit(X, y)

Create a logistic regression model and fit it to the training data

model = LogisticRegression()
model.fit(Xtrain, ytrain)

Evaluate the model on the testing data

score = model.score(Xtest, ytest)
print("Accuracy: ", score)