Question

我的项目使用NLTK。如何列出项目的语料库＆amp;模型要求，以便它们可以自动安装？我不想点击nltk.download() GUI，逐个安装软件包。

此外，任何方法都可以冻结相同的要求列表（例如pip freeze）？

Answer 1

NLTK网站列出了一个命令行界面，用于下载本页底部的包和集合：

http://www.nltk.org/data

命令行的使用情况因您使用的Python版本而异，但在我的Python2.6安装中，我注意到我错过了'spanish_grammar'模型，这很好用：

python -m nltk.downloader spanish_grammars

你提到列出项目的语料库和模型要求，虽然我不确定自动执行此操作的方法，但我认为我至少会分享这个。

Answer 2

安装所有NLTK语料库＆amp;机型：

python -m nltk.downloader all

或者，在Linux上，您可以使用：

sudo python -m nltk.downloader -d /usr/local/share/nltk_data all

如果您只想列出最受欢迎的语料库，请将all替换为popular。模型。

你也可以浏览语料库＆amp;通过命令行模型：

mlee@server:/scratch/jjylee/tests$ sudo python -m nltk.downloader
[sudo] password for jjylee:
NLTK Downloader
---------------------------------------------------------------------------
    d) Download   l) List    u) Update   c) Config   h) Help   q) Quit
---------------------------------------------------------------------------
Downloader> d

Download which package (l=list; x=cancel)?
  Identifier> l
Packages:
  [ ] averaged_perceptron_tagger_ru Averaged Perceptron Tagger (Russian)
  [ ] basque_grammars..... Grammars for Basque
  [ ] bllip_wsj_no_aux.... BLLIP Parser: WSJ Model
  [ ] book_grammars....... Grammars from NLTK Book
  [ ] cess_esp............ CESS-ESP Treebank
  [ ] chat80.............. Chat-80 Data Files
  [ ] city_database....... City Database
  [ ] cmudict............. The Carnegie Mellon Pronouncing Dictionary (0.6)
  [ ] comparative_sentences Comparative Sentence Dataset
  [ ] comtrans............ ComTrans Corpus Sample
  [ ] conll2000........... CONLL 2000 Chunking Corpus
  [ ] conll2002........... CONLL 2002 Named Entity Recognition Corpus
  [ ] conll2007........... Dependency Treebanks from CoNLL 2007 (Catalan
                           and Basque Subset)
  [ ] crubadan............ Crubadan Corpus
  [ ] dependency_treebank. Dependency Parsed Treebank
  [ ] europarl_raw........ Sample European Parliament Proceedings Parallel
                           Corpus
  [ ] floresta............ Portuguese Treebank
  [ ] framenet_v15........ FrameNet 1.5
Hit Enter to continue: 
  [ ] framenet_v17........ FrameNet 1.7
  [ ] gazetteers.......... Gazeteer Lists
  [ ] genesis............. Genesis Corpus
  [ ] gutenberg........... Project Gutenberg Selections
  [ ] hmm_treebank_pos_tagger Treebank Part of Speech Tagger (HMM)
  [ ] ieer................ NIST IE-ER DATA SAMPLE
  [ ] inaugural........... C-Span Inaugural Address Corpus
  [ ] indian.............. Indian Language POS-Tagged Corpus
  [ ] jeita............... JEITA Public Morphologically Tagged Corpus (in
                           ChaSen format)
  [ ] kimmo............... PC-KIMMO Data Files
  [ ] knbc................ KNB Corpus (Annotated blog corpus)
  [ ] large_grammars...... Large context-free and feature-based grammars
                           for parser comparison
  [ ] lin_thesaurus....... Lin's Dependency Thesaurus
  [ ] mac_morpho.......... MAC-MORPHO: Brazilian Portuguese news text with
                           part-of-speech tags
  [ ] machado............. Machado de Assis -- Obra Completa
  [ ] masc_tagged......... MASC Tagged Corpus
  [ ] maxent_ne_chunker... ACE Named Entity Chunker (Maximum entropy)
  [ ] moses_sample........ Moses Sample Models
Hit Enter to continue: x


Download which package (l=list; x=cancel)?
  Identifier> conll2002
    Downloading package conll2002 to
        /afs/mit.edu/u/m/mlee/nltk_data...
      Unzipping corpora/conll2002.zip.

---------------------------------------------------------------------------
    d) Download   l) List    u) Update   c) Config   h) Help   q) Quit
---------------------------------------------------------------------------
Downloader>

Answer 3

除了已经提到的命令行选项之外，您还可以通过向download()函数添加参数，以编程方式在Python脚本中安装NLTK数据。

请参阅help(nltk.download)文字，具体为：

Individual packages can be downloaded by calling the ``download()``
function with a single argument, giving the package identifier for the
package that should be downloaded:

    >>> download('treebank') # doctest: +SKIP
    [nltk_data] Downloading package 'treebank'...
    [nltk_data]   Unzipping corpora/treebank.zip.

我可以确认这适用于一次下载一个包，或者传递list或tuple。

>>> import nltk
>>> nltk.download('wordnet')
[nltk_data] Downloading package 'wordnet' to
[nltk_data]     C:\Users\_my-username_\AppData\Roaming\nltk_data...
[nltk_data]   Unzipping corpora\wordnet.zip.
True

您也可以尝试下载已下载的软件包：

>>> nltk.download('wordnet')
[nltk_data] Downloading package 'wordnet' to
[nltk_data]     C:\Users\_my-username_\AppData\Roaming\nltk_data...
[nltk_data]   Package wordnet is already up-to-date!
True

此外，看起来该函数返回一个布尔值，您可以使用该值来查看下载是否成功：

>>> nltk.download('not-a-real-name')
[nltk_data] Error loading not-a-real-name: Package 'not-a-real-name'
[nltk_data]     not found in index
False

Answer 4

我已设法使用以下代码在自定义目录中安装语料库和模型：

import nltk
nltk.download(info_or_id="popular", download_dir="/path/to/dir")
nltk.data.path.append("/path/to/dir")

这将在/path/to/dir内安装“所有”语料库/模型，并让我们知道NLTK在哪里查找（data.path.append）。

您无法“冻结”需求文件中的数据，但除了代码之外，您可以将此代码添加到__init__以检查文件是否已存在。

以编程方式安装NLTK语料库/模型，即没有GUI下载器？

4 个答案: