目前接触过两本,一本是Hetland的Python基础教程,一本是Python for kids。
回复内容:
个人情况:非计算机专业,学编程只是为了解决一些小问题方便,有C++基础推荐公开课Programming for Everybody
1.5倍速+快进一天撸完就基本完成过渡了(有C++基础)
这门课材料的授权都是CC的
课本:http://do1.dr-chuck.com/py4inf/EN-us/book.pdf
所有的课件和上课视频:http://open.umich.edu/education/si/coursera-programming-everybody/winter2014/sessions
课程:https://www.coursera.org/course/pythonlearn

中文书用的是这一本,好几百页,A4纸打出来比字典厚,绝逼不适合入门,从来没看完过,后来就只看document就不看书了,不推荐。

Python Pocket Reference, 5th Edition - O'Reilly Media这本也不错 Learn | Codecademy 用这个吧 个人感觉不管什么教程 适合自己,能在其中学到东西的教程就是好教程
推荐《Python基础教程》,从入门到进阶、高级整个一套都有,且是视频类的教程,很适合初学者 http://woodpecker.org.cn/abyteofpython_cn/chinese/
《简明PYTHON教程》,让你一天python入门。 你去看下这个文章吧,我记得是微博上王威廉还是csdn推荐的
Python数据结构与算法设计(总结篇) 个人感觉目前还没有。入门这种书,设计上考究比正常教程需要考量多。
目前看过的书很多都有先入为主的计算机观念,就是为了让你知道究竟怎么回事,多说了很多话,反而把内容变复杂了,因为个人感觉入门就是告诉你这么做就能实现这样的功能,让你很神奇的感觉的开展。
但所幸的是,python入门其实很简单,所以给点书都能用,谈不上最好的。
如果你英文基础不错或者觉得还是自己理解不看中文的,下面的书都看英文版吧,好了列书单:
1、个人是看《python基础教程》之后配合官方文档的,总之当时的体会就是,讲的有点枯燥了,嗯前面讲列表、字典什么内置对象太多了,所以会有点烦,但是好像下面的都会这样,所以其实作为一个经典款,是不错的。
2、我之后的学习,发现一本还不错中文译名貌似是《像计算机科学家一样思考python》,嗯,这个好一点,不会感觉那么无聊吧,书里排版是设计过的,略微比上面那本浅显一点,缺点就是讲的少了,但是入门的话可以有。
3、好像还有一本针对入门的书,也是之后知道的《可爱的python》,嗯,不过当时我放弃看了,理由我忘了。
4、如果你受虐玩家且是有编程基础像迅速把python当成一个使用工具,《深入python》这种的就好了,咬了几个章节,后你就差不多可以看下去了。
5、假如你很有耐心,不嫌妈妈桑的唠叨,看《python学习手册》吧,我目前看这个英文版,顺便结合官方文档做深入前准备呢。
其他估计还有吧,但是如果上天能再给我一次机会的话,我会安安静静地看官方英文文档入门。 封面是老鼠那本
http://book.douban.com/subject/3988517/
从来没见过写得这么清晰易懂的教材,读起来非常流畅 Byte of Python。对有其他语言编程经验的人来讲,花几个小时看一下Byte of Python,就可以开始干活了。手头再配一个官方doc查类库即可。 Python Programming for the Absolute Beginner, 3rd Edition
每一章都教你一个小游戏,非常有趣,适合入门!

There are many methods to connect two lists in Python: 1. Use operators, which are simple but inefficient in large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use the = operator, which is both efficient and readable; 4. Use itertools.chain function, which is memory efficient but requires additional import; 5. Use list parsing, which is elegant but may be too complex. The selection method should be based on the code context and requirements.

There are many ways to merge Python lists: 1. Use operators, which are simple but not memory efficient for large lists; 2. Use extend method, which is efficient but will modify the original list; 3. Use itertools.chain, which is suitable for large data sets; 4. Use * operator, merge small to medium-sized lists in one line of code; 5. Use numpy.concatenate, which is suitable for large data sets and scenarios with high performance requirements; 6. Use append method, which is suitable for small lists but is inefficient. When selecting a method, you need to consider the list size and application scenarios.

Compiledlanguagesofferspeedandsecurity,whileinterpretedlanguagesprovideeaseofuseandportability.1)CompiledlanguageslikeC arefasterandsecurebuthavelongerdevelopmentcyclesandplatformdependency.2)InterpretedlanguageslikePythonareeasiertouseandmoreportab

In Python, a for loop is used to traverse iterable objects, and a while loop is used to perform operations repeatedly when the condition is satisfied. 1) For loop example: traverse the list and print the elements. 2) While loop example: guess the number game until you guess it right. Mastering cycle principles and optimization techniques can improve code efficiency and reliability.

To concatenate a list into a string, using the join() method in Python is the best choice. 1) Use the join() method to concatenate the list elements into a string, such as ''.join(my_list). 2) For a list containing numbers, convert map(str, numbers) into a string before concatenating. 3) You can use generator expressions for complex formatting, such as ','.join(f'({fruit})'forfruitinfruits). 4) When processing mixed data types, use map(str, mixed_list) to ensure that all elements can be converted into strings. 5) For large lists, use ''.join(large_li

Pythonusesahybridapproach,combiningcompilationtobytecodeandinterpretation.1)Codeiscompiledtoplatform-independentbytecode.2)BytecodeisinterpretedbythePythonVirtualMachine,enhancingefficiencyandportability.

ThekeydifferencesbetweenPython's"for"and"while"loopsare:1)"For"loopsareidealforiteratingoversequencesorknowniterations,while2)"while"loopsarebetterforcontinuinguntilaconditionismetwithoutpredefinediterations.Un

In Python, you can connect lists and manage duplicate elements through a variety of methods: 1) Use operators or extend() to retain all duplicate elements; 2) Convert to sets and then return to lists to remove all duplicate elements, but the original order will be lost; 3) Use loops or list comprehensions to combine sets to remove duplicate elements and maintain the original order.


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