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Python史上最全种类数据库操作方法分享

作者：techlead_krischang

本文将详细探讨如何在Python中连接全种类数据库以及实现相应的CRUD（创建，读取，更新，删除）操作，文中的示例代码讲解详细，需要的可以参考一下

本文将详细探讨如何在Python中连接全种类数据库以及实现相应的CRUD（创建，读取，更新，删除）操作。我们将逐一解析连接MySQL，SQL Server，Oracle，PostgreSQL，MongoDB，SQLite，DB2，Redis，Cassandra，Microsoft Access，ElasticSearch，Neo4j，InfluxDB，Snowflake，Amazon DynamoDB，Microsoft Azure CosMos DB数据库的方法，并演示相应的CRUD操作。

MySQL

连接数据库

Python可以使用mysql-connector-python库连接MySQL数据库：

import mysql.connector
conn = mysql.connector.connect(user='username', password='password', host='127.0.0.1', database='my_database')
print("Opened MySQL database successfully")
conn.close()

CRUD操作

接下来，我们将展示在MySQL中如何进行基本的CRUD操作。

创建（Create）

conn = mysql.connector.connect(user='username', password='password', host='127.0.0.1', database='my_database')
cursor = conn.cursor()
cursor.execute("CREATE TABLE Employees (ID INT PRIMARY KEY NOT NULL, NAME TEXT NOT NULL, AGE INT, ADDRESS CHAR(50), SALARY REAL)")
print("Table created successfully")
conn.close()

读取（Retrieve）

conn = mysql.connector.connect(user='username', password='password', host='127.0.0.1', database='my_database')
cursor = conn.cursor()
cursor.execute("SELECT id, name, address, salary from Employees")
rows = cursor.fetchall()
for row in rows:
    print("ID = ", row[0])
    print("NAME = ", row[1])
    print("ADDRESS = ", row[2])
    print("SALARY = ", row[3])
conn.close()

更新（Update）

conn = mysql.connector.connect(user='username', password='password', host='127.0.0.1', database='my_database')
cursor = conn.cursor()
cursor.execute("UPDATE Employees set SALARY = 25000.00 where ID = 1")
conn.commit()
print("Total number of rows updated :", cursor.rowcount)
conn.close()

删除（Delete）

conn = mysql.connector.connect(user='username', password='password', host='127.0.0.1', database='my_database')
cursor = conn.cursor()
cursor.execute("DELETE from Employees where ID = 1")
conn.commit()
print("Total number of rows deleted :", cursor.rowcount)
conn.close()

SQL Server

连接数据库

Python可以使用pyodbc库连接SQL Server数据库：

import pyodbc
conn = pyodbc.connect('DRIVER={SQL Server};SERVER=localhost;DATABASE=my_database;UID=username;PWD=password')
print("Opened SQL Server database successfully")
conn.close()

CRUD操作

接下来，我们将展示在SQL Server中如何进行基本的CRUD操作。

创建（Create）

conn = pyodbc.connect('DRIVER={SQL Server};SERVER=localhost;DATABASE=my_database;UID=username;PWD=password')
cursor = conn.cursor()
cursor.execute("CREATE TABLE Employees (ID INT PRIMARY KEY NOT NULL, NAME VARCHAR(20) NOT NULL, AGE INT, ADDRESS CHAR(50), SALARY REAL)")
conn.commit()
print("Table created successfully")
conn.close()

读取（Retrieve）

conn = pyodbc.connect('DRIVER={SQL Server};SERVER=localhost;DATABASE=my_database;UID=username;PWD=password')
cursor = conn.cursor()
cursor.execute("SELECT id, name, address, salary from Employees")
rows = cursor.fetchall()
for row in rows:
    print("ID = ", row[0])
    print("NAME = ", row[1])
    print("ADDRESS = ", row[2])
    print("SALARY = ", row[3])
conn.close()

更新（Update）

conn = pyodbc.connect('DRIVER={SQL Server};SERVER=localhost;DATABASE=my_database;UID=username;PWD=password')
cursor = conn.cursor()
cursor.execute("UPDATE Employees set SALARY = 25000.00 where ID = 1")
conn.commit()
print("Total number of rows updated :", cursor.rowcount)
conn.close()

删除（Delete）

conn = pyodbc.connect('DRIVER={SQL Server};SERVER=localhost;DATABASE=my_database;UID=username;PWD=password')
cursor = conn.cursor()
cursor.execute("DELETE from Employees where ID = 1")
conn.commit()
print("Total number of rows deleted :", cursor.rowcount)
conn.close()

Oracle

连接数据库

Python可以使用cx_Oracle库连接Oracle数据库：

import cx_Oracle
dsn_tns = cx_Oracle.makedsn('localhost', '1521', service_name='my_database') 
conn = cx_Oracle.connect(user='username', password='password', dsn=dsn_tns)
print("Opened Oracle database successfully")
conn.close()

CRUD操作

接下来，我们将展示在Oracle中如何进行基本的CRUD操作。

创建（Create）

dsn_tns = cx_Oracle.makedsn('localhost', '1521', service_name='my_database') 
conn = cx_Oracle.connect(user='username', password='password', dsn=dsn_tns)
cursor = conn.cursor()
cursor.execute("CREATE TABLE Employees (ID NUMBER(10) NOT NULL PRIMARY KEY, NAME VARCHAR2(20) NOT NULL, AGE NUMBER(3), ADDRESS CHAR(50), SALARY NUMBER(10, 2))")
conn.commit()
print("Table created successfully")
conn.close()

读取（Retrieve）

dsn_tns = cx_Oracle.makedsn('localhost', '1521', service_name='my_database') 
conn = cx_Oracle.connect(user='username', password='password', dsn=dsn_tns)
cursor = conn.cursor()
cursor.execute("SELECT id, name, address, salary from Employees")
rows = cursor.fetchall()
for row in rows:
    print("ID = ", row[0])
    print("NAME = ", row[1])
    print("ADDRESS = ", row[2])
    print("SALARY = ", row[3])
conn.close()

更新（Update）

dsn_tns = cx_Oracle.makedsn('localhost', '1521', service_name='my_database') 
conn = cx_Oracle.connect(user='username', password='password', dsn=dsn_tns)
cursor = conn.cursor()
cursor.execute("UPDATE Employees set SALARY = 25000.00 where ID = 1")
conn.commit()
print("Total number of rows updated :", cursor.rowcount)
conn.close()

删除（Delete）

dsn_tns = cx_Oracle.makedsn('localhost', '1521', service_name='my_database') 
conn = cx_Oracle.connect(user='username', password='password', dsn=dsn_tns)
cursor = conn.cursor()
cursor.execute("DELETE from Employees where ID = 1")
conn.commit()
print("Total number of rows deleted :", cursor.rowcount)
conn.close()

PostgreSQL

连接数据库

Python可以使用psycopg2库连接PostgreSQL数据库：

import psycopg2
conn = psycopg2.connect(database="my_database", user="username", password="password", host="127.0.0.1", port="5432")
print("Opened PostgreSQL database successfully")
conn.close()

CRUD操作

接下来，我们将展示在PostgreSQL中如何进行基本的CRUD操作。

创建（Create）

conn = psycopg2.connect(database="my_database", user="username", password="password", host="127.0.0.1", port="5432")
cursor = conn.cursor()
cursor.execute('''CREATE TABLE Employees
      (ID INT PRIMARY KEY     NOT NULL,
      NAME           TEXT    NOT NULL,
      AGE            INT     NOT NULL,
      ADDRESS        CHAR(50),
      SALARY         REAL);''')
conn.commit()
print("Table created successfully")
conn.close()

读取（Retrieve）

conn = psycopg2.connect(database="my_database", user="username", password="password", host="127.0.0.1", port="5432")
cursor = conn.cursor()
cursor.execute("SELECT id, name, address, salary from Employees")
rows = cursor.fetchall()
for row in rows:
    print("ID = ", row[0])
    print("NAME = ", row[1])
    print("ADDRESS = ", row[2])
    print("SALARY = ", row[3])
conn.close()

更新（Update）

conn = psycopg2.connect(database="my_database", user="username", password="password", host="127.0.0.1", port="5432")
cursor = conn.cursor()
cursor.execute("UPDATE Employees set SALARY = 25000.00 where ID = 1")
conn.commit()
print("Total number of rows updated :", cursor.rowcount)
conn.close()

删除（Delete）

conn = psycopg2.connect(database="my_database", user="username", password="password", host="127.0.0.1", port="5432")
cursor = conn.cursor()
cursor.execute("DELETE from Employees where ID = 1")
conn.commit()
print("Total number of rows deleted :", cursor.rowcount)
conn.close()

MongoDB

连接数据库

Python可以使用pymongo库连接MongoDB数据库：

from pymongo import MongoClient
client = MongoClient("mongodb://localhost:27017/")
db = client["my_database"]
print("Opened MongoDB database successfully")
client.close()

CRUD操作

接下来，我们将展示在MongoDB中如何进行基本的CRUD操作。

创建（Create）

在MongoDB中，文档的创建操作通常包含在插入操作中：

client = MongoClient("mongodb://localhost:27017/")
db = client["my_database"]
employees = db["Employees"]
employee = {"id": "1", "name": "John", "age": "30", "address": "New York", "salary": "1000.00"}
employees.insert_one(employee)
print("Document inserted successfully")
client.close()

读取（Retrieve）

client = MongoClient("mongodb://localhost:27017/")
db = client["my_database"]
employees = db["Employees"]
cursor = employees.find()
for document in cursor:
    print(document)
client.close()

更新（Update）

client = MongoClient("mongodb://localhost:27017/")
db = client["my_database"]
employees = db["Employees"]
query = { "id": "1" }
new_values = { "$set": { "salary": "25000.00" } }
employees.update_one(query, new_values)
print("Document updated successfully")
client.close()

删除（Delete）

client = MongoClient("mongodb://localhost:27017/")
db = client["my_database"]
employees = db["Employees"]
query = { "id": "1" }
employees.delete_one(query)
print("Document deleted successfully")
client.close()

SQLite

连接数据库

Python使用sqlite3库连接SQLite数据库：

import sqlite3
conn = sqlite3.connect('my_database.db')
print("Opened SQLite database successfully")
conn.close()

CRUD操作

接下来，我们将展示在SQLite中如何进行基本的CRUD操作。

创建（Create）

conn = sqlite3.connect('my_database.db')
cursor = conn.cursor()
cursor.execute('''CREATE TABLE Employees
      (ID INT PRIMARY KEY     NOT NULL,
      NAME           TEXT    NOT NULL,
      AGE            INT     NOT NULL,
      ADDRESS        CHAR(50),
      SALARY         REAL);''')
conn.commit()
print("Table created successfully")
conn.close()

读取（Retrieve）

conn = sqlite3.connect('my_database.db')
cursor = conn.cursor()
cursor.execute("SELECT id, name, address, salary from Employees")
rows = cursor.fetchall()
for row in rows:
    print("ID = ", row[0])
    print("NAME = ", row[1])
    print("ADDRESS = ", row[2])
    print("SALARY = ", row[3])
conn.close()

更新（Update）

conn = sqlite3.connect('my_database.db')
cursor = conn.cursor()
cursor.execute("UPDATE Employees set SALARY = 25000.00 where ID = 1")
conn.commit()
print("Total number of rows updated :", cursor.rowcount)
conn.close()

删除（Delete）

conn = sqlite3.connect('my_database.db')
cursor = conn.cursor()
cursor.execute("DELETE from Employees where ID = 1")
conn.commit()
print("Total number of rows deleted :", cursor.rowcount)
conn.close()

DB2

连接数据库

Python可以使用ibm_db库连接DB2数据库：

import ibm_db
dsn = (
    "DRIVER={{IBM DB2 ODBC DRIVER}};"
    "DATABASE=my_database;"
    "HOSTNAME=127.0.0.1;"
    "PORT=50000;"
    "PROTOCOL=TCPIP;"
    "UID=username;"
    "PWD=password;"
)
conn = ibm_db.connect(dsn, "", "")
print("Opened DB2 database successfully")
ibm_db.close(conn)

CRUD操作

接下来，我们将展示在DB2中如何进行基本的CRUD操作。

创建（Create）

conn = ibm_db.connect(dsn, "", "")
sql = '''CREATE TABLE Employees
      (ID INT PRIMARY KEY     NOT NULL,
      NAME           VARCHAR(20)    NOT NULL,
      AGE            INT     NOT NULL,
      ADDRESS        CHAR(50),
      SALARY         DECIMAL(9, 2));'''
stmt = ibm_db.exec_immediate(conn, sql)
print("Table created successfully")
ibm_db.close(conn)

读取（Retrieve）

conn = ibm_db.connect(dsn, "", "")
sql = "SELECT id, name, address, salary from Employees"
stmt = ibm_db.exec_immediate(conn, sql)
while ibm_db.fetch_row(stmt):
    print("ID = ", ibm_db.result(stmt, "ID"))
    print("NAME = ", ibm_db.result(stmt, "NAME"))
    print("ADDRESS = ", ibm_db.result(stmt, "ADDRESS"))
    print("SALARY = ", ibm_db.result(stmt, "SALARY"))
ibm_db.close(conn)

更新（Update）

conn = ibm_db.connect(dsn, "", "")
sql = "UPDATE Employees set SALARY = 25000.00 where ID = 1"
stmt = ibm_db.exec_immediate(conn, sql)
ibm_db.commit(conn)
print("Total number of rows updated :", ibm_db.num_rows(stmt))
ibm_db.close(conn)

删除（Delete）

conn = ibm_db.connect(dsn, "", "")
sql = "DELETE from Employees where ID = 1"
stmt = ibm_db.exec_immediate(conn, sql)
ibm_db.commit(conn)
print("Total number of rows deleted :", ibm_db.num_rows(stmt))
ibm_db.close(conn)

Microsoft Access

连接数据库

Python可以使用pyodbc库连接Microsoft Access数据库：

import pyodbc
conn_str = (
    r'DRIVER={Microsoft Access Driver (*.mdb, *.accdb)};'
    r'DBQ=path_to_your_access_file.accdb;'
)
conn = pyodbc.connect(conn_str)
print("Opened Access database successfully")
conn.close()

CRUD操作

接下来，我们将展示在Access中如何进行基本的CRUD操作。

创建（Create）

conn = pyodbc.connect(conn_str)
cursor = conn.cursor()
cursor.execute('''CREATE TABLE Employees
      (ID INT PRIMARY KEY     NOT NULL,
      NAME           TEXT    NOT NULL,
      AGE            INT     NOT NULL,
      ADDRESS        CHAR(50),
      SALARY         DECIMAL(9, 2));''')
conn.commit()
print("Table created successfully")
conn.close()

读取（Retrieve）

conn = pyodbc.connect(conn_str)
cursor = conn.cursor()
cursor.execute("SELECT id, name, address, salary from Employees")
rows = cursor.fetchall()
for row in rows:
    print("ID = ", row[0])
    print("NAME = ", row[1])
    print("ADDRESS = ", row[2])
    print("SALARY = ", row[3])
conn.close()

更新（Update）

conn = pyodbc.connect(conn_str)
cursor = conn.cursor()
cursor.execute("UPDATE Employees set SALARY = 25000.00 where ID = 1")
conn.commit()
print("Total number of rows updated :", cursor.rowcount)
conn.close()

删除（Delete）

conn = pyodbc.connect(conn_str)
cursor = conn.cursor()
cursor.execute("DELETE from Employees where ID = 1")
conn.commit()
print("Total number of rows deleted :", cursor.rowcount)
conn.close()

Cassandra

连接数据库

Python可以使用cassandra-driver库连接Cassandra数据库：

from cassandra.cluster import Cluster
cluster = Cluster(['127.0.0.1'])
session = cluster.connect('my_keyspace')
print("Opened Cassandra database successfully")
cluster.shutdown()

CRUD操作

接下来，我们将展示在Cassandra中如何进行基本的CRUD操作。

创建（Create）

cluster = Cluster(['127.0.0.1'])
session = cluster.connect('my_keyspace')
session.execute("""
    CREATE TABLE Employees (
        id int PRIMARY KEY,
        name text,
        age int,
        address text,
        salary decimal
    )
""")
print("Table created successfully")
cluster.shutdown()

读取（Retrieve）

cluster = Cluster(['127.0.0.1'])
session = cluster.connect('my_keyspace')
rows = session.execute('SELECT id, name, address, salary FROM Employees')
for row in rows:
    print("ID = ", row.id)
    print("NAME = ", row.name)
    print("ADDRESS = ", row.address)
    print("SALARY = ", row.salary)
cluster.shutdown()

更新（Update）

cluster = Cluster(['127.0.0.1'])
session = cluster.connect('my_keyspace')
session.execute("UPDATE Employees SET salary = 25000.00 WHERE id = 1")
print("Row updated successfully")
cluster.shutdown()

删除（Delete）

cluster = Cluster(['127.0.0.1'])
session = cluster.connect('my_keyspace')
session.execute("DELETE FROM Employees WHERE id = 1")
print("Row deleted successfully")
cluster.shutdown()

Redis

连接数据库

Python可以使用redis-py库连接Redis数据库：

import redis
r = redis.Redis(host='localhost', port=6379, db=0)
print("Opened Redis database successfully")

CRUD操作

接下来，我们将展示在Redis中如何进行基本的CRUD操作。

创建（Create）

r = redis.Redis(host='localhost', port=6379, db=0)
r.set('employee:1:name', 'John')
r.set('employee:1:age', '30')
r.set('employee:1:address', 'New York')
r.set('employee:1:salary', '1000.00')
print("Keys created successfully")

读取（Retrieve）

r = redis.Redis(host='localhost', port=6379, db=0)
print("NAME = ", r.get('employee:1:name').decode('utf-8'))
print("AGE = ", r.get('employee:1:age').decode('utf-8'))
print("ADDRESS = ", r.get('employee:1:address').decode('utf-8'))
print("SALARY = ", r.get('employee:1:salary').decode('utf-8'))

更新（Update）

r = redis.Redis(host='localhost', port=6379, db=0)

r.set('employee:1:salary', '25000.00')

print("Key updated successfully")

删除（Delete）

r = redis.Redis(host='localhost', port=6379, db=0)

r.delete('employee:1:name', 'employee:1:age', 'employee:1:address', 'employee:1:salary')

print("Keys deleted successfully")

ElasticSearch

连接数据库

Python可以使用elasticsearch库连接ElasticSearch数据库：

from elasticsearch import Elasticsearch
es = Elasticsearch([{'host': 'localhost', 'port': 9200}])
print("Opened ElasticSearch database successfully")

CRUD操作

接下来，我们将展示在ElasticSearch中如何进行基本的CRUD操作。

创建（Create）

es = Elasticsearch([{'host': 'localhost', 'port': 9200}])

employee = {
    'name': 'John',
    'age': 30,
    'address': 'New York',
    'salary': 1000.00
}
res = es.index(index='employees', doc_type='employee', id=1, body=employee)

print("Document created successfully")

读取（Retrieve）

es = Elasticsearch([{'host': 'localhost', 'port': 9200}])

res = es.get(index='employees', doc_type='employee', id=1)
print("Document details:")
for field, details in res['_source'].items():
    print(f"{field.upper()} = ", details)

更新（Update）

es = Elasticsearch([{'host': 'localhost', 'port': 9200}])

res = es.update(index='employees', doc_type='employee', id=1, body={
    'doc': {
        'salary': 25000.00
    }
})

print("Document updated successfully")

删除（Delete）

es = Elasticsearch([{'host': 'localhost', 'port': 9200}])

res = es.delete(index='employees', doc_type='employee', id=1)

print("Document deleted successfully")

Neo4j

连接数据库

Python可以使用neo4j库连接Neo4j数据库：

from neo4j import GraphDatabase
driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password"))
print("Opened Neo4j database successfully")
driver.close()

CRUD操作

接下来，我们将展示在Neo4j中如何进行基本的CRUD操作。

创建（Create）

driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password"))

with driver.session() as session:
    session.run("CREATE (:Employee {id: 1, name: 'John', age: 30, address: 'New York', salary: 1000.00})")

print("Node created successfully")

driver.close()

读取（Retrieve）

driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password"))

with driver.session() as session:
    result = session.run("MATCH (n:Employee) WHERE n.id = 1 RETURN n")
    for record in result:
        print("ID = ", record["n"]["id"])
        print("NAME = ", record["n"]["name"])
        print("ADDRESS = ", record["n"]["address"])
        print("SALARY = ", record["n"]["salary"])

driver.close()

更新（Update）

driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password"))

with driver.session() as session:
    session.run("MATCH (n:Employee) WHERE n.id = 1 SET n.salary = 25000.00")

print("Node updated successfully")

driver.close()

删除（Delete）

driver = GraphDatabase.driver("bolt://localhost:7687", auth=("neo4j", "password"))

with driver.session() as session:
    session.run("MATCH (n:Employee) WHERE n.id = 1 DETACH DELETE n")

print("Node deleted successfully")

driver.close()

InfluxDB

连接数据库

Python可以使用InfluxDB-Python库连接InfluxDB数据库：

from influxdb import InfluxDBClient
client = InfluxDBClient(host='localhost', port=8086)
print("Opened InfluxDB database successfully")
client.close()

CRUD操作

接下来，我们将展示在InfluxDB中如何进行基本的CRUD操作。

创建（Create）

client = InfluxDBClient(host='localhost', port=8086)

json_body = [
    {
        "measurement": "employees",
        "tags": {
            "id": "1"
        },
        "fields": {
            "name": "John",
            "age": 30,
            "address": "New York",
            "salary": 1000.00
        }
    }
]

client.write_points(json_body)

print("Point created successfully")

client.close()

读取（Retrieve）

client = InfluxDBClient(host='localhost', port=8086)

result = client.query('SELECT "name", "age", "address", "salary" FROM "employees"')

for point in result.get_points():
    print("ID = ", point['id'])
    print("NAME = ", point['name'])
    print("AGE = ", point['age'])
    print("ADDRESS = ", point['address'])
    print("SALARY = ", point['salary'])

client.close()

更新（Update）

InfluxDB的数据模型和其他数据库不同，它没有更新操作。但是你可以通过写入一个相同的数据点（即具有相同的时间戳和标签）并改变字段值，实现类似更新操作的效果。

删除（Delete）

同样，InfluxDB也没有提供删除单个数据点的操作。然而，你可以删除整个系列（即表）或者删除某个时间段的数据。

client = InfluxDBClient(host='localhost', port=8086)

# 删除整个系列
client.query('DROP SERIES FROM "employees"')

# 删除某个时间段的数据
# client.query('DELETE FROM "employees" WHERE time < now() - 1d')

print("Series deleted successfully")

client.close()

Snowflake

连接数据库

Python可以使用snowflake-connector-python库连接Snowflake数据库：

from snowflake.connector import connect
con = connect(
    user='username',
    password='password',
    account='account_url',
    warehouse='warehouse',
    database='database',
    schema='schema'
)
print("Opened Snowflake database successfully")
con.close()

CRUD操作

接下来，我们将展示在Snowflake中如何进行基本的CRUD操作。

创建（Create）

con = connect(
    user='username',
    password='password',
    account='account_url',
    warehouse='warehouse',
    database='database',
    schema='schema'
)

cur = con.cursor()
cur.execute("""
CREATE TABLE EMPLOYEES (
    ID INT,
    NAME STRING,
    AGE INT,
    ADDRESS STRING,
    SALARY FLOAT
)
""")

cur.execute("""
INSERT INTO EMPLOYEES (ID, NAME, AGE, ADDRESS, SALARY) VALUES
(1, 'John', 30, 'New York', 1000.00)
""")

print("Table created and row inserted successfully")

con.close()

读取（Retrieve）

con = connect(
    user='username',
    password='password',
    account='account_url',
    warehouse='warehouse',
    database='database',
    schema='schema'
)

cur = con.cursor()
cur.execute("SELECT * FROM EMPLOYEES WHERE ID = 1")

rows = cur.fetchall()

for row in rows:
    print("ID = ", row[0])
    print("NAME = ", row[1])
    print("AGE = ", row[2])
    print("ADDRESS = ", row[3])
    print("SALARY = ", row[4])

con.close()

更新（Update）

con = connect(
    user='username',
    password='password',
    account='account_url',
    warehouse='warehouse',
    database='database',
    schema='schema'
)

cur = con.cursor()
cur.execute("UPDATE EMPLOYEES SET SALARY = 25000.00 WHERE ID = 1")

print("Row updated successfully")

con.close()

删除（Delete）

con = connect(
    user='username',
    password='password',
    account='account_url',
    warehouse='warehouse',
    database='database',
    schema='schema'
)

cur = con.cursor()
cur.execute("DELETE FROM EMPLOYEES WHERE ID = 1")

print("Row deleted successfully")

con.close()

Amazon DynamoDB

连接数据库

Python可以使用boto3库连接Amazon DynamoDB：

import boto3
dynamodb = boto3.resource('dynamodb', region_name='us-west-2',
                          aws_access_key_id='Your AWS Access Key',
                          aws_secret_access_key='Your AWS Secret Key')
print("Opened DynamoDB successfully")

CRUD操作

接下来，我们将展示在DynamoDB中如何进行基本的CRUD操作。

创建（Create）

table = dynamodb.create_table(
    TableName='Employees',
    KeySchema=[
        {
            'AttributeName': 'id',
            'KeyType': 'HASH'
        },
    ],
    AttributeDefinitions=[
        {
            'AttributeName': 'id',
            'AttributeType': 'N'
        },
    ],
    ProvisionedThroughput={
        'ReadCapacityUnits': 5,
        'WriteCapacityUnits': 5
    }
)

table.put_item(
   Item={
        'id': 1,
        'name': 'John',
        'age': 30,
        'address': 'New York',
        'salary': 1000.00
    }
)

print("Table created and item inserted successfully")

读取（Retrieve）

table = dynamodb.Table('Employees')

response = table.get_item(
   Key={
        'id': 1,
    }
)

item = response['Item']
print(item)

更新（Update）

table = dynamodb.Table('Employees')

table.update_item(
    Key={
        'id': 1,
    },
    UpdateExpression='SET salary = :val1',
    ExpressionAttributeValues={
        ':val1': 25000.00
    }
)

print("Item updated successfully")

删除（Delete）

table = dynamodb.Table('Employees')

table.delete_item(
    Key={
        'id': 1,
    }
)

print("Item deleted successfully")

Microsoft Azure CosMos DB

连接数据库

Python可以使用azure-cosmos库连接Microsoft Azure CosMos DB：

from azure.cosmos import CosmosClient, PartitionKey, exceptions
url = 'Cosmos DB Account URL'
key = 'Cosmos DB Account Key'
client = CosmosClient(url, credential=key)
database_name = 'testDB'
database = client.get_database_client(database_name)
container_name = 'Employees'
container = database.get_container_client(container_name)
print("Opened CosMos DB successfully")

CRUD操作

接下来，我们将展示在CosMos DB中如何进行基本的CRUD操作。

创建（Create）

database = client.create_database_if_not_exists(id=database_name)

container = database.create_container_if_not_exists(
    id=container_name, 
    partition_key=PartitionKey(path="/id"),
    offer_throughput=400
)

container.upsert_item({
    'id': '1',
    'name': 'John',
    'age': 30,
    'address': 'New York',
    'salary': 1000.00
})

print("Container created and item upserted successfully")

读取（Retrieve）

for item in container.read_all_items():
    print(item)

更新（Update）

for item in container.read_all_items():
    if item['id'] == '1':
        item['salary'] = 25000.00
        container.upsert_item(item)
        
print("Item updated successfully")

删除（Delete）

for item in container.read_all_items():
    if item['id'] == '1':
        container.delete_item(item, partition_key='1')
        
print("Item deleted successfully")

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