Web scraping from html code of a database using python

user_16534568 0
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I am new to python and am learning things slowly. I have earlier performed API calls from databases to extract infromation. However, I was dealing with a particular Indian database. The html script seems confusing to extract the particular infromation I am looking for. Basically, I have a list of herb name links as input which looks like this(only the ID changes):

http://envis.frlht.org/plantdetails/3315/fd01bd598f0869d65fe5a2861845f9f8
http://envis.frlht.org/plantdetails/2133/fd01bd598f0869d65fe5a2861845f9f9
http://envis.frlht.org/plantdetails/845/fd01bd598f0869d65fe5a2861845f9f10
http://envis.frlht.org/plantdetails/363/fd01bd598f0869d65fe5a2861845f9f11

When I open each of this, I want to extract the "Distribution" detail for these herb links from the webpage. That's all. But, in the html script, I cant figure which header has the detail. I tried a lot before coming here. Can someone please help me. Thanks in advance.

Code:

import requests
import urllib.request
import time
from bs4 import BeautifulSoup
import json
import pandas as pd
import os
from pathlib import Path
from pprint import pprint

user_home = os.path.expanduser('~')
OUTPUT_DIR = os.path.join(user_home, 'vk_frlht')
Path(OUTPUT_DIR).mkdir(parents=True, exist_ok=True)

herb_url = 'http://envis.frlht.org/bot_search'
response = requests.get(herb_url)
soup = BeautifulSoup(response.text, "html.parser")
token = soup.find('Type Botanical Name', {'type': 'hidden', 'name': 'token'})
herb_query_url = 'http://envis.frlht.org/plantdetails/3315/fd01bd598f0869d65fe5a2861845f9f8'

response = requests.get('http://envis.frlht.org/plantdetails/3315/fd01bd598f0869d65fe5a2861845f9f8')

#optional code for many links at once

with open(Path, 'r') as f:
    frlhtinput = f.readlines()
    frlht = [x[:-1] for x in frlhtinput]

    for line in frlht:
        out = requests.get(f'http://envis.frlht.org/plantdetails/{line}')
#end of the optional code

herb_query_soup = BeautifulSoup(response.text, "html.parser")
text = herb_query_soup.find('div', {'id': 'result-details'})
pprint(text)
web-scraping beautifulsoup html python database
4 Answers

This is how this page looks after scrapping:

enter image description here

Loading sign in the middle means that content can be loaded only after JavaScript code executes. Meaning someone protected this content with JS code. You have to use Selenium browser instead of BS4.

See tutorial here on how to use it.

user_21199410

Try it.

import requests
from bs4 import BeautifulSoup
from pprint import pprint

plant_ids = ["3315", "2133", "845", "363"]
results = []
for plant_id in plant_ids:
    herb_query_url = f"http://envis.frlht.org/plantdetails/{plant_id}/fd01bd598f0869d65fe5a2861845f9f8"
    headers = {
        "Referer": herb_query_url,
    }
    response = requests.get(
        f"http://envis.frlht.org/bot_search/plantdetails/plantid/{plant_id}/nocache/0.7763327765552295/referredfrom/extplantdetails",
        headers=headers,
    )
    herb_query_soup = BeautifulSoup(response.text, "html.parser")
    result = herb_query_soup.findAll("div", {"class": "initbriefdescription"})
    for r in result:
        result_dict = {r.text.split(":", 1)[0].strip(): r.text.split(":", 1)[1].strip()}
        results.append(result_dict)
pprint(results)
user_188784660

The information is obtained from another URL based on the URLs you have. First you need to construct the required URL (which was found looking at the browser) and requesting that.

This information could be written to a CSV file as follows. It assumes you have a text file IDs.txt as follows:

http://envis.frlht.org/plantdetails/3315/fd01bd598f0869d65fe5a2861845f9f8
http://envis.frlht.org/plantdetails/2133/fd01bd598f0869d65fe5a2861845f9f9
http://envis.frlht.org/plantdetails/845/fd01bd598f0869d65fe5a2861845f9f10
http://envis.frlht.org/plantdetails/363/fd01bd598f0869d65fe5a2861845f9f11

import requests
from bs4 import BeautifulSoup
import csv


fieldnames = ["ID", "Accepted Name", "Family", "Used in", "Distribution"]

with open('IDs.txt') as f_input, open('output.csv', 'w', newline='') as f_output:
    csv_output = csv.DictWriter(f_output, fieldnames=fieldnames, extrasaction='ignore')
    csv_output.writeheader()

    for line in f_input:
        url = line.strip()  # Remove newline
        print(url)
        url_split = url.split('/')
        url_details = f"http://envis.frlht.org/bot_search/plantdetails/plantid/{url_split[4]}/nocache/{url_split[5]}/referredfrom/extplantdetails"
        
        headers = {
            'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/35.0.1916.47 Safari/537.36',
            'Referer' : url,
        }
        
        req = requests.get(url_details, headers=headers)
        soup = BeautifulSoup(req.content, "html.parser")
        row = {field : '' for field in fieldnames}      # default values
        row['ID'] = url_split[4]
            
        for div in soup.find_all('div', class_="initbriefdescription"):
            entry, value = div.get_text(strip=True).split(":" ,1)
            row[entry] = value

        csv_output.writerow(row)

Giving an output starting:

ID,Accepted Name,Family,Used in,Distribution
3315,Amaranthus hybridusL. subsp.cruentusvar.paniculatusTHELL.,AMARANTHACEAE,"Ayurveda, Siddha, Folk","This species is globally distributed in Africa, Asia and India. It is said to be cultivated as a leafy vegetable in Maharashtra, Karnataka (Coorg) and on the Nilgiri hills of Tamil Nadu. It is also found as an escape."
2133,Triticum aestivumL.,POACEAE,"Ayurveda, Siddha, Unani, Folk, Chinese, Modern",
845,Dolichos biflorusL.,FABACEAE,"Ayurveda, Siddha, Unani, Folk, Sowa Rigpa","This species is native to India, globally distributed in the Paleotropics. Within India, it occurs all over up to an altitude of 1500 m. It is an important pulse crop particularly in Madras, Mysore, Bombay and Hyderabad."
363,Brassica oleraceaL.,BRASSICACEAE,"Ayurveda, Siddha",
user_49857330 
enter code here

import requests
from bs4 import BeautifulSoup
import csv


fieldnames = ["ID", "Accepted Name", "Family", "Used in", "Distribution"]

with open('IDs.txt') as f_input, open('output.csv', 'w', newline='') as f_output:
csv_output = csv.DictWriter(f_output, fieldnames=fieldnames, extrasaction='ignore')
csv_output.writeheader()

for line in f_input:
    url = line.strip()  # Remove newline
    print(url)
    url_split = url.split('/')
    url_details = f"http://envis.frlht.org/bot_search/plantdetails/plantid/{url_split[4]}/nocache/{url_split[5]}/referredfrom/extplantdetails"
    
    headers = {
        'User-Agent': 'Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_3) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/35.0.1916.47 Safari/537.36',
        'Referer' : url,
    }
    
    req = requests.get(url_details, headers=headers)
    soup = BeautifulSoup(req.content, "html.parser")
    row = {field : '' for field in fieldnames}      # default values
    row['ID'] = url_split[4]
    
    result = soup.findAll("div", {"class": "initbriefdescription"})
    for r in result:
        result_dict = r.get_text(strip=True).split(":" ,1)
        results.append(result_dict)
        
        row[entry] = results
        print(row)

with open('output.csv', 'w', newline='') as f_output:
    csv_output = csv.DictWriter(f_output, fieldnames=fieldnames, extrasaction='ignore')
    csv_output.writeheader()
    csv_output.writerow(row)
user_165345680
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