python中常见的数据库有哪些呢？数据库大致分为两大类，第一类是包括关系数据库，第二类是非关系数据库，下面介绍一下这两类数据库的相关知识。
包括关系数据库：sqlite,mysql,mssql
非关系数据库：MongoDB,Redis
1. 连接Sqlite
import sqlite3
import traceback
try:
# 如果表不存在,就创建
with sqlite3.connect('test.db') as conn:
print("Opened database successfully")
# 删除表
conn.execute("DROP TABLE IF EXISTS COMPANY")
# 创建表
sql = """
CREATE TABLE IF NOT EXISTS COMPANY
(ID INTEGER PRIMARY KEY AUTOINCREMENT,
NAME TEXT NOT NULL,
AGE INT NOT NULL,
ADDRESS CHAR(50),
SALARY REAL);
"""
conn.execute(sql)
print("create table successfully")
# 添加数据
conn.executemany("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES (?, ?, ?, ? )",
[('Paul', 32, 'California', 20000.00),
('Allen', 25, 'Texas', 15000.00),
('Teddy', 23, 'Norway', 20000.00),
('Mark', 25, 'Rich-Mond ', 65000.00),
('David', 27, 'Texas', 85000.00),
('Kim', 22, 'South-Hall', 45000.00),
('James', 24, 'Houston', 10000.00)])
# conn.execute("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)\
# VALUES ( 'Paul', 32, 'California', 20000.00 )")
#
# conn.execute("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)\
# VALUES ('Allen', 25, 'Texas', 15000.00 )")
#
# conn.execute("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)\
# VALUES ('Teddy', 23, 'Norway', 20000.00 )")
#
# conn.execute("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)\
# VALUES ( 'Mark', 25, 'Rich-Mond ', 65000.00 )")
#
# conn.execute("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)\
# VALUES ( 'David', 27, 'Texas', 85000.00 )");
#
# conn.execute("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)\
# VALUES ( 'Kim', 22, 'South-Hall', 45000.00 )")
#
# conn.execute("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY)\
# VALUES ( 'James', 24, 'Houston', 10000.00 )")
# 提交,否则重新运行程序时,表中无数据
conn.commit()
print("insert successfully")
# 查询表
sql = """
select id,NAME,AGE,ADDRESS,SALARY FROM COMPANY
"""
result = conn.execute(sql)
for row in result:
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("id", row[0])) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row[1]))
print("%-10s %s" % ("age", row[2]))
print("%-10s %s" % ("address", row[3]))
print("%-10s %.2f" % ("salary", row[4]))
# or
# print('{:10s} {:.2f}'.format("salary", row[4]))
except sqlite3.Error as e:
print("sqlite3 Error:", e)
traceback.print_exc()2.连接mysql
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2.2 使用MySQLdb
2.1使用mysqldb库中的_mysql
import MySQLdb
from contextlib import closing
import traceback
try:
# 获取一个数据库连接
with closing(MySQLdb.connect(host='localhost', user='root', passwd='root', db='test', port=3306,charset='utf8')) as conn:
print("connect database successfully")
with closing(conn.cursor()) as cur:
# 删除表
cur.execute("DROP TABLE IF EXISTS COMPANY")
# 创建表
sql = """
CREATE TABLE IF NOT EXISTS COMPANY
(ID INTEGER PRIMARY KEY NOT NULL auto_increment,
NAME TEXT NOT NULL,
AGE INT NOT NULL,
ADDRESS CHAR(50),
SALARY REAL);
"""
cur.execute(sql)
print("create table successfully")
# 添加数据
# 在一个conn.execute里面里面执行多个sql语句是非法的
cur.executemany("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( %s, %s, %s, %s )",
[('Paul', 32, 'California', 20000.00),
('Allen', 25, 'Texas', 15000.00),
('Teddy', 23, 'Norway', 20000.00),
('Mark', 25, 'Rich-Mond ', 65000.00),
('David', 27, 'Texas', 85000.00),
('Kim', 22, 'South-Hall', 45000.00),
('James', 24, 'Houston', 10000.00)])
# 提交,否则重新运行程序时,表中无数据
conn.commit()
print("insert successfully")
# 查询表
sql = """
select id,NAME,AGE,ADDRESS,SALARY FROM COMPANY
"""
cur.execute(sql)
for row in cur.fetchall():
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("id", row[0])) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row[1]))
print("%-10s %s" % ("age", row[2]))
print("%-10s %s" % ("address", row[3]))
print("%-10s %s" % ("salary", row[4]))
except MySQLdb.Error as e:
print("Mysql Error:", e)
traceback.print_exc() # 打印错误栈信息2.2 使用MySQLdb
import MySQLdb
from contextlib import closing
import traceback
try:
# 获取一个数据库连接
with closing(MySQLdb.connect(host='localhost', user='root', passwd='root', db='test', port=3306,charset='utf8')) as conn:
print("connect database successfully")
with closing(conn.cursor()) as cur:
# 删除表
cur.execute("DROP TABLE IF EXISTS COMPANY")
# 创建表
sql = """
CREATE TABLE IF NOT EXISTS COMPANY
(ID INTEGER PRIMARY KEY NOT NULL auto_increment,
NAME TEXT NOT NULL,
AGE INT NOT NULL,
ADDRESS CHAR(50),
SALARY REAL);
"""
cur.execute(sql)
print("create table successfully")
# 添加数据
# 在一个conn.execute里面里面执行多个sql语句是非法的
cur.executemany("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( %s, %s, %s, %s )",
[('Paul', 32, 'California', 20000.00),
('Allen', 25, 'Texas', 15000.00),
('Teddy', 23, 'Norway', 20000.00),
('Mark', 25, 'Rich-Mond ', 65000.00),
('David', 27, 'Texas', 85000.00),
('Kim', 22, 'South-Hall', 45000.00),
('James', 24, 'Houston', 10000.00)])
# 提交,否则重新运行程序时,表中无数据
conn.commit()
print("insert successfully")
# 查询表
sql = """
select id,NAME,AGE,ADDRESS,SALARY FROM COMPANY
"""
cur.execute(sql)
for row in cur.fetchall():
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("id", row[0])) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row[1]))
print("%-10s %s" % ("age", row[2]))
print("%-10s %s" % ("address", row[3]))
print("%-10s %s" % ("salary", row[4]))
except MySQLdb.Error as e:
print("Mysql Error:", e)
traceback.print_exc() # 打印错误栈信息2.3使用pymysql
2.1和2.2节使用MySQLdb，不支持Python3.x
pymysql对Python2.x和Python3.x的支持都比较好
import pymysql
from contextlib import closing
import traceback
try:
# 获取一个数据库连接,with关键字 表示退出时,conn自动关闭
# with 嵌套上一层的with 要使用closing()
with closing(pymysql.connect(host='localhost', user='root', passwd='root', db='test', port=3306,
charset='utf8')) as conn:
print("connect database successfully")
# 获取游标,with关键字 表示退出时,cur自动关闭
with conn.cursor() as cur:
# 删除表
cur.execute("DROP TABLE IF EXISTS COMPANY")
# 创建表
sql = """
CREATE TABLE IF NOT EXISTS COMPANY
(ID INTEGER PRIMARY KEY NOT NULL auto_increment,
NAME TEXT NOT NULL,
AGE INT NOT NULL,
ADDRESS CHAR(50),
SALARY REAL);
"""
cur.execute(sql)
print("create table successfully")
# 添加数据
# 在一个conn.execute里面里面执行多个sql语句是非法的
cur.executemany("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( %s, %s, %s, %s )",
[('Paul', 32, 'California', 20000.00),
('Allen', 25, 'Texas', 15000.00),
('Teddy', 23, 'Norway', 20000.00),
('Mark', 25, 'Rich-Mond ', 65000.00),
('David', 27, 'Texas', 85000.00),
('Kim', 22, 'South-Hall', 45000.00),
('James', 24, 'Houston', 10000.00)])
# 提交,否则重新运行程序时,表中无数据
conn.commit()
print("insert successfully")
# 查询表
sql = """
select id,NAME,AGE,ADDRESS,SALARY FROM COMPANY
"""
cur.execute(sql)
for row in cur.fetchall():
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("id", row[0])) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row[1]))
print("%-10s %s" % ("age", row[2]))
print("%-10s %s" % ("address", row[3]))
print("%-10s %s" % ("salary", row[4]))
except pymysql.Error as e:
print("Mysql Error:", e)
traceback.print_exc()3.连接mssql
import pymssql
from contextlib import closing
try:
# 先要保证数据库中有test数据库
# 获取一个数据库连接,with关键字 表示退出时,conn自动关闭
# with 嵌套上一层的with 要使用closing()
with closing(pymssql.connect(host='192.168.100.114', user='sa', password='sa12345', database='test', port=1433,
charset='utf8')) as conn:
print("connect database successfully")
# 获取游标,with关键字 表示退出时,cur自动关闭
with conn.cursor() as cur:
# 删除表
cur.execute(
'''if exists (select 1 from sys.objects where name='COMPANY' and type='U') drop table COMPANY''')
# 创建表
sql = """
CREATE TABLE COMPANY
(ID INT IDENTITY(1,1) PRIMARY KEY NOT NULL ,
NAME TEXT NOT NULL,
AGE INT NOT NULL,
ADDRESS CHAR(50),
SALARY REAL);
"""
cur.execute(sql)
print("create table successfully")
# 添加数据
# 在一个conn.execute里面里面执行多个sql语句是非法的
cur.executemany("INSERT INTO COMPANY (NAME,AGE,ADDRESS,SALARY) VALUES ( %s, %s, %s, %s )",
[('Paul', 32, 'California', 20000.00),
('Allen', 25, 'Texas', 15000.00),
('Teddy', 23, 'Norway', 20000.00),
('Mark', 25, 'Rich-Mond', 65000.00),
('David', 27, 'Texas', 85000.00),
('Kim', 22, 'South-Hall', 45000.00),
('James', 24, 'Houston', 10000.00)])
# 提交,否则重新运行程序时,表中无数据
conn.commit()
print("insert successfully")
# 查询表
sql = """
select id,NAME,AGE,ADDRESS,SALARY FROM COMPANY
"""
cur.execute(sql)
for row in cur.fetchall():
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("id", row[0])) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row[1]))
print("%-10s %s" % ("age", row[2]))
print("%-10s %s" % ("address", row[3]))
print("%-10s %s" % ("salary", row[4]))
except pymssql.Error as e:
print("mssql Error:", e)
# traceback.print_exc()4.连接MongoDB
import pymongo
from pymongo.mongo_client import MongoClient
import pymongo.errors
import traceback
try:
# 连接到 mongodb 服务
mongoClient = MongoClient('localhost', 27017)
# 连接到数据库
mongoDatabase = mongoClient.test
print("connect database successfully")
# 获取集合
mongoCollection = mongoDatabase.COMPANY
# 移除所有数据
mongoCollection.remove()
# 添加数据
mongoCollection.insert_many([{"Name": "Paul", "Age": "32", "Address": "California", "Salary": "20000.00"},
{"Name": "Allen", "Age": "25", "Address": "Texas", "Salary": "15000.00"},
{"Name": "Teddy", "Age": "23", "Address": "Norway", "Salary": "20000.00"},
{"Name": "Mark", "Age": "25", "Address": "Rich-Mond", "Salary": "65000.00"},
{"Name": "David", "Age": "27", "Address": "Texas", "Salary": "85000.00"},
{"Name": "Kim", "Age": "22", "Address": "South-Hall", "Salary": "45000.00"},
{"Name": "James", "Age": "24", "Address": "Houston", "Salary": "10000.00"}, ])
#获取集合中的值
for row in mongoCollection.find():
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("_id", row['_id'])) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row['Name']))
print("%-10s %s" % ("age", row['Age']))
print("%-10s %s" % ("address", row['Address']))
print("%-10s %s" % ("salary", row['Salary']))
print('\n\n\n')
# 使id自增
mongoCollection.remove()
# 创建计数表
mongoDatabase.counters.save({"_id": "people_id", "sequence_value": 0})
# 创建存储过程
mongoDatabase.system_js.getSequenceValue = '''function getSequenceValue(sequenceName){
var sequenceDocument = db.counters.findAndModify({
query: {_id: sequenceName},
update: {$inc:{sequence_value: 1}},
new:true
});
return sequenceDocument.sequence_value;
}'''
mongoCollection.insert_many(
[{"_id": mongoDatabase.eval("getSequenceValue('people_id')"), "Name": "Paul", "Age": "32",
"Address": "California", "Salary": "20000.00"},
{"_id": mongoDatabase.eval("getSequenceValue('people_id')"), "Name": "Allen", "Age": "25",
"Address": "Texas", "Salary": "15000.00"},
{"_id": mongoDatabase.eval("getSequenceValue('people_id')"), "Name": "Teddy", "Age": "23",
"Address": "Norway", "Salary": "20000.00"},
{"_id": mongoDatabase.eval("getSequenceValue('people_id')"), "Name": "Mark", "Age": "25",
"Address": "Rich-Mond", "Salary": "65000.00"},
{"_id": mongoDatabase.eval("getSequenceValue('people_id')"), "Name": "David", "Age": "27",
"Address": "Texas", "Salary": "85000.00"},
{"_id": mongoDatabase.eval("getSequenceValue('people_id')"), "Name": "Kim", "Age": "22",
"Address": "South-Hall", "Salary": "45000.00"},
{"_id": mongoDatabase.eval("getSequenceValue('people_id')"), "Name": "James", "Age": "24",
"Address": "Houston", "Salary": "10000.00"}, ])
for row in mongoCollection.find():
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("_id", int(row['_id']))) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row['Name']))
print("%-10s %s" % ("age", row['Age']))
print("%-10s %s" % ("address", row['Address']))
print("%-10s %s" % ("salary", row['Salary']))
except pymongo.errors.PyMongoError as e:
print("mongo Error:", e)
traceback.print_exc()5.连接Redis
5.1使用redis
import redis
r = redis.Redis(host='localhost', port=6379, db=0, password="12345")
print("connect", r.ping())
# 看信息
info = r.info()
# or 查看部分信息
# info = r.info("Server")
# 输出信息
items = info.items()
for i, (key, value) in enumerate(items):
print("item %s----%s:%s" % (i, key, value))
# 删除键和对应的值
r.delete("company")
# 可以一次性push一条或多条数据
r.rpush("company", {"id": 1, "Name": "Paul", "Age": "32", "Address": "California", "Salary": "20000.00"},
{"id": 2, "Name": "Allen", "Age": "25", "Address": "Texas", "Salary": "15000.00"},
{"id": 3, "Name": "Teddy", "Age": "23", "Address": "Norway", "Salary": "20000.00"})
r.rpush("company", {"id": 4, "Name": "Mark", "Age": "25", "Address": "Rich-Mond", "Salary": "65000.00"})
r.rpush("company", {"id": 5, "Name": "David", "Age": "27", "Address": "Texas", "Salary": "85000.00"})
r.rpush("company", {"id": 6, "Name": "Kim", "Age": "22", "Address": "South-Hall", "Salary": "45000.00"})
r.rpush("company", {"id": 7, "Name": "James", "Age": "24", "Address": "Houston", "Salary": "10000.00"})
# eval用来将dict格式的字符串转换成dict
for row in map(lambda x: eval(x), r.lrange("company", 0, r.llen("company"))):
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("_id", row['id'])) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row['Name']))
print("%-10s %s" % ("age", row['Age']))
print("%-10s %s" % ("address", row['Address']))
print("%-10s %s" % ("salary", row['Salary']))
# 关闭当前连接
# r.shutdown() #这个是关闭redis服务端5.2使用pyredis
import pyredis
r = pyredis.Client(host='localhost', port=6379, database=0, password="12345")
print("connect", r.ping().decode("utf-8"))
# 看信息
# info = r.execute("info").decode()
# or 查看部分信息
info = r.execute("info", "Server").decode()
# 输出信息
print(info)
# 删除键和对应的值
r.delete("company")
# 可以一次性push一条或多条数据
r.rpush("company", '''{"id": 1, "Name": "Paul", "Age": "32", "Address": "California", "Salary": "20000.00"}''',
'''{"id": 2, "Name": "Allen", "Age": "25", "Address": "Texas", "Salary": "15000.00"}''',
'''{"id": 3, "Name": "Teddy", "Age": "23", "Address": "Norway", "Salary": "20000.00"}''')
r.rpush("company", '''{"id": 4, "Name": "Mark", "Age": "25", "Address": "Rich-Mond", "Salary": "65000.00"}''')
r.rpush("company", '''{"id": 5, "Name": "David", "Age": "27", "Address": "Texas", "Salary": "85000.00"}''')
r.rpush("company", '''{"id": 6, "Name": "Kim", "Age": "22", "Address": "South-Hall", "Salary": "45000.00"}''')
r.rpush("company", '''{"id": 7, "Name": "James", "Age": "24", "Address": "Houston", "Salary": "10000.00"}''')
# eval用来将dict格式的字符串转换成dict
for row in map(lambda x: eval(x), r.lrange("company", 0, r.llen("company"))):
print("-" * 50) # 输出50个-,作为分界线
print("%-10s %s" % ("_id", row['id'])) # 字段名固定10位宽度,并且左对齐
print("%-10s %s" % ("name", row['Name']))
print("%-10s %s" % ("age", row['Age']))
print("%-10s %s" % ("address", row['Address']))
print("%-10s %s" % ("salary", row['Salary']))
# 关闭当前连接
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Alat panas
Hantar Studio 13.0.1
Persekitaran pembangunan bersepadu PHP yang berkuasa
SublimeText3 Linux versi baharu
SublimeText3 Linux versi terkini
DVWA
Damn Vulnerable Web App (DVWA) ialah aplikasi web PHP/MySQL yang sangat terdedah. Matlamat utamanya adalah untuk menjadi bantuan bagi profesional keselamatan untuk menguji kemahiran dan alatan mereka dalam persekitaran undang-undang, untuk membantu pembangun web lebih memahami proses mengamankan aplikasi web, dan untuk membantu guru/pelajar mengajar/belajar dalam persekitaran bilik darjah Aplikasi web keselamatan. Matlamat DVWA adalah untuk mempraktikkan beberapa kelemahan web yang paling biasa melalui antara muka yang mudah dan mudah, dengan pelbagai tahap kesukaran. Sila ambil perhatian bahawa perisian ini
Notepad++7.3.1
Editor kod yang mudah digunakan dan percuma
MantisBT
Mantis ialah alat pengesan kecacatan berasaskan web yang mudah digunakan yang direka untuk membantu dalam pengesanan kecacatan produk. Ia memerlukan PHP, MySQL dan pelayan web. Lihat perkhidmatan demo dan pengehosan kami.
