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Kognetics - Link it -> DARPA MEMEX - Linkalytics is a suite of back-end analytics to link together disparate data. Linkalytics is intended to be hosted as an API that users can use to enhance, group, and cluster data. (Python)

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anukat2015/linkalytics

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Linkalytics

License Version Travis

Backend analytics to link together disparate data

Support

Here’s a list of Python platforms that are officially supported.

  • Python 3.5 (Latest)
  • Python 3.4

Quickstart

Clone Repository

$ git clone https://github.com/qadium-memex/linkalytics.git

*Optional Git LFS

This repository contains some large filed stored using Git (Large File System) LFS.

Git Large File Storage (LFS) replaces large files such as audio samples, videos, datasets, and graphics with text pointers inside Git, while storing the file contents on a remote server.

Instructions for installing Git LFS

After installing LFS, to retrieve the text pointers with the actual files runha.

$ git lfs pull

Install Python Dependencies

$ pip3 install -r requirements.txt

Also it is necessary to install the dependencies pandas and scipy

$ pip3 install scipy pandas

Install Disque

Currently we utilize Disque as a distributed work queue.

To install disque, ensure that you have a proper C Compiler installed and grab the repository

$ git clone https://github.com/antirez/disque.git

Make and install binaries

make && make install

Or use sudo if necessary

make && sudo make install

Instantiate credentials from shared repository using credstmpl

See Qadium's credstmpl github repository for installation instructions.

Also, please note this requires AWS credentials.

$ credstmpl linkalytics/environment/*.j2

Install Foreman

$ gem install foreman

Run Services

$ foreman run

Swagger Badge

Interactive documentation for the Linkalytics API can be found here.

For more information about generating a client or server, check out swagger project

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Kognetics - Link it -> DARPA MEMEX - Linkalytics is a suite of back-end analytics to link together disparate data. Linkalytics is intended to be hosted as an API that users can use to enhance, group, and cluster data. (Python)

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