Add pagination and some other stuff

backend/app.py

@@ -1,13 +1,14 @@
 from flask import Flask, jsonify, request
 from elasticsearch_dsl import Search
 from elasticsearch_dsl.connections import connections
+from elasticsearch.exceptions import NotFoundError
 from tqdm import tqdm
 from beeprint import pp
 import csv
 import click
+import requests
 
 from .question import Question
-from .question_search import QuestionSearch
 
 app = Flask(__name__)
 
@@ -22,23 +23,22 @@ def index():
 
     query = request.args.get("q")
     categories = request.args.get("categories", None)
+    page = int(request.args.get("page", 1)) - 1
 
-    facets = {}
-    if categories is not None:
-        category_list = categories.split(",")
-        facets["category"] = category_list
-
-    search = Search.from_dict({
+    search_dict = {
+        "from": page * 10,
         "query": {
-            "query_string": {
-                "query": query,
-            },
+            "bool": {
+                "must": [
+                    {"query_string": {"query": query}},
+                ]
+            }
         },
         "aggregations": {
             "category": {
                 "terms": {"field": "category"},
             },
-            "suggestions": {
+            "chips": {
                 "significant_terms": {
                     "field": "body",
                     "mutual_information": {
@@ -48,19 +48,25 @@ def index():
                 },
             }
         },
-    })
+    }
 
+    if categories is not None:
+        category_list = categories.split(",")
+        search_dict["post_filter"] = {
+            "terms": {"category": category_list},
+        }
+
+    search = Search.from_dict(search_dict)
     response = search.execute()
+    pp(response.to_dict())
 
-    #date_facets = [{"timestamp": date.timestamp(), "count": count}
-                   #for date, count, _ in response.facets.date_frequency]
     category_facets = [
         {"category": bucket.key, "count": round_sigfig(bucket.doc_count, 3)}
         for bucket in response.aggregations.category.buckets
     ]
 
-    suggestions = [{"key": bucket.key, "count": bucket.doc_count}
-                   for bucket in response.aggregations.suggestions.buckets]
+    chips = [{"key": bucket.key, "count": bucket.doc_count}
+             for bucket in response.aggregations.chips.buckets]
 
     date_facets = []
 
@@ -69,10 +75,15 @@ def index():
         summary = Question.summary(hit)
         url = Question.url(hit)
 
+        try:
+            dead = hit.dead
+        except AttributeError:
+            dead = False
+
         results.append({
             "id": hit.meta.id, "score": hit.meta.score, "title": hit.title,
             "body": summary, "category": hit.category, "date": hit.date,
-            "url": url,
+            "url": url, "dead": dead,
         })
 
     return jsonify(
@@ -80,7 +91,7 @@ def index():
             "months": date_facets,
             "categories": category_facets,
         },
-        suggestions=suggestions,
+        chips=chips,
         results=results,
         hits=round_sigfig(response.hits.total, 4),
         took=response.took / 1000,
@@ -90,7 +101,8 @@ def index():
 @app.cli.command()
 @click.argument("questions")
 @click.argument("categories")
-def import_data(questions, categories):
+@click.argument("answers")
+def import_data(questions, categories, answers):
     categories_dict = {}
     num_lines = sum(1 for line in open(categories))
     with open(categories, newline="") as csv_file:
@@ -101,23 +113,73 @@ def import_data(questions, categories):
 
             categories_dict[id_] = category
 
-    num_lines = sum(1 for line in open(questions))
-    with open(questions, newline="") as csv_file:
-        reader = csv.reader(csv_file)
+    if questions != "skip":
+        num_lines = sum(1 for line in open(questions))
+        with open(questions, newline="") as csv_file:
+            reader = csv.reader(csv_file)
 
-        it = tqdm(reader, desc="Reading questions", total=num_lines)
-        for i, row in enumerate(it):
-            try:
-                id_ = int(row[0])
-                category_id = int(row[3])
+            it = tqdm(reader, desc="Reading questions", total=num_lines)
+            for i, row in enumerate(it):
+                try:
+                    id_ = int(row[0])
+                    category_id = int(row[3])
 
-                question = Question(meta={"id": id_})
+                    question = Question(meta={"id": id_})
 
-                question.date = row[1]
-                question.category = categories_dict[category_id]
-                question.title = row[4]
-                question.body = "\n".join(row[5:])
+                    question.date = row[1]
+                    question.category = categories_dict[category_id]
+                    question.title = row[4]
+                    question.body = "\n".join(row[5:])
 
-                question.save()
-            except (IndexError, ValueError):
-                continue
+                    question.save()
+                except (IndexError, ValueError):
+                    continue
+
+    if answers != "skip":
+        with open(answers, newline="") as csv_file:
+            reader = csv.reader(csv_file)
+
+            it = tqdm(reader, desc="Reading answers")
+            for i, row in enumerate(it):
+                try:
+                    question_id = int(row[3])
+                    question = Question.get(id=question_id)
+                    if question.answers is None:
+                        question.answers = row[4]
+                    else:
+                        question.answers += "\n\n" + row[4]
+                    question.save()
+                except (IndexError, ValueError, NotFoundError):
+                    continue
+
+
+@app.cli.command()
+def cleanup_database():
+    dead_count = 0
+    alive_count = 0
+
+    for question in Question.search().scan():
+        if question.dead is not None or question.error:
+            print(end="_")
+            dead_count += 1
+            continue
+
+        url = question.url()
+        response = requests.head(url)
+
+        if response.status_code == 404:
+            dead_count += 1
+            question.dead = True
+            question.save()
+            print(end=".")
+        elif response.status_code == 302:
+            alive_count += 1
+            question.dead = False
+            print(end="#")
+        elif response.status_code == 500:
+            question.error = True
+            print(end="!")
+        else:
+            continue
+
+        question.save()

backend/question.py

@@ -1,4 +1,4 @@
-from elasticsearch_dsl import Document, Date, Keyword, Text
+from elasticsearch_dsl import Document, Date, Keyword, Text, Boolean
 
 
 class Question(Document):
@@ -9,6 +9,10 @@ class Question(Document):
     )
     category = Keyword()
     date = Date()
+    answers = Text(analyzer="snowball")
+
+    dead = Boolean()
+    error = Boolean()
 
     class Index:
         name = "goeievraag"

backend/question_search.py

@@ -1,12 +0,0 @@
-from elasticsearch_dsl import FacetedSearch, TermsFacet, DateHistogramFacet
-from .question import Question
-
-
-class QuestionSearch(FacetedSearch):
-    doc_types = Question,
-    fields = "title", "body"
-
-    facets = {
-        "date_frequency": DateHistogramFacet(field="date", interval="month"),
-        "category": TermsFacet(field="category"),
-    }

backend/requirements.txt

@@ -2,3 +2,4 @@ elasticsearch-dsl
 flask
 tqdm
 beeprint
+requests

frontend/src/components/ResultBody.vue

@@ -1,9 +1,8 @@
 <template>
 <div class="body">
-  <div class="suggestions">
-    <div v-for="suggestion in json.suggestions" class="suggestion"
-         @click="appendToQuery(suggestion.key)">
-      {{suggestion.key}}
+  <div class="chips">
+    <div v-for="chip in chips" class="chip" @click="appendToQuery(chip.key)">
+      {{chip.key}}
     </div>
   </div>
 
@@ -26,7 +25,10 @@
     <div class="body__results">
       <div v-for="result in results" v-bind:key="result.id" class="result">
         <a :href="result.url" target="_blank">
-          <div class="result__title">{{result.title}}</div>
+          <div class="result__title">
+            {{result.title}}
+            <span v-if="result.dead">(404)</span>
+          </div>
           <div class="result__link">
             {{result.url}} &bullet; {{result.category}} &bullet; {{result.score.toFixed(3)}}
           </div>
@@ -36,9 +38,26 @@
           </div>
         </a>
       </div>
-    </div>
 
-    <!--pre>{{JSON.stringify(json, null, 2)}}</pre-->
+      <div class="pagination">
+        <div class="pagination__page">
+          <img src="@/assets/pages_start.png" />
+        </div>
+
+        <div v-for="page in pages" class="pagination__page"
+             v-if="page > currentPage - 5 && page < currentPage + 5"
+             v-bind:class="{active: page === currentPage}" @click="switchPage(page)">
+          <img v-if="page === currentPage" src="@/assets/pages_active.png" />
+          <img v-else src="@/assets/pages_inactive.png" />
+
+          {{page}}
+        </div>
+
+        <div class="pagination__page">
+          <img src="@/assets/pages_end.png" />
+        </div>
+      </div>
+    </div>
   </div>
 </div>
 </template>
@@ -57,6 +76,13 @@ export default class ResultBody extends Vue {
   results = [];
   responseTime = 0;
   facets = {};
+  chips = [];
+
+  currentPage = 1;
+
+  get pages() {
+    return Math.ceil(this.hits / 10);
+  }
 
   @Watch("value")
   async onQueryChanged(value) {
@@ -83,7 +109,7 @@ export default class ResultBody extends Vue {
 
   async search() {
     const query = encodeURIComponent(this.value);
-    let queryString = `?q=${query}`;
+    let queryString = `?q=${query}&page=${this.currentPage}`;
 
     if (this.activeCategories.length > 0) {
       const categories = encodeURIComponent(this.activeCategories.join(","));
@@ -96,15 +122,21 @@ export default class ResultBody extends Vue {
     let response = await fetch(url);
     this.json = await response.json();
 
-    this.results = this.json.results;
+    this.chips = this.json.chips;
+    this.facets = this.json.facets;
     this.hits = this.json.hits;
     this.responseTime = this.json.took;
-    this.facets = this.json.facets;
+    this.results = this.json.results;
   }
 
   appendToQuery(value) {
     this.$emit("input", `${this.value} AND ${value}`)
   }
+
+  async switchPage(page) {
+    this.currentPage = page;
+    await this.search();
+  }
 }
 </script>
 
@@ -191,7 +223,7 @@ export default class ResultBody extends Vue {
     text-align: right;
 }
 
-.suggestions {
+.chips {
     display: flex;
     flex-flow: row wrap;
     max-width: 1000px;
@@ -201,7 +233,7 @@ export default class ResultBody extends Vue {
     overflow-y: hidden;
 }
 
-.suggestion {
+.chip {
     border: 1px solid rgba(0, 0, 0, 0.2);
     border-radius: 12px;
 
@@ -210,5 +242,29 @@ export default class ResultBody extends Vue {
     margin: 2px;
 
     cursor: pointer;
+    height: 32px;
+}
+
+.pagination {
+    display: flex;
+    margin: 0 0 16px;
+}
+
+.pagination__page {
+    height: 50px;
+    text-align: center;
+    display: flex;
+    flex-flow: column;
+}
+
+.pagination img {
+    height: 40px;
+    margin: 0 1px;
+}
+
+.pagination__page:not(.active) {
+    text-decoration: underline;
+    color: blue;
+    cursor: pointer;
 }
 </style>