Python操作MongoDB文档数据库

任大宝儿 發表於 2019-9-10 21:34:00

<h4>1.Pymongo 安装</h4>
<pre class="hljs sql"><code>安装pymongo：

pip install pymongo</code></pre>
<ul>
<li>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；</li>
</ul>
<h4>2.Pymongo 方法</h4>
<ul>
<li><code>insert_one()</code>：插入一条记录；</li>
<li><code>insert()</code>：插入多条记录；</li>
<li><code>find_one()</code>：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；</li>
<li><code>find()</code>：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；</li>
<li><code>count()</code>：查看记录总数；</li>
<li><code>create_index()</code>：创建索引；</li>
<li><code>update_one()</code>：更新匹配到的第一条数据；</li>
<li><code>update()</code>：更新匹配到的所有数据；</li>
<li><code>remove()</code>：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；</li>
<li><code>delete_one()</code>：删除单条记录；</li>
<li><code>delete_many()</code>：删除多条记录；</li>
</ul>
<h4>3.Pymongo 中的操作</h4>
<ul>
<li>查看数据库</li>
</ul>
<pre class="hljs lisp"><code>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())</code></pre>
<ul>
<li>获取数据库实例</li>
</ul>
<pre class="hljs ini"><code>test_db = connect['test']</code></pre>
<ul>
<li>获取collection实例</li>
</ul>
<pre class="hljs ini"><code>collection = test_db['students']</code></pre>
<ul>
<li>插入一行document, 查询一行document，取出一行document的值</li>
</ul>
<pre class="hljs coffeescript"><code>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')})</code></pre>
<ul>
<li>插入多行documents, 查询多行document，查看collections有多少行document</li>
</ul>
<pre class="hljs coffeescript"><code>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)</code></pre>
<ul>
<li>范围比较查询</li>
</ul>
<pre class="hljs coffeescript"><code>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)</code></pre>
<ul>
<li>创建索引</li>
</ul>
<pre class="hljs python"><code>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)</code></pre>
<ul>
<li>document修改</li>
</ul>
<pre class="hljs perl"><code>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</code></pre>
<ul>
<li>document删除</li>
</ul>
<pre class="hljs perl"><code>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</code></pre>
<h4>4.MongoDB ODM 详解</h4>
<ul>
<li>MongoDB ODM 与 Django ORM使用方法类似；</li>
<li>MongoEngine是一个对象文档映射器，用Python编写，用于处理MongoDB；</li>
<li>MongoEngine提供的抽象是基于类的，创建的所有模型都是类；</li>
</ul>
<pre class="hljs sql"><code># 安装mongoengine
pip install mongoengine</code></pre>
<ul>
<li>mongoengine使用的字段类型</li>
</ul>
<pre class="hljs groovy"><code>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</code></pre>
<h4>5.使用mongoengine创建数据库连接</h4>
<pre class="hljs lisp"><code>from mongoengine import connect

conn = connect(db='test', host='localhost', port=27017, username='root', password='123456', authentication_source='admin')
print(conn)</code></pre>
<code>connect（db = None，alias ='default'，** kwargs ）；</code>
<ul>
<li><code>db</code>：要使用的数据库的名称，以便与connect兼容；</li>
<li><code>host</code> ：要连接的mongod实例的主机名；</li>
<li><code>port</code> ：运行mongod实例的端口；</li>
<li><code>username</code>：用于进行身份验证的用户名；</li>
<li><code>password</code>：用于进行身份验证的密码；</li>
<li><code>authentication_source</code> ：要进行身份验证的数据库；</li>
</ul>
构建文档模型，插入数据
<pre class="hljs haskell"><code>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=)
 students.save()</code></pre>
查询数据
<pre class="hljs python"><code>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)</code></pre>
修改、更新、删除数据
<pre class="hljs haskell"><code>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()</code></pre>
<ul>
<li><code>all()</code>：返回所有文档；</li>
<li><code>all_fields()</code>：包括所有字段；</li>
<li><code>as_pymongo()</code>：返回的不是Document实例而是pymongo值；</li>
<li><code>average()</code>：平均值超过指定字段的值；</li>
<li><code>batch_size()</code>：限制单个批次中返回的文档数量；</li>
<li><code>clone()</code>：创建当前查询集的副本；</li>
<li><code>comment()</code>：在查询中添加注释；</li>
<li><code>count()</code>：计算查询中的选定元素；</li>
<li><code>create()</code>：创建新对象，返回保存的对象实例；</li>
<li><code>delete()</code>：删除查询匹配的文档；</li>
<li><code>distinct()</code>：返回给定字段的不同值列表；</li>
</ul>
<h4>嵌入式文档查询的方法</h4>
<ul>
<li><code>count()</code>：列表中嵌入文档的数量，列表的长度；</li>
<li><code>create()</code>：创建新的嵌入式文档并将其保存到数据库中；</li>
<li><code>delete()</code>：从数据库中删除嵌入的文档；</li>
<li><code>exclude(** kwargs )</code>：通过使用给定的关键字参数排除嵌入的文档来过滤列表；</li>
<li><code>first()</code>：返回列表中的第一个嵌入文档；</li>
<li><code>get()</code>：检索由给定关键字参数确定的嵌入文档；</li>
<li><code>save()</code>：保存祖先文档；</li>
<li><code>update()</code>：使用给定的替换值更新嵌入的文档；</li>
</ul> 
来源：https://www.cnblogs.com/wefeng/p/11503102.html

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Python操作MongoDB文档数据库