Python操作MongoDB文档数据库_ITPUB博客

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* `find_one()`：查询一条记录，不带任何参数返回第一条记录，带参数则按条件查找返回； * `find()`：查询多条记录，不带参数返回所有记录，带参数按条件查找返回； * `count()`：查看记录总数； * `create_index()`：创建索引； * `update_one()`：更新匹配到的第一条数据； * `update()`：更新匹配到的所有数据； * `remove()`：删除记录，不带参表示删除全部记录，带参则表示按条件删除； * `delete_one()`：删除单条记录； * `delete_many()`：删除多条记录； #### 3.Pymongo 中的操作 * 查看数据库 from pymongo import MongoClient connect = MongoClient(host='localhost', port=27017, username="root", password="123456") connect = MongoClient('mongodb://localhost:27017/', username="root", password="123456") print(connect.list_database_names()) * 获取数据库实例 test_db = connect['test'] * 获取collection实例 collection = test_db['students'] * 插入一行document, 查询一行document，取出一行document的值 from pymongo import MongoClient from datetime import datetime connect = MongoClient(host='localhost', port=27017, username="root", password="123456",) # 获取db test_db = connect['test'] # 获取collection collection = test_db['students'] # 构建document document = {"author": "Mike", "text": "My first blog post!", "tags": ["mongodb", "python", "pymongo"], "date": datetime.now()} # 插入document one_insert = collection.insert_one(document=document) print(one_insert.inserted_id) # 通过条件过滤出一条document one_result = collection.find_one({"author": "Mike"}) # 解析document字段 print(one_result, type(one_result)) print(one_result['_id']) print(one_result['author']) 注意：如果需要通过id查询一行document，需要将id包装为ObjectId类的实例对象 from bson.objectid import ObjectId collection.find_one({'_id': ObjectId('5c2b18dedea5818bbd73b94c')}) * 插入多行documents, 查询多行document，查看collections有多少行document from pymongo import MongoClient from datetime import datetime connect = MongoClient(host='localhost', port=27017, username="root", password="123456",) # 获取db test_db = connect['test'] # 获取collection collection = test_db['students'] documents = [{"author": "Mike","text": "Another post!","tags": ["bulk", "insert"], "date": datetime(2009, 11, 12, 11, 14)}, {"author": "Eliot", "title": "MongoDB is fun", "text": "and pretty easy too!", "date": datetime(2009, 11, 10, 10, 45)}] collection.insert_many(documents=documents) # 通过条件过滤出多条document documents = collection.find({"author": "Mike"}) # 解析document字段 print(documents, type(documents)) print('*'*300) for document in documents: print(document) print('*'*300) result = collection.count_documents({'author': 'Mike'}) print(result) * 范围比较查询 from pymongo import MongoClient from datetime import datetime connect = MongoClient(host='localhost', port=27017, username="root", password="123456",) # 获取db test_db = connect['test'] # 获取collection collection = test_db['students'] # 通过条件过滤时间小于datetime(2019, 1,1,15,40,3) 的document documents = collection.find({"date": {"$lt": datetime(2019, 1,1,15,40,3)}}).sort('date') # 解析document字段 print(documents, type(documents)) print('*'*300) for document in documents: print(document) * 创建索引 from pymongo import MongoClient import pymongo from datetime import datetime connect = MongoClient(host='localhost', port=27017, username="root", password="123456",) # 获取db test_db = connect['test'] # 获取collection collection = test_db['students'] # 创建字段索引 collection.create_index(keys=[("name", pymongo.DESCENDING)], unique=True) # 查询索引 result = sorted(list(collection.index_information())) print(result) * document修改 from pymongo import MongoClient connect = MongoClient(host='localhost', port=27017, username="root", password="123456",) # 获取db test_db = connect['test'] # 获取collection collection = test_db['students'] result = collection.update({'name': 'robby'}, {'$set': {"name": "Petter"}}) print(result) 注意：还有update_many()方法 * document删除 from pymongo import MongoClient connect = MongoClient(host='localhost', port=27017, username="root", password="123456",) # 获取db test_db = connect['test'] # 获取collection collection = test_db['students'] result = collection.delete_one({'name': 'Petter'}) print(result.deleted_count) 注意：还有delete_many()方法 #### 4.MongoDB ODM 详解 * MongoDB ODM 与 Django ORM使用方法类似； * MongoEngine是一个对象文档映射器，用Python编写，用于处理MongoDB； * MongoEngine提供的抽象是基于类的，创建的所有模型都是类； # 安装mongoengine pip install mongoengine * mongoengine使用的字段类型 BinaryField BooleanField ComplexDateTimeField DateTimeField DecimalField DictField DynamicField EmailField EmbeddedDocumentField EmbeddedDocumentListField FileField FloatField GenericEmbeddedDocumentField GenericReferenceField GenericLazyReferenceField GeoPointField ImageField IntField ListField:可以将自定义的文档类型嵌套 MapField ObjectIdField ReferenceField LazyReferenceField SequenceField SortedListField StringField URLField UUIDField PointField LineStringField PolygonField MultiPointField MultiLineStringField MultiPolygonField #### 5.使用mongoengine创建数据库连接 from mongoengine import connect conn = connect(db='test', host='localhost', port=27017, username='root', password='123456', authentication_source='admin') print(conn) `connect（db = None，alias ='default'，** kwargs ）；` * `db`：要使用的数据库的名称，以便与connect兼容； * `host` ：要连接的mongod实例的主机名； * `port` ：运行mongod实例的端口； * `username`：用于进行身份验证的用户名； * `password`：用于进行身份验证的密码； * `authentication_source` ：要进行身份验证的数据库； **构建文档模型，插入数据** from mongoengine import connect, \ Document, \ StringField,\ IntField, \ FloatField,\ ListField, \ EmbeddedDocumentField,\ DateTimeField, \ EmbeddedDocument from datetime import datetime # 嵌套文档 class Score(EmbeddedDocument): name = StringField(max_length=50, required=True) value = FloatField(required=True) class Students(Document): choice = (('F', 'female'), ('M', 'male'),) name = StringField(max_length=100, required=True, unique=True) age = IntField(required=True) hobby = StringField(max_length=100, required=True, ) gender = StringField(choices=choice, required=True) # 这里使用到了嵌套文档，这个列表中的每一个元素都是一个字典，因此使用嵌套类型的字段 score = ListField(EmbeddedDocumentField(Score)) time = DateTimeField(default=datetime.now()) if __name__ == '__main__': connect(db='test', host='localhost', port=27017, username='root', password='123456', authentication_source='admin') math_score = Score(name='math', value=94) chinese_score = Score(name='chinese', value=100) python_score = Score(name='python', value=99) for i in range(10): students = Students(name='robby{}'.format(i), age=int('{}'.format(i)), hobby='read', gender='M', score=[math_score, chinese_score, python_score]) students.save() **查询数据** from mongoengine import connect, \ Document, \ StringField,\ IntField, \ FloatField,\ ListField, \ EmbeddedDocumentField,\ DateTimeField, \ EmbeddedDocument from datetime import datetime # 嵌套文档 class Score(EmbeddedDocument): name = StringField(max_length=50, required=True) value = FloatField(required=True) class Students(Document): choice = (('F', 'female'), ('M', 'male'),) name = StringField(max_length=100, required=True, unique=True) age = IntField(required=True) hobby = StringField(max_length=100, required=True, ) gender = StringField(choices=choice, required=True) # 这里使用到了嵌套文档，这个列表中的每一个元素都是一个字典，因此使用嵌套类型的字段 score = ListField(EmbeddedDocumentField(Score)) time = DateTimeField(default=datetime.now()) if __name__ == '__main__': connect(db='test', host='localhost', port=27017, username='root', password='123456', authentication_source='admin') first_document = Students.objects.first() all_document = Students.objects.all() # 如果只有一条，也可以使用get specific_document = Students.objects.filter(name='robby3') print(first_document.name, first_document.age, first_document.time) for document in all_document: print(document.name) for document in specific_document: print(document.name, document.age) **修改、更新、删除数据** from mongoengine import connect, \ Document, \ StringField,\ IntField, \ FloatField,\ ListField, \ EmbeddedDocumentField,\ DateTimeField, \ EmbeddedDocument from datetime import datetime # 嵌套文档 class Score(EmbeddedDocument): name = StringField(max_length=50, required=True) value = FloatField(required=True) class Students(Document): choice = (('F', 'female'), ('M', 'male'),) name = StringField(max_length=100, required=True, unique=True) age = IntField(required=True) hobby = StringField(max_length=100, required=True, ) gender = StringField(choices=choice, required=True) # 这里使用到了嵌套文档，这个列表中的每一个元素都是一个字典，因此使用嵌套类型的字段 score = ListField(EmbeddedDocumentField(Score)) time = DateTimeField(default=datetime.now()) if __name__ == '__main__': connect(db='test', host='localhost', port=27017, username='root', password='123456', authentication_source='admin') specific_document = Students.objects.filter(name='robby3') specific_document.update(set__age=100) specific_document.update_one(set__age=100) for document in specific_document: document.name = 'ROBBY100' document.save() for document in specific_document: document.delete() * `all()`：返回所有文档； * `all_fields()`：包括所有字段； * `as_pymongo()`：返回的不是Document实例而是pymongo值； * `average()`：平均值超过指定字段的值； * `batch_size()`：限制单个批次中返回的文档数量； * `clone()`：创建当前查询集的副本； * `comment()`：在查询中添加注释； * `count()`：计算查询中的选定元素； * `create()`：创建新对象，返回保存的对象实例； * `delete()`：删除查询匹配的文档； * `distinct()`：返回给定字段的不同值列表； #### 嵌入式文档查询的方法 * `count()`：列表中嵌入文档的数量，列表的长度； * `create()`：创建新的嵌入式文档并将其保存到数据库中； * `delete()`：从数据库中删除嵌入的文档； * `exclude(** kwargs )`：通过使用给定的关键字参数排除嵌入的文档来过滤列表； * `first()`：返回列表中的第一个嵌入文档； * `get()`：检索由给定关键字参数确定的嵌入文档； * `save()`：保存祖先文档； * `update()`：使用给定的替换值更新嵌入的文档；参考：[https://www.9xkd.com/user/plan-view.html?id=2253255600](https://www.9xkd.com/user/plan-view.html?id=2253255600) 来自 “ ITPUB博客 ” ，链接：http://blog.itpub.net/69908432/viewspace-2643763/，如需转载，请注明出处，否则将追究法律责任。

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