一、相关代码
数据库配置类 MongoDBConn.py
代码如下:
#encoding=utf-8
'''
Mongo Conn连接类
'''
import pymongo
class DBConn:
conn = None
servers = "mongodb://localhost:27017"
def connect(self):
self.conn = pymongo.Connection(self.servers)
def close(self):
return self.conn.disconnect()
def getConn(self):
return self.conn
MongoDemo.py 类
代码如下:
#encoding=utf-8
'''
Mongo操作Demo
Done:
'''
import MongoDBConn
dbconn = MongoDBConn.DBConn()
conn = None
lifeba_users = None
def process():
#建立连接
dbconn.connect()
global conn
conn = dbconn.getConn()
#列出server_info信息
print conn.server_info()
#列出全部数据库
databases = conn.database_names()
print databases
#删除库和表
dropTable()
#添加数据库lifeba及表(collections)users
createTable()
#插入数据
insertDatas()
#更新数据
updateData()
#查询数据
queryData()
#删除数据
deleteData()
#释放连接
dbconn.close()
def insertDatas():
datas=[{"name":"steven1","realname":"测试1","age":25},
{"name":"steven2","realname":"测试2","age":26},
{"name":"steven1","realname":"测试3","age":23}]
lifeba_users.insert(datas)
def updateData():
'''只修改最后一条匹配到的数据
第3个参数设置为True,没找到该数据就添加一条
第4个参数设置为True,有多条记录就不更新
'''
lifeba_users.update({'name':'steven1'},{'$set':{'realname':'测试1修改'}}, False,False)
def deleteData():
lifeba_users.remove({'name':'steven1'})
def queryData():
#查询全部数据
rows = lifeba_users.find()
printResult(rows)
#查询一个数据
print lifeba_users.find_one()
#带条件查询
printResult(lifeba_users.find({'name':'steven2'}))
printResult(lifeba_users.find({'name':{'$gt':25}}))
def createTable():
'''创建库和表'''
global lifeba_users
lifeba_users = conn.lifeba.users
def dropTable():
'''删除表'''
global conn
conn.drop_database("lifeba")
def printResult(rows):
for row in rows:
for key in row.keys():#遍历字典
print row[key], #加, 不换行打印
print ''
if __name__ == '__main__':
process()

Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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