文档:http://api.mongodb.com/python/current/api/index.html
第一步当然是配置环境,启动数据库服务
mongodb的安装及简单使用-mac环境
引入模块
# -*- coding: utf-8 -*-
# @File : pymongo_demo.py
# @Date : 2018-06-02
# @Author : Peng Shiyu
import pymongo
1、创建MongoDB的连接对象
# client = pymongo.MongoClient(host="localhost", port=27017)
client = pymongo.MongoClient('mongodb://localhost:27017/')
2、指定数据库
# db = client["mydemo"]
db = client.mydemo
3、指定集合Collection对象
# collection = db["students"]
collection = db.students
4、插入数据
# 一条数据
student = {
'id': '20170101',
'name': '小明',
'age': 22,
'gender': '男性'
}
# result = collection.insert(student)
result = collection.insert_one(student)
print(result) #
print(result.inserted_id) # 5b1205b2d7696c4230dd9456
# 多条数据
student1 = {
'id': '20170101',
'name': 'Jordan',
'age': 20,
'gender': 'male'
}
student2 = {
'id': '20170202',
'name': 'Mike',
'age': 21,
'gender': 'male'
}
#
# # result = collection.insert([student1, student2])
result = collection.insert_many([student1, student2])
print(result) #
print(result.inserted_ids)
# # [ObjectId('5b1205b2d7696c4230dd9457'), ObjectId('5b1205b2d7696c4230dd9458')]
5、查询数据库
# 查询一条数据
result = collection.find_one({"name": "Mike"})
print(type(result)) #
print(result)
# {'_id': ObjectId('5b1204a3d7696c41c083d21e'),
# 'id': '20170202', 'name': 'Mike', 'age': 21, 'gender': 'male'}
# 通过_id属性来查询, 不存在则返回None
from bson.objectid import ObjectId
result = collection.find_one({'_id': ObjectId('5b1204a3d7696c41c083d21e')})
print(result)
# {'_id': ObjectId('5b1204a3d7696c41c083d21e'),
# 'id': '20170202', 'name': 'Mike', 'age': 21, 'gender': 'male'}
# 查询多条数据, 返回一个生成器
results = collection.find({"age": 21})
print(results) #
for result in results:
print(result)
# {'_id': ObjectId('5b12055fd7696c4208deb74a'),
# 'id': '20170202', 'name': 'Mike', 'age': 21, 'gender': 'male'}
# 条件查询
results = collection.find({"age": {"$gt": 20}})
for result in results:
print(result)
# {'_id': ObjectId('5b1209ccd7696c437c51d5bb'),
# 'id': '20170101', 'name': '小明', 'age': 22, 'gender': '男性'}
# {'_id': ObjectId('5b1209ccd7696c437c51d5bd'),
# 'id': '20170202', 'name': 'Mike', 'age': 21, 'gender': 'male'}
# 正则匹配查询
results = collection.find({"name": {"$regex": "^M.*"}})
for result in results:
print(result)
# {'_id': ObjectId('5b1209ccd7696c437c51d5bd'),
# 'id': '20170202', 'name': 'Mike', 'age': 21, 'gender': 'male'}
## 转为list
>>> db.collection.find()
>>> list(db.collection.find())
[
{'_id': ObjectId('5839b12eee86fb71849a0905'), 'name': 'Tom'}
]
比较符号
符号表示含义示例:=等于{“age”: 20}$lt大于{“age”: {"$gt": 20}}$lte=大于等于{“age”: {"$gte": 20}}$ne!=不等于{“age”: {"$ne": 20}}$inin范围内{“age”: {"$in": [20, 30]}}$ninnot in不在范围内{“age”: {"$nin": [20, 30]}}说明: lt: less than gt: great than e: equal
功能符号
符号含义示例示例说明$regex匹配正则表达式{“name”: {"$regex": “^M.*”}}name以M开头$exists属性是否存在{“name”: {"$exists": True}}name属性存在$type类型判断{“age”: {"$type": “int”}}age的类型为int$mod数字模操作{“age”: {"$mod": [5, 0]}}年龄模5余0$text文本查询{“text”: {"$search": “Mike”}}text类型的属性中包含字符串Mike$where高级条件查询{“name”: {"$where": “obj.age==obj.count”}}自身年龄等于自身数量 6、查询计数count = collection.find().count()
print(count) # 3
7、数据排序
# 升序pymongo.ASCENDING 降序pymongo.DESCENDING
results = collection.find().sort("name", pymongo.ASCENDING)
print([result["name"] for result in results])
# ['Jordan', 'Mike', '小明']
8、数据的偏移
results = collection.find().sort('name', pymongo.ASCENDING).skip(2)
print([result['name'] for result in results])
# ['小明']
results = collection.find().sort('name', pymongo.ASCENDING).skip(1).limit(1)
print([result['name'] for result in results])
# ['Mike']
# 数据库数量非常庞大的时候,不要使用大的偏移量
from bson.objectid import ObjectId
results = collection.find({'_id': {'$gt': ObjectId('5b1209ccd7696c437c51d5bb')}})
print([result['name'] for result in results])
9、更新数据库
更新函数
update_one(filter, update, upsert=False,
bypass_document_validation=False, collation=None, array_filters=None, session=None)
update_many(filter, update, upsert=False,
array_filters=None, bypass_document_validation=False, collation=None, session=None)
# 过时了
update(spec, document, upsert=False,
manipulate=False, multi=False, check_keys=True, **kwargs)
condition = {'name': 'Mike'}
student = collection.find_one(condition)
student['age'] = 25
# 全部用student字典替换
# result = collection.update(condition, student)
# 只更新student字典内存在的字段
result = collection.update(condition, {'$set': student})
print(result)
# {'n': 1, 'nModified': 1, 'ok': 1.0, 'updatedExisting': True}
condition = {'name': 'Mike'}
student = collection.find_one(condition)
student['age'] = 26
result = collection.update_one(condition, {'$set': student})
print(result)
#
print(result.matched_count, result.modified_count)
# 1 1
condition = {'age': {'$gt': 20}}
result = collection.update_one(condition, {'$inc': {'age': 1}})
print(result)
#
print(result.matched_count, result.modified_count)
# 1 1
10、数据删除
result = collection.remove({'name': 'Jordan'})
print(result)
# 删除一条
result = collection.delete_one({'name': 'Kevin'})
print(result)
print(result.deleted_count)
result = collection.delete_many({'age': {'$lt': 25}})
print(result.deleted_count)
# 删除多条
result = collection.delete_many({'name': 'Kevin'})
官方文档: http://api.mongodb.com/python/current/api/pymongo/collection.html
多条件查询
db.getCollection('table').find({"$and": [{"detail": {"$ne": null}}, {"detail": {"$ne": true}}]})
参考: 菜鸟用Python操作MongoDB,看这一篇就够了