fsEye is a programm for indexing and searching files in a computer's filesystem. Coursework.
Stemming tools (include/stemming .h files) I took from this repository: https://github.com/Blake-Madden/OleanderStemmingLibrary
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Download set of Boost libraries from here: https://www.boost.org/users/download/
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Follow this guide to build Boost: https://www.boost.org/doc/libs/1_62_0/more/getting_started/windows.html#simplified-build-from-source
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Download DuckX for processing doc/dockx files: https://github.com/amiremohamadi/DuckX Also for correct DuckX work you'll need:
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Download sqlite3 library (sqlite-amalgamation-3400000.zip)
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Download the project:
git clone https://github.com/lexxamcode/fsEye- Add path to boost, duckx, zip and pugixml files in CMakeLists.txt:
# Boost root and libraries directories are being set here
set(Boost_INCLUDE_DIR YOUR_PATH_TO_BOOST_ROOT)
set(Boost_LIBRARY_DIR YOUR_PATH_TO_BOOST_ROOT/stage/lib)
# DuckX library for doc/docx file processing
set(DINCLUDE_DIR YOUR_PATH_TO_DUCKX_ROOT/include)
set(PUGIXMLDIR YOUR_PATH_TO_PUGIXML_ROOT/src)
set(ZIPDIR YOUR_PATH_TO_ZIP_ROOT/src)
# sqlite3 library for working with database
set(SQLDIR YOUR_PATH_TO_SQLITE)
include_directories(${SQLDIR})
link_directories(${SQLDIR})- Before building project change one thing in duckx.cpp:
(Hope this issue is solved when someone need this project, but if it's not, just make the change i showed :) )
And this one in miniz.h if duckx does not open files with cyrillic symbols in their paths:
- Now build the project:
mkdir build
cd build
cmake ..
cmake --build .fsEye is going to be complete separate app, but still, fsEye source files and include files allow user to index text files by content in a directory in different languages:
FVectorMaker en_index_maker(en_dict_path, en_stopwords_path, "en");//Class that processes text and making the feature vector of given language of it
//INDEX DIRECTORY BY CONTENT
indexing::index_directory_by_content(DIRECTORY, DATABASE_FILENAME, en_index_maker);
//FIND BY CONTENT IN DIRECTORY
cout << "Enter your request: ";
string request;
cin >> request;
vector<string> found = indexing::knn_algorithm(request, DATABASE_FILENAME, en_index_maker, k);
cout << found.size() << endl;
for (auto& file: found)
cout << file << endl;
//INDEX DIRECTORY
cout << "Indexing Samples" << endl;
indexing::index_directory_to_db(DIRECTORY, DATABASE_FILENAME);
// FIND IN DIRECTORY:
while(true)
{
cout << "Enter your request: ";
string request;
cin >> request;
unordered_set<string> found = indexing::find_in_db(request, DATABASE_FILENAME);
for (auto& path: found)
cout << path << endl;
};
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