3

在 linux 下，我设置了 env var $NLTK_DATA('/home/user/data/nltk')，并且测试按预期工作

>>> from nltk.corpus import brown
>>> brown.words()
['The', 'Fulton', 'County', 'Grand', 'Jury', 'said', ...]

但是当运行另一个python脚本时，我得到了：

LookupError: 
**********************************************************************
Resource u'tokenizers/punkt/english.pickle' not found.  Please
use the NLTK Downloader to obtain the resource:  >>>
nltk.download()
Searched in:
- '/home/user/nltk_data'
- '/usr/share/nltk_data'
- '/usr/local/share/nltk_data'
- '/usr/lib/nltk_data'
- '/usr/local/lib/nltk_data'
- u''

正如我们所见，在手动添加 NLTK_DATA 目录后，nltk 不会将 $NLTK_DATA 添加到搜索路径：

nltk.data.path.append("/NLTK_DATA_DIR");

脚本按预期运行，问题是：

如何让 nltk 自动将 $NLTK_DATA 添加到它的搜索路径？

4

2 回答 2

6

如果您不想在运行脚本之前设置 $NLTK_DATA，您可以在 python 脚本中执行以下操作：

import nltk
nltk.path.append('/home/alvas/some_path/nltk_data/')

例如，让我们将 移至nltk_dataNLTK 不会自动找到它的非标准路径：

alvas@ubi:~$ ls nltk_data/
chunkers  corpora  grammars  help  misc  models  stemmers  taggers  tokenizers
alvas@ubi:~$ mkdir some_path
alvas@ubi:~$ mv nltk_data/ some_path/
alvas@ubi:~$ ls nltk_data/
ls: cannot access nltk_data/: No such file or directory
alvas@ubi:~$ ls some_path/nltk_data/
chunkers  corpora  grammars  help  misc  models  stemmers  taggers  tokenizers

现在，我们使用nltk.path.append()hack：

alvas@ubi:~$ python
>>> import os
>>> import nltk
>>> nltk.path.append('/home/alvas/some_path/nltk_data/')
>>> nltk.pos_tag('this is a foo bar'.split())
[('this', 'DT'), ('is', 'VBZ'), ('a', 'DT'), ('foo', 'JJ'), ('bar', 'NN')]
>>> nltk.data
<module 'nltk.data' from '/usr/local/lib/python2.7/dist-packages/nltk/data.pyc'>
>>> nltk.data.path
['/home/alvas/some_path/nltk_data/', '/home/alvas/nltk_data', '/usr/share/nltk_data', '/usr/local/share/nltk_data', '/usr/lib/nltk_data', '/usr/local/lib/nltk_data']
>>> exit()

让我们把它移回去，看看它是否有效：

alvas@ubi:~$ ls nltk_data
ls: cannot access nltk_data: No such file or directory
alvas@ubi:~$ mv some_path/nltk_data/ .
alvas@ubi:~$ python
>>> import nltk
>>> nltk.data.path
['/home/alvas/nltk_data', '/usr/share/nltk_data', '/usr/local/share/nltk_data', '/usr/lib/nltk_data', '/usr/local/lib/nltk_data']
>>> nltk.pos_tag('this is a foo bar'.split())
[('this', 'DT'), ('is', 'VBZ'), ('a', 'DT'), ('foo', 'JJ'), ('bar', 'NN')]

如果您真的真的想自动查找 nltk_data，请使用以下内容：

import scandir
import os, sys
import time

import nltk

def find(name, path):
    for root, dirs, files in scandir.walk(path):
        if root.endswith(name):
            return root

def find_nltk_data():
    start = time.time()
    path_to_nltk_data = find('nltk_data', '/')
    print >> sys.stderr, 'Finding nltk_data took', time.time() - start
    print >> sys.stderr,  'nltk_data at', path_to_nltk_data
    with open('where_is_nltk_data.txt', 'w') as fout:
        fout.write(path_to_nltk_data)
    return path_to_nltk_data

def magically_find_nltk_data():
    if os.path.exists('where_is_nltk_data.txt'):
        with open('where_is_nltk_data.txt') as fin:
            path_to_nltk_data = fin.read().strip()
        if os.path.exists(path_to_nltk_data):
            nltk.data.path.append(path_to_nltk_data)
        else:
            nltk.data.path.append(find_nltk_data())
    else:
        path_to_nltk_data  = find_nltk_data()
        nltk.data.path.append(path_to_nltk_data)


magically_find_nltk_data()
print nltk.pos_tag('this is a foo bar'.split())

让我们称之为python脚本test.py：

alvas@ubi:~$ ls nltk_data/
chunkers  corpora  grammars  help  misc  models  stemmers  taggers  tokenizers
alvas@ubi:~$ python test.py
Finding nltk_data took 4.27330780029
nltk_data at /home/alvas/nltk_data
[('this', 'DT'), ('is', 'VBZ'), ('a', 'DT'), ('foo', 'JJ'), ('bar', 'NN')]
alvas@ubi:~$ mv nltk_data/ some_path/
alvas@ubi:~$ python test.py
Finding nltk_data took 4.75850391388
nltk_data at /home/alvas/some_path/nltk_data
[('this', 'DT'), ('is', 'VBZ'), ('a', 'DT'), ('foo', 'JJ'), ('bar', 'NN')]
于 2016-04-03T08:39:56.037 回答
0

如果您想在 conda 环境中安装 NLTK 数据，并且不想在每个脚本中指定数据位置或导出环境变量，则需要执行以下操作：

  1. 激活您想要的 conda 环境。
  2. 在您的 conda 环境中打印sys.prefix，并复制此路径（假设/home/dickens/envs/nltk_env.
  3. 在 conda 环境中运行nltk.download()，选择所需的包，然后/share/nltk_data从上方附加到您的路径作为下载位置。例如，在我们的例子中，它将变为/home/dickens/envs/nltk_env/share/nltk_data。
  4. 你现在可以走了！
于 2018-11-25T02:16:23.507 回答