Why do I get a TypeError when importing a textfile line by line for sentiment analysis instead of using a sentence hard-coded?

Question

I am trying to analyze the sentiment of each given sentence from a text file line by line. The code is working whenever I am using the hard coded sentences from the first question linked. When I use the text file input, I get the TypeError.

This is related to the question asked here. And the line by line from text file code is coming from this question:

The first one works, the second with the text-file ("I love you. I hate him. You are nice. He is dumb") does not work. Here is the code :

from pycorenlp import StanfordCoreNLP
nlp = StanfordCoreNLP('http://localhost:9000')
results = []    
with open("c:/nlp/test.txt","r") as f:
    for line in f.read().split('\n'):
        print("Line:" + line)
        res = nlp.annotate(line,
                   properties={
                       'annotators': 'sentiment',
                       'outputFormat': 'json',
                       'timeout': 1000,
                   })
        results.append(res)      

for res in results:             
    s = res["sentences"]         
    print("%d: '%s': %s %s" % (
        s["index"], 
        " ".join([t["word"] for t in s["tokens"]]),
        s["sentimentValue"], s["sentiment"]))

I get this error:

line 21, in

s["index"],

TypeError: list indices must be integers or slices, not str

Answer 1

Looks like I solved the problem. As londo pointed out: This line sets S as List, but it should be dict, just like in the original code:

s = res["sentences"] 

I moved the code into the same loop where the file is read and analyzed line by line and I print the result directly there. So the new code looks like this:

from pycorenlp import StanfordCoreNLP

nlp = StanfordCoreNLP('http://localhost:9000')

with open("c:/nlp/test.txt","r") as f:
    for line in f.read().split('\n'):
        res = nlp.annotate(line,
                    properties={
                        'annotators': 'sentiment',
                        'outputFormat': 'json',
                        'timeout': 15000,
                   }) 
        for s in res["sentences"]:
            print("%d: '%s': %s %s" % (
            s["index"], 
            " ".join([t["word"] for t in s["tokens"]]),
            s["sentimentValue"], s["sentiment"]))

The result looks just as intended and without any error message:

0: 'I love you .': 3 Positive
0: 'I hate him .': 1 Negative
0: 'You are nice .': 3 Positive
0: 'He is dumb .': 1 Negative