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logistic.py
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logistic.py
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import json
import time
import requests
from pyecharts.charts import Map, Timeline
from pyecharts import options as opts
def update_news():
url = 'https://lab.isaaclin.cn/nCoV/api/news?num=5'
news_data = []
res = requests.get(url)
while res.status_code != 200:
res = requests.get(url)
data = json.loads(res.text)
for r in reversed(data['results']):
news_data.append({
'title': r['title'],
'sourceUrl': r['sourceUrl'],
'infoSource': time.strftime('%m-%d %H:%M:%S', time.localtime(r['pubDate'] / 1000)) + ' ' + r[
'infoSource']
})
return news_data
def update_overall():
url = 'https://lab.isaaclin.cn/nCoV/api/overall?latest=1'
res = requests.get(url)
while res.status_code != 200:
res = requests.get(url)
overall_data = json.loads(res.text)
overall_data['time'] = time.strftime("%m-%d %H:%M", time.localtime(time.time()))
return overall_data
def update_map(unit=3600 * 2):
map_data = {}
start_time = 1579701600
url = 'https://lab.isaaclin.cn/nCoV/api/area?latest=1'
# params = {'country': '中国'}
res = requests.get(url)
while res.status_code != 200:
res = requests.get(url)
# print(res.status_code)
data = json.loads(res.text)
time_zone = set()
provinces = set()
start_num = {}
for r in data['results']:
if 'confirmedCount' not in r or r['countryName']!="中国":
continue
mtime = int(r['updateTime']) / 1000
if mtime < start_time:
continue
provinces.add(r['provinceShortName'])
if r['provinceShortName'] not in map_data:
map_data[r['provinceShortName']] = {}
start_num[r['provinceShortName']] = {
'确诊人数': 100000,
'治愈人数': 100000,
'死亡人数': 100000,
'疑似感染人数': 100000
}
time_str = time.strftime("%m-%d %H:%M", time.localtime(mtime - mtime % unit))
time_zone.add(time_str)
if time_str not in map_data[r['provinceShortName']]:
map_data[r['provinceShortName']][time_str] = {
}
map_data[r['provinceShortName']][time_str]['确诊人数'] = r['confirmedCount']
map_data[r['provinceShortName']][time_str]['疑似感染人数'] = r['suspectedCount']
map_data[r['provinceShortName']][time_str]['治愈人数'] = r['curedCount']
map_data[r['provinceShortName']][time_str]['死亡人数'] = r['deadCount']
start_num[r['provinceShortName']]['确诊人数'] = min(start_num[r['provinceShortName']]['确诊人数'], r['confirmedCount'])
try:
start_num[r['provinceShortName']]['疑似感染人数'] = min(start_num[r['provinceShortName']]['疑似感染人数'],
r['suspectedCount'])
except Exception as e:
start_num[r['provinceShortName']]['疑似感染人数'] = min(start_num[r['provinceShortName']]['疑似感染人数'],
0)
print(r)
start_num[r['provinceShortName']]['治愈人数'] = min(start_num[r['provinceShortName']]['治愈人数'], r['curedCount'])
start_num[r['provinceShortName']]['死亡人数'] = min(start_num[r['provinceShortName']]['死亡人数'], r['deadCount'])
# 修正宁夏起始数量
start_num['宁夏'] = {
'确诊人数': 2,
'治愈人数': 0,
'死亡人数': 0,
'疑似感染人数': 0
}
time_zone = sorted(list(time_zone))
process_data = {}
for i in range(len(time_zone)):
t = time_zone[i]
process_data[t] = {
'确诊人数': [],
'治愈人数': [],
'死亡人数': [],
'疑似感染人数': []
}
for p in provinces:
if p not in map_data:
process_data[t]['确诊人数'] += [[p, start_num[p]['确诊人数']]]
process_data[t]['治愈人数'] += [[p, start_num[p]['治愈人数']]]
process_data[t]['死亡人数'] += [[p, start_num[p]['死亡人数']]]
process_data[t]['疑似感染人数'] += [[p, start_num[p]['疑似感染人数']]]
continue
if t in map_data[p]:
process_data[t]['确诊人数'] += [[p, map_data[p][t]['确诊人数']]]
process_data[t]['治愈人数'] += [[p, map_data[p][t]['治愈人数']]]
process_data[t]['死亡人数'] += [[p, map_data[p][t]['死亡人数']]]
process_data[t]['疑似感染人数'] += [[p, map_data[p][t]['疑似感染人数']]]
else:
flag = i - 1
for j in range(i - 1, -1, -1):
tj = time_zone[j]
if tj in map_data[p]:
process_data[t]['确诊人数'] += [[p, map_data[p][tj]['确诊人数']]]
process_data[t]['治愈人数'] += [[p, map_data[p][tj]['治愈人数']]]
process_data[t]['死亡人数'] += [[p, map_data[p][tj]['死亡人数']]]
process_data[t]['疑似感染人数'] += [[p, map_data[p][tj]['疑似感染人数']]]
break
flag -= 1
if flag == -1:
process_data[t]['确诊人数'] += [[p, start_num[p]['确诊人数']]]
process_data[t]['治愈人数'] += [[p, start_num[p]['治愈人数']]]
process_data[t]['死亡人数'] += [[p, start_num[p]['死亡人数']]]
process_data[t]['疑似感染人数'] += [[p, start_num[p]['疑似感染人数']]]
return process_data
def confirmed_map(map_data):
tl = Timeline()
for t in map_data:
map0 = (
Map()
.add(
"确诊人数", [p for p in map_data[t]['确诊人数'] if p[1] != 0],maptype='china'
)
.set_series_opts(label_opts=opts.LabelOpts(is_show=False))
.set_global_opts(
visualmap_opts=opts.VisualMapOpts(max_=2000),
legend_opts=opts.LegendOpts(is_show=False)
)
)
tl.add(map0, t)
return tl
if __name__ == '__main__':
print(update_map())