Add a simple example model that operates on webcompat issues

First model enabled by the work on #259

Author: marco-c

bugbug/models/__init__.py

@@ -12,6 +12,7 @@
     "annotateignore": "bugbug.models.annotate_ignore.AnnotateIgnoreModel",
     "assignee": "bugbug.models.assignee.AssigneeModel",
     "backout": "bugbug.models.backout.BackoutModel",
+    "browsername": "bugbug.models.browsername.BrowserNameModel",
     "bug": "bugbug.model.BugModel",
     "bugtype": "bugbug.models.bugtype.BugTypeModel",
     "component": "bugbug.models.component.ComponentModel",

bugbug/models/browsername.py

@@ -0,0 +1,82 @@
+# -*- coding: utf-8 -*-
+# This Source Code Form is subject to the terms of the Mozilla Public
+# License, v. 2.0. If a copy of the MPL was not distributed with this file,
+# You can obtain one at http://mozilla.org/MPL/2.0/.
+
+import logging
+
+import xgboost
+from sklearn.compose import ColumnTransformer
+from sklearn.feature_extraction import DictVectorizer
+from sklearn.pipeline import Pipeline
+
+from bugbug import feature_cleanup, github, issue_features, utils
+from bugbug.model import IssueModel
+
+logger = logging.getLogger(__name__)
+
+
+class BrowserNameModel(IssueModel):
+    def __init__(self, lemmatization=False):
+        IssueModel.__init__(self, lemmatization)
+
+        feature_extractors = [
+            issue_features.comment_count(),
+        ]
+
+        cleanup_functions = [
+            feature_cleanup.fileref(),
+            feature_cleanup.url(),
+            feature_cleanup.synonyms(),
+        ]
+
+        self.extraction_pipeline = Pipeline(
+            [
+                (
+                    "issue_extractor",
+                    issue_features.IssueExtractor(
+                        feature_extractors, cleanup_functions
+                    ),
+                ),
+                (
+                    "union",
+                    ColumnTransformer(
+                        [
+                            ("data", DictVectorizer(), "data"),
+                            ("title", self.text_vectorizer(min_df=0.0001), "title"),
+                            (
+                                "first_comment",
+                                self.text_vectorizer(min_df=0.0001),
+                                "first_comment",
+                            ),
+                        ]
+                    ),
+                ),
+            ]
+        )
+
+        self.clf = xgboost.XGBClassifier(n_jobs=utils.get_physical_cpu_count())
+        self.clf.set_params(predictor="cpu_predictor")
+
+    def get_labels(self):
+        classes = {}
+
+        for issue in github.get_issues():
+            for label in issue["labels"]:
+                if label["name"] == "browser-firefox":
+                    classes[issue["number"]] = 1
+
+            if issue["number"] not in classes:
+                classes[issue["number"]] = 0
+
+        logger.info(
+            f"{sum(1 for label in classes.values() if label == 1)} issues belong to Firefox"
+        )
+        logger.info(
+            f"{sum(1 for label in classes.values() if label == 0)} issues do not belong to Firefox"
+        )
+
+        return classes, [0, 1]
+
+    def get_feature_names(self):
+        return self.extraction_pipeline.named_steps["union"].get_feature_names()