def picoTone()

in src/plugins/utils/tone.py [0:0]

• 48 lines of code
• 14 McCabe index (conditional complexity)

def picoTone(KibbleBit, bodies):
    """ Sentiment analysis using picoAPI Text Analysis """
    if 'picoapi' in KibbleBit.config:
        headers = {
            'Content-Type': 'application/json',
            'PicoAPI-Key': KibbleBit.config['picoapi']['key']
        }
        
        
        js = {
            "texts": []
          }
        
        # For each body...
        a = 0
        moods = []
        for body in bodies:
            # Crop out quotes
            lines = body.split("\n")
            body = "\n".join([x for x in lines if not x.startswith(">")])
            doc = {
                "id": str(a),
                "body": body
              }
            js['texts'].append(doc)
            moods.append({}) # placeholder for each doc, to be replaced
            a += 1
        try:
            rv = requests.post(
                "https://v1.picoapi.com/api/text/sentiment",
                headers = headers,
                data = json.dumps(js)
            )
            jsout = rv.json()
        except:
            jsout = {} # borked sentiment analysis?
        
        if 'results' in jsout and len(jsout['results']) > 0:
            for doc in jsout['results']:
                mood = {}
                
                # Sentiment is the overall score, and we use that for the neutrality of a text
                val = (1 + doc['sentiment']) / 2
                
                mood['negative'] = doc['negativity'] # Use the direct Bayesian score from picoAPI
                mood['positive'] = doc['positivity'] # Use the direct Bayesian score from picoAPI
                mood['neutral'] = doc['neutrality'] # Calc neutrality to favor a middle sentiment score, ignore high/low
                
                # Additional (optional) emotion weighting
                if 'emotions' in doc:
                    for k, v in doc['emotions'].items():
                        mood[k] = v / 100 # Value is betwen 0 and 100.
                        
                moods[int(doc['id'])] = mood # Replace moods[X] with the actual mood
                
        else:
            KibbleBit.pprint("Failed to analyze email body.")
            print(jsout)
            # 403 returned on invalid key, 429 on rate exceeded.
            # If we see a code return, let's just stop for now.
            # Later scans can pick up the slack.
            if 'code' in jsout:
                KibbleBit.pprint("Possible rate limiting in place, stopping for now.")
                return False
        return moods