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

This article presents a step‑by‑step guide to essential Python features, organized into several sections.

1. Numbers – Demonstrates absolute value, binary/hex/octal conversion, character code lookup, truth testing, boolean conversion, division with remainder, rounding, complex numbers and exponentiation.

<code>abs(-6)          # 6
bin(10)          # '0b1010'
oct(9)          # '0o11'
hex(15)         # '0xf'
chr(65)         # 'A'
ord('A')        # 65
all([1,0,3,6])  # False
any([0,0,1])    # True
bool([0,0,0])   # True
bool([])        # False
divmod(10,3)    # (3, 1)
round(10.0222222,3)  # 10.022
complex(1,2)    # (1+2j)
pow(3,2,4)      # 1
</code>

2. Strings – Shows conversion to bytes, generic string conversion, compiling and executing code strings, evaluating expressions, and formatting with format and format specifications.

<code>s = "apple"
bytes(s, encoding='utf-8')   # b'apple'
str(100)                     # '100'
code_obj = compile("print('helloworld')", "<string>", "exec")
exec(code_obj)               # prints helloworld
eval("1 + 3 + 5")          # 9
print("i am {0},age{1}".format("tom",18))  # i am tom,age18
</code>

3. Functions – Covers built‑in functions such as sorted , sum , nonlocal , global , lambda expressions, and custom functions with positional, keyword, default, *args and **kwargs parameters.

<code>a = [1,4,2,3,1]
sorted(a, reverse=True)   # [4,3,2,1,1]
sum(a)                    # 11
sum(a,10)                 # 21

def excepter(f):
    i = 0
    t1 = time.time()
    def wrapper():
        try:
            f()
        except Exception as e:
            nonlocal i
            i += 1
            print(f"{e.args[0]}: {i}")
    return wrapper

def f(*lists, **d):
    return max(*lists, key=lambda v: len(v))
</code>

4. Data Structures – Illustrates creation and conversion of dictionaries, frozensets, sets, tuples, and slice objects.

<code>dict(a=1, b=2)                     # {'a': 1, 'b': 2}
frozenset([1,1,3,2,3])            # frozenset({1,2,3})
set([1,4,2,3,1])                  # {1,2,3,4}
tuple([1,3,5])                    # (1, 3, 5)
my_slice = slice(1,10,2)
a[my_slice]                      # slice operation
</code>

5. Classes and Objects – Defines a Student class with __init__ , __repr__ , demonstrates callable , custom __call__ , class methods, dynamic attribute access ( getattr , setattr , delattr ), introspection ( dir , hasattr , isinstance , issubclass ), and explains metaclasses.

<code>class Student:
    def __init__(self, id, name):
        self.id = id
        self.name = name
    def __repr__(self):
        return f"id = {self.id}, name = {self.name}"
    def __call__(self):
        print("I can be called", f"my name is {self.name}")

xiaoming = Student('001', 'xiaoming')
callable(Student)          # True
callable(xiaoming)        # False
xiaoming()                 # I can be called, my name is xiaoming
hasattr(xiaoming, 'name') # True
getattr(xiaoming, 'name') # 'xiaoming'
</code>

6. Tools – Shows enumeration, memory size with sys.getsizeof , filtering, hashing, help, iteration protocols ( iter , reversed , zip ), and JSON serialization of objects.

<code>for i, v in enumerate(['a','b','c'], 1):
    print(i, v)

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]
hash(xiaoming)                     # e.g., 6139638
help(Student)
rev = reversed([1,4,2,3,1])
list(rev)                          # [1,3,2,4,1]
import json
with open('json.txt','w',encoding='utf-8') as f:
    json.dump([xiaoming, xiaohong], f, default=lambda o: o.__dict__, ensure_ascii=False, indent=2, sort_keys=True)
</code>

The article concludes with a QR‑code invitation to a free Python public course and additional reading links.