Extract Weights and scores from result about aspect-based-sentiment-analysis HOT 1 OPEN

# Convert slack from list to string.
slack = str(slack)

import re
# Replace suitable characters with new line characters.
wei = slack.replace(")", " \n ")
sco = slack.replace("]", " \n ")
asp = slack.replace(",", " \n ")

# Find out the weights, scores and aspect in the above 3 strings.
weights = re.findall(r"\bwei.*", wei)
scores = re.search(r"\bsco.*", sco)
scores = str(scores.group()) + "]"
aspec = re.search(r"\basp.*", asp)

print(weights)
print(scores)
print(aspec.group())

# Results are as following:
['weights=[0.28, 1.0, 0.71] ', 'weights=[0.13, 0.58, 0.58] ', 'weights=[0.25, 0.25, 0.17] ']
scores=[0.0005469012, 0.0009526044, 0.99850047 ]
aspect='mascara' 

an_string = str(slack)

# Extract aspect
aspect = an_string.split('aspect=')[1].split(',')[0]
print("aspect", aspect)

# Extract scores
scores = an_string.split("scores=[")[1].split("]")[0].split(",")
scores = [float(score) for score in scores]
print("scores", scores)

# Extract weights
def extract_weights(an_string,i):
    weights = an_string.split("weights=[")[i].split("]")[0].split(",")
    weights = [float(weight) for weight in weights]
    print(weights)

print("weights")
extract_weights(an_string,1)
extract_weights(an_string,2)
extract_weights(an_string,3)

# Results are as following:
aspect 'mascara'
scores [0.0005469007, 0.0009526035, 0.99850047]
weights
[0.28, 1.0, 0.71]
[0.13, 0.58, 0.58]
[0.25, 0.25, 0.17]