# Python 3 快速参考

*基础到 pandas、requests、csv、json*

> Source: Official Python documentation (docs.python.org) · MIT

## 基础

### 变量

```
name = "Alice"   # str
age = 20         # int
gpa = 3.85       # float
active = True    # bool
```

### 数据类型

| Command | Description |
|---------|-------------|
| `str` | 文本：`"hello"` |
| `int` | 整数：`42` |
| `float` | 小数：`3.14` |
| `bool` | `True` / `False` |
| `list` | 有序可变：`[1, 2, 3]` |
| `tuple` | 有序不可变：`(1, 2)` |
| `dict` | 键值对：`{"a": 1}` |
| `set` | 唯一元素集合：`{1, 2, 3}` |

### 算术运算

| Command | Description |
|---------|-------------|
| `+ - *` | 加、减、乘 |
| `/` | 除法（浮点）：7/2 → 3.5 |
| `//` | 整除：7//2 → 3 |
| `%` | 取模：7%2 → 1 |
| `**` | 幂运算：2**3 → 8 |

### 类型转换

```
int("42")     # 42
float("3.14") # 3.14
str(100)      # "100"
list("abc")   # ['a','b','c']
```

### 用户输入

```
name = input("Your name? ")
age = int(input("Age? "))
```

## 字符串

### 创建字符串

```
s1 = 'single quotes'
s2 = "double quotes"
s3 = """triple quotes
    for multiline"""
```

### f-String（Python 3.6+）

```
name = "Alice"
f"Hello, {name}!"  # Hello, Alice!
f"{2 + 3}"         # 5
f"{3.14159:.2f}"   # 3.14
f"{1000:,}"        # 1,000
```

### 字符串切片

```
s = "Python"
# Index: 0 1 2 3 4 5
s[0]    # 'P'
s[-1]   # 'n'
s[2:5]  # 'tho'
s[:2]   # 'Py'
s[2:]   # 'thon'
s[::-1] # 'nohtyP' (reverse)
```

### 字符串方法

| Command | Description |
|---------|-------------|
| `len(s)` | 字符串长度 |
| `s.upper()` | 转大写 |
| `s.lower()` | 转小写 |
| `s.strip()` | 去除首尾空白 |
| `s.split(",")` | 分割为列表 |
| `",".join(lst)` | 列表合并为字符串 |
| `s.replace(a, b)` | 将 a 替换为 b |
| `s.find("x")` | 首个匹配的索引（未找到返回 -1） |
| `s.startswith(x)` | 检查前缀 → bool |
| `s.endswith(x)` | 检查后缀 → bool |
| `s.count(x)` | 统计出现次数 |
| `"x" in s` | 包含检查 → bool |

## 列表

### 创建与访问

```
fruits = ["apple", "banana", "cherry"]
fruits[0]   # "apple"
fruits[-1]  # "cherry"
fruits[1:3] # ["banana", "cherry"]
```

### 列表推导式

```
squares = [x**2 for x in range(5)]
# [0, 1, 4, 9, 16]
evens = [x for x in range(10) if x%2==0]
# [0, 2, 4, 6, 8]
```

### 列表方法

| Command | Description |
|---------|-------------|
| `lst.append(x)` | 追加到末尾 |
| `lst.extend(lst2)` | 追加 lst2 的所有元素 |
| `lst.insert(i, x)` | 在索引 i 处插入 |
| `lst.pop()` | 移除并返回最后一个元素 |
| `lst.pop(i)` | 移除并返回索引 i 处的元素 |
| `lst.remove(x)` | 移除第一个 x |
| `del lst[i]` | 按索引删除 |
| `lst.sort()` | 原地排序 |
| `sorted(lst)` | 返回排序副本 |
| `lst.reverse()` | 原地反转 |
| `len(lst)` | 元素数量 |
| `x in lst` | 成员检查 |
| `lst.index(x)` | x 的第一个索引 |
| `lst.count(x)` | x 的出现次数 |

## 元组与集合

### 元组（不可变）

```
point = (3, 4)
x, y = point  # unpacking
point[0]      # 3 (read-only)
```

### 集合（唯一元素）

```
s = {1, 2, 3}
s.add(4); s.remove(1)
a & b  # intersection
a | b  # union
a - b  # difference
```

## 字典

### 创建与访问

```
student = {"name": "Alice", "age": 20}
student["name"]      # "Alice"
student.get("gpa", 0) # 0 (default)
student["gpa"] = 3.85  # add/update
```

### 字典推导式

```
sq = {x: x**2 for x in range(5)}
# {0:0, 1:1, 2:4, 3:9, 4:16}
```

### 遍历

```
for k, v in student.items():
    print(f"{k}: {v}")
```

### 字典方法

| Command | Description |
|---------|-------------|
| `d.keys()` | 所有键 |
| `d.values()` | 所有值 |
| `d.items()` | 所有（键, 值）对 |
| `d.get(k, default)` | 获取值，带默认值 |
| `d.update(d2)` | 将 d2 合并到 d |
| `d.pop(k)` | 移除并返回值 |
| `del d[k]` | 删除键 |
| `"k" in d` | 键是否存在 → bool |
| `len(d)` | 条目数量 |

## 控制流

### if / elif / else

```
if score >= 90:
    grade = "A"
elif score >= 80:
    grade = "B"
else:
    grade = "C"
```

### 三元表达式

```
status = "pass" if score >= 60 else "fail"
```

## 循环

### for 循环

```
for fruit in ["apple", "banana"]:
    print(fruit)
```

### range()

```
range(5)        # 0, 1, 2, 3, 4
range(2, 5)     # 2, 3, 4
range(0, 10, 2) # 0, 2, 4, 6, 8
```

### while 循环

```
while count < 10:
    count += 1
```

### enumerate() 与 zip()

```
for i, val in enumerate(["a", "b"]):
    print(i, val) # 0 a, 1 b

for a, b in zip([1, 2], ["x", "y"]):
    print(a, b) # 1 x, 2 y
```

### break 与 continue

```
for x in range(10):
    if x == 5: break      # stop loop
    if x % 2 == 0: continue # skip
```

## 函数

### 定义与调用

```
def greet(name, greeting="Hi"):
    return f"{greeting}, {name}!"

greet("Alice")        # "Hi, Alice!"
greet("Bob", "Hello") # "Hello, Bob!"
```

### 多返回值

```
def min_max(lst):
    return min(lst), max(lst)
lo, hi = min_max([3, 1, 4, 1, 5])
```

### *args 与 **kwargs

```
def total(*args): # args is a tuple
    return sum(args)
total(1, 2, 3) # 6

def info(**kwargs): # kwargs is a dict
    print(kwargs)
```

### Lambda 函数

```
square = lambda x: x**2
square(5) # 25
sorted(lst, key=lambda x: x["age"])
```

## 类

```
class Dog:
    def __init__(self, name, breed):
        self.name = name
        self.breed = breed

    def bark(self):
        return f"{self.name} says Woof!"

dog = Dog("Rex", "Lab")
dog.bark() # "Rex says Woof!"
```

### 继承

```
class Puppy(Dog):
    def __init__(self, name, breed, toy):
        super().__init__(name, breed)
        self.toy = toy
```

## 异常处理

```
try:
    result = 10 / 0
except ZeroDivisionError as e:
    print(f"Error: {e}")
finally:
    print("Always runs")
```

## 文件读写

### 读取文件

```
with open("data.txt") as f:
    content = f.read() # full text

with open("data.txt") as f:
    for line in f: # line by line
        print(line.strip())
```

### 写入文件

```
with open("out.txt", "w") as f:
    f.write("Hello\n")
```

*"r" = 读  "w" = 写（覆盖）  "a" = 追加*

## CSV

```
import csv

with open("data.csv") as f:
    reader = csv.DictReader(f)
    for row in reader:
        print(row["name"])

with open("out.csv", "w", newline="") as f:
    writer = csv.writer(f)
    writer.writerow(["name", "age"])
```

## JSON

```
import json

data = json.loads('{"name":"Alice"}') # parse
text = json.dumps(data)               # serialize

with open("data.json") as f:
    data = json.load(f)               # read file
with open("out.json", "w") as f:
    json.dump(data, f, indent=2)      # write file
```

## HTTP 请求

```
import requests

# GET
r = requests.get("https://api.example.com/data")
r.status_code # 200
data = r.json() # parse JSON

# POST
r = requests.post(url, json={"key": "val"})
```

## pandas 基础

```
import pandas as pd
df = pd.read_csv("data.csv")
df.head()           # first 5 rows
df.shape            # (rows, cols)
df["name"]          # single column
df[df["age"] > 20]  # filter rows
```

## 常用内置函数

| Command | Description |
|---------|-------------|
| `print()` | 输出到控制台 |
| `len()` | 长度 / 数量 |
| `type()` | 对象类型 |
| `range()` | 数字序列 |
| `enumerate()` | 索引 + 值对 |
| `zip()` | 配对多个可迭代对象 |
| `sorted()` | 返回排序副本 |
| `sum() min() max()` | 聚合函数 |

## 模块

```
import math
from math import sqrt, pi
import pandas as pd # alias
```