import os

"""
Performs some core NLP operations as a proof of concept for the library.
"""

from stanford_corenlp_pywrapper import CoreNLP

class StanfordCoreNLP:
    def __init__(self):
        # I don't see anywhere to put properties like this path...
        # For now it's hardcoded and would need to be changed when deployed...
        print "Some stuff"
        print os.path.abspath(__file__)
        coreNLPPath = os.path.join(os.path.dirname(__file__), '../../lib/stanfordCoreNLP.jar')
        print coreNLPPath
        self.proc = CoreNLP('pos', corenlp_jars=[coreNLPPath])

    def run(self, data):
        results = []
        for corpus in data:
            results.append(self.proc.parse_doc(corpus.contents))
        return results

import os

"""
Performs some core NLP operations as a proof of concept for the library.
"""

from stanford_corenlp_pywrapper import CoreNLP

class StanfordCoreNLP:
    def __init__(self):
        # I don't see anywhere to put properties like this path...
        # For now it's hardcoded and would need to be changed when deployed...
        
        coreNLPPath = os.path.join(os.path.dirname(__file__), '../../lib/stanfordCoreNLP.jar')
        coreNLPModelsPath = os.path.join(os.path.dirname(__file__), '../../lib/stanfordCoreNLPModels.jar')
        self.proc = CoreNLP('pos', corenlp_jars=[coreNLPPath, coreNLPModelsPath])

    def run(self, data):
        results = []
        for corpus in data:
            results.append(self.proc.parse_doc(corpus.contents))
        return results

Add coreNLP models jar relative path as well
Add coreNLP models jar relative path  as well

  import os
  
  """
  Performs some core NLP operations as a proof of concept for the library.
  """
  
  from stanford_corenlp_pywrapper import CoreNLP
  
  class StanfordCoreNLP:
      def __init__(self):
          # I don't see anywhere to put properties like this path...
          # For now it's hardcoded and would need to be changed when deployed...
+         
-         print "Some stuff"
-         print os.path.abspath(__file__)
          coreNLPPath = os.path.join(os.path.dirname(__file__), '../../lib/stanfordCoreNLP.jar')
-         print coreNLPPath
+         coreNLPModelsPath = os.path.join(os.path.dirname(__file__), '../../lib/stanfordCoreNLPModels.jar')
-         self.proc = CoreNLP('pos', corenlp_jars=[coreNLPPath])
+         self.proc = CoreNLP('pos', corenlp_jars=[coreNLPPath, coreNLPModelsPath])
  
      def run(self, data):
          results = []
          for corpus in data:
              results.append(self.proc.parse_doc(corpus.contents))
          return results
  
Add coreNLP models jar relative path as well
## Code Before:
import os

"""
Performs some core NLP operations as a proof of concept for the library.
"""

from stanford_corenlp_pywrapper import CoreNLP

class StanfordCoreNLP:
    def __init__(self):
        # I don't see anywhere to put properties like this path...
        # For now it's hardcoded and would need to be changed when deployed...
        print "Some stuff"
        print os.path.abspath(__file__)
        coreNLPPath = os.path.join(os.path.dirname(__file__), '../../lib/stanfordCoreNLP.jar')
        print coreNLPPath
        self.proc = CoreNLP('pos', corenlp_jars=[coreNLPPath])

    def run(self, data):
        results = []
        for corpus in data:
            results.append(self.proc.parse_doc(corpus.contents))
        return results

## Instruction:
Add coreNLP models jar relative path as well
## Code After:
import os

"""
Performs some core NLP operations as a proof of concept for the library.
"""

from stanford_corenlp_pywrapper import CoreNLP

class StanfordCoreNLP:
    def __init__(self):
        # I don't see anywhere to put properties like this path...
        # For now it's hardcoded and would need to be changed when deployed...
        
        coreNLPPath = os.path.join(os.path.dirname(__file__), '../../lib/stanfordCoreNLP.jar')
        coreNLPModelsPath = os.path.join(os.path.dirname(__file__), '../../lib/stanfordCoreNLPModels.jar')
        self.proc = CoreNLP('pos', corenlp_jars=[coreNLPPath, coreNLPModelsPath])

    def run(self, data):
        results = []
        for corpus in data:
            results.append(self.proc.parse_doc(corpus.contents))
        return results
