101 lines
3.6 KiB
Python
Executable file
101 lines
3.6 KiB
Python
Executable file
#!/usr/bin/env python3
|
|
# -*- coding: utf-8 -*-
|
|
"""
|
|
Created on Wed Aug 19 14:33:51 2020
|
|
|
|
@author: tanu
|
|
"""
|
|
|
|
|
|
#%% load packages
|
|
import os,sys
|
|
import subprocess
|
|
import argparse
|
|
import requests
|
|
import re
|
|
import time
|
|
from bs4 import BeautifulSoup
|
|
import pandas as pd
|
|
from pandas.api.types import is_string_dtype
|
|
from pandas.api.types import is_numeric_dtype
|
|
#%%============================================================================
|
|
|
|
batch_result_url = 'http://biosig.unimelb.edu.au/dynamut/results_prediction/15955901077'
|
|
|
|
mut = 'S104R'
|
|
single_result_url = 'http://biosig.unimelb.edu.au/dynamut/single_results/15955901077' + '/' + mut
|
|
|
|
|
|
|
|
#%%============================================================================
|
|
param_dict = {}
|
|
|
|
result_response = requests.get(single_result_url)
|
|
if result_response.status_code == 200:
|
|
print('Fetching results')
|
|
# extract results using the html parser
|
|
soup = BeautifulSoup(result_response.text, features = 'html.parser')
|
|
#web_result_raw = soup.find(id = 'predictions').get_text()
|
|
ddg_dynamut = soup.find(id = 'ddg_dynamut').get_text()
|
|
ddg_encom = soup.find(id = 'ddg_encom').get_text()
|
|
ddg_mcsm = soup.find(id = 'ddg_mcsm').get_text()
|
|
ddg_sdm = soup.find(id = 'ddg_sdm').get_text()
|
|
ddg_duet = soup.find(id = 'ddg_duet').get_text()
|
|
dds_encom = soup.find(id = 'dds_encom').get_text()
|
|
|
|
param_dict = {"mutationinformation" : mut
|
|
, "ddg_dynamut" : ddg_dynamut
|
|
, "ddg_encom" : ddg_encom
|
|
, "ddg_mcsm" : ddg_mcsm
|
|
, "ddg_sdm" : ddg_sdm
|
|
, "ddg_duet" : ddg_duet
|
|
, "dds_encom" : dds_encom
|
|
|
|
}
|
|
results_df = pd.DataFrame.from_dict(param_dict, orient = "index").T
|
|
|
|
#%% for loop
|
|
#%%
|
|
host_dynamut = 'http://biosig.unimelb.edu.au/dynamut'
|
|
batch_url_number = re.search(r'([0-9]+)$', batch_result_url).group(0)
|
|
single_url = host_dynamut + '/single_results/' + batch_url_number
|
|
|
|
muts = ["S104R", "G24R"]
|
|
|
|
# initilialise empty df
|
|
dynamut_results_df = pd.DataFrame()
|
|
|
|
for i, mut in enumerate(muts):
|
|
#param_dict = {}
|
|
print('Running mutation', i, ':', mut)
|
|
snp = mut
|
|
single_result_url = single_url + '/' + snp
|
|
print('Getting results from:', single_result_url)
|
|
|
|
result_response = requests.get(single_result_url)
|
|
if result_response.status_code == 200:
|
|
print('Fetching results')
|
|
# extract results using the html parser
|
|
soup = BeautifulSoup(result_response.text, features = 'html.parser')
|
|
#web_result_raw = soup.find(id = 'predictions').get_text()
|
|
ddg_dynamut = soup.find(id = 'ddg_dynamut').get_text()
|
|
ddg_encom = soup.find(id = 'ddg_encom').get_text()
|
|
ddg_mcsm = soup.find(id = 'ddg_mcsm').get_text()
|
|
ddg_sdm = soup.find(id = 'ddg_sdm').get_text()
|
|
ddg_duet = soup.find(id = 'ddg_duet').get_text()
|
|
dds_encom = soup.find(id = 'dds_encom').get_text()
|
|
|
|
param_dict = {"mutationinformation" : snp
|
|
, "ddg_dynamut" : ddg_dynamut
|
|
, "ddg_encom" : ddg_encom
|
|
, "ddg_mcsm" : ddg_mcsm
|
|
, "ddg_sdm" : ddg_sdm
|
|
, "ddg_duet" : ddg_duet
|
|
, "dds_encom" : dds_encom
|
|
}
|
|
results_df = pd.DataFrame.from_dict(param_dict, orient = "index").T
|
|
print(results_df)
|
|
dynamut_results_df = dynamut_results_df.append(results_df)
|
|
print(dynamut_results_df)
|
|
|
|
|