Covid: nCov Data by Python

Covid: nCov Data by Python

Websites

Intsall

pip install Covid

Python package to get information regarding the novel corona virus provided by Johns Hopkins university and worldometers.info

1. John Hopkins University API

優點：有經緯度信息，方便畫地圖缺點：國內鏈接速度較慢

Get All Data

from covid import Covid

covid = Covid()
covid.get_data()

理論上你將獲得：

[
    {
        'id': '53',
        'country': 'China',
        'confirmed': 81020,
        'active': 9960,
        'deaths': 3217,
        'recovered': 67843,
        'latitude': 30.5928,
        'longitude': 114.3055,
        'last_update': 1584097775000
    },
    {...

實際上：

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/usr/local/lib/python3.7/site-packages/covid/john_hopkins/covid.py", line 137, in get_data
    return [CovidModel(**case["attributes"]).dict() for case in cases]
  File "/usr/local/lib/python3.7/site-packages/covid/john_hopkins/covid.py", line 137, in <listcomp>
    return [CovidModel(**case["attributes"]).dict() for case in cases]
  File "pydantic/main.py", line 338, in pydantic.main.BaseModel.__init__
pydantic.error_wrappers.ValidationError: 1 validation error for CovidModel
Recovered
  none is not an allowed value (type=type_error.none.not_allowed)

不過並不影響你獲取單個國際或地區的數據：

Get Data by Country

italy_cases = covid.get_status_by_country_id(115)

{
    'id': '115',
    'country': 'Italy',
    'confirmed': 24747,
    'active': 20603,
    'deaths': 1809,
    'recovered': 2335,
    'latitude': 41.8719,
    'longitude': 12.5674,
    'last_update': 1584318130000
}

國家編號獲取：

countries = covid.list_countries()

[{'id': '18', 'name': 'US'}, {'id': '22', 'name': 'Brazil'},...

Other Datas

##Get Total Active cases
active = covid.get_total_active_cases()
##Get Total Confirmed cases
confirmed = covid.get_total_confirmed_cases()
##Get Total Recovered cases
recovered = covid.get_total_recovered()
##Get Total Deaths
deaths = covid.get_total_deaths()

2. Worldometers.info

速度快，但是沒有經緯度信息

covid = Covid(source="worldometers")
##Get Data
covid.get_data()

[{'country': 'North America', 'confirmed': 2258033, 'new_cases': 4166, 'deaths': 135128, 'rec...

畫圖

因爲種種原因- - 我放棄使用python了，還是用R的ggplot的好。 哼哼 = =

1. 數據獲取

from covid import Covid

covid = Covid()
countries = covid.list_countries()
covid.get_status_by_country_id(int(countries[0]['id']))

## 多線程快速獲取
import multiprocessing as mp

def worker(i, return_dict):
  '''worker function'''
  Result = covid.get_status_by_country_id(int(countries[i]['id']))
  return_dict[Result] = Result
  print(Result)



def multicore(Pool=10):
  pool = mp.Pool(processes=Pool)
  #return_dict = manager.dict()
  for i in range(10):
    # Working function "echo" and the arg 'i'
    multi_res = [pool.apply_async(worker,(i,return_dict))]
  pool.close()
  pool.join()


if __name__ == '__main__':
  manager = mp.Manager()
  return_dict = manager.dict()
  jobs = []
  Num = 0
  for i in range(10):
    Num +=1
    print (Num)
    p = mp.Process(target=worker, args=(i,return_dict))
    jobs.append(p)
    p.start()
  for proc in jobs:
    proc.join()

= =

放棄了- - 太慢了