List
1. An ordered collection of arbitrary objects
A list is a set of any Type of values, combined in a certain order
2. Read through offset
The values that make up the list are called elements (Elements). Each element is marked with an index, the first index is 0, and the functions of the sequence can be realized
3. Variable length, heterogeneous and arbitrary nesting
Elements in the list can It is any type, even a list type, which means that lists can be nested
4. Variable sequences
support indexing, slicing, merging, deletion and other operations, they are all in the original Modify the list
5. Object reference array
The list can be treated as an ordinary array. Whenever a reference is used, Python will always point the reference to an object, so the program only needs Operations that handle objects. When assigning an object to a data structure element or variable name, Python always stores a reference to the object, rather than a copy of the object
Dictionary
1 .Read by key instead of offset
The dictionary is an associative array, a collection of objects indexed by keywords, stored using key-value, and the search speed is fast
2. An unordered collection of arbitrary objects
The items in the dictionary have no specific order, symbolized by "keys"
3. Variable length, heterogeneous , Arbitrary nesting
Same as list, nesting can include lists and other dictionaries, etc.
4. Belongs to variable mapping type
Because it is unordered, it cannot be performed Sequence operations, but can be modified remotely, by mapping keys to values. Dictionaries are the only built-in mapping type (objects that map keys to values)
5. Object reference table
Dictionaries store object references, not copies, just like lists. The key of the dictionary cannot be changed, and the list cannot be used as the key. Strings, primitives, integers, etc. can be compared
with the list. The dict has the following characteristics:
1. The speed of search and insertion is extremely fast and will not increase with the increase of key
2. It takes up a lot of memory and wastes a lot of memory
The opposite is true for list:
1. The time for searching and inserting increases as the number of elements increases
2. It occupies a small space and wastes very little memory
So, dict uses space in exchange for time. Method
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Python and C each have their own advantages, and the choice should be based on project requirements. 1) Python is suitable for rapid development and data processing due to its concise syntax and dynamic typing. 2)C is suitable for high performance and system programming due to its static typing and manual memory management.

Choosing Python or C depends on project requirements: 1) If you need rapid development, data processing and prototype design, choose Python; 2) If you need high performance, low latency and close hardware control, choose C.

By investing 2 hours of Python learning every day, you can effectively improve your programming skills. 1. Learn new knowledge: read documents or watch tutorials. 2. Practice: Write code and complete exercises. 3. Review: Consolidate the content you have learned. 4. Project practice: Apply what you have learned in actual projects. Such a structured learning plan can help you systematically master Python and achieve career goals.

Methods to learn Python efficiently within two hours include: 1. Review the basic knowledge and ensure that you are familiar with Python installation and basic syntax; 2. Understand the core concepts of Python, such as variables, lists, functions, etc.; 3. Master basic and advanced usage by using examples; 4. Learn common errors and debugging techniques; 5. Apply performance optimization and best practices, such as using list comprehensions and following the PEP8 style guide.

Python is suitable for beginners and data science, and C is suitable for system programming and game development. 1. Python is simple and easy to use, suitable for data science and web development. 2.C provides high performance and control, suitable for game development and system programming. The choice should be based on project needs and personal interests.

Python is more suitable for data science and rapid development, while C is more suitable for high performance and system programming. 1. Python syntax is concise and easy to learn, suitable for data processing and scientific computing. 2.C has complex syntax but excellent performance and is often used in game development and system programming.

It is feasible to invest two hours a day to learn Python. 1. Learn new knowledge: Learn new concepts in one hour, such as lists and dictionaries. 2. Practice and exercises: Use one hour to perform programming exercises, such as writing small programs. Through reasonable planning and perseverance, you can master the core concepts of Python in a short time.

Python is easier to learn and use, while C is more powerful but complex. 1. Python syntax is concise and suitable for beginners. Dynamic typing and automatic memory management make it easy to use, but may cause runtime errors. 2.C provides low-level control and advanced features, suitable for high-performance applications, but has a high learning threshold and requires manual memory and type safety management.


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