Profile Builder: add report for remove_disable_flag at the top level

dataprofiler/profilers/base_column_profilers.py

@@ -235,7 +235,8 @@ def report(self, remove_disabled_flag=False):
         """
         Private abstract method for returning report.
 
-        :param remove_disabled_flag: flag to determine if disabled options should be excluded in the report.
+        :param remove_disabled_flag: flag to determine if disabled 
+            options should be excluded in the report.
         :type remove_disabled_flag: boolean
         """
 

dataprofiler/profilers/categorical_column_profile.py

@@ -121,7 +121,8 @@ def report(self, remove_disabled_flag=False):
         """
         Private abstract method for returning report.
 
-        :param remove_disabled_flag: flag to determine if disabled options should be excluded in the report.
+        :param remove_disabled_flag: flag to determine if disabled
+            options should be excluded in the report.
         :type remove_disabled_flag: boolean
         """
         return self.profile

dataprofiler/profilers/data_labeler_column_profile.py

@@ -243,7 +243,8 @@ def report(self, remove_disabled_flag=False):
         """
         Private abstract method for returning report.
 
-        :param remove_disabled_flag: flag to determine if disabled options should be excluded in the report.
+        :param remove_disabled_flag: flag to determine if disabled
+            options should be excluded in the report.
         :type remove_disabled_flag: boolean
         """
         return self.profile

dataprofiler/profilers/datetime_column_profile.py

@@ -115,7 +115,8 @@ def report(self, remove_disabled_flag=False):
         """
         Private abstract method for returning report.
 
-        :param remove_disabled_flag: flag to determine if disabled options should be excluded in the report.
+        :param remove_disabled_flag: flag to determine if disabled
+            options should be excluded in the report.
         :type remove_disabled_flag: boolean
         """
         return self.profile

dataprofiler/profilers/int_column_profile.py

@@ -57,7 +57,8 @@ def report(self, remove_disabled_flag=False):
         """
         Private abstract method for returning report.
 
-        :param remove_disabled_flag: flag to determine if disabled options should be excluded in the report.
+        :param remove_disabled_flag: flag to determine if disabled
+            options should be excluded in the report.
         :type remove_disabled_flag: boolean
         """
         return self.profile

dataprofiler/profilers/order_column_profile.py

@@ -232,7 +232,8 @@ def report(self, remove_disabled_flag=False):
         """
         Private abstract method for returning report.
 
-        :param remove_disabled_flag: flag to determine if disabled options should be excluded in the report.
+        :param remove_disabled_flag: flag to determine if disabled
+            options should be excluded in the report.
         :type remove_disabled_flag: boolean
         """
         return self.profile

dataprofiler/profilers/profile_builder.py

@@ -264,12 +264,11 @@ def diff(self, other_profile, options=None):
                 profile[key] = None
 
         return profile
-
-    @property
-    def profile(self):
+
+    def report(self, remove_disabled_flag=False):
         unordered_profile = dict()
         for profile in self.profiles.values():
-            utils.dict_merge(unordered_profile, profile.profile)
+            utils.dict_merge(unordered_profile, profile.report(remove_disabled_flag))
 
         name = self.name
         if isinstance(self.name, np.integer):
@@ -313,6 +312,10 @@ def profile(self):
 
         return profile
 
+    @property
+    def profile(self):
+        return self.report(remove_disabled_flag=False)
+
     def _update_base_stats(self, base_stats):
         self.sample_size += base_stats["sample_size"]
         self._last_batch_size = base_stats["sample_size"]
@@ -1099,10 +1102,12 @@ def report(self, report_options=None):
             report_options = {
                 "output_format": None,
                 "omit_keys": None,
+                "remove_disabled_flag": False,
             }
 
         output_format = report_options.get("output_format", None)
         omit_keys = report_options.get("omit_keys", None)
+        remove_disabled_flag = report_options.get("remove_disabled_flag", False)
 
         report = OrderedDict([
             ("global_stats", {
@@ -1115,7 +1120,7 @@ def report(self, report_options=None):
             }),
             ("data_stats", OrderedDict()),
         ])
-        report["data_stats"] = self._profile.profile
+        report["data_stats"] = self._profile.report(remove_disabled_flag)
         return _prepare_report(report, output_format, omit_keys)
 
     @utils.method_timeit(name="clean_and_base_stats")
@@ -1550,11 +1555,13 @@ def report(self, report_options=None):
             report_options = {
                 "output_format": None,
                 "num_quantile_groups": 4,
+                "remove_disabled_flag": False,
             }
 
         output_format = report_options.get("output_format", None)
         omit_keys = report_options.get("omit_keys", [])
         num_quantile_groups = report_options.get("num_quantile_groups", 4)
+        remove_disabled_flag = report_options.get("remove_disabled_flag", False)
 
         report = OrderedDict([
             ("global_stats", {
@@ -1578,7 +1585,7 @@ def report(self, report_options=None):
         for i in range(len(self._profile)):
             col_name = self._profile[i].name
             report["global_stats"]["profile_schema"][col_name].append(i)
-            report["data_stats"].append(self._profile[i].profile)
+            report["data_stats"].append(self._profile[i].report(remove_disabled_flag))
             quantiles = report["data_stats"][i]["statistics"].get('quantiles')
             if quantiles:
                 quantiles = calculate_quantiles(num_quantile_groups, quantiles)

dataprofiler/tests/profilers/test_profile_builder.py

@@ -972,6 +972,63 @@ def test_omit_cols_preserves_schema(self):
         for col_report in report["data_stats"]:
             self.assertIsNone(col_report)
 
+    def test_report_remove_disabled_flag(self):
+        data = pd.DataFrame([[1.01, 2.02, 'if you'],
+                            [10.01, 20.02,'read this you'],
+                            [100.01,200.02, 'are cool']],
+                    columns=["a", "b", "wordy_text_words"])
+
+        # with options to disable FloatColumn `precision`
+        # and with remove_disabled_flag == True
+        profiler_options = ProfilerOptions()
+        profiler_options.set({"precision.is_enabled": False})
+        profiler = dp.StructuredProfiler(data=data, options=profiler_options)
+        report = profiler.report(report_options={"remove_disabled_flag": True})
+
+        for iter_value in range(0, len(data.columns)-1):
+            self.assertNotIn("precision", report["data_stats"][iter_value]["statistics"])
+
+        # with options to disable NumericalMixIn cal `min`
+        # and with remove_disabled_flag == True
+        profiler_options = ProfilerOptions()
+        profiler_options.set({"min.is_enabled": False})
+        profiler = dp.StructuredProfiler(data=data, options=profiler_options)
+        report = profiler.report(report_options={"remove_disabled_flag": True})
+
+        for iter_value in range(0,len(data.columns)-1):
+            self.assertNotIn("min", report["data_stats"][iter_value]["statistics"])
+
+        # with options to disable TextColumn cal `vocab`
+        # and with remove_disabled_flag == True
+        profiler_options = ProfilerOptions()
+        profiler_options.set({"vocab.is_enabled": False})
+        profiler = dp.StructuredProfiler(data=data, options=profiler_options)
+        report = profiler.report(report_options={"remove_disabled_flag": True})
+
+        for iter_value in range(0,len(data.columns)):
+            self.assertNotIn("vocab", report["data_stats"][iter_value])
+
+        # with profiler options and default remove_disabled_flag
+        profiler_options = ProfilerOptions()
+        profiler_options.set({"min.is_enabled": False})
+        profiler = dp.StructuredProfiler(data=data, options=profiler_options)
+        report = profiler.report()
+
+        for iter_value in range(0,len(data.columns)):
+            self.assertIn("min", report["data_stats"][iter_value]["statistics"])
+
+        # w/o profiler options and default remove_disabled_flag
+        profiler = dp.StructuredProfiler(data=data)
+        report = profiler.report()
+
+        for iter_value in range(0, len(data.columns)-1):
+            self.assertIn("precision", report["data_stats"][iter_value]["statistics"])
+            self.assertIn("min", report["data_stats"][iter_value]["statistics"])
+
+        self.assertNotIn("precision", report["data_stats"][2]["statistics"])
+        self.assertIn("min", report["data_stats"][2]["statistics"])
+        self.assertIn("vocab", report["data_stats"][2]["statistics"])
+
     def test_report_quantiles(self):
         report_none = self.trained_schema.report(
             report_options={"num_quantile_groups": None})
@@ -2607,6 +2664,19 @@ def test_update_profile(self):
             expected_word_count,
             report['data_stats']['statistics']['word_count'])
 
+    def test_report_remove_disabled_flag(self):
+        profiler_options = ProfilerOptions()
+        profiler_options.set({"vocab.is_enabled": False})
+        profiler = dp.UnstructuredProfiler(data=self.dataset, options=profiler_options)
+        report = profiler.report(report_options={"remove_disabled_flag": True})
+        self.assertNotIn('vocab', report['data_stats']['statistics'])
+        self.assertIn('words', report['data_stats']['statistics'])
+
+        profiler = dp.UnstructuredProfiler(data=self.dataset)
+        report = profiler.report(report_options={"remove_disabled_flag": True})
+        self.assertIn('vocab', report['data_stats']['statistics'])
+        self.assertIn('words', report['data_stats']['statistics'])
+
     def test_save_and_load(self):
         data_folder = "dataprofiler/tests/data/"
         test_files = ["txt/code.txt", "txt/sentence-10x.txt"]