I'm on a team that's working on a number of disease modeling efforts, and we're wanting to collect historical weekly influenza data from the WHO on a number of countries. The data are nominally available at
My goal is to collect the data shown in this table for a number of countries.
API oddities (AFAIK)
When a user fills out the form at the top and hits "Display report", a POST
request is submitted to https://apps.who.int/flumart/Default?ReportNo=12 that includes the obvious data, as well as some not-obvious data. Here's an example from the above screenshot:
ScriptManager1=ScriptManager1|ctl_ReportViewer$ctl09$Reserved_AsyncLoadTarget
__EVENTTARGET=ctl_ReportViewer$ctl09$Reserved_AsyncLoadTarget
__EVENTARGUMENT
__LASTFOCUS
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ddlFilterBy=1
lstSearchBy=Mexico
ctl_list_YearFrom=2017
ctl_list_WeekFrom=1
ctl_list_YearTo=2021
ctl_list_WeekTo=53
ctl_ReportViewer$ctl03$ctl00
ctl_ReportViewer$ctl03$ctl01
ctl_ReportViewer$ctl10=ltr
ctl_ReportViewer$ctl11=standards
ctl_ReportViewer$AsyncWait$HiddenCancelField=False
ctl_ReportViewer$ctl04$ctl03$ddValue=1
ctl_ReportViewer$ctl04$ctl05$ddValue=1
ctl_ReportViewer$ToggleParam$store
ctl_ReportViewer$ToggleParam$collapse=false
ctl_ReportViewer$ctl05$ctl00$CurrentPage
ctl_ReportViewer$ctl05$ctl03$ctl00
ctl_ReportViewer$ctl08$ClientClickedId
ctl_ReportViewer$ctl07$store
ctl_ReportViewer$ctl07$collapse=false
ctl_ReportViewer$ctl09$VisibilityState$ctl00=None
ctl_ReportViewer$ctl09$ScrollPosition
ctl_ReportViewer$ctl09$ReportControl$ctl02
ctl_ReportViewer$ctl09$ReportControl$ctl03
ctl_ReportViewer$ctl09$ReportControl$ctl04=100
__ASYNCPOST=true
I figured that I could whip out requests
and issue a simple query like this:
import requests
with requests.Session() as s:
data = {'lstSearchBy': 'Mexico',
'ctl_list_YearFrom': '2017',
'ctl_list_WeekFrom': '1',
'ctl_list_YearTo': '2021',
'ctl_list_WeekTo': '53'}
r = s.post('https://apps.who.int/flumart/Default?ReportNo=12', data=data)
print(r.text)
Unfortunately, rather than returning the table in the screenshot, this query simply returns the form at the top of the screenshot. At this point, I start to think that some of those other POST
parameters must actually be required (__EVENTTARGET
, __VIEWSTATE
, __VIEWSTATEGENERATOR
, etc.).
Looking at the original form that's returned when I visit https://apps.who.int/flumart/Default?ReportNo=12, I see this:
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 4.0 Transitional//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-transitional.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head id="Head1"><title>
WHO FLUMART OUTPUTS
</title></head>
<body>
<form method="post" action="./Default?ReportNo=12" id="form1">
<div class="aspNetHidden">
<input type="hidden" name="__EVENTTARGET" id="__EVENTTARGET" value="" />
<input type="hidden" name="__EVENTARGUMENT" id="__EVENTARGUMENT" value="" />
<input type="hidden" name="__LASTFOCUS" id="__LASTFOCUS" value="" />
<input type="hidden" name="__VIEWSTATE" id="__VIEWSTATE" value="u38eXuRq1rlncPtmBq04xgVPASJukKZ8QVDUb
...
(this is truncated for brevity)
Here, there are a number of hidden inputs with names that correspond to the POST
request that Firefox issues (__EVENTTARGET
, __EVENTARGUMENT
, __LASTFOCUS
, __EVENTVALIDATION
, etc.). This made me think that what I could do is just grab those values and then tack them onto the POST
data like this:
import requests
from bs4 import BeautifulSoup
with requests.Session() as s:
r = s.get('https://apps.who.int/flumart/Default?ReportNo=12')
soup = BeautifulSoup(r.text, 'lxml')
data = {'lstSearchBy': 'Mexico',
'ctl_list_YearFrom': '2017',
'ctl_list_WeekFrom': '1',
'ctl_list_YearTo': '2021',
'ctl_list_WeekTo': '53'}
hidden_inputs = soup.find_all('input', {'type': 'hidden'})
for i in hidden_inputs:
data.update({i['id']: i['value']})
r = s.post('https://apps.who.int/flumart/Default?ReportNo=12', data=data)
print(r.text)
But this unfortunately doesn't work either; I just get the same submission form.
I'm a bit stuck at this point. I'm clearly missing something. Does anyone have any insights in how I could grab the table that's produced in the screenshot? Any help is appreciated!
CodePudding user response:
There are a couple complexities that occur when scraping this site:
- In order to get the actual data from a request to the site's endpoint, the entire headers of the original browser's request must be sent, containing in particular the user agent and cookies.
- The
data
payload of thePOST
request should be encoded as it is displayed in the browser's developer network settings.
import requests
from bs4 import BeautifulSoup as soup
def parse_headers(s):
return dict(i.split(': ') for i in filter(None, s.split('\n')))
def get_page_data(headers, data):
return requests.post('https://apps.who.int/flumart/Default?ReportNo=12', headers=headers, data=data).text
def parse_table(page):
_, _, h, *body = [list(filter(None, [i.get_text(strip=True) for i in b.select('td')]))
for b in page.select('table table table table tr:nth-of-type(5) table tr')]
return [dict(zip([*filter(None, h)], i)) for i in body]
def data_format(filter_by, year_from, week_from, year_to, week_to):
return f'ScriptManager1=ScriptManager1|ctl_ReportViewer$ctl09$Reserved_AsyncLoadTarget&ddlFilterBy=1&lstSearchBy={filter_by}&ctl_list_YearFrom={year_from}&ctl_list_WeekFrom={week_from}&ctl_list_YearTo={year_to}&ctl_list_WeekTo={week_to}&ctl_ReportViewer$ctl03$ctl00=&ctl_ReportViewer$ctl03$ctl01=&ctl_ReportViewer$ctl10=ltr&ctl_ReportViewer$ctl11=standards&ctl_ReportViewer$AsyncWait$HiddenCancelField=False&ctl_ReportViewer$ctl04$ctl03$ddValue=2&ctl_ReportViewer$ctl04$ctl05$ddValue=1&ctl_ReportViewer$ToggleParam$store=&ctl_ReportViewer$ToggleParam$collapse=false&ctl_ReportViewer$ctl05$ctl00$CurrentPage=&ctl_ReportViewer$ctl05$ctl03$ctl00=&ctl_ReportViewer$ctl08$ClientClickedId=&ctl_ReportViewer$ctl07$store=&ctl_ReportViewer$ctl07$collapse=false&ctl_ReportViewer$ctl09$VisibilityState$ctl00=None&ctl_ReportViewer$ctl09$ScrollPosition=&ctl_ReportViewer$ctl09$ReportControl$ctl02=&ctl_ReportViewer$ctl09$ReportControl$ctl03=&ctl_ReportViewer$ctl09$ReportControl$ctl04=100&__EVENTTARGET=ctl_ReportViewer$ctl09$Reserved_AsyncLoadTarget&__EVENTARGUMENT=&__LASTFOCUS=&__VIEWSTATE=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&__VIEWSTATEGENERATOR=15FCE702&__EVENTVALIDATION=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&__ASYNCPOST=true&'
headers = """Host: apps.who.int
authority: apps.who.int
sec-ch-ua: "Chromium";v="94", "Google Chrome";v="94", ";Not A Brand";v="99"
sec-ch-ua-mobile: ?0
user-agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/94.0.4606.81 Safari/537.36
content-type: application/x-www-form-urlencoded; charset=UTF-8
cache-control: no-cache
x-requested-with: XMLHttpRequest
x-microsoftajax: Delta=true
sec-ch-ua-platform: "macOS"
accept: */*
origin: https://apps.who.int
sec-fetch-site: same-origin
sec-fetch-mode: cors
sec-fetch-dest: empty
referer: https://apps.who.int/flumart/Default?ReportNo=12
accept-language: en-US,en;q=0.9
cookie: ASP.NET_SessionId=bnx31vt1hsfsldihuszbk452; BIGipServerpool_apps.who.int_http=rd2o00000000000000000000ffff9ee80c4eo80; TS01ac0ef4=015dd60f3e1f352f15a41d299fd9ecd7a082e0b85eb62504deed1220d15a2f9bb946cec46693ae3a5e8d2733baff23250470302f28f8d768bf0028a5807d15b3cf9569ac54cf66bc629d7233dd96a586a1ceb17a95
Content-Length: 24277"""
data = data_format('United States of America', 2020, 2, 2020, 9)
print(parse_table(soup(get_page_data(parse_headers(headers), data), 'html.parser')))
Due to the character limits on Stack Overflow posts, the output from the script can be found here.