我正在尝试下载整个教科书，但它只是显示内核繁忙。我离开了半个小时，但仍处于繁忙状态。当我停止它时，出现以下错误。谁能指导我解决问题，或者我没有正确执行步骤。
KeyboardInterrupt Traceback (most recent call last)
<ipython-input-3-fec50ed38a60> in <module>()
1 import nltk
----> 2 nltk.download()
C:\Users\\Anaconda2\lib\site-packages\nltk\downloader.pyc in download(self, info_or_id, download_dir, quiet, force, prefix, halt_on_error, raise_on_error)
659 # function should make a new copy of self to use?
660 if download_dir is not None: self._download_dir = download_dir
--> 661 self._interactive_download()
662 return True
663
C:\Users\\Anaconda2\lib\site-packages\nltk\downloader.pyc in _interactive_download(self)
980 if TKINTER:
981 try:
--> 982 DownloaderGUI(self).mainloop()
983 except TclError:
984 DownloaderShell(self).run()
C:\Users\\Anaconda2\lib\site-packages\nltk\downloader.pyc in mainloop(self, *args, **kwargs)
1715
1716 def mainloop(self, *args, **kwargs):
-> 1717 self.top.mainloop(*args, **kwargs)
1718
1719 #/////////////////////////////////////////////////////////////////
C:\Users\\Anaconda2\lib\lib-tk\Tkinter.pyc in mainloop(self, n)
1127 def mainloop(self, n=0):
1128 """Call the mainloop of Tk."""
-> 1129 self.tk.mainloop(n)
1130 def quit(self):
1131 """Quit the Tcl interpreter. All widgets will be destroyed."""
KeyboardInterrupt:
命令
import nltk
nltk.download()
答案 0 :(得分：2)
我会尝试逐步下载您需要的内容。我实际上遇到了这个问题，并通过使用nltk.download('name of resource')
答案 1 :(得分：1)
转到您的终端并运行“ ipython”
import nltk
nltk.download()
按照指南进行操作，这会影响您的笔记本
答案 2 :(得分：1)
首先在Jupiter笔记本上，您必须导入nltk
import nltk
在运行以下命令时，会列出您可以安装的软件包
nltk.download()
然后您将看到以下软件包列表：
Download which package (l=list; x=cancel)?
Identifier> l
Packages:
[ ] abc................. Australian Broadcasting Commission 2006
[ ] alpino.............. Alpino Dutch Treebank
[ ] averaged_perceptron_tagger Averaged Perceptron Tagger
[ ] averaged_perceptron_tagger_ru Averaged Perceptron Tagger (Russian)
[ ] basque_grammars..... Grammars for Basque
[ ] biocreative_ppi..... BioCreAtIvE (Critical Assessment of Information
Extraction Systems in Biology)
[ ] bllip_wsj_no_aux.... BLLIP Parser: WSJ Model
[ ] book_grammars....... Grammars from NLTK Book
[ ] brown............... Brown Corpus
[ ] brown_tei........... Brown Corpus (TEI XML Version)
[ ] cess_cat............ CESS-CAT Treebank
[ ] 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
Hit Enter to continue:
[ ] conll2007........... Dependency Treebanks from CoNLL 2007 (Catalan
and Basque Subset)
[ ] crubadan............ Crubadan Corpus
[ ] dependency_treebank. Dependency Parsed Treebank
[ ] dolch............... Dolch Word List
[ ] europarl_raw........ Sample European Parliament Proceedings Parallel
Corpus
[ ] floresta............ Portuguese Treebank
[ ] framenet_v15........ FrameNet 1.5
[ ] framenet_v17........ FrameNet 1.7
[ ] gazetteers.......... Gazeteer Lists
[ ] genesis............. Genesis Corpus
[ ] gutenberg........... Project Gutenberg Selections
[ ] 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
Hit Enter to continue:
[ ] 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)
[ ] maxent_treebank_pos_tagger Treebank Part of Speech Tagger (Maximum entropy)
[ ] moses_sample........ Moses Sample Models
[ ] movie_reviews....... Sentiment Polarity Dataset Version 2.0
[ ] mte_teip5........... MULTEXT-East 1984 annotated corpus 4.0
[ ] mwa_ppdb............ The monolingual word aligner (Sultan et al.
2015) subset of the Paraphrase Database.
[ ] names............... Names Corpus, Version 1.3 (1994-03-29)
[ ] nombank.1.0......... NomBank Corpus 1.0
[ ] nonbreaking_prefixes Non-Breaking Prefixes (Moses Decoder)
[ ] nps_chat............ NPS Chat
[ ] omw................. Open Multilingual Wordnet
[ ] opinion_lexicon..... Opinion Lexicon
[ ] panlex_swadesh...... PanLex Swadesh Corpora
[ ] paradigms........... Paradigm Corpus
[ ] pe08................ Cross-Framework and Cross-Domain Parser
Evaluation Shared Task
Hit Enter to continue:
[ ] perluniprops........ perluniprops: Index of Unicode Version 7.0.0
character properties in Perl
[ ] pil................. The Patient Information Leaflet (PIL) Corpus
[ ] pl196x.............. Polish language of the XX century sixties
[ ] porter_test......... Porter Stemmer Test Files
[ ] ppattach............ Prepositional Phrase Attachment Corpus
[ ] problem_reports..... Problem Report Corpus
[ ] product_reviews_1... Product Reviews (5 Products)
[ ] product_reviews_2... Product Reviews (9 Products)
[ ] propbank............ Proposition Bank Corpus 1.0
[ ] pros_cons........... Pros and Cons
[ ] ptb................. Penn Treebank
[ ] punkt............... Punkt Tokenizer Models
[ ] qc.................. Experimental Data for Question Classification
[ ] reuters............. The Reuters-21578 benchmark corpus, ApteMod
version
[ ] rslp................ RSLP Stemmer (Removedor de Sufixos da Lingua
Portuguesa)
[ ] rte................. PASCAL RTE Challenges 1, 2, and 3
[ ] sample_grammars..... Sample Grammars
[ ] semcor.............. SemCor 3.0
Hit Enter to continue:
[ ] senseval............ SENSEVAL 2 Corpus: Sense Tagged Text
[ ] sentence_polarity... Sentence Polarity Dataset v1.0
[ ] sentiwordnet........ SentiWordNet
[ ] shakespeare......... Shakespeare XML Corpus Sample
[ ] sinica_treebank..... Sinica Treebank Corpus Sample
[ ] smultron............ SMULTRON Corpus Sample
[ ] snowball_data....... Snowball Data
[ ] spanish_grammars.... Grammars for Spanish
[ ] state_union......... C-Span State of the Union Address Corpus
[ ] stopwords........... Stopwords Corpus
[ ] subjectivity........ Subjectivity Dataset v1.0
[ ] swadesh............. Swadesh Wordlists
[ ] switchboard......... Switchboard Corpus Sample
[ ] tagsets............. Help on Tagsets
[ ] timit............... TIMIT Corpus Sample
[ ] toolbox............. Toolbox Sample Files
[ ] treebank............ Penn Treebank Sample
[ ] twitter_samples..... Twitter Samples
[ ] udhr2............... Universal Declaration of Human Rights Corpus
(Unicode Version)
[ ] udhr................ Universal Declaration of Human Rights Corpus
Hit Enter to continue:
[ ] unicode_samples..... Unicode Samples
[ ] universal_tagset.... Mappings to the Universal Part-of-Speech Tagset
[ ] universal_treebanks_v20 Universal Treebanks Version 2.0
[ ] vader_lexicon....... VADER Sentiment Lexicon
[ ] verbnet3............ VerbNet Lexicon, Version 3.3
[ ] verbnet............. VerbNet Lexicon, Version 2.1
[ ] webtext............. Web Text Corpus
[ ] wmt15_eval.......... Evaluation data from WMT15
[ ] word2vec_sample..... Word2Vec Sample
[ ] wordnet............. WordNet
[ ] wordnet_ic.......... WordNet-InfoContent
[ ] words............... Word Lists
[ ] ycoe................ York-Toronto-Helsinki Parsed Corpus of Old
English Prose
Collections:
[ ] all-corpora......... All the corpora
[ ] all-nltk............ All packages available on nltk_data gh-pages
branch
[ ] all................. All packages
[ ] book................ Everything used in the NLTK Book
[ ] popular............. Popular packages
Hit Enter to continue:
[ ] tests............... Packages for running tests
[ ] third-party......... Third-party data packages
然后，您可以选择所需的软件包，例如，选择“ vader_lexicon”
nltk.download('vader_lexicon')
您还可以通过传递所有软件包来安装所有软件包……..所有软件包
nltk.download('all')