NOTE

Any issues related to Turbo Parser itself, or issues running samples/tests, please file in TurboParser's main repository: https://github.com/andre-martins/TurboParser 

README


TurboTextAnalysis project folder analysis
  TurboTextAnalysis\Data
    Models for TurboParser in english and spanish.
      
  TurboTextAnalysis\deps  
    External files/projects that are required. A version of config++ is hereby made available.

  TurboTextAnalysis\TurboTextAnalysis  
    Library that exposes the complete NLP pipeline exclusively in C++ 
    on top of TurboParser (namely, the libturboparser library)
    (replaces python code in "python" folder of TurboParser project folder).
    
  TurboTextAnalysis\DemoTextAnalysisTest  
    Example code that uses the TurboTextAnalysis library.

  TurboTextAnalysis\TurboTextAnalysisPython
    Python wrapper over the TurboTextAnalysis, made with Cython.

  TurboTextAnalysis\CrossPlatfTurboTextAnalysis
    Cross-platform run-time dynamic linking library for TurboTextAnalysis.
    (Reference: https://github.com/davidalbertonogueira/CrossPlatfDynamicLibraryPlugInArchitecture)

  TurboTextAnalysis\TestCrossPlatfTurboTextAnalysis
    Example code that uses the TurboTextAnalysis run-time dynamic linking library.
        
NOTE:    
Python 3.X is required. 
Cython is required (sudo apt-get install cython3).
ICU library is required (sudo apt-get install libicu-dev icu-devtools).


Build process

  To Build TurboParser 
    1. Clone or download TurboParser from master branch 
        of https://github.com/Priberam/TurboParser
    2. If OS is Linux - Ubuntu distro
         2.1. you can use the install-ubuntu.sh script.
       If OS is Linux - other distro
         2.1. execute the following commands:
                ./install_deps.sh 
                automake --add-missing 
                ./configure && make && make install
                export LD_LIBRARY_PATH="$LD_LIBRARY_PATH:`pwd;`/deps/local/lib:"
       If OS is Windows
         2.1. In vsprojects folder you will find a Microsoft Visual Studio solution. 
         2.2. Firstly, in deps folder, you need to extract the dependency libraries 
              and compile them (they also have Microsoft Visual Studio solutions).
         2.3. Use the Microsoft Visual Studio solution to build all the projects.

  To Build libturboparser 
    1. Clone or download TurboParser from master branch 
        of https://github.com/Priberam/TurboParser
    2. If OS is Linux
         2.1 Go to the libturboparser folder in the TurboParser project folder.
         2.2. Then, execute make using that Makefile.
       If OS is Windows
         2.1 In the Microsoft Visual Studio solution, one of the projects 
             is libturboparser. You just need to build that project 
             (if you already built the solution (i.e., all the projects), 
             you can ignore this step).
          
  To Build TurboTextAnalysis
    1. Obtain this repository.
        1.1. In deps/, compile libconfig lib in libconfig-1.4.9/ folder.
    2. If OS is Linux
         2.1. Go to the TurboTextAnalysis folder in the TurboTextAnalysis 
              project folder, where you will find a Makefile.
         2.2. Edit the Makefile in such a way that the paths are corrected 
              to the path in which you have TurboParser.
         2.3. Then, execute make using that edited Makefile.
       If OS is Windows
         2.1. In the root folder of TurboTextAnalysis you will find a 
              Microsoft Visual Studio solution. 
         2.2. Edit the project files in order for the include directories 
              to point to the path in which you have TurboParser.
         2.3. Build the TurboTextAnalysis project.
  
  To Build TurboTextAnalysisPython
    1. Go to the TurboTextAnalysisPython folder in the TurboTextAnalysis project folder.
    2. Edit setup.py in order to point to the paths 
       of the necessary libraries (TurboTextAnalysis and TurboParser).
    3. Execute 
         python setup.py build_ext --inplace
       Note: If the default python version is 2.X, in linux you may need to call, for example:
         python3.4 setup.py build_ext --inplace
       If you are in Windows with an Anaconda environment, you may need to 
       activate a python 3 environment if you default is python 2.
    4. Run
         python test.py 
       to check that everything works.    
       

================================================================================

Priberam’s TurboTextAnalysis is a TurboParser's wrapper for easy text analysis, allowing it to be readily used in production systems.

Copyright 2018 by PRIBERAM INFORMÁTICA, S.A. - www.priberam.com

Usage subject to The terms & Conditions of the "Priberam TurboTextAnalysis OS Software License" available at https://www.priberam.pt/docs/Priberam_TurboTextAnalysis_OS_Software_License.pdf

================================================================================