Merge pull request #6192 from dojutsu-user/remove-pie-chart

Remove pie-chart from search analytics page

Author: ericholscher

readthedocs/projects/views/private.py

@@ -947,12 +947,6 @@ def search_analytics_view(request, project_slug):
     query_count_of_1_month = SearchQuery.generate_queries_count_of_one_month(
         project_slug
     )
-    # data for plotting the doughnut-chart
-    distribution_of_top_queries = SearchQuery.generate_distribution_of_top_queries(
-        project_slug,
-        10,
-    )
-    now = timezone.now()
 
     queries = []
     qs = SearchQuery.objects.filter(project=project)
@@ -975,7 +969,6 @@ def search_analytics_view(request, project_slug):
             'queries': queries,
             'show_analytics': True,
             'query_count_of_1_month': query_count_of_1_month,
-            'distribution_of_top_queries': distribution_of_top_queries,
         }
     )
 

readthedocs/rtd_tests/tests/test_views.py

@@ -304,23 +304,6 @@ def test_top_queries(self):
                 list(resp.context['queries']),
             )
 
-    def test_distribution_of_top_queries(self):
-        with mock.patch('django.utils.timezone.now') as test_time:
-            test_time.return_value = self.test_time
-
-            expected_result = {
-                'labels': ['hello world', 'documentation', 'read the docs', 'advertising',
-                            'elasticsearch', 'sphinx', 'github', 'hello', 'search'],
-                'int_data': [5, 4, 4, 3, 2, 2, 1, 1, 1],
-            }
-            resp = self.client.get(self.analyics_page, {'version': self.version.slug})
-
-            self.assertEqual(resp.status_code, 200)
-            self.assertDictEqual(
-                expected_result,
-                resp.context['distribution_of_top_queries'],
-            )
-
     def test_query_count_of_1_month(self):
         with mock.patch('django.utils.timezone.now') as test_time:
             test_time.return_value = self.test_time

readthedocs/search/models.py

@@ -92,48 +92,3 @@ def generate_queries_count_of_one_month(cls, project_slug):
         }
 
         return final_data
-
-    @classmethod
-    def generate_distribution_of_top_queries(cls, project_slug, n):
-        """
-        Returns top `n` most searched queries with their count.
-
-        Structure of returned data is compatible to make graphs.
-        Sample returned data::
-            {
-                'labels': ['read the docs', 'documentation', 'sphinx'],
-                'int_data': [150, 200, 143]
-            }
-        This data shows that `read the docs` was searched 150 times,
-        `documentation` was searched 200 times and `sphinx` was searched 143 times.
-        """
-        qs = cls.objects.filter(project__slug=project_slug)
-
-        # total searches ever made
-        total_count = len(qs)
-
-        # search queries with their count
-        # Eg. [('read the docs', 150), ('documentation', 200), ('sphinx', 143')]
-        count_of_each_query = (
-            qs.values('query')
-            .annotate(count=Count('id'))
-            .order_by('-count')
-            .values_list('query', 'count')
-        )
-
-        # total number of searches made for top `n` queries
-        count_of_top_n = sum([value[1] for value in count_of_each_query][:n])
-
-        # total number of remaining searches
-        count_of_other = total_count - count_of_top_n
-
-        final_data = {
-            'labels': [value[0] for value in count_of_each_query][:n],
-            'int_data': [value[1] for value in count_of_each_query][:n],
-        }
-
-        if count_of_other:
-            final_data['labels'].append('Other queries')
-            final_data['int_data'].append(count_of_other)
-
-        return final_data

readthedocs/templates/projects/projects_search_analytics.html

@@ -35,13 +35,6 @@ <h3>{% trans "Top queries" %}</h3>
       </div>
     </div>
 
-    <br/>
-
-    {% if distribution_of_top_queries.labels and distribution_of_top_queries.int_data %}
-      <h2>{% trans "Distribution of top 10 queries" %}</h2>
-      <canvas id="analytics-doughnut-top-queries" width="400" height="150"></canvas>
-    {% endif %}
-
     <br/>
     {% if query_count_of_1_month.labels and query_count_of_1_month.int_data %}
       <h2>{% trans "Overview of the past 1 month:" %}</h2>
@@ -83,16 +76,6 @@ <h2>{% trans "Overview of the past 1 month:" %}</h2>
     var line_chart_labels = {{ query_count_of_1_month.labels|safe }};
     var line_chart_data = {{ query_count_of_1_month.int_data|safe }};
 
-    var ticks_options = {
-      precision: 0
-    }
-
-    // checks if line_chart_data only contains zero.
-    // if yes, set the minimum value to zero
-    if(!(/[^0]/).exec(line_chart_data.join(""))){
-      ticks_options.min = 0;
-    }
-
     var line_chart = new Chart(line_chart, {
       type: "line",
       data: {
@@ -104,56 +87,7 @@ <h2>{% trans "Overview of the past 1 month:" %}</h2>
           borderColor: "rgba(75, 192, 192, 1)",
           pointBorderColor: "rgba(75, 192, 192, 1)",
         }]
-      },
-      options: {
-        scales: {
-          yAxes: [{
-            ticks: ticks_options
-          }]
-        }
       }
     });
   {% endif %}
-
-  {% if distribution_of_top_queries.labels and distribution_of_top_queries.int_data and show_analytics %}
-    // Doughnut chart
-    var doughnut_chart = document.getElementById("analytics-doughnut-top-queries").getContext("2d");
-    var doughnut_labels = {{ distribution_of_top_queries.labels|safe }};
-    var doughnut_data = {{ distribution_of_top_queries.int_data|safe }};
-    colors = [ "#81ecec", "#74b9ff", "#a29bfe", "#ffeaa7", "#ff7675",
-                "#fdcb6e", "#636e72", "#e17055", "#e84393", "#00cec9" ];
-    var doughnut_chart = new Chart(doughnut_chart, {
-      type: "doughnut",
-      data: {
-        labels: doughnut_labels,
-        datasets: [{
-          data: doughnut_data,
-          backgroundColor: colors,
-        }],
-        borderAlign: "center",
-      },
-      options: {
-        responsive: true,
-        legend: {
-          position: "right",
-        },
-        tooltips: {
-          callbacks: {
-            label: function(tooltipItem, data) {
-              var dataset = data.datasets[tooltipItem.datasetIndex];
-              var meta = dataset._meta[Object.keys(dataset._meta)[0]];
-              var total = meta.total;
-              var currentValue = dataset.data[tooltipItem.index];
-              var percentage = parseFloat((currentValue/total*100).toFixed(1));
-              return percentage + '%';
-            },
-            title: function(tooltipItem, data) {
-              return data.labels[tooltipItem[0].index];
-            }
-          }
-        }
-      }
-    });
-  {% endif %}
-
 {% endblock %}