1.1 重构的重要性 重构,就如同对一幅日渐模糊的油画进行细致入微的修复和重新布局,它不是改变画的主题,而是使之更加鲜明生动。在编程领域,重构是指在不改变代码外部行为的前提下,对其内部结构进行改进的过程,旨在提升代码的可读性、可维护性和可扩展性。 1.1.1 何为重构 想象一下,你接手了一段复杂的Python代码,...
A function that merges both halves, producing a sorted array Here’s the code to merge two different arrays: Python 1def merge(left, right): 2 # If the first array is empty, then nothing needs 3 # to be merged, and you can return the second array as the result 4 if len(left) ...
In this example, we create a list of strings and use the sort() function with the key=len parameter to sort them based on the length of each string. The sort() function modifies the original fruits list in place and sorts it based on the length of each string. Summary The sort() fu...
def merge_sort(alist): """归并排序""" n = len(alist) if n <= 1: return alist mid = n // 2 # left 采用归并排序后形成的有序的新的列表 left_li = merge_sort(alist[:mid]) # right 采用归并排序后形成的有序的新的列表 right_li = merge_sort(alist[mid:]) # 将两个有序的子...
#compares the running time of a list compared to a generatorimporttime#generator function creates an iterator of odd numbers between n and mdefoddGen(n,m):whilen<m:yieldn n+=2#builds a list of odd numbers between n and mdefoddLst(n,m): ...
[mean, median, variance, std_dev, skewness, kurt, zero_cross_rate, num_waves, wave_duration, inst_freq, mobility, activity, complexity, k_complex, energy] def extract_frequency_domain_features(audio_array): fft_result = fft(audio_array) freq_domain = np.abs(fft_result[:len(fft_result)...
from cmath import pi, exp def discrete_fourier_transform(x, k): omega = 2 * pi * k / (N := len(x)) return sum(x[n] * exp(-1j * omega * n) for n in range(N)) This function is a literal transcription of the formulas above. Now you can run a frequency analysis on a...
...In Python, the sum and len functions are used to calculate the sum and length of a list, and the mean...In R, the print function is used to print values to the console...In Python, the print function is used in a similar way, but it also requires parentheses around the...
print('Number of documents: %d' % len(corpus)) Number of unique tokens: 6001 Number of documents: 403 通过词袋语料库,我们可以继续从文档中学习我们的主题模型。 训练LDA模型 In [9]: from gensim.models import LdaModel In [10]: %time model = LdaModel(corpus=corpus, id2word=id2word, chunks...
all_links.append(data)forlinkinall_links:print(f"ID:{link['id']}, Title:{link['title']}, URL:{link['url']}, Rank:{link['rank']}")# Run the main functionasyncio.run(main()) Pro Tip:In my experience, asyncio can dramatically reduce scraping time for multiple pages. It's a supe...