


Introduction to the usage of defaultdict type in Python's collections module
defaultdict is mainly used when value needs to be initialized. For a dictionary, the key must be hashable, immutable, and unique data, and the value can be any data type. If value is a data type such as list, dict, etc., it must be initialized to empty before use. In some cases, value needs to be initialized to a special value, such as 0 or ''.
from collections import defaultdict person_by_age = defaultdict(list) for person in persons: d[person.age].append(person.name)
defaultdict is used in the same way as dict, except that a callable object x must be passed in during initialization. When a key that does not exist yet is accessed, the value will be automatically set to x(). For example, in the above example, when a person of a certain age d[person.age] is accessed for the first time, it will become list(), that is, [].
Of course, you can also use your own defined callable object, such as:
d = defaultdict(lambda: 0) d["hello"] += 1 # 1 d["a"] # 0
defaultdict is more efficient than dict.set_default, and is more intuitive and convenient to use.
The standard dictionary includes a method setdefault() to get a value and create a default value if the value does not exist. defaultdict initializes the container to allow the caller to specify the default value in advance.
import collections def default_factory(): return 'default value' d = collections.defaultdict(default_factory, foo = 'bar') print 'd:', d print 'foo =>', d['foo'] print 'var =>', d['bar']
This method can be used as long as all keys have the same default value.
The result above is:
d: defaultdict(<function default_factory at 0x0201FAB0>, {'foo': 'bar'}) foo => bar var => default value

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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