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Mining Software Repositories 2020 Short Paper. We suggest using function calls and API documentation to identify relevant code elements, reducing irrelevant ones and improving text-code pair quality.

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Project description to be added...

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

Our project combines JupyterNotebook and Luigi in order to provide a flexible pipeline structure for code processing. Therefore, in order to run the tasks you need to have installed in your system the following programs.

Python 3
Luigi - upgrade luigi to 2.8.8
Jupyter Notebook

Running the tasks

  1. With luigi daemon luigid

Note that my_module needs to be in your PYTHONPATH, or else this can produce an error (ImportError: No module named my_module). Add the current working directory to the command PYTHONPATH with:

cd tasks
PYTHONPATH='.' luigi --module my_module MyTask
  1. Without luigi daemon and local scheduler
cd tasks
PYTHONPATH='.' luigi --module my_module MyTask --local-scheduler

Luigi GUI could be seen at http://localhost:8082/

Running the task earlier way

First of all, we need to launch the Luigi daemon with:

	luigid

This daemon will be responsible for scheduling and executing the tasks.

There are two ways to run a specific Luigi task:

	luigi --module my_module MyTask [parameters]

or

	python -m luigi --module my_module MyTask [parameters]

Note that if a parameter name contains ‘_’, it should be replaced by ‘-‘. For example, if MyTask had a parameter called ‘my_parameter‘:

	luigi --module my_module MyTask --my-parameter 100 

Developing a new Task

TBD

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Mining Software Repositories 2020 Short Paper. We suggest using function calls and API documentation to identify relevant code elements, reducing irrelevant ones and improving text-code pair quality.

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