Create rule S6974: Subclasses of Scikit-Learn's "BaseEstimator" shoul…

…d not set attributes ending with "_" in the "__init__" method (#3891)

rules/S6974/metadata.json

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+{
+}

rules/S6974/python/metadata.json

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+{
+  "title": "Subclasses of Scikit-Learn's \"BaseEstimator\" should not set attributes ending with \"_\" in the \"__init__\" method",
+  "type": "CODE_SMELL",
+  "status": "ready",
+  "remediation": {
+    "func": "Constant\/Issue",
+    "constantCost": "5min"
+  },
+  "tags": [
+  ],
+  "defaultSeverity": "Major",
+  "ruleSpecification": "RSPEC-6974",
+  "sqKey": "S6974",
+  "scope": "All",
+  "defaultQualityProfiles": ["Sonar way"],
+  "quickfix": "partial",
+  "code": {
+    "impacts": {
+      "MAINTAINABILITY": "MEDIUM",
+      "RELIABILITY": "HIGH"
+    },
+    "attribute": "CONVENTIONAL"
+  }
+}

rules/S6974/python/rule.adoc

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+This rule raises an issue when an attributes ending with ``++_++`` is set in the ``++__init__++`` method of a class inheriting from
+Scikit-Learn `BaseEstimator`
+
+
+== Why is this an issue?
+
+On a Scikit-Learn estimator, attributes that have a trailing underscore represents attributes that are estimated.
+These attributes have to be set in the fit method. Their presence are used to verify if an estimator has been fitted.
+
+[source,python]
+----
+from sklearn.neighbors import KNeighborsClassifier 
+
+X = [[0], [1], [2], [3]]
+y = [0, 0, 1, 1]
+knn = KNeighborsClassifier(n_neighbors=1) 
+knn.fit(X, y)
+knn.n_samples_fit_
+----
+
+In the example above the attributes of the `KNeighborsClassifier`, ``++n_samples_fit_++`` 
+is set only after the estimator's `fit` method is called. Calling ``++n_samples_fit_++`` before the estimator is fitted
+would raise an `AttributeError` exception.
+
+When implementing a custom estimator by subclassing Scikit-Learn's `BaseEstimator`, 
+it is important to follow the above convention and not set attributes with a trailing underscore inside the ``++__init__++`` method.
+
+== How to fix it
+
+To fix this issue, move the attributes with a trailing underscore from the ``++__init__++`` method to the `fit` method.
+
+=== Code examples
+
+==== Noncompliant code example
+
+[source,python,diff-id=1,diff-type=noncompliant]
+----
+from sklearn.base import BaseEstimator
+
+class MyEstimator(BaseEstimator):
+    def __init__(self):
+        self.estimated_attribute_ = None # Noncompliant: an estimated attribute is set in the __init__ method.
+----
+
+==== Compliant solution
+
+[source,python,diff-id=1,diff-type=compliant]
+----
+from sklearn.base import BaseEstimator
+
+class MyEstimator(BaseEstimator):
+    def fit(self, X, y):
+        self.estimated_attribute_ = some_estimation(X) # Compliant
+----
+
+== Resources
+=== Documentation
+
+* Scikit-Learn documentation - https://scikit-learn.org/stable/developers/develop.html#parameters-and-init[Parameters and init]
+* S6970 - The Scikit-learn `fit` method should be called before methods yielding results
+
+
+ifdef::env-github,rspecator-view[]
+
+(visible only on this page)
+
+== Implementation specification 
+
+Verify that subclasses of BaseEstimator do not have attributes with a trailing underscore in the __init__ method.
+Verify that inherited alongside BaseEstimator do not have attributes with a trailing underscore in the __init__ method.
+
+=== Message 
+
+Primary : Move this estimated attribute inside the `fit` method. 
+
+Secondary:  this attributes is used in this estimator (in the case of mixins)
+
+
+=== Issue location
+
+Primary : name of the attribute
+
+Secondary : the name of the estimator subclassing the mixin and the BaseEstimator 
+
+=== Quickfix
+
+Possible quickfix if the `fit` method does not exist. (Add the fit method with the estimated attribute) and delete the estimated attributes
+from the __init__ method. This is only possible in an estimator directly subclassing BaseEstimator.
+
+endif::env-github,rspecator-view[]