Reading the classification report of evaluation metric?

I am using the "classification_report" from:

from sklearn.metrics import classification_report


in order to evaluate a classification model.

How can I read this report? What is the value of precision, recall, and f1-score?

Is the precision = 56% or 25% and also for recall and f1-score?

Note: in order to understand this kind of classification report one needs to first understand how things work in a confusion matrix (with sklearn one can use the function confusion_matrix). A confusion matrix shows for every true class X and every predicted class Y the number of instances which have true class X and are predicted as class Y. The values in the classification report are calculated from the confusion matrix, it's a good exercise to do this calculation manually a few times in order to understand how things work in the classification report.