🐍 Python 全景速通:从解释器到生态,一篇吃透!

62 阅读2分钟

微信图片_20251014151033_10_20.jpg

① 解释器 & 安装:一句话搞定

# 国内镜像极速安装
python -m pip install -i https://pypi.tuna.tsinghua.edu.cn/simple -U pip
>>> import this   # Python 之道,背它!

② 语法速写:一张图背完📜

关键字场景一行 Demo
if三元表达式x = a if a > 0 else 0
for列表推导[i*2 for i in range(5)]
while海象运算符while (line := f.readline()):
try上下文管理with open('f') as f: ...
def函数def add(a, b=1): return a + b
class数据类@dataclass class Point: x: int
import别名import pandas as pd

③ 超常用数据类型:8 个走天下🌟

# 基本
int float bool str list tuple dict set
# 一行生成
lst = [1, 2, 3]
d = {'a': 1, 'b': 2}
t = (1, 2, 3)          # 单元素 (1,)
s = {1, 2, 2}          # 去重 {1, 2}

④ 趣味实战:彩色骑行排行榜 🌈

import csv, os
from pathlib import Path

riders = [(row[0], float(row[1])) for row in csv.reader(Path("riders.txt").read_text().splitlines())]
riders.sort(key=lambda x: x[1], reverse=True)

print("\033[36m🏆 骑行排行榜 🏆\033[0m")
for i, (name, km) in enumerate(riders, 1):
    bar = "█" * int(km / riders[0][1] * 30)
    print(f"{i:2}. {name:<8} {km:6.1f}km |{bar}")

运行:python rank.py → 终端彩色条!


⑤ 并发提速:线程池一把梭⚙️

from concurrent.futures import ThreadPoolExecutor as Pool
with Pool() as p:
    results = p.map(str.upper, ['a', 'b', 'c'])
print(list(results))  # ['A', 'B', 'C']

⑥ Web 速通:Flask 5 行 REST 🌐

from flask import Flask, request
app = Flask(__name__)

@app.route("/hello")
def hi(name=request.args.get("name", "world")):
    return f"Hello, {name}!"

启动:flask runhttp://127.0.0.1:5000/hello?name=Python


⑦ 数据科学:pandas 一行绘图📊

import pandas as pd, matplotlib.pyplot as plt
df = pd.read_csv("sales.csv")
df.groupby("month")["sales"].sum().plot(kind="bar")
plt.show()

⑧ 打包上线:pip install 你的代码📦

# pyproject.toml 极简
[project]
name = "mypkg"
version = "0.1.0"
dependencies = ["flask"]
python -m pip install build
python -m build
twine upload dist/*

⑨ 性能锦囊:3 个加速技巧⚡️

技巧代码效果
向量化np.array(lst) * 2比列表循环快 40×
列表推导[f(x) for x in data]比 map+lambda 直观
并发concurrent.futures.ProcessPoolExecutorCPU 密集并行

⑩ 学习路线图(可保存)

基础语法 → 集合/IO → 并发 → Flask → 数据 → Docker → 云原生
    ⏱️ 2周      ⏱️ 1周    ⏱️ 1周   ⏱️ 2周   ⏱️ 2周  ⏱️ 3天   ⏱️ 持续