科研系统的试用及其在计算机领域的应用

# 导入必要的库

import nltk

from nltk.corpus import stopwords

from nltk.tokenize import word_tokenize

# 定义函数用于文本预处理

def preprocess_text(text):

stop_words = set(stopwords.words('english'))

words = word_tokenize(text)

filtered_sentence = [word for word in words if not word in stop_words]

return " ".join(filtered_sentence)

# 示例文本

example_text = "This is an example of text that needs to be analyzed."

# 预处理文本

processed_text = preprocess_text(example_text)

print("Processed Text:", processed_text)

数据仓库

class TestPreprocessText(unittest.TestCase):

def test_preprocess_text(self):

example_text = "This is an example of text that needs to be analyzed."

expected_output = "example text needs analyzed"

self.assertEqual(preprocess_text(example_text), expected_output)

if __name__ == '__main__':

unittest.main()