API入門專案專案收集GitHub上熱門專案的資訊

API是網站的一部分，常用在如果我們想要網站上的一些資訊的時候，我們可以呼叫API請求資料再對這些資料可視化，并且這個資料還是實時的，大大提高了資料的可用性，

這次我們就用API呼叫GitHub上星級最高的python專案資訊，并使用plotly生成互動式的可視化圖表，

import requests#匯入request模塊
# 呼叫API并儲存回傳的回應
url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'
headers = {'Accept': 'application/vnd.github.v3+json'}#因為版本往往不一樣，我們指定使用這個我們指定的API
r = requests.get(url, headers=headers)#用函式呼叫API
print(f"Status code: {r.status_code}")
#將回應賦給response_dict
response_dict= r.json()
#API回傳的Json資訊儲存在response_dict
print (response_dict.keys())
#列印出來看看

https://api.github.com/search/repositories
關于這個地址，開頭的https://api.github.com/是把請求發送到GitHub網站，接下里search是搜索，物件是所有的倉庫repositories，q表示查詢，=表示開始指定查詢language:python是值要獲取語言為python的資訊，最后&sort=stars指定將專案按星排序

列印出來后是這樣子的：狀態碼為200，回應字典只有三個鍵：[‘total_count’, ‘incomplete_results’, ‘items’]

Status code: 200
dict_keys([‘total_count’, ‘incomplete_results’, ‘items’])

import requests
url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'
headers = {'Accept': 'application/vnd.github.v3+json'}
r = requests.get(url, headers=headers)
print(f"Status code: {r.status_code}")
response_dict= r.json()

print(f"Total repositories: {response_dict['total_count']}")

# 探索全部倉庫的資訊
repo_dicts = response_dict['items']#列印與total_count相關的值，它指出了GitHub共有多少個倉庫
print(f"Repositories returned: {len(repo_dicts)}")#將字典儲存在repo_dicts

#我們可以來看下第一個倉庫
repo_dict=repo_dicts[0]
print(f"\nKeys:{len(repo_dict)}")
for key in sorted(repo_dict.keys()):
     print(key)

#我們來提取一些repo_dict中于一些鍵相關聯的值

這個是列印出來的值，我們可以從這里了解到實際出來的資料
Status code: 200
Total repositories: 6622696
Repositories returned: 30

Keys:74
archive_url
archived
assignees_url
太多了，跳過一部分
watchers
watchers_count

現在我們來提取一些repo_dict中于一些鍵相關聯的值

import requests
url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'
headers = {'Accept': 'application/vnd.github.v3+json'}
r = requests.get(url, headers=headers)
print(f"Status code: {r.status_code}")
response_dict= r.json()
print(f"Total repositories: {response_dict['total_count']}")
repo_dicts = response_dict['items']
print(f"Repositories returned: {len(repo_dicts)}")

repo_dict=repo_dicts[0]
#我們來提取一些repo_dict中于一些鍵相關聯的值
print("\nSelected information about each repository:")

print(f"Name: {repo_dict['name']}")#人名
print(f"Owner: {repo_dict['owner']['login']}")
print(f"Stars: {repo_dict['stargazers_count']}")#獲得了多少個星
print(f"Repository: {repo_dict['html_url']}")
print(f"Created: {repo_dict['created_at']}")#專案創建的時間
print(f"Updated: {repo_dict['updated_at']}")#最后一次更新的時間
print(f"Description: {repo_dict['description']}")

結果就就是下面這樣子：
Status code: 200
Total repositories: 6618376
Repositories returned: 30

Selected information about each repository:
Name: system-design-primer
Owner: donnemartin
Stars: 119890
Repository: https://github.com/donnemartin/system-design-primer
Created: 2017-02-26T16:15:28Z
Updated: 2021-01-31T02:19:49Z
Description: Learn how to design large-scale systems. Prep for the system design interview. Includes Anki flashcards.

Process finished with exit code 0

理清了資料后，那么我們就可以總體開始了

import requests

from plotly.graph_objs import Bar#匯入bar類
from plotly import offline#匯入offline模塊

# Make an API call and store the response.
url = 'https://api.github.com/search/repositories?q=language:python&sort=stars'
headers = {'Accept': 'application/vnd.github.v3+json'}
r = requests.get(url, headers=headers)
print(f"Status code: {r.status_code}")

# 處理結果.
response_dict = r.json()
repo_dicts = response_dict['items']
repo_links, stars, labels = [], [], []#創建三個空串列用來存盤我們要用的資料
for repo_dict in repo_dicts:#遍歷repo_dicts中的所有的字典，列印專案的名稱、所有者、星級等資訊，
    repo_name = repo_dict['name']
    repo_url = repo_dict['html_url']
    repo_link = f"<a href='{repo_url}'>{repo_name}</a>"
    repo_links.append(repo_link)

    stars.append(repo_dict['stargazers_count'])

    owner = repo_dict['owner']['login']
    description = repo_dict['description']
    label = f"{owner}<br />{description}"
    labels.append(label)


#開始可視化，定義串列data
data = [{
    'type': 'bar',
    'x': repo_links,
    'y': stars,
    'hovertext': labels,
    'marker': {
        'color': 'rgb(60, 100, 150)',
        'line': {'width': 1.5, 'color': 'rgb(25, 25, 25)'}
    },
    'opacity': 0.6,
}]
#使用字典定義表格的布局
my_layout = {
    'title': 'Most-Starred Python Projects on GitHub',
    'titlefont': {'size': 28},
    'xaxis': {
        'title': 'Repository',
        'titlefont': {'size': 24},
        'tickfont': {'size': 14},
    },
    'yaxis': {
        'title': 'Stars',
        'titlefont': {'size': 24},
        'tickfont': {'size': 14},
    },

}

fig = {'data': data, 'layout': my_layout}
offline.plot(fig, filename='python_repos.html')

最后我們可以生成一個可視化的html檔案在瀏覽器打開