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Was sind die gängigen Datenbanken in Python?
- 爱喝马黛茶的安东尼Original
- 2019-06-12 11:11:539675Durchsuche
Was sind die gängigen Datenbanken in Python? Datenbanken werden grob in zwei Kategorien unterteilt. Die erste Kategorie umfasst relationale Datenbanken und die zweite Kategorie sind nicht relationale Datenbanken. Im Folgenden finden Sie eine Einführung in die relevanten Kenntnisse dieser beiden Datenbanktypen.
Einschließlich relationaler Datenbanken: SQLite, MySQL, MSSQL
Nicht-relationale Datenbanken: MongoDB, Redis
1 zu 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. MySQL verbinden
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2.2 MySQLdb verwenden
2.1 _mysql in der mysqldb-Bibliothek verwenden
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 Verwenden 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 Verwenden Sie pymysql
Abschnitt 2.1 und 2.2 verwenden MySQLdb, das Python3.x nicht unterstützt.
pymysql bietet eine bessere Unterstützung für Python2.x und Python3.x
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. Mit mssql verbinden
4. Mit MongoDB verbindenimport 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()
5.1 Redis verwenden
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()5.2 Pyredis verwenden
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Das obige ist der detaillierte Inhalt vonWas sind die gängigen Datenbanken in Python?. Für weitere Informationen folgen Sie bitte anderen verwandten Artikeln auf der PHP chinesischen Website!