Python Basics: Numbers, Strings, Functions, Data Structures, Classes, and Tools

This tutorial introduces essential Python concepts, starting with numeric operations such as absolute value, base conversions, complex numbers, and arithmetic utilities like abs, bin, oct, hex, divmod, round, and pow. It also demonstrates logical checks using all and any, and boolean conversion with bool.

In [1]: abs(-6)
Out[1]: 6
In [2]: bin(10)
Out[2]: '0b1010'
In [3]: oct(9)
Out[3]: '0o11'
In [4]: hex(15)
Out[4]: '0xf'
In [5]: divmod(10, 3)
Out[5]: (3, 1)
In[6]: round(10.0222222, 3)
Out[6]: 10.022
In[7]: pow(3, 2, 4)
Out[7]: 1

String handling examples include converting strings to bytes, casting objects to strings, executing code stored in strings, evaluating expressions, and formatting output with format:

In [12]: s = "apple"
In [13]: bytes(s, encoding='utf-8')
Out[13]: b'apple'
In [14]: str(100)
Out[14]: '100'
In [15]: exec(compile("print('helloworld')", "<string>", "exec"))
helloworld
In [16]: eval("1 + 3 + 5")
Out[16]: 9
In [18]: "i am {0},age{1}".format("tom", 18)
Out[18]: 'i am tom,age18'

Function utilities cover built‑in functions such as sorted, sum, and custom functions demonstrating variable arguments, keyword‑only arguments, and lambda expressions:

def max_len(*lists):
    return max(*lists, key=lambda v: len(v))

max_len([1,2,3], [4,5,6,7], [8])  # returns the longest list

Data‑structure sections show how to create dictionaries, frozensets, sets, slices, tuples, and how to convert between them:

dict(a=1, b=2)
frozenset([1,1,3,2,3])
set([1,4,2,3,1])
slice(1,10,2)
tuple([1,3,5])

The class and object part explains defining classes, using __init__, __repr__, checking callability, adding attributes dynamically, using classmethod, property decorators, and introspection functions like callable, hasattr, getattr, isinstance, issubclass, and type:

class Student:
    def __init__(self, id, name):
        self.id = id
        self.name = name
    def __repr__(self):
        return f'id = {self.id}, name = {self.name}'

xiaoming = Student('001', 'xiaoming')
print(callable(xiaoming))  # False
print(hasattr(xiaoming, 'name'))  # True

Tools covered include enumeration, size inspection with sys.getsizeof, filtering with filter, hashing with hash, help documentation, file I/O with open, range generation, reversed iteration, zip aggregation, chained operations, and JSON serialization of objects:

import sys
sys.getsizeof({"a":1, "b":2.0})  # 240 bytes

filtered = filter(lambda x: x>10, [1,11,2,45,7,6,13])
list(filtered)  # [11, 45, 13]

with open('json.txt', 'w', encoding='utf-8') as f:
    json.dump([xiaoming, xiaohong], f, default=lambda obj: obj.__dict__, ensure_ascii=False, indent=2)

Overall, the article serves as a practical reference for Python beginners and intermediate users, illustrating core language features and common utilities with ready‑to‑run code snippets.