Polymorphism is a core concept in Python object-oriented programming, referring to "one interface, multiple implementations", allowing for unified processing of different types of objects. 1. Polymorphism is implemented through method rewriting. Subclasses can redefine parent class methods. For example, the spoke() method of Animal class has different implementations in Dog and Cat subclasses. 2. The practical uses of polymorphism include simplifying the code structure and enhancing scalability, such as calling the draw() method uniformly in the graphical drawing program, or handling the common behavior of different characters in game development. 3. Python implementation polymorphism needs to satisfy: the parent class defines a method, and the child class overrides the method, but does not require inheritance of the same parent class. As long as the object implements the same method, this is called the "duck type". 4. Things to note include the maintenance

ListslicinginPythonextractsaportionofalistusingindices.1.Itusesthesyntaxlist[start:end:step],wherestartisinclusive,endisexclusive,andstepdefinestheinterval.2.Ifstartorendareomitted,Pythondefaultstothebeginningorendofthelist.3.Commonusesincludegetting

A class method is a method defined in Python through the @classmethod decorator. Its first parameter is the class itself (cls), which is used to access or modify the class state. It can be called through a class or instance, which affects the entire class rather than a specific instance; for example, in the Person class, the show_count() method counts the number of objects created; when defining a class method, you need to use the @classmethod decorator and name the first parameter cls, such as the change_var(new_value) method to modify class variables; the class method is different from the instance method (self parameter) and static method (no automatic parameters), and is suitable for factory methods, alternative constructors, and management of class variables. Common uses include:

Parameters are placeholders when defining a function, while arguments are specific values ??passed in when calling. 1. Position parameters need to be passed in order, and incorrect order will lead to errors in the result; 2. Keyword parameters are specified by parameter names, which can change the order and improve readability; 3. Default parameter values ??are assigned when defined to avoid duplicate code, but variable objects should be avoided as default values; 4. args and *kwargs can handle uncertain number of parameters and are suitable for general interfaces or decorators, but should be used with caution to maintain readability.

Python's csv module provides an easy way to read and write CSV files. 1. When reading a CSV file, you can use csv.reader() to read line by line and return each line of data as a string list; if you need to access the data through column names, you can use csv.DictReader() to map each line into a dictionary. 2. When writing to a CSV file, use csv.writer() and call writerow() or writerows() methods to write single or multiple rows of data; if you want to write dictionary data, use csv.DictWriter(), you need to define the column name first and write the header through writeheader(). 3. When handling edge cases, the module automatically handles them

Iterators are objects that implement __iter__() and __next__() methods. The generator is a simplified version of iterators, which automatically implement these methods through the yield keyword. 1. The iterator returns an element every time he calls next() and throws a StopIteration exception when there are no more elements. 2. The generator uses function definition to generate data on demand, saving memory and supporting infinite sequences. 3. Use iterators when processing existing sets, use a generator when dynamically generating big data or lazy evaluation, such as loading line by line when reading large files. Note: Iterable objects such as lists are not iterators. They need to be recreated after the iterator reaches its end, and the generator can only traverse it once.

There are many ways to merge two lists, and choosing the right way can improve efficiency. 1. Use number splicing to generate a new list, such as list1 list2; 2. Use = to modify the original list, such as list1 =list2; 3. Use extend() method to operate on the original list, such as list1.extend(list2); 4. Use number to unpack and merge (Python3.5), such as [list1,*list2], which supports flexible combination of multiple lists or adding elements. Different methods are suitable for different scenarios, and you need to choose based on whether to modify the original list and Python version.

To call a function in Python, you need to define the function first and then call it in the form of parentheses of the function name. 1. Use the def keyword to define the function, such as defgreet():print("Hello,world!"); 2. Call the function by adding parentheses to the function name, such as greet(); 3. If the function needs parameters, pass the corresponding value in the brackets when calling, such as defgreet(name):print(f"Hello,{name}!") and greet("Alice"); 4. Multiple parameters can be passed, such as defadd(a,b):result=a