用Github的Api发现stars最多开源项目

Github的API无需注册，在网上可以查到使用信息和一些限制：

查询的请求为每分钟１０次
此次用到的api格式如下：

url = ‘https://api.github.com/search/repositories?q=language:python&sort=stars’
/search/repositories 搜索github上的仓库
？传递一个查询参数q,=指定查询的内容language:python,查询语言为python的仓库信息
＆sort=stars项目按照获得的星星数量排名

倒入用到的库

import requests

# 获取最受欢迎的前３０个仓库的信息，返回对象为一个字典对象def get_info(language):    url = 'https://api.github.com/search/repositories?q=language:%s&sort=stars'%(language)    r = requests.get(url)    if r.status_code == 200:        print 'success'    return r.json()

# 获取python,java,C++三种语言最受欢迎的库response_python = get_info('python')response_java   = get_info('java')response_c_dplus = get_info('C++')

successsuccesssuccess

获取信息函数返回字典对象的键值

print (response_python.keys())

[u’total_count’, u’items’, u’incomplete_results’]

response_java['total_count']    # github上java语言仓库的数量

3453199

response_python['items'][0].keys()  # item包含仓库的一些详细信息的列表

[u'issues_url', u'deployments_url', u'stargazers_count', u'forks_url', u'mirror_url', u'subscription_url', u'notifications_url', u'collaborators_url', 　．．．．．．．． u'watchers', u'name', u'language', u'url', u'created_at', u'pushed_at', u'forks_count', u'default_branch', u'teams_url', u'trees_url', u'branches_url', u'subscribers_url', u'stargazers_url']

incomplete_results,在执行更复杂的Api调用是，需要检查它的结果．简单的调用可以忽略
对字典对象进行处理，生成一个DataFrame对象

# 返回一个dataframe对象import pandas as pddef ret_df(response_dict):    df = pd.DataFrame(columns=['created_at','updated_at','name','forks' ,'stars','size'])    for resp_dict in response_dict['items']:        df = df.append({            'created_at':resp_dict['created_at'],            'updated_at':resp_dict['updated_at'],            'name':resp_dict['name'],            'forks':resp_dict['forks'],            'stars':resp_dict['stargazers_count'],            'size':resp_dict['size']},ignore_index=True)    return df

　Python语言前５个最受欢迎的仓库

　 created_at updated_at name forks stars size 0 2014-06-27T21:00:06Z 2017-08-04T04:06:23Z awesome-python 6999 37000 3198 1 2012-02-25T12:39:13Z 2017-08-04T03:42:53Z httpie 2069 30840 3657 2 2015-04-08T15:08:04Z 2017-08-04T04:44:20Z thefuck 1476 29363 1914 3 2010-04-06T11:11:59Z 2017-08-04T03:55:18Z flask 9091 28759 4929 4 2010-10-31T14:35:07Z 2017-08-03T23:17:48Z youtube-dl 5281 27920 48358

可视化仓库

# pygal对仓库信息进行可视化import pygal

# 生成数据df_python = ret_df(response_python)df_java = ret_df(response_java)df_c_dplus = ret_df(response_c_dplus)

每个仓库的stars和forks

def show(df, language):    line_chart = pygal.Line(x_label_rotation=45)    line_chart.title = 'Most-Starred %s projects on Github'%language    line_chart.x_labels = df['name']    line_chart.add('forks',df['forks'])    line_chart.add('stars',df['stars'])    line_chart.render_to_file(language+'_projects.svg')

show(df_c_dplus, 'C++')

不同语言的比较

# 不同语言比较from pygal.style import TurquoiseStyledef compare_show(df_py,df_j,df_c, colu):    chart = pygal.Bar()    chart.title = 'Compare different language'    chart.x_labels = range(1,31)       #　项目星星排名    chart.add('Python', df_py[colu])    chart.add('Java', df_j[colu])    chart.add('C++', df_c[colu])    chart.render_to_file(colu+'.svg')

compare_show(df_python, df_java, df_c_dplus, 'stars')