zhunhung
48 lines
2.3 KiB
Python
48 lines
2.3 KiB
Python
import subprocess
|
|
import shlex
|
|
import os.path
|
|
import sys
|
|
import pandas as pd
|
|
from os import getcwd
|
|
|
|
class PySentiStr:
|
|
def __init__(self):
|
|
self.SentiStrengthLocation = os.path.join(getcwd(),"SentiStrength.jar")
|
|
self.SentiStrengthLanguageFolder = os.path.join(getcwd(),"SentiStrengthData/")
|
|
|
|
if not os.path.isfile(self.SentiStrengthLocation):
|
|
print("SentiStrength not found at: ", SentiStrengthLocation,'\nSet path using setSentiStrengthPath(path) function.')
|
|
if not os.path.isdir(self.SentiStrengthLanguageFolder):
|
|
print("SentiStrength data folder not found at: ", SentiStrengthLanguageFolder,'\nSet path using setSentiStrengthLanguageFolderPath(path) function.')
|
|
|
|
def setSentiStrengthPath(self, ss_Path):
|
|
self.SentiStrengthLocation = ss_Path
|
|
|
|
def setSentiStrengthLanguageFolderPath(self, sslf_Path):
|
|
self.SentiStrengthLanguageFolder = sslf_Path
|
|
|
|
def getSentiment(self, df_text, score='scale'):
|
|
# Able to take in single string or list of string and convert into pandas Series
|
|
if type(df_text) != pd.Series:
|
|
df_text = pd.Series(df_text)
|
|
df_text = df_text.str.replace('\n','')
|
|
df_text = df_text.str.replace('\r','')
|
|
conc_text = '\n'.join(df_text)
|
|
p = subprocess.Popen(shlex.split("java -jar '" + self.SentiStrengthLocation + "' stdin sentidata '" + self.SentiStrengthLanguageFolder + "'"),stdin=subprocess.PIPE,stdout=subprocess.PIPE,stderr=subprocess.PIPE)
|
|
b = bytes(conc_text.replace(" ","+"), 'utf-8')
|
|
stdout_byte, stderr_text = p.communicate(b)
|
|
stdout_text = stdout_byte.decode("utf-8")
|
|
stdout_text = stdout_text.rstrip().replace("\t"," ")
|
|
stdout_text = stdout_text.replace('\r\n','')
|
|
senti_score = stdout_text.split(' ')
|
|
if score == 'scale':
|
|
senti_score = list(map(int, senti_score))
|
|
senti_score = [sum(senti_score[i:i+2])/4 for i in range(0, len(senti_score), 2)]
|
|
elif score == 'binary': # Return Positive and Negative Score
|
|
senti_score = list(map(int, senti_score))
|
|
senti_score = [tuple(senti_score[i:i+2]) for i in range(0, len(senti_score), 2)]
|
|
else:
|
|
return "Argument 'score' takes in either 'scale' (between -1 to 1) or 'binary' (two scores, positive and negative rating)"
|
|
return senti_score
|
|
|