使用Python NLTK的AWS lambda中的路径

2019年8月3日 144次阅读

我在AWS Lambda中遇到NLTK包的问题.但是我认为这个问题更多地与Lambda中的路径配置不正确有关. NLTK无法找到本地存储的数据库,而不是模块安装的一部分. SO上列出的许多解决方案都是简单的路径配置,可以在这里找到,但我认为这个问题与Lambda中的路径有关：

How to config nltk data directory from code?

What to download in order to make nltk.tokenize.word_tokenize work?

还应该提到这也与我在此发布的上一个问题有关
Using NLTK corpora with AWS Lambda functions in Python

但问题似乎更为笼统,因此我选择重新定义问题,因为它涉及如何正确配置Lambda中的路径环境以使用需要外部库(如NLTK)的模块. NLTK将很多数据存储在本地的nltk_data文件夹中,但是在lambda zip中包含此文件夹以供上传,它似乎找不到它.

Lambda func zip文件中还包含以下文件和目录：

\nltk_data\taggers\averaged_perceptron_tagger\averaged_perceptron_tagger.pickle
\nltk_data\tokenizers\punkt\english.pickle
\nltk_data\tokenizers\punkt\PY3\english.pickle

从以下站点看来,var / task /似乎是lambda函数执行的文件夹,我尝试将此路径包含在内. https://alestic.com/2014/11/aws-lambda-environment/

从文档中看来,似乎有许多环境变量可以使用但是我不知道如何将它们包含在python脚本中(来自windows,而不是linux)http://docs.aws.amazon.com/lambda/latest/dg/current-supported-versions.html

希望在此处提出这个问题,任何人都有配置Lambda路径的经验.尽管有搜索,我还没有看到很多关于这个特定问题的问题,所以希望解决这个问题可能有用

代码就在这里

import nltk
import pymysql.cursors
import re
import rds_config
import logging
from boto_conn import botoConn
from warnings import filterwarnings
from nltk import word_tokenize

nltk.data.path.append("/nltk_data/tokenizers/punkt")
nltk.data.path.append("/nltk_data/taggers/averaged_perceptron_tagger")

logger = logging.getLogger()

logger.setLevel(logging.INFO)

rds_host = "nodexrd2.cw7jbiq3uokf.ap-southeast-2.rds.amazonaws.com"
name = rds_config.db_username
password = rds_config.db_password
db_name = rds_config.db_name

filterwarnings("ignore", category=pymysql.Warning)


def parse():

    tknzr = word_tokenize

    stopwords = ['i', 'me', 'my', 'myself', 'we', 'our', 'ours', 'ourselves', 'you', 'your', 'yours', 'yourself','yourselves', 'he', 'him', 'his', 'himself', 'she', 'her', 'hers', 'herself', 'it', 'its', 'itself',
                 'they', 'them', 'their', 'theirs', 'themselves', 'what', 'which', 'who', 'whom', 'this', 'that','these','those', 'am', 'is', 'are', 'was', 'were', 'be', 'been', 'being', 'have', 'has', 'had', 'having', 'do',
                 'does', 'did', 'doing', 'a', 'an', 'the', 'and', 'but', 'if', 'or', 'because', 'as', 'until', 'while', 'of','at', 'by', 'for', 'with', 'about', 'against', 'between', 'into', 'through', 'during', 'before', 'after', 'above',
                 'below','to', 'from', 'up', 'down', 'in', 'out', 'on', 'off', 'over', 'under', 'again', 'further', 'then','once', 'here','there', 'when', 'where', 'why', 'how', 'all', 'any', 'both', 'each', 'few', 'more', 'most', 'other',
                 'some', 'such','no', 'nor', 'not', 'only', 'own', 'same', 'so', 'than', 'too', 'very', 's', 't', 'can', 'will','just', 'don', 'should','now', 'd', 'll', 'm', 'o', 're', 've', 'y', 'ain', 'aren', 'couldn', 'didn', 'doesn', 'hadn', 'hasn',
                 'haven', 'isn', 'ma','mightn', 'mustn', 'needn', 'shan', 'shouldn', 'wasn', 'weren', 'won', 'wouldn']

    s3file = botoConn(None, 1).getvalue()
    db = pymysql.connect(rds_host, user=name, passwd=password, db=db_name, connect_timeout=5, charset='utf8mb4', cursorclass=pymysql.cursors.DictCursor)
    lines = s3file.split('\n')

    for line in lines:

        tkn = tknzr(line)
        tagged = nltk.pos_tag(tkn)

        excl = ['the', 'and', 'of', 'at', 'what', 'to', 'it', 'a', 'of', 'i', 's', 't', 'is', 'I\'m', 'Im', 'U', 'RT', 'RTs', 'its']  # Arg

        x = [i for i in tagged if i[0] not in stopwords]
        x = [i for i in x if i[0] not in excl]
        x = [i for i in x if len(i[0]) > 1]
        x = [i for i in x if 'https' not in i[0]]
        x = [i for i in x if i[1] == 'NNP' or i[1] == 'VB' or i[1] == 'NN']
        x = [(re.sub(r'[^A-Za-z0-9]+' + '()', r'', i[0])) for i in x]
        sql_dat_a, sql_dat = [], []

输出日志在这里：

   **********************************************************************
  Resource u'tokenizers/punkt/english.pickle' not found.  Please
  use the NLTK Downloader to obtain the resource:  >>>
  nltk.download()
  Searched in:
    - '/home/sbx_user1067/nltk_data'
    - '/usr/share/nltk_data'
    - '/usr/local/share/nltk_data'
    - '/usr/lib/nltk_data'
    - '/usr/local/lib/nltk_data'
    - '/nltk_data/tokenizers/punkt'
    - '/nltk_data/taggers/averaged_perceptron_tagger'
    - u''
**********************************************************************: LookupError
Traceback (most recent call last):
  File "/var/task/Tweetscrape_Timer.py", line 27, in schedule
    server()
  File "/var/task/Tweetscrape_Timer.py", line 14, in server
    parse()
  File "/var/task/parse_to_SQL.py", line 91, in parse
    tkn = tknzr(line)
  File "/var/task/nltk/tokenize/__init__.py", line 109, in word_tokenize
    return [token for sent in sent_tokenize(text, language)
  File "/var/task/nltk/tokenize/__init__.py", line 93, in sent_tokenize
    tokenizer = load('tokenizers/punkt/{0}.pickle'.format(language))
  File "/var/task/nltk/data.py", line 808, in load
    opened_resource = _open(resource_url)
  File "/var/task/nltk/data.py", line 926, in _open
    return find(path_, path + ['']).open()
  File "/var/task/nltk/data.py", line 648, in find
    raise LookupError(resource_not_found)
LookupError: 
**********************************************************************
  Resource u'tokenizers/punkt/english.pickle' not found.  Please
  use the NLTK Downloader to obtain the resource:  >>>
  nltk.download()
  Searched in:
    - '/home/sbx_user1067/nltk_data'
    - '/usr/share/nltk_data'
    - '/usr/local/share/nltk_data'
    - '/usr/lib/nltk_data'
    - '/usr/local/lib/nltk_data'
    - '/nltk_data/tokenizers/punkt'
    - '/nltk_data/taggers/averaged_perceptron_tagger'
    - u''
**********************************************************************

最佳答案 似乎您当前的Python代码是从/ var / task运行的.我建议尝试(没试过自己)：

nltk.data.path.append("/var/task/nltk_data")
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