Python技术参考大全

Python技术参考大全是一份综合性的Python编程技术指南，涵盖了Python的各个方面，包括语法基础、内置库、常用模块以及常见应用场景等。本文将从多个方面对Python技术参考大全进行详细阐述。

一、语法基础

1、Python基本语法

def hello_world():
    print("Hello, World!")

hello_world()

2、Python数据类型

num = 10
print(type(num))  # 输出

str_val = "Hello"
print(type(str_val))  # 输出

3、条件和循环语句

if num > 0:
    print("Positive")
elif num < 0:
    print("Negative")
else:
    print("Zero")

for i in range(5):
    print(i)

while num > 0:
    print(num)
    num -= 1

二、内置库

1、数学库math

import math

num = 16
sqrt_val = math.sqrt(num)
print(sqrt_val)

2、文件操作库os

import os

file_path = "data.txt"
if os.path.exists(file_path):
    with open(file_path, "r") as file:
        content = file.read()
        print(content)
else:
    print("File not found.")

3、日期时间库datetime

import datetime

now = datetime.datetime.now()
print(now)

today = datetime.date.today()
print(today)

三、常用模块

1、数据处理模块pandas

import pandas as pd

data = {'Name': ['John', 'Tom', 'Alice'],
        'Age': [25, 30, 28]}
df = pd.DataFrame(data)
print(df)

2、网络请求模块requests

import requests

url = "https://i.enlanhao.com/pic/pprefrom PIL import Imageimage = Image.open(image.jpg")
image.show()

四、常见应用场景

1、Web开发

from flask import Flask

app = Flask(__name__)

@app.route('/')
def hello_world():
    return 'Hello, World!'

if __name__ == '__main__':
    app.run()

2、数据分析与可视化

import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 2*np.pi, 100)
y = np.sin(x)

plt.plot(x, y)
plt.show()

3、机器学习

from sklearn import datasets
from sklearn.model_selection import train_test_split
from sklearn.linear_model import LogisticRegression

iris = datasets.load_iris()
X_train, X_test, y_train, y_test = train_test_split(iris.data, iris.target, test_size=0.2)

model = LogisticRegression()
model.fit(X_train, y_train)
y_pred = model.predict(X_test)

本文从语法基础、内置库、常用模块以及常见应用场景等多个方面对Python技术参考大全进行了详细阐述。希望这篇文章能够帮助你更好地了解和运用Python编程技术。