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
MultiPolygonField5.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；
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原作者 https://www.cnblogs.com/wefeng/p/11503102.html