Python is a popular programming language. It was created by Guido van Rossum and released in 1991.
1. Python syntax compared with other programming languages
- Python was designed for readability, has some similarities to English, and is influenced by mathematics.
- Python uses newlines to complete commands, unlike other programming languages that typically use semicolons or parentheses.
- Python relies on indentation, using spaces to define scope; such as the scope of loops, functions, and classes. Other programming languages often use curly braces for this purpose.
2. Data type checking
2.1 Basic type specification
For example:
def test(a: int, b: str) -> str:
print(a, b)
return 12345 # 返回值类型错误，pycharm解释器会警告
if __name__ == '__main__':
test(12, "wer")
test('test', "aaa") # 错误示例，一般pycharm解释器会警告
The function test above specifies that the input parameter a is of type int, and b is of type str, and the return value is of type srt. It can be seen that in the method, we finally returned an int, and pycharm will have a warning at this time; when we call this method, the parameter a we input is a string, and there will be a warning at this time; but it is very important The point is that pycharm only gives a warning, but in fact it will not report an error when running. After all, the essence of python is still a dynamic language.
2.2 Complex type specification
from typing import List
Vector = List[float]
def scale(scalar: float, vector: Vector) -> Vector:
return [scalar * num for num in vector]
# 类型检查，将float类型的集合赋值给vector集合
new_vector = scale(2.0, [1.0, -4.2, 5.4])
from typing import Dict, Tuple, Sequence
ConnectionOptions = Dict[str, str]
Address = Tuple[str, int]
Server = Tuple[Address, ConnectionOptions]
def broadcast_message(message: str, servers: Sequence[Server]) -> None:
pass
# 静态类型检查器将把之前的类型签名视为与这个签名完全等同
def broadcast_message(
message: str,
servers: Sequence[Tuple[Tuple[str, int], Dict[str, str]]]) -> None:
pass
2.3 Generic specification
from typing import Sequence, TypeVar, Union
T = TypeVar('T')
def first(l: Sequence[T]) -> T:
return l[0]
T = TypeVar('T') # 可以是任意类型
A = TypeVar('A', str, bytes) # 必须是str或bytes类型
A = Union[str, None] # 必须是str或None类型
2.4 Type specification when creating variables
from typing import NamedTuple
class Employee(NamedTuple):
name: str
id: int = 3
employee = Employee('Guido')
assert employee.id == 3
3. Python data types
3.1 Built-in data types
| type | keywords |
|---|---|
| text type: | str |
| Numeric type: | int, float, complex |
| sequence type: | list, tuple, range |
| Mapping type: | dict |
| collection type: | set, frozenset |
| Boolean type: | bool |
| Binary type: | bytes, bytearray, memoryview |
3.2 Set data type
| example | type of data |
|---|---|
| x = “Hello World” | str |
| x = 29 | int |
| x = 29.5 | float |
| x = 1j | complex |
| x = [“apple”, “banana”, “cherry”] | list |
| x = (“apple”, “banana”, “cherry”) | tuple |
| x = range(6) | range |
| x = {“name” : “Bill”, “age” : 63} | dict |
| x = {“apple”, “banana”, “cherry”} | set |
| x = frozenset({“apple”, “banana”, “cherry”}) | frozenset |
| x = True | bool |
| x = b"Hello" | bytes |
| x = bytearray(5) | bytearray |
| x = memoryview(bytes(5)) | memoryview |
3.3 Set a specific data type
| example | type of data |
|---|---|
| x = str(“Hello World”) | str |
| x = int(29) | int |
| x = float(29.5) | float |
| x = complex(1j) | complex |
| x = list((“apple”, “banana”, “cherry”)) | list |
| x = tuple((“apple”, “banana”, “cherry”)) | tuple |
| x = range(6) | range |
| x = dict(name=“Bill”, age=36) | dict |
| x = set((“apple”, “banana”, “cherry”)) | set |
| x = frozenset((“apple”, “banana”, “cherry”)) | frozenset |
| x = bool(5) | bool |
| x = bytes(5) | bytes |
| x = bytearray(5) | bytearray |
| x = memoryview(bytes(5)) | memoryview |