60 lines
1.4 KiB
Python
60 lines
1.4 KiB
Python
import time
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import urllib.request
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import urllib.parse
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import json
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import hashlib
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import base64
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from utils import config_util as cfg
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__URL = "https://ltpapi.xfyun.cn/v2/sa"
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def __quest(text):
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body = urllib.parse.urlencode({'text': text}).encode('utf-8')
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param = {"type": "dependent"}
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x_param = base64.b64encode(json.dumps(param).replace(' ', '').encode('utf-8'))
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x_time = str(int(time.time()))
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x_checksum = hashlib.md5(cfg.key_xf_ltp_api_key.encode('utf-8') + str(x_time).encode('utf-8') + x_param).hexdigest()
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x_header = {
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'X-Appid': cfg.key_xf_ltp_app_id,
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'X-CurTime': x_time,
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'X-Param': x_param,
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'X-CheckSum': x_checksum
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}
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req = urllib.request.Request(__URL, body, x_header)
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result = urllib.request.urlopen(req)
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result = result.read()
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return json.loads(result.decode('utf-8'))
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"""
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情感分析
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:param text: 文本
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:returns: 情感分数 (0.7以上为褒义, 0.3-0.7为中性 0.3以下为贬义,, -1为分析失败)
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"""
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def get_score(text):
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result = __quest(text)
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if result['desc'] == 'success':
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return float(result['data']['score'])
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return -1
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"""
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情感分析
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:param text: 文本
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:returns: 情感极性分类 (2为褒义, 1为中性 0为贬义,, -1为分析失败)
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"""
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def get_sentiment(text):
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result = __quest(text)
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if result['desc'] == 'success':
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return int(result['data']['sentiment']) + 1
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return -1
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