本文所述实例来自独立软件开发者 Alex Marandon,在他的博客中曾介绍了数个关于 Python Collection 的实用小技巧,在此与大家分享。供大家学习借鉴之用。具体如下:
1.判断一个 list 是否为空
传统的方式:
if len(mylist): # Do something with my list else: # The list is empty
由于一个空 list 本身等同于 False,所以可以直接:
if mylist: # Do something with my list else: # The list is empty
2.遍历 list 的同时获取索引
传统的方式:
i = 0 for element in mylist: # Do something with i and element i += 1
这样更简洁些:
for i, element in enumerate(mylist): # Do something with i and element pass
3.list 排序
在包含某元素的列表中依据某个属性排序是一个很常见的操作。例如这里我们先创建一个包含 person 的 list:
class Person(object): def __init__(self, age): self.age = age persons = [Person(age) for age in (14, 78, 42)]
传统的方式是:
def get_sort_key(element): return element.age for element in sorted(persons, key=get_sort_key): print "Age:", element.age
更加简洁、可读性更好的方法是使用 Python 标准库中的 operator 模块:
from operator import attrgetter for element in sorted(persons, key=attrgetter('age')): print "Age:", element.age
attrgetter 方法优先返回读取的属性值作为参数传递给 sorted 方法。operator 模块还包括 itemgetter 和 methodcaller 方法,作用如其字面含义。
4.在 Dictionary 中元素分组
和上面类似,先创建 Persons:
class Person(object): def __init__(self, age): self.age = age persons = [Person(age) for age in (78, 14, 78, 42, 14)]
如果现在我们要按照年龄分组的话,一种方法是使用 in 操作符:
persons_by_age = {} for person in persons: age = person.age if age in persons_by_age: persons_by_age[age].append(person) else: persons_by_age[age] = [person] assert len(persons_by_age[78]) == 2
相比较之下,使用 collections 模块中 defaultdict 方法的途径可读性更好:
from collections import defaultdict persons_by_age = defaultdict(list) for person in persons: persons_by_age[person.age].append(person)
defaultdict 将会利用接受的参数为每个不存在的 key 创建对应的值,这里我们传递的是 list,所以它将为每个 key 创建一个 list 类型的值。
本文示例仅为程序框架,具体功能还需要读者根据自身应用环境加以完善。希望本文所述实例对大家学习Python能起到一定的帮助作用。

Is it enough to learn Python for two hours a day? It depends on your goals and learning methods. 1) Develop a clear learning plan, 2) Select appropriate learning resources and methods, 3) Practice and review and consolidate hands-on practice and review and consolidate, and you can gradually master the basic knowledge and advanced functions of Python during this period.

Key applications of Python in web development include the use of Django and Flask frameworks, API development, data analysis and visualization, machine learning and AI, and performance optimization. 1. Django and Flask framework: Django is suitable for rapid development of complex applications, and Flask is suitable for small or highly customized projects. 2. API development: Use Flask or DjangoRESTFramework to build RESTfulAPI. 3. Data analysis and visualization: Use Python to process data and display it through the web interface. 4. Machine Learning and AI: Python is used to build intelligent web applications. 5. Performance optimization: optimized through asynchronous programming, caching and code

Python is better than C in development efficiency, but C is higher in execution performance. 1. Python's concise syntax and rich libraries improve development efficiency. 2.C's compilation-type characteristics and hardware control improve execution performance. When making a choice, you need to weigh the development speed and execution efficiency based on project needs.

Python's real-world applications include data analytics, web development, artificial intelligence and automation. 1) In data analysis, Python uses Pandas and Matplotlib to process and visualize data. 2) In web development, Django and Flask frameworks simplify the creation of web applications. 3) In the field of artificial intelligence, TensorFlow and PyTorch are used to build and train models. 4) In terms of automation, Python scripts can be used for tasks such as copying files.

Python is widely used in data science, web development and automation scripting fields. 1) In data science, Python simplifies data processing and analysis through libraries such as NumPy and Pandas. 2) In web development, the Django and Flask frameworks enable developers to quickly build applications. 3) In automated scripts, Python's simplicity and standard library make it ideal.

Python's flexibility is reflected in multi-paradigm support and dynamic type systems, while ease of use comes from a simple syntax and rich standard library. 1. Flexibility: Supports object-oriented, functional and procedural programming, and dynamic type systems improve development efficiency. 2. Ease of use: The grammar is close to natural language, the standard library covers a wide range of functions, and simplifies the development process.

Python is highly favored for its simplicity and power, suitable for all needs from beginners to advanced developers. Its versatility is reflected in: 1) Easy to learn and use, simple syntax; 2) Rich libraries and frameworks, such as NumPy, Pandas, etc.; 3) Cross-platform support, which can be run on a variety of operating systems; 4) Suitable for scripting and automation tasks to improve work efficiency.

Yes, learn Python in two hours a day. 1. Develop a reasonable study plan, 2. Select the right learning resources, 3. Consolidate the knowledge learned through practice. These steps can help you master Python in a short time.


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