Python操作MongoDB数据库PyMongo库使用方法
引用PyMongo
>>> import pymongo
创建连接Connection
>>> import pymongo
>>> conn = pymongo.Connection('localhost',27017)
或
>>> from pymongo import Connection
>>> conn = Connection('localhost',27017)
创建Connection时,指定host及port参数
>>> import pymongo
>>> conn = pymongo.Connection(host='127.0.0.1',port=27017)
连接数据库
>>> db = conn.ChatRoom
或
>>> db = conn['ChatRoom']
连接聚集
>>> account = db.Account
或
>>> account = db["Account"]
查看全部聚集名称
>>> db.collection_names()
查看聚集的一条记录
>>> db.Account.find_one()
>>> db.Account.find_one({"UserName":"keyword"})
查看聚集的字段
>>> db.Account.find_one({},{"UserName":1,"Email":1})
{u'UserName': u'libing', u'_id': ObjectId('4ded95c3b7780a774a099b7c'), u'Email': u'libing@35.cn'}
>>> db.Account.find_one({},{"UserName":1,"Email":1,"_id":0})
{u'UserName': u'libing', u'Email': u'libing@35.cn'}
查看聚集的多条记录
>>> for item in db.Account.find():
item
>>> for item in db.Account.find({"UserName":"libing"}):
item["UserName"]
查看聚集的记录统计
>>> db.Account.find().count()
>>> db.Account.find({"UserName":"keyword"}).count()
聚集查询结果排序
>>> db.Account.find().sort("UserName") --默认为升序
>>> db.Account.find().sort("UserName",pymongo.ASCENDING) --升序
>>> db.Account.find().sort("UserName",pymongo.DESCENDING) --降序
聚集查询结果多列排序
>>> db.Account.find().sort([("UserName",pymongo.ASCENDING),("Email",pymongo.DESCENDING)])
添加记录
>>> db.Account.insert({"AccountID":21,"UserName":"libing"})
修改记录
>>> db.Account.update({"UserName":"libing"},{"$set":{"Email":"libing@126.com","Password":"123"}})
删除记录
>>> db.Account.remove() -- 全部删除
>>> db.Test.remove({"UserName":"keyword"})

Hot AI Tools

Undresser.AI Undress
AI-powered app for creating realistic nude photos

AI Clothes Remover
Online AI tool for removing clothes from photos.

Undress AI Tool
Undress images for free

Clothoff.io
AI clothes remover

Video Face Swap
Swap faces in any video effortlessly with our completely free AI face swap tool!

Hot Article

Hot Tools

Notepad++7.3.1
Easy-to-use and free code editor

SublimeText3 Chinese version
Chinese version, very easy to use

Zend Studio 13.0.1
Powerful PHP integrated development environment

Dreamweaver CS6
Visual web development tools

SublimeText3 Mac version
God-level code editing software (SublimeText3)

Hot Topics

PHP is mainly procedural programming, but also supports object-oriented programming (OOP); Python supports a variety of paradigms, including OOP, functional and procedural programming. PHP is suitable for web development, and Python is suitable for a variety of applications such as data analysis and machine learning.

Python is more suitable for beginners, with a smooth learning curve and concise syntax; JavaScript is suitable for front-end development, with a steep learning curve and flexible syntax. 1. Python syntax is intuitive and suitable for data science and back-end development. 2. JavaScript is flexible and widely used in front-end and server-side programming.

PHP is suitable for web development and rapid prototyping, and Python is suitable for data science and machine learning. 1.PHP is used for dynamic web development, with simple syntax and suitable for rapid development. 2. Python has concise syntax, is suitable for multiple fields, and has a strong library ecosystem.

PHP originated in 1994 and was developed by RasmusLerdorf. It was originally used to track website visitors and gradually evolved into a server-side scripting language and was widely used in web development. Python was developed by Guidovan Rossum in the late 1980s and was first released in 1991. It emphasizes code readability and simplicity, and is suitable for scientific computing, data analysis and other fields.

When developing an e-commerce website, I encountered a difficult problem: how to provide users with personalized product recommendations. Initially, I tried some simple recommendation algorithms, but the results were not ideal, and user satisfaction was also affected. In order to improve the accuracy and efficiency of the recommendation system, I decided to adopt a more professional solution. Finally, I installed andres-montanez/recommendations-bundle through Composer, which not only solved my problem, but also greatly improved the performance of the recommendation system. You can learn composer through the following address:

Running Python code in Notepad requires the Python executable and NppExec plug-in to be installed. After installing Python and adding PATH to it, configure the command "python" and the parameter "{CURRENT_DIRECTORY}{FILE_NAME}" in the NppExec plug-in to run Python code in Notepad through the shortcut key "F6".

Visual Studio Code (VSCode) is a cross-platform, open source and free code editor developed by Microsoft. It is known for its lightweight, scalability and support for a wide range of programming languages. To install VSCode, please visit the official website to download and run the installer. When using VSCode, you can create new projects, edit code, debug code, navigate projects, expand VSCode, and manage settings. VSCode is available for Windows, macOS, and Linux, supports multiple programming languages and provides various extensions through Marketplace. Its advantages include lightweight, scalability, extensive language support, rich features and version

Golang is better than Python in terms of performance and scalability. 1) Golang's compilation-type characteristics and efficient concurrency model make it perform well in high concurrency scenarios. 2) Python, as an interpreted language, executes slowly, but can optimize performance through tools such as Cython.
