python mongodb_Python操作MongoDB文档数据库

1.Pymongo 安装

安装pymongo：

pip install pymongo

PyMongo是驱动程序，使python程序能够使用Mongodb数据库，使用python编写而成；

2.Pymongo 方法

insert_one()：插入一条记录；

insert()：插入多条记录；

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；