Python操作MongoDB文档数据库

thunderstorm

2020-03-08

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()