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Commit a66215bd authored by 张彦钊's avatar 张彦钊
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es_tag.py
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...@@ -56,10 +56,383 @@ def es_query(doc, body, offset, size, es=None): ...@@ -56,10 +56,383 @@ def es_query(doc, body, offset, size, es=None):
from_=offset, from_=offset,
size=size) size=size)
number = res["hits"]["total"] number = res["hits"]["total"] or 0
return number return number
def answer():
tags = ["下颌角切除术", "M唇", "瘦身", "抽脂", "隆胸", "丰乳房", "孕睫术", "眶隔脂肪释放术", "小腿神经阻断术", '瘦脸针',
'水光针',
'光子嫩肤',
'热玛吉',
'瘦腿针',
'超声刀',
'面部吸脂',
'瘦肩针',
'皮秒',
'果酸焕肤',
'热拉提',
'微针',
'牙齿矫正',
'超皮秒',
'点阵激光',
'植发',
'小气泡',
'双眼皮修复',
'自体脂肪隆胸',
'鼻翼缩小',
'假体隆胸',
'玻尿酸丰下巴',
'埋线双眼皮',
'纹眉',
'颧骨内推',
'拉皮',
'玻尿酸隆鼻',
'女性私密紧致',
'嗨体',
'溶脂针瘦脸',
'黄金微针',
'磨骨',
'肋骨鼻',
'洗牙',
'植发际线',
'光纤溶脂',
'点痣',
'下颌角切除',
'切开双眼皮',
'腰腹吸脂',
'激光祛斑',
'白瓷娃娃',
'大腿吸脂',
'假体下巴',
'除皱针注射',
'溶解酶',
'吸脂瘦手臂',
'微针祛痘坑',
'厚唇改薄',
'玻尿酸',
'大分子玻尿酸',
'耳软骨',
'鼻中隔软骨',
'肋软骨',
'硅胶',
'膨体',
'假体',
'自体真皮',
'自体脂肪',
'自体软骨',
'自体血清',
'溶解酶',
'嗨体',
'胶原蛋白',
'双美胶原蛋白',
'黄金',
'药物',
'生长因子',
'肉毒素',
'埋线提升',
'悦升线',
'蛋白线',
'水杨酸',
'果酸',
'杏仁酸',
'奥美定',
'干细胞',
'纳米树脂',
'黑脸娃娃',
'眼睑下至',
'童颜针',
'微笑唇',
'减肥',
'瘦身',
'隆鼻',
'V脸',
'祛斑',
'祛痣',
'祛黑头',
'祛疤',
'祛痘',
'溶脂',
'吸脂',
'嘟嘟唇',
'丰唇',
'丰下巴',
'丰胸',
'皮秒',
'蜂巢皮秒',
'超皮秒',
'深蓝射频',
'美瞳',
'提眉',
'纹眉',
'孕睫',
'瓷贴面',
'全瓷牙',
'美容冠',
'黄金微雕',
'微雕',
'削骨',
'截骨',
'脂肪胶',
'prp',
'轮廓针',
'水光针',
'婴儿针',
'三文鱼针',
'少女针',
'素颜针',
'瘦脸针',
'熊猫针',
'瘦腿针',
'小气泡',
'正颌',
'一针降颧骨',
'脱毛',
'近视',
'面部提升',
'嫩肤',
'镭射净肤',
'红蓝光',
'二氧化碳点阵',
'狐臭',
'清洁',
'补水',
'内窥镜',
'热立塑',
'威塑',
'优立塑',
'酷塑',
'调Q激光',
'DPL',
'染料激光',
'体检',
'产后',
'正骨术',
'隔空溶脂',
'pst',
'唇裂',
'塑身',
'微晶瓷',
'ICL晶体植入',
'全飞秒',
'半飞秒',
'根管治疗',
'抗衰',
'紧致',
'飞梭雷射',
'三点双眼皮',
'颊脂垫',
'嫩红',
'眶隔脂肪释放',
'针清',
'美白',
'冷光美白',
'美白仓',
'小腿神经阻断',
'正畸',
'变性',
'干细胞疗法',
'月光脱毛',
'火凤凰溶脂',
'微拉美',
'剥落点阵',
'非剥落点阵']
total_list = []
query_operator = "and"
query_type = "cross_fields"
for i in tags:
tmp = [i]
query = i
star3_q = {
"query": {"filtered": {
"filter": {
"bool": {
"must": [{
"multi_match": {
"fields": ["title^1", "desc^1", "answer^1"],
"operator": query_operator,
"type": query_type,
"query": query
}
}, {
"term": {
"is_online": True
}
}, {"term": {
"content_level": 3
}
}]
}
}
}
}
}
tmp.append(es_query('answer', star3_q, 0, 1))
star4_q = {
"query": {
"filtered": {
"filter": {
"bool": {
"must": [{
"multi_match": {
"fields": ["title^1", "desc^1", "answer^1"],
"operator": query_operator,
"type": query_type,
"query": query
}
}, {
"term": {
"is_online": True
}
}, {"term": {
"content_level": 4
}
}]
}
}
}
}
}
tmp.append(es_query('answer', star4_q, 0, 1))
star5_q = {
"query": {
"filtered": {
"filter": {
"bool": {
"must": [{
"multi_match": {
"fields": ["title^1", "desc^1", "answer^1"],
"operator": query_operator,
"type": query_type,
"query": query
}
}, {
"term": {
"is_online": True
}
}, {"term": {
"content_level": 5
}
}]
}
}
}
}
}
tmp.append(es_query('answer', star5_q, 0, 1))
video_star3_q = {
"query": {
"filtered": {
"filter": {
"bool": {
"must": [{
"multi_match": {
"fields": ["title^1", "desc^1", "answer^1"],
"operator": query_operator,
"type": query_type,
"query": query
}
}, {
"term": {
"is_online": True
}
}, {
"term": {
"content_type": 1
}
}, {"term": {
"content_level": 3
}
}]
}
}
}
}
}
tmp.append(es_query('answer', video_star3_q, 0, 1))
video_star4_q = {
"query": {
"filtered": {
"filter": {
"bool": {
"must": [{
"multi_match": {
"fields": ["title^1", "desc^1", "answer^1"],
"operator": query_operator,
"type": query_type,
"query": query
}
}, {
"term": {
"is_online": True
}
}, {
"term": {
"content_type": 1
}
}, {"term": {
"content_level": 4
}
}]
}
}
}
}
}
tmp.append(es_query('answer', video_star4_q, 0, 1))
video_star5_q = {
"query": {
"filtered": {
"filter": {
"bool": {
"must": [{
"multi_match": {
"fields": ["title^1", "desc^1", "answer^1"],
"operator": query_operator,
"type": query_type,
"query": query
}
}, {
"term": {
"is_online": True
}
}, {
"term": {
"content_type": 1
}
}, {"term": {
"content_level": 5
}
}]
}
}
}
}
}
tmp.append(es_query('answer', video_star5_q, 0, 1))
total_list.append(tmp)
print(i)
print(tmp)
df = pd.DataFrame(total_list)
df = df.rename(columns={0: "tag", 1: "star_3", 2: "star_4", 3: "star_5",
4: "video_star_3", 5: "video_star_4", 6: "video_star_5"})
df.to_csv("/home/gmuser/answer.csv", index=False)
def question(): def question():
tags = ["下颌角切除术", "M唇", "瘦身", "抽脂", "隆胸", "丰乳房", "孕睫术", "眶隔脂肪释放术", "小腿神经阻断术", '瘦脸针', tags = ["下颌角切除术", "M唇", "瘦身", "抽脂", "隆胸", "丰乳房", "孕睫术", "眶隔脂肪释放术", "小腿神经阻断术", '瘦脸针',
'水光针', '水光针',
...@@ -240,10 +613,11 @@ def question(): ...@@ -240,10 +613,11 @@ def question():
total_list = [] total_list = []
query_operator = "and" query_operator = "and"
query_type = "cross_fields" query_type = "cross_fields"
category = 'question'
for i in tags: for i in tags:
tmp = [i] tmp = [i]
query = i query = i
# TODO 下面两个q语句
q = { q = {
"query": {"filtered": { "query": {"filtered": {
"filter": { "filter": {
...@@ -266,7 +640,7 @@ def question(): ...@@ -266,7 +640,7 @@ def question():
} }
} }
} }
tmp.append(es_query('answer', q, 0, 1)) tmp.append(es_query(category, q, 0, 1))
video_q = { video_q = {
"query": { "query": {
...@@ -295,7 +669,7 @@ def question(): ...@@ -295,7 +669,7 @@ def question():
} }
} }
} }
tmp.append(es_query('answer', video_q, 0, 1)) tmp.append(es_query(category, video_q, 0, 1))
total_list.append(tmp) total_list.append(tmp)
print(i) print(i)
...@@ -303,219 +677,220 @@ def question(): ...@@ -303,219 +677,220 @@ def question():
df = pd.DataFrame(total_list) df = pd.DataFrame(total_list)
df = df.rename(columns={0: "tag", 1: "number", 2: "video_number"}) df = df.rename(columns={0: "tag", 1: "number", 2: "video_number"})
df.to_csv("/home/gmuser/qa.csv", index=False) df.to_csv("/home/gmuser/question.csv", index=False)
if __name__ == "__main__": def topic():
tags = ["下颌角切除术","M唇","瘦身","抽脂","隆胸","丰乳房","孕睫术","眶隔脂肪释放术","小腿神经阻断术",'瘦脸针', tags = ["下颌角切除术", "M唇", "瘦身", "抽脂", "隆胸", "丰乳房", "孕睫术", "眶隔脂肪释放术", "小腿神经阻断术", '瘦脸针',
'水光针', '水光针',
'光子嫩肤', '光子嫩肤',
'热玛吉', '热玛吉',
'瘦腿针', '瘦腿针',
'超声刀', '超声刀',
'面部吸脂', '面部吸脂',
'瘦肩针', '瘦肩针',
'皮秒', '皮秒',
'果酸焕肤', '果酸焕肤',
'热拉提', '热拉提',
'微针', '微针',
'牙齿矫正', '牙齿矫正',
'超皮秒', '超皮秒',
'点阵激光', '点阵激光',
'植发', '植发',
'小气泡', '小气泡',
'双眼皮修复', '双眼皮修复',
'自体脂肪隆胸', '自体脂肪隆胸',
'鼻翼缩小', '鼻翼缩小',
'假体隆胸', '假体隆胸',
'玻尿酸丰下巴', '玻尿酸丰下巴',
'埋线双眼皮', '埋线双眼皮',
'纹眉', '纹眉',
'颧骨内推', '颧骨内推',
'拉皮', '拉皮',
'玻尿酸隆鼻', '玻尿酸隆鼻',
'女性私密紧致', '女性私密紧致',
'嗨体', '嗨体',
'溶脂针瘦脸', '溶脂针瘦脸',
'黄金微针', '黄金微针',
'磨骨', '磨骨',
'肋骨鼻', '肋骨鼻',
'洗牙', '洗牙',
'植发际线', '植发际线',
'光纤溶脂', '光纤溶脂',
'点痣', '点痣',
'下颌角切除', '下颌角切除',
'切开双眼皮', '切开双眼皮',
'腰腹吸脂', '腰腹吸脂',
'激光祛斑', '激光祛斑',
'白瓷娃娃', '白瓷娃娃',
'大腿吸脂', '大腿吸脂',
'假体下巴', '假体下巴',
'除皱针注射', '除皱针注射',
'溶解酶', '溶解酶',
'吸脂瘦手臂', '吸脂瘦手臂',
'微针祛痘坑', '微针祛痘坑',
'厚唇改薄', '厚唇改薄',
'玻尿酸', '玻尿酸',
'大分子玻尿酸', '大分子玻尿酸',
'耳软骨', '耳软骨',
'鼻中隔软骨', '鼻中隔软骨',
'肋软骨', '肋软骨',
'硅胶', '硅胶',
'膨体', '膨体',
'假体', '假体',
'自体真皮', '自体真皮',
'自体脂肪', '自体脂肪',
'自体软骨', '自体软骨',
'自体血清', '自体血清',
'溶解酶', '溶解酶',
'嗨体', '嗨体',
'胶原蛋白', '胶原蛋白',
'双美胶原蛋白', '双美胶原蛋白',
'黄金', '黄金',
'药物', '药物',
'生长因子', '生长因子',
'肉毒素', '肉毒素',
'埋线提升', '埋线提升',
'悦升线', '悦升线',
'蛋白线', '蛋白线',
'水杨酸', '水杨酸',
'果酸', '果酸',
'杏仁酸', '杏仁酸',
'奥美定', '奥美定',
'干细胞', '干细胞',
'纳米树脂', '纳米树脂',
'黑脸娃娃', '黑脸娃娃',
'眼睑下至', '眼睑下至',
'童颜针', '童颜针',
'微笑唇', '微笑唇',
'减肥', '减肥',
'瘦身', '瘦身',
'隆鼻', '隆鼻',
'V脸', 'V脸',
'祛斑', '祛斑',
'祛痣', '祛痣',
'祛黑头', '祛黑头',
'祛疤', '祛疤',
'祛痘', '祛痘',
'溶脂', '溶脂',
'吸脂', '吸脂',
'嘟嘟唇', '嘟嘟唇',
'丰唇', '丰唇',
'丰下巴', '丰下巴',
'丰胸', '丰胸',
'皮秒', '皮秒',
'蜂巢皮秒', '蜂巢皮秒',
'超皮秒', '超皮秒',
'深蓝射频', '深蓝射频',
'美瞳', '美瞳',
'提眉', '提眉',
'纹眉', '纹眉',
'孕睫', '孕睫',
'瓷贴面', '瓷贴面',
'全瓷牙', '全瓷牙',
'美容冠', '美容冠',
'黄金微雕', '黄金微雕',
'微雕', '微雕',
'削骨', '削骨',
'截骨', '截骨',
'脂肪胶', '脂肪胶',
'prp', 'prp',
'轮廓针', '轮廓针',
'水光针', '水光针',
'婴儿针', '婴儿针',
'三文鱼针', '三文鱼针',
'少女针', '少女针',
'素颜针', '素颜针',
'瘦脸针', '瘦脸针',
'熊猫针', '熊猫针',
'瘦腿针', '瘦腿针',
'小气泡', '小气泡',
'正颌', '正颌',
'一针降颧骨', '一针降颧骨',
'脱毛', '脱毛',
'近视', '近视',
'面部提升', '面部提升',
'嫩肤', '嫩肤',
'镭射净肤', '镭射净肤',
'红蓝光', '红蓝光',
'二氧化碳点阵', '二氧化碳点阵',
'狐臭', '狐臭',
'清洁', '清洁',
'补水', '补水',
'内窥镜', '内窥镜',
'热立塑', '热立塑',
'威塑', '威塑',
'优立塑', '优立塑',
'酷塑', '酷塑',
'调Q激光', '调Q激光',
'DPL', 'DPL',
'染料激光', '染料激光',
'体检', '体检',
'产后', '产后',
'正骨术', '正骨术',
'隔空溶脂', '隔空溶脂',
'pst', 'pst',
'唇裂', '唇裂',
'塑身', '塑身',
'微晶瓷', '微晶瓷',
'ICL晶体植入', 'ICL晶体植入',
'全飞秒', '全飞秒',
'半飞秒', '半飞秒',
'根管治疗', '根管治疗',
'抗衰', '抗衰',
'紧致', '紧致',
'飞梭雷射', '飞梭雷射',
'三点双眼皮', '三点双眼皮',
'颊脂垫', '颊脂垫',
'嫩红', '嫩红',
'眶隔脂肪释放', '眶隔脂肪释放',
'针清', '针清',
'美白', '美白',
'冷光美白', '冷光美白',
'美白仓', '美白仓',
'小腿神经阻断', '小腿神经阻断',
'正畸', '正畸',
'变性', '变性',
'干细胞疗法', '干细胞疗法',
'月光脱毛', '月光脱毛',
'火凤凰溶脂', '火凤凰溶脂',
'微拉美', '微拉美',
'剥落点阵', '剥落点阵',
'非剥落点阵'] '非剥落点阵']
total_list = [] total_list = []
query_operator = "and" query_operator = "and"
query_type = "cross_fields" query_type = "cross_fields"
category = 'tractate'
for i in tags: for i in tags:
tmp = [i] tmp = [i]
query = i query = i
star3_q = { star3_q = {
"query": {"filtered": { "query": {"filtered": {
"filter": { "filter": {
"bool": { "bool": {
"must": [{ "must": [{
"multi_match": { "multi_match": {
"fields": ["title^1", "desc^1", "answer^1"], "fields": ["title^1", "desc^1", "answer^1"],
"operator": query_operator, "operator": query_operator,
"type": query_type, "type": query_type,
"query": query "query": query
}
}, {
"term": {
"is_online": True
}
},{"term": {
"content_level": 3
}
}]
} }
}, {
"term": {
"is_online": True
}
}, {"term": {
"content_level": 3
} }
}]
} }
} }
} }
tmp.append(es_query('answer', star3_q, 0, 1)) }
}
tmp.append(es_query(category, star3_q, 0, 1))
star4_q = { star4_q = {
"query": { "query": {
...@@ -533,17 +908,17 @@ if __name__ == "__main__": ...@@ -533,17 +908,17 @@ if __name__ == "__main__":
"term": { "term": {
"is_online": True "is_online": True
} }
},{"term": { }, {"term": {
"content_level": 4 "content_level": 4
} }
}] }]
} }
} }
} }
} }
} }
tmp.append(es_query('answer', star4_q, 0, 1)) tmp.append(es_query(category, star4_q, 0, 1))
star5_q = { star5_q = {
"query": { "query": {
...@@ -561,17 +936,17 @@ if __name__ == "__main__": ...@@ -561,17 +936,17 @@ if __name__ == "__main__":
"term": { "term": {
"is_online": True "is_online": True
} }
},{"term": { }, {"term": {
"content_level": 5 "content_level": 5
} }
}] }]
} }
} }
} }
} }
} }
tmp.append(es_query('answer', star5_q, 0, 1)) tmp.append(es_query(category, star5_q, 0, 1))
video_star3_q = { video_star3_q = {
"query": { "query": {
...@@ -589,21 +964,21 @@ if __name__ == "__main__": ...@@ -589,21 +964,21 @@ if __name__ == "__main__":
"term": { "term": {
"is_online": True "is_online": True
} }
},{ }, {
"term": { "term": {
"content_type": 1 "is_video": True
} }
},{"term": { }, {"term": {
"content_level": 3 "content_level": 3
} }
}] }]
} }
} }
} }
} }
} }
tmp.append(es_query('answer', video_star3_q, 0, 1)) tmp.append(es_query(category, video_star3_q, 0, 1))
video_star4_q = { video_star4_q = {
"query": { "query": {
...@@ -621,21 +996,21 @@ if __name__ == "__main__": ...@@ -621,21 +996,21 @@ if __name__ == "__main__":
"term": { "term": {
"is_online": True "is_online": True
} }
},{ }, {
"term": { "term": {
"content_type": 1 "is_video": True
} }
},{"term": { }, {"term": {
"content_level": 4 "content_level": 4
} }
}] }]
} }
} }
} }
} }
} }
tmp.append(es_query('answer', video_star4_q, 0, 1)) tmp.append(es_query(category, video_star4_q, 0, 1))
video_star5_q = { video_star5_q = {
"query": { "query": {
...@@ -653,29 +1028,33 @@ if __name__ == "__main__": ...@@ -653,29 +1028,33 @@ if __name__ == "__main__":
"term": { "term": {
"is_online": True "is_online": True
} }
},{ }, {
"term": { "term": {
"content_type": 1 "is_video": True
} }
},{"term": { }, {"term": {
"content_level": 5 "content_level": 5
} }
}] }]
} }
} }
} }
} }
} }
tmp.append(es_query('answer', video_star5_q, 0, 1)) tmp.append(es_query(category, video_star5_q, 0, 1))
total_list.append(tmp) total_list.append(tmp)
print(i) print(i)
print(tmp) print(tmp)
df = pd.DataFrame(total_list) df = pd.DataFrame(total_list)
df = df.rename(columns={0:"tag",1: "star_3", 2: "star_4", 3:"star_5", df = df.rename(columns={0: "tag", 1: "star_3", 2: "star_4", 3: "star_5",
4:"video_star_3",5:"video_star_4",6:"video_star_5"}) 4: "video_star_3", 5: "video_star_4", 6: "video_star_5"})
df.to_csv("/home/gmuser/qa.csv",index = False) df.to_csv("/home/gmuser/topic.csv", index=False)
if __name__ == "__main__":
answer()
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