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extracting single mut url from the batch processing step

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Tanushree Tunstall 2021-02-11 17:19:04 +00:00
parent 5d6ddb7639
commit 2e047fd548
2 changed files with 95 additions and 10 deletions
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72
dynamut/get_results.py
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@ -17,13 +17,13 @@ import pandas as pd
from pandas.api.types import is_string_dtype
from pandas.api.types import is_numeric_dtype
#%%============================================================================
#streptomycin/gid_complex.pdb
host = 'http://biosig.unimelb.edu.au/dynamut'
pred_dynamut_batch = '/results_prediction/161287964015'
result_id = re.search( r"([0-9]+)$", pred_dynamut).group(0)
host = 'http://biosig.unimelb.edu.au'
pred_dynamut_batch = '/dynamut/results_prediction/161287964015'
batch_result_url = host + pred_dynamut_batch
batch_result_url
# build a single url with a given mutation
result_id = re.search( r"([0-9]+)$", pred_dynamut_batch).group(0)
mut = 'S2C'
single_url = host + '/single_results/' + str(result_id)
single_result_url = host + '/single_results/' + str(result_id) + '/' + mut
@ -58,10 +58,8 @@ if result_response.status_code == 200:
print(results_df)
#%% for loop
single_url = host + '/single_results/' + str(result_id)
#%% looping over mutation
single_url = host + '/single_results/' + str(result_id)
muts = ["S2C", "S2F"]
# initilialise empty df
@ -100,4 +98,58 @@ for i, mut in enumerate(muts):
dynamut_results_df = dynamut_results_df.append(results_df)
print(dynamut_results_df)
#%% Derive the single url from the batch result itself
# get request from a batch url
# corresponding to href
batch_result_url
batch_response = requests.get(batch_result_url)
batch_soup = BeautifulSoup(batch_response.text, features = 'html.parser')
print(batch_soup)
#table = batch_soup.find('table', attrs = {'class':'table table-striped table-bordered table-responsive'})
#btn = batch_soup.find_all(href = True, attrs = {'class':'btn btn-default btn-sm'})
#print(btn)
# initilialise empty df
dynamut_results_df = pd.DataFrame()
for a in batch_soup.find_all('a', href=True, attrs = {'class':'btn btn-default btn-sm'}):
print ("Found the URL:", a['href'])
single_result_url = host + a['href']
snp = re.search(r'([A-Z]+[0-9]+[A-Z]+$)', single_result_url).group(0)
print(snp)
print('\nGetting results from:', single_result_url)
result_response = requests.get(single_result_url)
if result_response.status_code == 200:
print('\nFetching results for SNP:', snp)
# 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)
print('\nWriting dynamut results df')
dynamut_results_df.to_csv('test_dynamut.csv', index = False)
print('\nResults File:'
, '\nNo. of rows:', dynamut_results_df.shape[0]
, '\nNo. of cols:', dynamut_results_df.shape[1])