how to find parameters used in decision tree algorithm
Just type clf after defining it; in your case it gives:

clf
# result:

DecisionTreeClassifier(ccp_alpha=0.0, class_weight=None, criterion='gini',
                       max_depth=None, max_features=None, max_leaf_nodes=None,
                       min_impurity_decrease=0.0, min_impurity_split=None,
                       min_samples_leaf=1, min_samples_split=2,
                       min_weight_fraction_leaf=0.0, presort='deprecated',
                       random_state=None, splitter='best')

i.e. all arguments with their default values, since you did not specify anything in the definition clf = tree.DecisionTreeClassifier().
You can get the parameters of any algorithm in scikit-learn in a similar way.
Tested with scikit-learn v0.22.2
UPDATE
As Ben Reiniger correctly points out in the comment below, from scikit-learn v0.23 onwards, we need to set the display configuration first in order for this to work:
sklearn.set_config(print_changed_only=False)