How can I run NLTK on App Engine or Kubernetes?












1















I am busy writing a model to predict types of text like names or dates on a pdf document.



The model uses nltk.word_tokenize and nltk.pos_tag



When I try to use this on Kubernetes on Google Cloud Platform I get the following error:



    from nltk.tag import pos_tag
from nltk.tokenize import word_tokenize

tokenized_word = tokenize_word('x')
tagges_word = pos_tag(['x'])


stacktrace:



      Resource punkt not found.
Please use the NLTK Downloader to obtain the resource:

>>> import nltk
>>> nltk.download('punkt')

Searched in:
- '/root/nltk_data'
- '/usr/share/nltk_data'
- '/usr/local/share/nltk_data'
- '/usr/lib/nltk_data'
- '/usr/local/lib/nltk_data'
- '/env/nltk_data'
- '/env/share/nltk_data'
- '/env/lib/nltk_data'
- ''


But obviously downloading it to your local device will not solve the problem if it has to run on Kubernetes and we do not have NFS set up on the project yet.










share|improve this question



























    1















    I am busy writing a model to predict types of text like names or dates on a pdf document.



    The model uses nltk.word_tokenize and nltk.pos_tag



    When I try to use this on Kubernetes on Google Cloud Platform I get the following error:



        from nltk.tag import pos_tag
    from nltk.tokenize import word_tokenize

    tokenized_word = tokenize_word('x')
    tagges_word = pos_tag(['x'])


    stacktrace:



          Resource punkt not found.
    Please use the NLTK Downloader to obtain the resource:

    >>> import nltk
    >>> nltk.download('punkt')

    Searched in:
    - '/root/nltk_data'
    - '/usr/share/nltk_data'
    - '/usr/local/share/nltk_data'
    - '/usr/lib/nltk_data'
    - '/usr/local/lib/nltk_data'
    - '/env/nltk_data'
    - '/env/share/nltk_data'
    - '/env/lib/nltk_data'
    - ''


    But obviously downloading it to your local device will not solve the problem if it has to run on Kubernetes and we do not have NFS set up on the project yet.










    share|improve this question

























      1












      1








      1








      I am busy writing a model to predict types of text like names or dates on a pdf document.



      The model uses nltk.word_tokenize and nltk.pos_tag



      When I try to use this on Kubernetes on Google Cloud Platform I get the following error:



          from nltk.tag import pos_tag
      from nltk.tokenize import word_tokenize

      tokenized_word = tokenize_word('x')
      tagges_word = pos_tag(['x'])


      stacktrace:



            Resource punkt not found.
      Please use the NLTK Downloader to obtain the resource:

      >>> import nltk
      >>> nltk.download('punkt')

      Searched in:
      - '/root/nltk_data'
      - '/usr/share/nltk_data'
      - '/usr/local/share/nltk_data'
      - '/usr/lib/nltk_data'
      - '/usr/local/lib/nltk_data'
      - '/env/nltk_data'
      - '/env/share/nltk_data'
      - '/env/lib/nltk_data'
      - ''


      But obviously downloading it to your local device will not solve the problem if it has to run on Kubernetes and we do not have NFS set up on the project yet.










      share|improve this question














      I am busy writing a model to predict types of text like names or dates on a pdf document.



      The model uses nltk.word_tokenize and nltk.pos_tag



      When I try to use this on Kubernetes on Google Cloud Platform I get the following error:



          from nltk.tag import pos_tag
      from nltk.tokenize import word_tokenize

      tokenized_word = tokenize_word('x')
      tagges_word = pos_tag(['x'])


      stacktrace:



            Resource punkt not found.
      Please use the NLTK Downloader to obtain the resource:

      >>> import nltk
      >>> nltk.download('punkt')

      Searched in:
      - '/root/nltk_data'
      - '/usr/share/nltk_data'
      - '/usr/local/share/nltk_data'
      - '/usr/lib/nltk_data'
      - '/usr/local/lib/nltk_data'
      - '/env/nltk_data'
      - '/env/share/nltk_data'
      - '/env/lib/nltk_data'
      - ''


      But obviously downloading it to your local device will not solve the problem if it has to run on Kubernetes and we do not have NFS set up on the project yet.







      kubernetes google-cloud-platform nltk google-kubernetes-engine






      share|improve this question













      share|improve this question











      share|improve this question




      share|improve this question










      asked Nov 14 '18 at 16:40









      Levenshtein's Nearest NeihgborLevenshtein's Nearest Neihgbor

      264




      264
























          1 Answer
          1






          active

          oldest

          votes


















          2














          How I ended up solving this problem was adding the download of the nltk packages in an init function



          import logging
          import nltk
          from nltk import word_tokenize, pos_tag

          LOGGER = logging.getLogger(__name__)

          LOGGER.info('Catching broad nltk errors')
          DOWNLOAD_DIR = '/usr/lib/nltk_data'
          LOGGER.info(f'Saving files to {DOWNLOAD_DIR} ')

          try:
          tokenized = word_tokenize('x')
          LOGGER.info(f'Tokenized word: {tokenized}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('punkt', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')

          try:
          tagged_word = pos_tag(['x'])
          LOGGER.info(f'Tagged word: {tagged_word}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('averaged_perceptron_tagger', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')


          I realize that the amount of try catch expressions are not needed. I also specify the download dir because it seemed that if you do not do that it downloads and unzips 'tagger' to /usr/lib and the nltk does not look for the the files there.



          This will download the files on every first run on a new pod and the files will persist until the pod dies.



          The error was solved on a Kubernetes stateless set which means this can deal with non persistent applications like App Engine, but will not be the most efficient because it will need to be download every time the instance spins up.






          share|improve this answer



















          • 1





            Yah this seems to work fine, I would just add, only download the packages that you require. downloading all packages might slow your application down

            – Illegal Operator
            Nov 14 '18 at 16:55











          Your Answer






          StackExchange.ifUsing("editor", function () {
          StackExchange.using("externalEditor", function () {
          StackExchange.using("snippets", function () {
          StackExchange.snippets.init();
          });
          });
          }, "code-snippets");

          StackExchange.ready(function() {
          var channelOptions = {
          tags: "".split(" "),
          id: "1"
          };
          initTagRenderer("".split(" "), "".split(" "), channelOptions);

          StackExchange.using("externalEditor", function() {
          // Have to fire editor after snippets, if snippets enabled
          if (StackExchange.settings.snippets.snippetsEnabled) {
          StackExchange.using("snippets", function() {
          createEditor();
          });
          }
          else {
          createEditor();
          }
          });

          function createEditor() {
          StackExchange.prepareEditor({
          heartbeatType: 'answer',
          autoActivateHeartbeat: false,
          convertImagesToLinks: true,
          noModals: true,
          showLowRepImageUploadWarning: true,
          reputationToPostImages: 10,
          bindNavPrevention: true,
          postfix: "",
          imageUploader: {
          brandingHtml: "Powered by u003ca class="icon-imgur-white" href="https://imgur.com/"u003eu003c/au003e",
          contentPolicyHtml: "User contributions licensed under u003ca href="https://creativecommons.org/licenses/by-sa/3.0/"u003ecc by-sa 3.0 with attribution requiredu003c/au003e u003ca href="https://stackoverflow.com/legal/content-policy"u003e(content policy)u003c/au003e",
          allowUrls: true
          },
          onDemand: true,
          discardSelector: ".discard-answer"
          ,immediatelyShowMarkdownHelp:true
          });


          }
          });














          draft saved

          draft discarded


















          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53304958%2fhow-can-i-run-nltk-on-app-engine-or-kubernetes%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown

























          1 Answer
          1






          active

          oldest

          votes








          1 Answer
          1






          active

          oldest

          votes









          active

          oldest

          votes






          active

          oldest

          votes









          2














          How I ended up solving this problem was adding the download of the nltk packages in an init function



          import logging
          import nltk
          from nltk import word_tokenize, pos_tag

          LOGGER = logging.getLogger(__name__)

          LOGGER.info('Catching broad nltk errors')
          DOWNLOAD_DIR = '/usr/lib/nltk_data'
          LOGGER.info(f'Saving files to {DOWNLOAD_DIR} ')

          try:
          tokenized = word_tokenize('x')
          LOGGER.info(f'Tokenized word: {tokenized}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('punkt', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')

          try:
          tagged_word = pos_tag(['x'])
          LOGGER.info(f'Tagged word: {tagged_word}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('averaged_perceptron_tagger', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')


          I realize that the amount of try catch expressions are not needed. I also specify the download dir because it seemed that if you do not do that it downloads and unzips 'tagger' to /usr/lib and the nltk does not look for the the files there.



          This will download the files on every first run on a new pod and the files will persist until the pod dies.



          The error was solved on a Kubernetes stateless set which means this can deal with non persistent applications like App Engine, but will not be the most efficient because it will need to be download every time the instance spins up.






          share|improve this answer



















          • 1





            Yah this seems to work fine, I would just add, only download the packages that you require. downloading all packages might slow your application down

            – Illegal Operator
            Nov 14 '18 at 16:55
















          2














          How I ended up solving this problem was adding the download of the nltk packages in an init function



          import logging
          import nltk
          from nltk import word_tokenize, pos_tag

          LOGGER = logging.getLogger(__name__)

          LOGGER.info('Catching broad nltk errors')
          DOWNLOAD_DIR = '/usr/lib/nltk_data'
          LOGGER.info(f'Saving files to {DOWNLOAD_DIR} ')

          try:
          tokenized = word_tokenize('x')
          LOGGER.info(f'Tokenized word: {tokenized}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('punkt', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')

          try:
          tagged_word = pos_tag(['x'])
          LOGGER.info(f'Tagged word: {tagged_word}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('averaged_perceptron_tagger', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')


          I realize that the amount of try catch expressions are not needed. I also specify the download dir because it seemed that if you do not do that it downloads and unzips 'tagger' to /usr/lib and the nltk does not look for the the files there.



          This will download the files on every first run on a new pod and the files will persist until the pod dies.



          The error was solved on a Kubernetes stateless set which means this can deal with non persistent applications like App Engine, but will not be the most efficient because it will need to be download every time the instance spins up.






          share|improve this answer



















          • 1





            Yah this seems to work fine, I would just add, only download the packages that you require. downloading all packages might slow your application down

            – Illegal Operator
            Nov 14 '18 at 16:55














          2












          2








          2







          How I ended up solving this problem was adding the download of the nltk packages in an init function



          import logging
          import nltk
          from nltk import word_tokenize, pos_tag

          LOGGER = logging.getLogger(__name__)

          LOGGER.info('Catching broad nltk errors')
          DOWNLOAD_DIR = '/usr/lib/nltk_data'
          LOGGER.info(f'Saving files to {DOWNLOAD_DIR} ')

          try:
          tokenized = word_tokenize('x')
          LOGGER.info(f'Tokenized word: {tokenized}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('punkt', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')

          try:
          tagged_word = pos_tag(['x'])
          LOGGER.info(f'Tagged word: {tagged_word}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('averaged_perceptron_tagger', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')


          I realize that the amount of try catch expressions are not needed. I also specify the download dir because it seemed that if you do not do that it downloads and unzips 'tagger' to /usr/lib and the nltk does not look for the the files there.



          This will download the files on every first run on a new pod and the files will persist until the pod dies.



          The error was solved on a Kubernetes stateless set which means this can deal with non persistent applications like App Engine, but will not be the most efficient because it will need to be download every time the instance spins up.






          share|improve this answer













          How I ended up solving this problem was adding the download of the nltk packages in an init function



          import logging
          import nltk
          from nltk import word_tokenize, pos_tag

          LOGGER = logging.getLogger(__name__)

          LOGGER.info('Catching broad nltk errors')
          DOWNLOAD_DIR = '/usr/lib/nltk_data'
          LOGGER.info(f'Saving files to {DOWNLOAD_DIR} ')

          try:
          tokenized = word_tokenize('x')
          LOGGER.info(f'Tokenized word: {tokenized}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('punkt', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')

          try:
          tagged_word = pos_tag(['x'])
          LOGGER.info(f'Tagged word: {tagged_word}')
          except Exception as err:
          LOGGER.info(f'NLTK dependencies not downloaded: {err}')
          try:
          nltk.download('averaged_perceptron_tagger', download_dir=DOWNLOAD_DIR)
          except Exception as e:
          LOGGER.info(f'Error occurred while downloading file: {e}')


          I realize that the amount of try catch expressions are not needed. I also specify the download dir because it seemed that if you do not do that it downloads and unzips 'tagger' to /usr/lib and the nltk does not look for the the files there.



          This will download the files on every first run on a new pod and the files will persist until the pod dies.



          The error was solved on a Kubernetes stateless set which means this can deal with non persistent applications like App Engine, but will not be the most efficient because it will need to be download every time the instance spins up.







          share|improve this answer












          share|improve this answer



          share|improve this answer










          answered Nov 14 '18 at 16:53









          Levenshtein's Nearest NeihgborLevenshtein's Nearest Neihgbor

          264




          264








          • 1





            Yah this seems to work fine, I would just add, only download the packages that you require. downloading all packages might slow your application down

            – Illegal Operator
            Nov 14 '18 at 16:55














          • 1





            Yah this seems to work fine, I would just add, only download the packages that you require. downloading all packages might slow your application down

            – Illegal Operator
            Nov 14 '18 at 16:55








          1




          1





          Yah this seems to work fine, I would just add, only download the packages that you require. downloading all packages might slow your application down

          – Illegal Operator
          Nov 14 '18 at 16:55





          Yah this seems to work fine, I would just add, only download the packages that you require. downloading all packages might slow your application down

          – Illegal Operator
          Nov 14 '18 at 16:55




















          draft saved

          draft discarded




















































          Thanks for contributing an answer to Stack Overflow!


          • Please be sure to answer the question. Provide details and share your research!

          But avoid



          • Asking for help, clarification, or responding to other answers.

          • Making statements based on opinion; back them up with references or personal experience.


          To learn more, see our tips on writing great answers.




          draft saved


          draft discarded














          StackExchange.ready(
          function () {
          StackExchange.openid.initPostLogin('.new-post-login', 'https%3a%2f%2fstackoverflow.com%2fquestions%2f53304958%2fhow-can-i-run-nltk-on-app-engine-or-kubernetes%23new-answer', 'question_page');
          }
          );

          Post as a guest















          Required, but never shown





















































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown

































          Required, but never shown














          Required, but never shown












          Required, but never shown







          Required, but never shown







          Popular posts from this blog

          List item for chat from Array inside array React Native

          Thiostrepton

          Caerphilly