1. Python variables are containers used to store data. They can store different types of data, such as integers, floating point numbers, strings, etc.

2. Python variable names consist of letters, numbers, and underscores, and cannot start with numbers.

3. Variables in Python do not need to be declared. Variables can be created by assigning values ​​directly.

4. Variable names are case-sensitive. For example, var and Var will be regarded as two different variables.

5. You can modify the value of a variable through an assignment statement, or delete a variable through the del keyword.

1. Data types in Python include: integer (int), floating point number (float), string (str), list (list), tuple (tuple) and dictionary (dict).

2. A list is a mutable ordered collection that can store different types of data.

3. Tuples are immutable ordered collections, similar to lists, but tuples are represented using parentheses instead of square brackets.

4. A dictionary is an unordered data structure consisting of key-value pairs, with each key corresponding to a value.

5. Python also provides other data types, such as sets and bool, for processing specific data scenarios.

6. When writing Python code, understanding different data types and their characteristics can help us process and manipulate data more effectively.

arithmetic operators :addition -: Subtraction *:multiplication /:division //: Integer division (floor division) %: Modulo (remainder) **: Power operation

operator precedence Operator precedence in Python from highest to lowest is: brackets Exponential operations (**) Sign (x, -x, ~x) Multiplication, division, modulo and integer division (*, /, //, %) Addition and subtraction ( , -) Bit operations (<<, >>, &, ^, |) Comparison operators (<, <=, >, >=, !=, ==) Identity operator (is, is not) Membership operator (in, not in) Logical operators (not, and, or)

1. Objects in Python are instances of classes, and classes define the structure and behavior of objects.

2. Use the `class` keyword to define a class and create an object by calling the class name.

3. Object attributes: variables in the class, used to store the state of the object.

4. Object methods: functions in the class, used to describe the behavior of the object.

5. Construction method: `__init__` method, used to initialize object attributes.

6. Inheritance: Subclasses can inherit the attributes and methods of the parent class to achieve code reuse.

7. Polymorphism: Objects of different classes can use the same method name, but the specific implementation may be different.

8. Encapsulation: Hide the internal implementation details of the object and expose only the necessary interfaces to external access.

binary search Binary search can be replaced by a binary tree

linear search

Bubble(O(N^2))

Merge (O(N*log(N)))

List is one of the most commonly used data structures in Python. It is an ordered collection of elements, usually placed in [] Ordering: The elements in the list are ordered according to their position in the list, the first index is 0, the second is 1, and so on Mutability: elements in the list can be added, removed, and modified at any time as needed

A tuple is similar to a list. It is also an ordered collection of elements that can store different types of elements. However, once a tuple is created, it cannot be modified. Elements cannot be added, deleted, or modified to the tuple. Tuples are represented by parentheses (), and the elements are also separated by commas. Immutability: Tuples cannot be modified after they are created. Orderliness: The elements in the tuple also have positional relationships, and the elements in the tuple can be accessed through indexing and slicing operations.

Dictionary is the only mapping type in Python, which stores key-value pairs. Keys in a dictionary must be unique, while values ​​can be any type of data Dictionaries are represented by braces {}, with each key-value pair separated by commas. Unordered: The data in the dictionary is arranged in an unordered manner, which is different from the order of lists and tuples. Mutability: Dictionaries are mutable, key-value pairs can be added, deleted, or modified. Dictionaries are very powerful in Python and are often used to store data that needs to be looked up quickly. You can use keys to quickly access, modify, or delete corresponding values.

A set is an unordered and non-repeating collection of elements Disorder: The elements in a set have no specific order. Non-repetition: All elements in the set are unique, no duplicate elements are allowed

Concatenation: Use the operator to concatenate two strings. Copy: Use the * operator to copy a string. Slicing: Use [start:stop:step] to obtain substrings of a string. Length: Use the len() function to get the length of a string. Search: Use find(), index(), startswith(), endswith() and other methods to find substrings or characters. Replacement: Use the replace() method to replace a substring. Split: Use the split() method to split a string into a list. Case conversion: Use upper(), lower(), capitalize(), title() and other methods to convert the case of strings. Remove whitespace: Use strip(), lstrip(), rstrip() methods to remove whitespace characters at both ends of the string. Determination: Use isalpha(), isdigit(), isalnum(), isspace() and other methods to determine the type of the string.

Sequence is another important type of data structure in Python, which contains an ordered set of elements. Index: Access elements in a sequence by index (position). Slicing: Use the slicing operation to access subsequences of a sequence. Add: Use the operator to join two sequences. Multiply: Use the * operator to repeat a sequence. Length: Use the len() function to get the length of the sequence. Maximum/Minimum Values: Use the max() and min() functions to get the maximum and minimum values ​​in a sequence (for numeric sequences)