1. 安装requests
$ pip install --user requests
- 处理API响应(找出GitHub上星际最高的Python项目):
import requests
#执行API调用并存储响应
url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'
r = requests.get(url)
print("Status code",r.status_code)
#将API响应存储在一个变量中
response_dict = r.json()
#处理结束
print(response_dict.keys())
打印结果
Status code 200
dict_keys(['total_count', 'incomplete_results', 'items'])
- 处理响应字典(分析最受欢迎的第一个仓库)
import requests
#执行API调用并存储响应
url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'
r = requests.get(url)
print("Status code",r.status_code)
#将API响应存储在一个变量中
response_dict = r.json()
print("Total repositories:",response_dict['total_count'])
#探索有关仓库的信息
repo_dicts = response_dict['items']
print("Repositories returned:",len(repo_dicts))
#研究第一个仓库
repo_dict = repo_dicts[0]
print("\nKeys:", len(repo_dict))
for key in sorted(repo_dict.keys()):
print(key)
print("\nSelected information about first repository:")
print('Name:', repo_dict['name'])
print('Owner:', repo_dict['owner']['login'])
print('Stars:', repo_dict['stargazers_count'])
print('Repository:', repo_dict['html_url'])
print('Created:', repo_dict['created_at'])
print('Updated:', repo_dict['updated_at'])
print('Description:', repo_dict['description'])
- 监视API的速率限制
大多数API都存在速率限制，即你在特定时间内可执行的请求数存在限制,浏览器输入网址https://api.github.com/rate_limit查看GitHub的限制
resources
core
limit 60
remaining 42
reset 1525228123
search
limit 10
remaining 10
reset 1525225082
graphql
limit 0
remaining 0
reset 1525228622
rate
limit 60
remaining 42
reset 1525228123
- 使用Pygal可视化仓库
import requests
import pygal
from pygal.style import LightColorizedStyle as LCS,LightenStyle as LS
#执行API调用并存储响应
url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'
r = requests.get(url)
print("Status code",r.status_code)
#将API响应存储在一个变量中
response_dict = r.json()
print("Total repositories:",response_dict['total_count'])
#探索有关仓库的信息
repo_dicts = response_dict['items']
names,stars = [],[]
for repo_dict in repo_dicts:
names.append(repo_dict['name'])
stars.append(repo_dict['stargazers_count'])
#可视化
my_style = LS('#333366',base_style=LCS)
chart = pygal.Bar(style=my_style,x_label_rotation=45,show_legend=False)
chart.title = 'Most-Starred Python Projects on GitHub'
chart.x_labels = names
chart.add('',stars)
chart.render_to_file('python_repos.svg')
使用LightenStyle类(别名LS)定义了一种样式，并将其基色设置为深蓝色。传递了实参base_style，以使用LightColorizedStyle类(别名LCS)。然后，使用 Bar()创建一个简单的条形图，并向它传递了my_style.传递了另外两个样式实参: 让标签绕x轴旋转45度(x_label_rotation=45)，并隐藏了图例(show_legend=False)，因为在图表中绘制一个数据系列。接下来，给图表指定了标题，并将属性x_labels设置为列表 names。
- 改进Pygal图表
创建一个配置对象，其中包含传递给Bar()的所有定制
#可视化
my_style = LS('#333366',base_style=LCS)
#改进Pygal图表
#通过修改my_config的属性，可定制图标的外观
my_config = pygal.Config()
my_config.x_label_rotation = 45
my_config.show_legend = False
#图表标题、副标 签和主标签的字体大小
my_config.title_font_size = 24
my_config.label_font_size = 14
my_config.major_label_font_size = 18
#使用 3 truncate_label将较长的项目名缩短为15个字符
my_config.truncate_label = 15
my_config.show_y_guides = False
设置自定义宽度，让图表更充分地利用浏览器中的可用空间
my_config.width =1000
chart = pygal.Bar(my_config,style=my_style)
6.添加自定义工具提示
chart = pygal.Bar(style=my_style, x_label_rotation=45, show_legend=False)
chart.title = 'Python Projects'
chart.x_labels = ['httpie','django','flask']
plot_dicts = [
{'value': 16101, 'label': 'Description of httpie.'},
{'value': 15028, 'label': 'Description of django.'},
{'value': 14798, 'label': 'Description of flask.'},
]
chart.add('',plot_dicts)
chart.render_to_file('python_repos.svg')
image
- 根据数据绘制图
自定生成plot_dicts
import requests
import pygal
from pygal.style import LightColorizedStyle as LCS,LightenStyle as LS
def description(repo_dict_json):
description_str = repo_dict_json['description']
if description_str:
return description_str
else:
return ""
#执行API调用并存储响应
url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'
r = requests.get(url)
print("Status code",r.status_code)
#将API响应存储在一个变量中
response_dict = r.json()
print("Total repositories:",response_dict['total_count'])
#探索有关仓库的信息
repo_dicts = response_dict['items']
names,plot_dicts = [],[]
for repo_dict in repo_dicts:
names.append(repo_dict['name'])
plot_dict = {
'value':repo_dict['stargazers_count'],
'label':description(repo_dict),
}
plot_dicts.append(plot_dict)
#可视化
my_style = LS('#333366',base_style=LCS)
chart = pygal.Bar(style=my_style, x_label_rotation=45, show_legend=False)
chart.title = 'Python Projects'
chart.x_labels = names
chart.add('',plot_dicts)
chart.render_to_file('python_repos.svg')
开始plot_dict写的是
plot_dict = {
'value': repo_dict['stargazers_count'],
'label': repo_dict['description'],
}
报错：AttributeError: 'NoneType' object has no attribute 'decode'，是因为有的item的description是空的，于是添加方法description对其进行判断
image
- 在图表中添加可单机的链接
plot_dict = {
'value':repo_dict['stargazers_count'],
'label':description(repo_dict),
'xlink': repo_dict['html_url']
}
Pygal根据与键‘xlink’相关联的URL将每个条形都转换为活跃的链接，单机可以打开一个新的标签页
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