本文实例分析了python开发之list操作。分享给大家供大家参考,具体如下:
对python中list的操作,大家可以参考《Python list操作用法总结》
以下是我个人的笔记:
#python list ''' 创建list有很多方法: 1.使用一对方括号创建一个空的list:[] 2.使用一对方括号,用','隔开里面的元素:[a, b, c], [a] 3.Using a list comprehension:[x for x in iterable] 4.Using the type constructor:list() or list(iterable) ''' def create_empty_list(): '''Using a pair of square brackets to denote the empty list: [].''' return [] def create_common_list(): '''Using square brackets, separating items with commas: [a], [a, b, c].''' return ['a', 'b', 'c', 1, 3, 5] def create_common_list2(): '''Using a list comprehension: [x for x in iterable].''' return [x for x in range(1, 10)] def str_to_list(s): '''Using a string to convert list''' if s != None: return list(s) else: return [] def main(): test_listA = create_empty_list() print(test_listA) print('#' * 50) test_listB = create_common_list() print(test_listB) print('#' * 50) test_listC = create_common_list2() print(test_listC) print('#' * 50) test_str = 'i want to talk about this problem!' test_listD = str_to_list(test_str) print(test_listD) if __name__ == '__main__': main()
运行效果:
Python 3.3.2 (v3.3.2:d047928ae3f6, May 16 2013, 00:03:43) [MSC v.1600 32 bit (Intel)] on win32 Type "copyright", "credits" or "license()" for more information. >>> ================================ RESTART ================================ >>> [] ################################################## ['a', 'b', 'c', 1, 3, 5] ################################################## [1, 2, 3, 4, 5, 6, 7, 8, 9] ################################################## ['i', ' ', 'w', 'a', 'n', 't', ' ', 't', 'o', ' ', 't', 'a', 'l', 'k', ' ', 'a', 'b', 'o', 'u', 't', ' ', 't', 'h', 'i', 's', ' ', 'p', 'r', 'o', 'b', 'l', 'e', 'm', '!'] >>>
下面有更多的demo:
Python 3.3.2 (v3.3.2:d047928ae3f6, May 16 2013, 00:03:43) [MSC v.1600 32 bit (Intel)] on win32 Type "copyright", "credits" or "license()" for more information. >>> counter = 100 >>> miles = 1000.0 >>> name = "hongten" >>> numberA,numberB,nameC = 1,2,"Hongten" >>> list = [counter,miles,name,numberA,numberB,nameC] >>> print(list) [100, 1000.0, 'hongten', 1, 2, 'Hongten'] >>> #这是注释部分,注释用"#"开始 >>> for element in list: print(element) 100 1000.0 hongten 1 2 Hongten >>> #上面是遍历列表list >>> print(list[0]) #获取列表list里面的第一个元素值 100 >>> print(list[-1]) #获取列表list里面的最后一个元素值 Hongten >>> print(len(list)) #用len(list)获取list列表的长度 6 >>> num_inc_list = range(10) #产生一个数值递增的列表 >>> print(num_inc_list) range(0, 10) >>> for inc_list in num_inc_list: print(inc_list) 0 1 2 3 4 5 6 7 8 9 >>> #从这里我们可以看到range(10)是产生了一个从0开始到9的一个数值递增列表 >>> initial_value = 10 >>> list_length = 5 >>> myList = [initial_value for i in range(10)] >>> print(myList) [10, 10, 10, 10, 10, 10, 10, 10, 10, 10] >>> list_length = 2 >>> myList = myList * list_length >>> print(myList) [10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10] >>> print(len(myList)) 20 >>> #上面是用一个固定值initial_value去初始化一个列表myList >>> #同时用myList = myList * list_length去复制myList >>> #下面再看看复制的效果 >>> copyList = [1,2,3,"hongten"] >>> copyList = copyList * list_length >>> print(len(copyList)) 8 >>> for cl in copyList: print(cl) 1 2 3 hongten 1 2 3 hongten >>> #下面我们来仔细研究一下python里面的list >>> #在一个list中可以包含不同类型的元素,这个和ActionScript 3.0(AS3.0)中的数组类似 >>> test_list = ["hello",1,2,"world",4,5,"hongten"] >>> print(len(test_list)) 7 >>> print(test_list[0]) # 打印test_list hello >>> #打印test_list中的第一元素 >>> print(test_list[-1]) #打印test_list中最后一个元素 hongten >>> print(test_list[-len]) #打印第一个元素 Traceback (most recent call last): File "<pyshell#44>", line 1, in <module> print(test_list[-len]) #打印第一个元素 TypeError: bad operand type for unary -: 'builtin_function_or_method' >>> print(test_list[-len(test_list)]) #打印第一个元素 hello >>> print(test_list[len(test_list) - 1]) #打印最后一个元素 hongten >>> test_list.append(6) #向列表中追加一个元素 >>> print(test_list[-1]) 6 >>> test_list.insert(1,0) >>> print(test_list) ['hello', 0, 1, 2, 'world', 4, 5, 'hongten', 6] >>> #上面的操作是向列表test_list的小标为1的地方插入元素0 >>> test_list.insert(1,0) >>> print(test_list) ['hello', 0, 0, 1, 2, 'world', 4, 5, 'hongten', 6] >>> test_list.insert(2,1) >>> print(test_list) ['hello', 0, 1, 0, 1, 2, 'world', 4, 5, 'hongten', 6] >>> print(test_list.pop(0)) #返回最后一个元素,并从test_list中删除之 hello >>> print(test_list) [0, 1, 0, 1, 2, 'world', 4, 5, 'hongten', 6] >>> print(test_list.pop(2)) #上面的注释有错误,pop(index)的操作是返回数组下标为index的元素,并从列表中删除之 0 >>> print(test_list) [0, 1, 1, 2, 'world', 4, 5, 'hongten', 6] >>> test_list.remove(1) >>> print(test_list) [0, 1, 2, 'world', 4, 5, 'hongten', 6] >>> #remove(1)表示的是删除第一次出现的元素1 >>> test_list.insert(0,1) >>> print(test_list) [1, 0, 1, 2, 'world', 4, 5, 'hongten', 6] >>> test_list.remove(1) >>> print(test_list) [0, 1, 2, 'world', 4, 5, 'hongten', 6] >>> test_list.insert(2,"hongten") >>> print(test_list) [0, 1, 'hongten', 2, 'world', 4, 5, 'hongten', 6] >>> test_list.count("hongten") 2 >>> #count(var)是统计var元素在列表中出现的个数 >>> test_list.count("foo") 0 >>> test_list_extend = ["a","b","c"] >>> test_list.extend(test_list_extend) >>> print(test_list) [0, 1, 'hongten', 2, 'world', 4, 5, 'hongten', 6, 'a', 'b', 'c'] >>> #使用extend(list)作用是追加一个list到源list上面 >>> print(test_list.sort()) Traceback (most recent call last): File "<pyshell#76>", line 1, in <module> print(test_list.sort()) TypeError: unorderable types: str() < int() >>> test_list_extend.append("h") >>> test_lsit_extend.append("e") Traceback (most recent call last): File "<pyshell#78>", line 1, in <module> test_lsit_extend.append("e") NameError: name 'test_lsit_extend' is not defined >>> list_a = ["e","z","o","r"] >>> list_a.extend(test_list_extend) >>> print(list_a) ['e', 'z', 'o', 'r', 'a', 'b', 'c', 'h'] >>> print(list_a.sort()) #对list_a列表进行排序 None >>> #不知道为什么以上排序都有报错...... >>> list_b = [1,3,5,2,6,4] >>> print(list_b.sort()) None >>> print(sort(list_b)) Traceback (most recent call last): File "<pyshell#86>", line 1, in <module> print(sort(list_b)) NameError: name 'sort' is not defined >>> #不去管排序问题了,先看看删除操作吧!!!!! >>> print(list_b) [1, 2, 3, 4, 5, 6] >>> print(del list_b[1]) SyntaxError: invalid syntax >>> del list_b[1] >>> print(list_b) [1, 3, 4, 5, 6] >>> del list_b[0,2] Traceback (most recent call last): File "<pyshell#92>", line 1, in <module> del list_b[0,2] TypeError: list indices must be integers, not tuple >>> del list_b[0:2] >>> print(list_b) [4, 5, 6] >>> #del list[index]删除下标为index的元素,del list[start:end]删除从start下标开始到end下标结束的元素 >>> del list_b[10] Traceback (most recent call last): File "<pyshell#96>", line 1, in <module> del list_b[10] IndexError: list assignment index out of range >>> #如果我们删除的下标超出了列表的长度范围,就会报错啦!!!!! >>> ########################################################################## >>> list_c = range(5); >>> for c in list_c: print(c) 0 1 2 3 4 >>> list_d = list_c >>> for d in list_d: print(d) 0 1 2 3 4 >>> #上面是列表的复制 >>> list_d[2] = 23 Traceback (most recent call last): File "<pyshell#108>", line 1, in <module> list_d[2] = 23 TypeError: 'range' object does not support item assignment >>> list_e = [1,2,3,4,5] >>> list_f = list_e >>> list_f[2] = 234 >>> print(list_e) [1, 2, 234, 4, 5] >>> #从这里我们可以知道,list_f复制了list_e,list_f是对list_e的一个引用, >>> #他们共同指向一个对象:[1,2,3,4,5],当我们视图修改list_f[2]的值的时候, >>> #list_f所指向的对象的行为发生了变化,即元素值发生了变化,但是他们的引用是没有 >>> #发生变化的。所以list_e[2] = 234也是在情理之中。 >>> ####################################################################### >>> list_i = list_e[:] >>> print(list_i) [1, 2, 234, 4, 5] >>> print(list_e) [1, 2, 234, 4, 5] >>> list_i[2] = 3 >>> print(list_e) [1, 2, 234, 4, 5] >>> print(list_i) [1, 2, 3, 4, 5] >>> #上面是进行了列表的克隆操作,即拷贝了另一个列表,这样的操作,会创造出新的一个列表对象 >>> #使得list_i和list_e指向不同的对象,就有着不同的引用,所以当list_i[2] = 3的时候, >>> #list_e[2]还是等于234,即不变 >>>
希望本文所述对大家Python程序设计有所帮助。

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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