Python进阶教程（第二阶段）#

欢迎来到Python进阶教程的第二阶段！在第一阶段中，我们学习了Python的基础知识，包括环境搭建、语法基础、数据类型、控制流等内容。在本阶段中，我们将深入学习Python的高级特性，包括面向对象编程进阶、异常处理、正则表达式、数据库操作、Web开发等内容，帮助你成为一名更专业的Python开发者。

1. 面向对象编程进阶#

1.1 类的高级特性#

类方法和静态方法：

1
class Person:
2
    # 类变量
3
    species = "Homo sapiens"
4

5
    def __init__(self, name, age):
6
        self.name = name
7
        self.age = age
8

9
    # 实例方法
10
    def greet(self):
11
        return f"Hello, my name is {self.name}."
12

13
    # 类方法
14
    @classmethod
15
    def from_birth_year(cls, name, birth_year):
16
        current_year = 2026
17
        age = current_year - birth_year
18
        return cls(name, age)
19

20
    # 静态方法
21
    @staticmethod
22
    def is_adult(age):
23
        return age >= 18
24

25
# 使用类方法
26
person1 = Person.from_birth_year("John", 1996)
27
print(person1.name)
28
print(person1.age)
29

30
# 使用静态方法
31
print(Person.is_adult(18))
32
print(Person.is_adult(17))

属性装饰器：

1
class Person:
2
    def __init__(self, name, age):
3
        self.name = name
4
        self._age = age  # 私有变量（约定）
5

6
    @property
7
    def age(self):
8
        return self._age
9

10
    @age.setter
11
    def age(self, value):
12
        if value < 0:
13
            raise ValueError("Age cannot be negative")
14
        self._age = value
15

16
    @age.deleter
17
    def age(self):
18
        del self._age
19

20
person = Person("John", 30)
21
print(person.age)  # 使用@property获取值
22
person.age = 31  # 使用@age.setter设置值
23
print(person.age)
24
# person.age = -1  # 会报错
25
# del person.age  # 使用@age.deleter删除属性

抽象基类：

1
from abc import ABC, abstractmethod
2

3
class Animal(ABC):
4
    @abstractmethod
5
    def speak(self):
6
        pass
7

8
class Dog(Animal):
9
    def speak(self):
10
        return "Woof!"
11

12
class Cat(Animal):
13
    def speak(self):
14
        return "Meow!"
15

16
# animal = Animal()  # 会报错，抽象类不能实例化
17
dog = Dog()
18
print(dog.speak())
19
cat = Cat()
20
print(cat.speak())

1.2 继承和多态进阶#

多重继承：

1
class A:
2
    def method(self):
3
        print("Method from A")
4

5
class B:
6
    def method(self):
7
        print("Method from B")
8

9
class C(A, B):
10
    pass
11

12
class D(B, A):
13
    pass
14

15
c = C()
16
c.method()  # 输出"Method from A"，因为A在B之前
17

18
d = D()
19
d.method()  # 输出"Method from B"，因为B在A之前
20

21
# 查看方法解析顺序（MRO）
22
print(C.mro())
23
print(D.mro())

方法重写：

1
class Animal:
2
    def speak(self):
3
        return "Some generic sound"
4

5
class Dog(Animal):
6
    def speak(self):
7
        return "Woof!"
8

9
class Cat(Animal):
10
    def speak(self):
11
        return "Meow!"
12

13
animal = Animal()
14
print(animal.speak())
15

16
dog = Dog()
17
print(dog.speak())
18

19
cat = Cat()
20
print(cat.speak())

super()函数：

1
class Parent:
2
    def __init__(self, name):
3
        self.name = name
4
        print(f"Parent initialized with name: {self.name}")
5

6
class Child(Parent):
7
    def __init__(self, name, age):
8
        super().__init__(name)  # 调用父类的__init__方法
9
        self.age = age
10
        print(f"Child initialized with age: {self.age}")
11

12
child = Child("John", 10)
13
print(child.name)
14
print(child.age)

1.3 特殊方法#

常用特殊方法：

1
class Vector:
2
    def __init__(self, x, y):
3
        self.x = x
4
        self.y = y
5

6
    # 字符串表示
7
    def __str__(self):
8
        return f"Vector({self.x}, {self.y})"
9

10
    def __repr__(self):
11
        return f"Vector({self.x}, {self.y})"
12

13
    # 算术运算
14
    def __add__(self, other):
15
        return Vector(self.x + other.x, self.y + other.y)
16

17
    def __sub__(self, other):
18
        return Vector(self.x - other.x, self.y - other.y)
19

20
    def __mul__(self, scalar):
21
        return Vector(self.x * scalar, self.y * scalar)
22

23
    # 比较运算
24
    def __eq__(self, other):
25
        return self.x == other.x and self.y == other.y
26

27
    # 容器操作
28
    def __len__(self):
29
        return 2
30

31
    def __getitem__(self, index):
32
        if index == 0:
33
            return self.x
34
        elif index == 1:
35
            return self.y
36
        else:
37
            raise IndexError("Vector index out of range")
38

39
v1 = Vector(1, 2)
40
v2 = Vector(3, 4)
41

42
print(v1)  # 使用__str__
43
print(repr(v1))  # 使用__repr__
44

45
v3 = v1 + v2  # 使用__add__
46
print(v3)
47

48
v4 = v1 - v2  # 使用__sub__
49
print(v4)
50

51
v5 = v1 * 2  # 使用__mul__
52
print(v5)
53

54
print(v1 == v2)  # 使用__eq__
55
print(len(v1))  # 使用__len__
56
print(v1[0])  # 使用__getitem__
57
print(v1[1])  # 使用__getitem__

2. 异常处理#

2.1 异常类型#

常见异常：

SyntaxError：语法错误
NameError：名称错误（变量未定义）
TypeError：类型错误（操作不支持）
ValueError：值错误（值不合法）
ZeroDivisionError：除零错误
IndexError：索引错误（索引超出范围）
KeyError：键错误（字典键不存在）
FileNotFoundError：文件未找到错误
ImportError：导入错误

2.2 异常处理机制#

try-except：

1
try:
2
    # 可能引发异常的代码
3
    result = 10 / 0
4
except ZeroDivisionError:
5
    # 处理特定异常
6
    print("Cannot divide by zero")
7
except Exception as e:
8
    # 处理其他所有异常
9
    print(f"An error occurred: {e}")
10
else:
11
    # 没有异常时执行
12
    print(f"Result: {result}")
13
finally:
14
    # 无论是否有异常都执行
15
    print("Execution completed")

嵌套try-except：

1
try:
2
    try:
3
        result = 10 / 0
4
    except ZeroDivisionError:
5
        print("Inner except: Cannot divide by zero")
6
        raise  # 重新抛出异常
7
except Exception as e:
8
    print(f"Outer except: An error occurred: {e}")

2.3 自定义异常#

1
class MyError(Exception):
2
    """自定义异常类"""
3
    def __init__(self, message):
4
        self.message = message
5
        super().__init__(self.message)
6

7
class ValueTooSmallError(MyError):
8
    """值太小异常"""
9
    pass
10

11
class ValueTooLargeError(MyError):
12
    """值太大异常"""
13
    pass
14

15
# 使用自定义异常
16
def check_value(value):
17
    if value < 0:
18
        raise ValueTooSmallError("Value is too small")
19
    elif value > 100:
20
        raise ValueTooLargeError("Value is too large")
21
    else:
22
        print("Value is within range")
23

24
try:
25
    check_value(-1)
26
except ValueTooSmallError as e:
27
    print(f"Error: {e}")
28
except ValueTooLargeError as e:
29
    print(f"Error: {e}")
30
try:
31
    check_value(200)
32
except ValueTooSmallError as e:
33
    print(f"Error: {e}")
34
except ValueTooLargeError as e:
35
    print(f"Error: {e}")
36
try:
37
    check_value(50)
38
except ValueTooSmallError as e:
39
    print(f"Error: {e}")
40
except ValueTooLargeError as e:
41
    print(f"Error: {e}")

3. 正则表达式#

3.1 正则表达式基础#

正则表达式语法：

.：匹配任意字符（除换行符）
^：匹配字符串开头
$：匹配字符串结尾
\d：匹配数字
\D：匹配非数字
\w：匹配字母、数字、下划线
\W：匹配非字母、数字、下划线
\s：匹配空白字符
\S：匹配非空白字符
[abc]：匹配方括号内的任意字符
[^abc]：匹配除方括号内的任意字符
a|b：匹配a或b
a*：匹配0个或多个a
a+：匹配1个或多个a
a?：匹配0个或1个a
a{n}：匹配n个a
a{n,}：匹配至少n个a
a{n,m}：匹配n到m个a
(abc)：捕获组，匹配abc并捕获

3.2 re模块#

常用函数：

1
import re
2

3
# 1. match()：从字符串开头匹配
4
pattern = r"\d+"
5
text = "123abc"
6
match = re.match(pattern, text)
7
if match:
8
    print(f"Match found: {match.group()}")
9
else:
10
    print("No match")
11

12
# 2. search()：在整个字符串中查找匹配
13
pattern = r"\d+"
14
text = "abc123def"
15
search = re.search(pattern, text)
16
if search:
17
    print(f"Search found: {search.group()}")
18
else:
19
    print("No match")
20

21
# 3. findall()：查找所有匹配
22
pattern = r"\d+"
23
text = "abc123def456ghi"
24
findall = re.findall(pattern, text)
25
print(f"Findall found: {findall}")
26

27
# 4. finditer()：查找所有匹配并返回迭代器
28
pattern = r"\d+"
29
text = "abc123def456ghi"
30
for match in re.finditer(pattern, text):
31
    print(f"Match found at {match.start()}-{match.end()}: {match.group()}")
32

33
# 5. sub()：替换匹配
34
pattern = r"\d+"
35
text = "abc123def456ghi"
36
replaced = re.sub(pattern, "X", text)
37
print(f"Replaced text: {replaced}")
38

39
# 6. split()：根据匹配分割字符串
40
pattern = r"\d+"
41
text = "abc123def456ghi"
42
split = re.split(pattern, text)
43
print(f"Split text: {split}")

编译正则表达式：

1
import re
2

3
# 编译正则表达式（提高性能）
4
pattern = re.compile(r"\d+")
5

6
# 使用编译后的正则表达式
7
text = "abc123def456ghi"
8
print(pattern.findall(text))
9
print(pattern.sub("X", text))

3.3 正则表达式示例#

验证邮箱：

1
import re
2

3
def validate_email(email):
4
    pattern = r"^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\.[a-zA-Z0-9-.]+$")
5
    return bool(re.match(pattern, email))
6

7
emails = [
8
    "user@example.com",
9
    "user.name@example.com",
10
    "user_name@example.com",
11
    "user@example.co.uk",
12
    "user@",
13
    "@example.com",
14
    "user@.com"
15
]
16

17
for email in emails:
18
    print(f"{email}: {validate_email(email)}")

验证电话号码：

1
import re
2

3
def validate_phone(phone):
4
    pattern = r"^\+?[1-9]\d{1,14}$"
5
    return bool(re.match(pattern, phone))
6

7
phones = [
8
    "+1234567890",
9
    "1234567890",
10
    "+12345678901234",
11
    "123",
12
    "+0123456789",
13
    "abc123456789"
14
]
15

16
for phone in phones:
17
    print(f"{phone}: {validate_phone(phone)}")

提取URL：

1
import re
2

3
def extract_urls(text):
4
    pattern = r"https?://[\w\-._~:/?#[\]@!$&'()*+,;=.]+"
5
    return re.findall(pattern, text)
6

7
text = "Visit https://www.example.com and https://google.com for more information."
8
urls = extract_urls(text)
9
print(f"Extracted URLs: {urls}")

4. 数据库操作#

4.1 SQLite#

SQLite简介：

SQLite是一种轻量级的嵌入式数据库，不需要单独的服务器进程，数据存储在单个文件中。Python内置了对SQLite的支持，无需安装额外的库。

基本操作：

1
import sqlite3
2

3
# 连接到SQLite数据库（如果不存在则创建）
4
conn = sqlite3.connect('example.db')
5

6
# 创建游标
7
cursor = conn.cursor()
8

9
# 创建表
10
cursor.execute('''
11
CREATE TABLE IF NOT EXISTS users (
12
    id INTEGER PRIMARY KEY AUTOINCREMENT,
13
    name TEXT NOT NULL,
14
    email TEXT NOT NULL UNIQUE,
15
    age INTEGER
16
)
17
''')
18

19
# 插入数据
20
cursor.execute('''
21
INSERT INTO users (name, email, age) VALUES (?, ?, ?)
22
''', ('John', 'john@example.com', 30))
23

24
cursor.execute('''
25
INSERT INTO users (name, email, age) VALUES (?, ?, ?)
26
''', ('Jane', 'jane@example.com', 25))
27

28
# 提交事务
29
conn.commit()
30

31
# 查询数据
32
cursor.execute('SELECT * FROM users')
33
rows = cursor.fetchall()
34
print("All users:")
35
for row in rows:
36
    print(row)
37

38
# 条件查询
39
cursor.execute('SELECT * FROM users WHERE age > ?', (26,))
40
rows = cursor.fetchall()
41
print("\nUsers older than 26:")
42
for row in rows:
43
    print(row)
44

45
# 更新数据
46
cursor.execute('UPDATE users SET age = ? WHERE id = ?', (31, 1))
47
conn.commit()
48

49
# 删除数据
50
cursor.execute('DELETE FROM users WHERE id = ?', (2,))
51
conn.commit()
52

53
# 再次查询
54
cursor.execute('SELECT * FROM users')
55
rows = cursor.fetchall()
56
print("\nUsers after update and delete:")
57
for row in rows:
58
    print(row)
59

60
# 关闭游标和连接
61
cursor.close()
62
conn.close()

4.2 MySQL#

安装依赖：

1
pip install mysql-connector-python

基本操作：

1
import mysql.connector
2

3
# 连接到MySQL数据库
4
conn = mysql.connector.connect(
5
    host="localhost",
6
    user="username",
7
    password="password",
8
    database="mydatabase"
9
)
10

11
# 创建游标
12
cursor = conn.cursor()
13

14
# 创建表
15
cursor.execute('''
16
CREATE TABLE IF NOT EXISTS users (
17
    id INT AUTO_INCREMENT PRIMARY KEY,
18
    name VARCHAR(255) NOT NULL,
19
    email VARCHAR(255) NOT NULL UNIQUE,
20
    age INT
21
)
22
''')
23

24
# 插入数据
25
cursor.execute('''
26
INSERT INTO users (name, email, age) VALUES (%s, %s, %s)
27
''', ('John', 'john@example.com', 30))
28

29
cursor.execute('''
30
INSERT INTO users (name, email, age) VALUES (%s, %s, %s)
31
''', ('Jane', 'jane@example.com', 25))
32

33
# 提交事务
34
conn.commit()
35

36
# 查询数据
37
cursor.execute('SELECT * FROM users')
38
rows = cursor.fetchall()
39
print("All users:")
40
for row in rows:
41
    print(row)
42

43
# 条件查询
44
cursor.execute('SELECT * FROM users WHERE age > %s', (26,))
45
rows = cursor.fetchall()
46
print("\nUsers older than 26:")
47
for row in rows:
48
    print(row)
49

50
# 更新数据
51
cursor.execute('UPDATE users SET age = %s WHERE id = %s', (31, 1))
52
conn.commit()
53

54
# 删除数据
55
cursor.execute('DELETE FROM users WHERE id = %s', (2,))
56
conn.commit()
57

58
# 再次查询
59
cursor.execute('SELECT * FROM users')
60
rows = cursor.fetchall()
61
print("\nUsers after update and delete:")
62
for row in rows:
63
    print(row)
64

65
# 关闭游标和连接
66
cursor.close()
67
conn.close()

4.3 PostgreSQL#

安装依赖：

1
pip install psycopg2-binary

基本操作：

1
import psycopg2
2

3
# 连接到PostgreSQL数据库
4
conn = psycopg2.connect(
5
    host="localhost",
6
    user="username",
7
    password="password",
8
    database="mydatabase"
9
)
10

11
# 创建游标
12
cursor = conn.cursor()
13

14
# 创建表
15
cursor.execute('''
16
CREATE TABLE IF NOT EXISTS users (
17
    id SERIAL PRIMARY KEY,
18
    name VARCHAR(255) NOT NULL,
19
    email VARCHAR(255) NOT NULL UNIQUE,
20
    age INTEGER
21
)
22
''')
23

24
# 插入数据
25
cursor.execute('''
26
INSERT INTO users (name, email, age) VALUES (%s, %s, %s)
27
''', ('John', 'john@example.com', 30))
28

29
cursor.execute('''
30
INSERT INTO users (name, email, age) VALUES (%s, %s, %s)
31
''', ('Jane', 'jane@example.com', 25))
32

33
# 提交事务
34
conn.commit()
35

36
# 查询数据
37
cursor.execute('SELECT * FROM users')
38
rows = cursor.fetchall()
39
print("All users:")
40
for row in rows:
41
    print(row)
42

43
# 条件查询
44
cursor.execute('SELECT * FROM users WHERE age > %s', (26,))
45
rows = cursor.fetchall()
46
print("\nUsers older than 26:")
47
for row in rows:
48
    print(row)
49

50
# 更新数据
51
cursor.execute('UPDATE users SET age = %s WHERE id = %s', (31, 1))
52
conn.commit()
53

54
# 删除数据
55
cursor.execute('DELETE FROM users WHERE id = %s', (2,))
56
conn.commit()
57

58
# 再次查询
59
cursor.execute('SELECT * FROM users')
60
rows = cursor.fetchall()
61
print("\nUsers after update and delete:")
62
for row in rows:
63
    print(row)
64

65
# 关闭游标和连接
66
cursor.close()
67
conn.close()

5. Web开发#

5.1 Flask#

安装Flask：

1
pip install flask

基本应用：

1
from flask import Flask, render_template, request, redirect, url_for
2

3
app = Flask(__name__)
4

5
# 路由
6
@app.route('/')
7
def index():
8
    return 'Hello, World!'
9

10
@app.route('/hello/<name>')
11
def hello(name):
12
    return f'Hello, {name}!'
13

14
@app.route('/form', methods=['GET', 'POST'])
15
def form():
16
    if request.method == 'POST':
17
        name = request.form['name']
18
        return redirect(url_for('hello', name=name))
19
    return '''
20
    <form method="post">
21
        <input type="text" name="name" placeholder="Enter your name">
22
        <input type="submit" value="Submit">
23
    </form>
24
    '''
25

26
if __name__ == '__main__':
27
    app.run(debug=True)

模板：

创建templates目录，添加index.html文件：

1
<!DOCTYPE html>
2
<html>
3
<head>
4
    <title>Flask App</title>
5
</head>
6
<body>
7
    <h1>Hello, {{ name }}!</h1>
8
    <form method="post">
9
        <input type="text" name="name" placeholder="Enter your name">
10
        <input type="submit" value="Submit">
11
    </form>
12
</body>
13
</html>

修改Flask应用：

1
from flask import Flask, render_template, request, redirect, url_for
2

3
app = Flask(__name__)
4

5
@app.route('/', methods=['GET', 'POST'])
6
def index():
7
    if request.method == 'POST':
8
        name = request.form['name']
9
        return render_template('index.html', name=name)
10
    return render_template('index.html', name='World')
11

12
if __name__ == '__main__':
13
    app.run(debug=True)

5.2 Django#

安装Django：

1
pip install django

创建Django项目：

1
django-admin startproject myproject
2
cd myproject
3
python manage.py startapp myapp

基本配置：

修改myproject/settings.py，添加myapp到INSTALLED_APPS：

1
INSTALLED_APPS = [
2
    'django.contrib.admin',
3
    'django.contrib.auth',
4
    'django.contrib.contenttypes',
5
    'django.contrib.sessions',
6
    'django.contrib.messages',
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    'django.contrib.staticfiles',
8
    'myapp',
9
]

修改myapp/views.py：

1
from django.shortcuts import render
2
from django.http import HttpResponse
3

4
def index(request):
5
    return HttpResponse("Hello, World!")
6

7
def hello(request, name):
8
    return HttpResponse(f"Hello, {name}!")

创建myapp/urls.py：

1
from django.urls import path
2
from . import views
3

4
urlpatterns = [
5
    path('', views.index, name='index'),
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    path('hello/<str:name>/', views.hello, name='hello'),
7
]

修改myproject/urls.py：

1
from django.contrib import admin
2
from django.urls import path, include
3

4
urlpatterns = [
5
    path('admin/', admin.site.urls),
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    path('', include('myapp.urls')),
7
]

运行开发服务器：

1
python manage.py runserver

6. 并发编程#

6.1 线程#

基本使用：

1
import threading
2
import time
3

4
def worker(name, delay):
5
    print(f"Worker {name} started")
6
    time.sleep(delay)
7
    print(f"Worker {name} finished")
8

9
# 创建线程
10
thread1 = threading.Thread(target=worker, args=('A', 2))
11
thread2 = threading.Thread(target=worker, args=('B', 1))
12

13
# 启动线程
14
thread1.start()
15
thread2.start()
16

17
# 等待线程完成
18
thread1.join()
19
thread2.join()
20

21
print("All workers finished")

线程安全：

1
import threading
2

3
counter = 0
4
lock = threading.Lock()
5

6
def increment():
7
    global counter
8
    for _ in range(100000):
9
        with lock:  # 使用锁确保线程安全
10
            counter += 1
11

12
# 创建线程
13
threads = []
14
for i in range(10):
15
    thread = threading.Thread(target=increment)
16
    threads.append(thread)
17
    thread.start()
18

19
# 等待所有线程完成
20
for thread in threads:
21
    thread.join()
22

23
print(f"Final counter value: {counter}")

6.2 进程#

基本使用：

1
import multiprocessing
2
import time
3

4
def worker(name, delay):
5
    print(f"Worker {name} started")
6
    time.sleep(delay)
7
    print(f"Worker {name} finished")
8

9
if __name__ == '__main__':
10
    # 创建进程
11
    process1 = multiprocessing.Process(target=worker, args=('A', 2))
12
    process2 = multiprocessing.Process(target=worker, args=('B', 1))
13

14
    # 启动进程
15
    process1.start()
16
    process2.start()
17

18
    # 等待进程完成
19
    process1.join()
20
    process2.join()
21

22
    print("All workers finished")

进程池：

1
import multiprocessing
2
import time
3

4
def worker(name):
5
    print(f"Worker {name} started")
6
    time.sleep(1)
7
    print(f"Worker {name} finished")
8
    return f"Result from worker {name}"
9

10
if __name__ == '__main__':
11
    # 创建进程池
12
    with multiprocessing.Pool(processes=4) as pool:
13
        # 映射函数到多个参数
14
        results = pool.map(worker, [1, 2, 3, 4, 5])
15
        print(f"Results: {results}")
16

17
    print("All workers finished")

6.3 异步编程#

asyncio：

1
import asyncio
2

3
async def worker(name, delay):
4
    print(f"Worker {name} started")
5
    await asyncio.sleep(delay)
6
    print(f"Worker {name} finished")
7
    return f"Result from worker {name}"
8

9
async def main():
10
    # 并发执行多个协程
11
    tasks = [
12
        worker('A', 2),
13
        worker('B', 1),
14
        worker('C', 3)
15
    ]
16

17
    # 等待所有任务完成
18
    results = await asyncio.gather(*tasks)
19
    print(f"Results: {results}")
20

21
# 运行主协程
22
asyncio.run(main())

7. 数据分析#

7.1 NumPy#

安装NumPy：

1
pip install numpy

基本操作：

1
import numpy as np
2

3
# 创建数组
4
arr1 = np.array([1, 2, 3, 4, 5])
5
arr2 = np.array([[1, 2, 3], [4, 5, 6]])
6
print(f"arr1 shape: {arr1.shape}")
7
print(f"arr2 shape: {arr2.shape}")
8

9
# 数组操作
10
print(f"arr1 + 1: {arr1 + 1}")
11
print(f"arr1 * 2: {arr1 * 2}")
12
print(f"arr1 mean: {arr1.mean()}")
13
print(f"arr1 sum: {arr1.sum()}")
14
print(f"arr1 max: {arr1.max()}")
15
print(f"arr1 min: {arr1.min()}")
16

17
# 矩阵运算
18
arr3 = np.array([[1, 2], [3, 4]])
19
arr4 = np.array([[5, 6], [7, 8]])
20
print(f"arr3 + arr4:\n{arr3 + arr4}")
21
print(f"arr3 * arr4:\n{arr3 * arr4}")  # 元素级乘法
22
print(f"arr3 @ arr4:\n{arr3 @ arr4}")  # 矩阵乘法
23

24
# 数组索引和切片
25
print(f"arr1[0]: {arr1[0]}")
26
print(f"arr1[1:4]: {arr1[1:4]}")
27
print(f"arr2[0, 1]: {arr2[0, 1]}")
28
print(f"arr2[:, 1]: {arr2[:, 1]}")
29

30
# 特殊数组
31
print(f"Zeros:\n{np.zeros((2, 3))}")
32
print(f"Ones:\n{np.ones((2, 3))}")
33
print(f"Identity matrix:\n{np.eye(3)}")
34
print(f"Range: {np.arange(10)}")
35
print(f"Linspace: {np.linspace(0, 1, 5)}")

7.2 Pandas#

安装Pandas：

1
pip install pandas

基本操作：

1
import pandas as pd
2

3
# 创建Series
4
s = pd.Series([1, 2, 3, 4, 5], index=['a', 'b', 'c', 'd', 'e'])
5
print(f"Series:\n{s}")
6

7
# 创建DataFrame
8
data = {
9
    'name': ['John', 'Jane', 'Bob', 'Alice'],
10
    'age': [30, 25, 35, 28],
11
    'city': ['New York', 'London', 'Paris', 'Tokyo']
12
}
13
df = pd.DataFrame(data)
14
print(f"DataFrame:\n{df}")
15

16
# 数据访问
17
print(f"df['name']:\n{df['name']}")
18
print(f"df.loc[0]:\n{df.loc[0]}")
19
print(f"df.iloc[0, 1]: {df.iloc[0, 1]}")
20

21
# 数据过滤
22
print(f"df[df['age'] > 28]:\n{df[df['age'] > 28]}")
23

24
# 数据排序
25
print(f"df sorted by age:\n{df.sort_values('age')}")
26

27
# 数据分组
28
print(f"Mean age by city:\n{df.groupby('city')['age'].mean()}")
29

30
# 数据统计
31
print(f"df describe:\n{df.describe()}")
32

33
# 缺失值处理
34
df.loc[0, 'age'] = None
35
print(f"df with NaN:\n{df}")
36
print(f"df filled:\n{df.fillna(0)}")
37
print(f"df dropped:\n{df.dropna()}")
38

39
# 读取和写入数据
40
# df.to_csv('data.csv', index=False)
41
# df_read = pd.read_csv('data.csv')

7.3 Matplotlib#

安装Matplotlib：

1
pip install matplotlib

基本绘图：

1
import matplotlib.pyplot as plt
2
import numpy as np
3

4
# 折线图
5
x = np.linspace(0, 10, 100)
6
y = np.sin(x)
7

8
plt.plot(x, y)
9
plt.title('Sine Wave')
10
plt.xlabel('x')
11
plt.ylabel('sin(x)')
12
plt.grid(True)
13
plt.show()
14

15
# 散点图
16
x = np.random.rand(100)
17
y = np.random.rand(100)
18
colors = np.random.rand(100)
19
sizes = 1000 * np.random.rand(100)
20

21
plt.scatter(x, y, c=colors, s=sizes, alpha=0.5)
22
plt.title('Scatter Plot')
23
plt.xlabel('x')
24
plt.ylabel('y')
25
plt.show()
26

27
# 柱状图
28
categories = ['A', 'B', 'C', 'D', 'E']
29
values = [10, 20, 15, 25, 30]
30

31
plt.bar(categories, values)
32
plt.title('Bar Chart')
33
plt.xlabel('Category')
34
plt.ylabel('Value')
35
plt.show()
36

37
# 直方图
38
data = np.random.randn(1000)
39

40
plt.hist(data, bins=30)
41
plt.title('Histogram')
42
plt.xlabel('Value')
43
plt.ylabel('Frequency')
44
plt.show()

8. 学习资源推荐#

8.1 Python官方文档#

8.2 B站Python视频（播放量高于50W）#

8.3 推荐书籍#

《流畅的Python》
《Python Cookbook》
《Effective Python》
《Python编程：从入门到实践》
《Python数据科学手册》
《Django实战》
《Flask Web开发》

9. 总结#

本教程介绍了Python的高级特性，包括：

面向对象编程进阶（类方法、静态方法、属性装饰器、抽象基类、多重继承等）
异常处理（异常类型、异常处理机制、自定义异常）
正则表达式（语法、re模块、常见应用）
数据库操作（SQLite、MySQL、PostgreSQL）
Web开发（Flask、Django）
并发编程（线程、进程、异步编程）
数据分析（NumPy、Pandas、Matplotlib）

通过本教程的学习，你应该已经掌握了Python的高级特性，可以开始编写更复杂、更专业的Python程序了。在接下来的教程中，我们将学习Python的实际应用场景和项目实战。

祝你学习愉快！

提示：本教程是Python学习的第二阶段，后续将推出Python项目实战教程，包括Web应用开发、数据分析项目、爬虫项目等内容。

私のブログ

Python进阶教程（第二阶段）#

1. 面向对象编程进阶#

1.1 类的高级特性#

1.2 继承和多态进阶#

1.3 特殊方法#

2. 异常处理#

2.1 异常类型#

2.2 异常处理机制#

2.3 自定义异常#

3. 正则表达式#

3.1 正则表达式基础#

3.2 re模块#

3.3 正则表达式示例#

4. 数据库操作#

4.1 SQLite#

4.2 MySQL#

4.3 PostgreSQL#

5. Web开发#

5.1 Flask#

5.2 Django#

6. 并发编程#

6.1 线程#

6.2 进程#

6.3 异步编程#

7. 数据分析#

7.1 NumPy#

7.2 Pandas#

7.3 Matplotlib#

8. 学习资源推荐#

8.1 Python官方文档#

8.2 B站Python视频（播放量高于50W）#

8.3 推荐书籍#

9. 总结#