1 先下載wikipedia

$wget https://dumps.wikimedia.org/enwiki/latest/enwiki-latest-pages-articles.xml.bz2

2 利用wikiextractor將其提取出來

$git clone https://github.com/attardi/wikiextractor $python wikiextractor/WikiExtractor.py INPUT_FILE -o OUTPUT_PATH --json

3 將wikidedia的數據進行清洗，具體做法如下

首先用下面的代碼去除doc和空格，只保留文本

def deal_enwiki(read_path, write_path): # 去掉doc和空格，只保留文本regex_str = "[^<doc.*>$]|[^</doc>$]"file = open(read_path, "r", encoding="utf-8")output = open(write_path, "w+", encoding="utf-8")content_line = file.readline()article_contents = ""while content_line:match_obj = re.match(regex_str, content_line)if content_line.isspace():content_line = file.readline()continueelse:content_line = content_line.strip("\n")if len(content_line) > 0:if match_obj:article_contents += content_line + " "else:if len(article_contents) > 0:output.write(article_contents + "\n")article_contents = ""# output.write(content_line+"\n")content_line = file.readline()file.close()output.close() def generate_corpus():wiki_path = "/Wiki_processing/wikiextractor/extracted/AA"save_path = "/Wiki_processing/wikiextractor/extracted/AA"for i in range(14):if i < 10:file_path = os.path.join(wiki_path, str("wiki_0%s" % str(i)))else:file_path = os.path.join(wiki_path, str("wiki_%s" % str(i)))deal_enwiki(file_path, os.path.join(save_path, "wiki_corpus%s" % str(i)))print("Finish "+str(i)+" files generate")

將所有的句子變成一個文件,生成wiki_corpus_not_divide

def merge_corpus(): # 合并corpusoutput = open("/Wiki_processing/wikiextractor/extracted/AA/wiki_corpus_not_divide", "w", encoding="utf-8")input = "/Wiki_processing/wikiextractor/extracted/AA"for i in range(14):file_path = os.path.join(input, str("wiki_corpus%s" % str(i)))file = open(file_path, "r", encoding="utf-8")line = file.readline()while line:output.writelines(line)line = file.readline()file.close()print("Finish " + str(i) + " files merge")output.close()

將wiki_corpus_not_divide里面的文件變成一句話一行

def divide_sentence(read_path, write_path): # 把句子分開punkt_param = PunktParameters()abbreviation = ['i.e', 'e.g', "U.S"]punkt_param.abbrev_types = set(abbreviation)tokenizer = PunktSentenceTokenizer(punkt_param)file = open(read_path, "r", encoding="utf-8")output = open(write_path, "w+", encoding="utf-8")content_line = file.readline()while content_line:sentence_list = tokenizer.tokenize(content_line)for sentence in sentence_list:output.write(sentence + "\n")print("finish divide")content_line = file.readline()file.close()output.close() if __name__ == "__main__":# generate_corpus()# print("generate_corpus is finishing")# merge_corpus()# print("merge_corpus is finishing")divide_sentence("/Wiki_processing/wikiextractor/extracted/AA/wiki_corpus_not_divide","/Wiki_processing/wikiextractor/extracted/AA/wiki_corpus")

4 利用Elasticsearch進行檢索

進入elasticsearch安裝包里

$cd elasticsearch-5.0.0/ $./bin/elasticsearch -d

打開另外一個終端進行測試

$curl 'localhost:9200/_cat/health?v'

如果status為green,則說明為好的

創建索引 mainCreateIndex

def deleteInices(my_index):if True and es.indices.exists(my_index): # 確認刪除再改為Trueprint("delete is complete")es.indices.delete(index=my_index)def createIndex(my_index, my_doc):# index settingssettings = \{"mappings": {my_doc: {"properties": {"my_id": {"type": "integer"},"my_word": {"type": "text"}}}}}# create indexes.indices.create(index=my_index, ignore=400, body=settings)print("creating index is succeed!") if __name__ == "__main__":mainCreateIndex()

運行完上面的.py文件之后，打開終端進行查看，是否創建成功索引

$curl 'localhost:9200/_cat/indices?v'

上述，出現index，就說明索引創建成功了

插入wikipedia的文本數據 mainInsert

def insertData(words, my_index, my_doc, one_bulk):# 插入數據# one_bulk表示一個bulk里裝多少個body = []body_count = 0 # 記錄body里面有多少個.# 最后一個bulk可能沒滿one_bulk,但也要插入print("need to insert %d" % len(words))pbar = tqdm(total=len(words))for id, word in words:data1 = {"my_id": id, # id"my_word": word} # textevery_body = \{"_index": my_index, # 索引文件名"_type": my_doc, # 數據文件名"_source": data1 # 文檔正文}if body_count < one_bulk:body.append(every_body)body_count += 1else:helpers.bulk(es, body) # 還是要用bulk啊，不然太慢了pbar.update(one_bulk)body_count = 0body = []body.append(every_body)body_count += 1if len(body) > 0:# 如果body里面還有，則再插入一次（最后非整塊的）helpers.bulk(es, body)# pbar.update(len(body))print('done2')pbar.close()# res = es.index(index=my_index,doc_type=my_doc,id=my_key_id,body=data1) #一條插入print("insert data completed!")def mainInsert():# 調用后插入數據my_index = "my_index"my_doc = "my_doc"words = getAllWords(path="/Wiki_processing/wikiextractor/extracted/AA/wikipedia_sentences.txt")insertData(words, my_index, my_doc, one_bulk=5000)if __name__ == "__main__":mainInsert()

運行完上面的.py文件之后，打開終端進行查看，可以通過查看store.size的大小來驗證是否成功插入數據

$curl 'localhost:9200/_cat/indices?v'

可以看到store.size的大小明顯發生了變化，說明成功插入數據

用自己的數據進行檢索 mainSearch

def mainSearch():# 調用后檢索數據my_index = "my_index"my_doc = "my_doc"keywords1 = "Vaccinations needed come Doha"keywordSearch(keywords1, my_index, my_doc)if __name__ == "__main__":mainSearch()

以上就是如果用python針對ES進行檢索的詳細步驟。如有疑惑，歡迎評論交流

總結

以上是生活随笔為你收集整理的python使用Elasticsearch对wikipedia的数据进行检索（详细流程）的全部內容，希望文章能夠幫你解決所遇到的問題。

如果覺得生活随笔網站內容還不錯，歡迎將生活随笔推薦給好友。