如何在Python 3中获取此站点的JSON数据?

2024-04-28 15:32:17 发布

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我的工作基本上是:

-进入本网站“https://aplicacoes.mds.gov.br/sagirmps/estrutura_fisica/preenchimento_municipio_cras_new1.php

-填写2张表格(例如AC - AcreBujari

-在生成的表的最后一列中单击“Dados Detalhados”(详细数据)(当您单击“Dados Detalhados”时,它将生成第二个表,其中的数据为每行1个月)

-通过点击“Visualizar Relat”访问第二个表生成的数据ó在每行的最后一列<;---这就是我要搜集的数据。但是它是一个动态的网站,我不能仅仅访问url2(当你点击“Visualizar relat”时)来获取数据ó里约'网站返回到初始网址,但与表我想刮)。代码如下:

import requests
from bs4 import BeautifulSoup  
import pandas as pd

url = 'http://aplicacoes.mds.gov.br/sagirmps/estrutura_fisica/preenchimento_municipio_cras_new1.php'
params ={
    'uf_ibge': '12',
    'nome_estado': 'AC - Acre'
    'p_ibge': '1200138'
    'nome_municipio': 'Bujari'    
}


r = requests.post(url, params = params, verify = False)
soup = BeautifulSoup(r.text, "lxml")
tables = pd.read_html(r.text)
unidades = tables[1]
print(unidades)


url2 = 'http://aplicacoes.mds.gov.br/sagirmps/estrutura_fisica/rel_preenchidos_cras.php?&p_id_cras=12001301971'
params2 ={
    'p_id_cras': '12001301971'
    'mes_referencia': '2019-02-01'
}
r2 = requests.post(url2, json = params2, verify = False)
soup2 = BeautifulSoup(r2.text, 'lxml')

soup2

请注意,url2是在“Dados Detalhados”中单击时生成的url,它的第二个字典是'p\u id\u cras'

params2应该是用来抓取我所说的数据的dict。我在第二个post请求中尝试了命令paramsdatajson,但都不起作用


Tags: 数据br网站paramsmdsgovphpurl2
1条回答
网友
1楼 · 发布于 2024-04-28 15:32:17

url2应该使用不带参数的GET
然后你有一个带有链接的页面和表,链接有href="javascript:"
而且onclick='enviadados(12001301971,"2019-02-01")'
所以你有下一个请求的参数

最后一个请求使用带有参数12001301971,2019-02-01和url的POST

https://aplicacoes.mds.gov.br/sagirmps/estrutura_fisica/visualiza_preenchimento_cras.php'`

我的密码。我希望它能正常工作

import requests
from bs4 import BeautifulSoup  
import pandas as pd

base = 'http://aplicacoes.mds.gov.br/sagirmps/estrutura_fisica/'

url = base + 'preenchimento_municipio_cras_new1.php'
#print('url:', url)
params ={
    'uf_ibge': '12',
    'nome_estado': 'AC - Acre',
    'p_ibge': '1200138',
    'nome_municipio': 'Bujari'    ,
}


r = requests.post(url, params=params, verify=False)
soup1 = BeautifulSoup(r.text, "lxml")
tables = pd.read_html(r.text)

#unidades = tables[1]
#print(unidades)

all_td1 = soup1.find('table', class_="panel-body").find_all('td')
#print('len(all_td1):', len(all_td1))
for td1 in all_td1:

    all_a1 = td1.find_all('a')[:1]
    #print('len(all_a1):', len(all_a1))
    for a1 in all_a1:

        url = base + a1['href']
        print('url:', url)

        r = requests.get(url, verify=False)
        soup2 = BeautifulSoup(r.text, "lxml")
        #print(soup.text)

        all_td2 = soup2.find('table', class_="panel-body").find_all('td')
        #print('len(all_td2):', len(all_td2))
        for td2 in all_td2:
            all_a2 = td2.find_all('a')
            #print('len(all_a2):', len(all_a2))
            for a2 in all_a2:
                print('onclick:', a2['onclick'])

                params = {
                    'p_id_cras': a2['onclick'][11:22], #'12001301971',
                    'mes_referencia': a2['onclick'][24:-2], #'2019-02-01',
                }

                print(params)

                url = 'https://aplicacoes.mds.gov.br/sagirmps/estrutura_fisica/visualiza_preenchimento_cras.php'
                r = requests.post(url, params=params, verify=False)
                soup = BeautifulSoup(r.text, "lxml")
                all_table = soup.find_all('table')
                print(all_table)

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