ce-scraper 0.0.2

ce刮刀（coursera刮刀）

这是一个简单的库，有助于从 coursera 获取一些数据，内容聚合器可以使用这些数据

用法

一、从pypi安装打包发行版

pip install ce-scraper 

1.简单的搜索功能

此功能为我们提供了搜索的前 10 个结果
以执行简单搜索。
首先导入search_courses模块并调用

from ce_scraper import search_courses
courses=search_courses.simple_search(search_phrase='machine learning',type='json')
print(courses)

＃＃输出

[
   {
      "course_title": "Machine Learning",
      "partner": "Stanford University",
      "rating_value": "4.9",
      "rating_count": "154,848",
      "enrollment_numbers": "3.9m",
      "course_difficulty": "Mixed",
      "type": "COURSE"
   },
   {
      "course_title": "Deep Learning",
      "partner": "DeepLearning.AI",
      "rating_value": "4.8",
      "rating_count": "117,652",
      "enrollment_numbers": "990k",
      "course_difficulty": "Intermediate",
      "type": "SPECIALIZATION"
   },
   {
      "course_title": "Machine Learning",
      "partner": "University of Washington",
      "rating_value": "4.6",
      "rating_count": "14,496",
      "enrollment_numbers": "400k",
      "course_difficulty": "Intermediate",
      "type": "SPECIALIZATION"
   },
   {
      "course_title": "Mathematics for Machine Learning",
      "partner": "Imperial College London",
      "rating_value": "4.6",
      "rating_count": "10,371",
      "enrollment_numbers": "250k",
      "course_difficulty": "Beginner",
      "type": "SPECIALIZATION"
   },
   {
      "course_title": "IBM Machine Learning",
      "partner": "IBM",
      "rating_value": "4.6",
      "rating_count": "211",
      "enrollment_numbers": "11k",
      "course_difficulty": "Intermediate",
      "type": "PROFESSIONAL CERTIFICATE"
   },
   {
      "course_title": "Applied Data Science with Python",
      "partner": "University of Michigan",
      "rating_value": "4.5",
      "rating_count": "28,245",
      "enrollment_numbers": "700k",
      "course_difficulty": "Intermediate",
      "type": "SPECIALIZATION"
   },
   {
      "course_title": "Machine Learning for All",
      "partner": "University of London",
      "rating_value": "4.7",
      "rating_count": "2,290",
      "enrollment_numbers": "80k",
      "course_difficulty": "Beginner",
      "type": "COURSE"
   },
   {
      "course_title": "IBM Data Science",
      "partner": "IBM",
      "rating_value": "4.6",
      "rating_count": "68,872",
      "enrollment_numbers": "740k",
      "course_difficulty": "Beginner",
      "type": "PROFESSIONAL CERTIFICATE"
   },
   {
      "course_title": "Naive Bayes 101: Resume Selection with Machine Learning",
      "partner": "Coursera Project Network",
      "rating_value": "Not Available",
      "rating_count": "Not Available",
      "enrollment_numbers": "Not Available",
      "course_difficulty": "Intermediate",
      "type": "GUIDED PROJECT"
   },
   {
      "course_title": "Advanced Machine Learning",
      "partner": "HSE University",
      "rating_value": "4.4",
      "rating_count": "3,701",
      "enrollment_numbers": "300k",
      "course_difficulty": "Advanced",
      "type": "SPECIALIZATION"
   }
]

search_phrase是用于搜索课程的关键字
type是我们想要从搜索结果中获得的文件类型。
这些是type此版本支持的值。

一世。list
ii. json
iii.dataframe

2. 高级搜索

为了执行高级搜索，我们在搜索课程模块中调用高级搜索，并将
过滤器字典作为参数。此功能目前仅支持页码作为过滤器。

from ce_scraper import search_courses
courses=search_courses.advanced_search(search_phrase='deep learning', filters={'pages': 2}, type=list)
print(courses)

上面的代码用关键字搜索，deep learning并从 coursera 页面上的两页结果中返回课程，大约 30 门课程。更多过滤器和功能将包含在该库的下一个版本中。