I write this Python application for my own bass guitar practice needs. It can be used with any instrument though. The name is inspired by the Jedi Training Remote, seen on Star Wars.
Python is needed to run this application. If you don't have it, download and install Python.
Create a new folder on your computer; presumably called GTR.
Download all files in this repository to that directory.
Open a terminal window, go to folder GTR and install a Python virtual environment by typing:
python3 -m venv venv
Now activate the virtual environment. On Windows, you need to type:
venv/bin/activate.bat
On Mac and Linux, you need to type:
venv/bin/activate
While your virtual environment is active, install Kivy and Vibhaga by typing:
pip install kivy
pip install git+http://github.com/keremkoseoglu/vibhaga.git
Note that Kivy installation might be a little trickier than it seems. Check installation notes in case you need help.
After activating the virtual environment (as described above), run the application by typing:
python3 main.py
To customize the practices, you can edit data/config.json .
This application will build a random set of practices (found in the package practice), and display them in a sequence. Practice every day will hopefully improve your skills over time.
You will notice that the content of some practices will be random as well, such as the chord or notes you need to work on.
You can modify the current configuration by editing config.json . You can modify or add new instruments, chords, modes, arpeggions, improvs, etc.
GTR is integrated with FlukeBox! If you have a FlukeBox playlist containing your backing tracks, every time the Improv exercise starts, your backing track playlist will open as well. Just make sure that the "flukebox" section of data/config.json contains the right path and playlist values.
The application builds the practice set completely automatically, based on what is found in the package practice. The assumptions are;
- Every practice must have its own file, and every file must include a single class
- Every practice must be derived from abstract_practice.AbstractPractice
Optionally, classes may also get advantage of built-in helpers; such as:
- Calling URL's
- Controlling the metronome
Just check a few classes under /practice, and see how easily you can add your own practices. If you would like to contribute, feel free to contact me.
Current active workout factory can be found in factory.some_practices . Others can be found under factory.
If you want to change the workout factory, implement a new factory class under factory , and change the factory definition in gui.face.
You may want to exclude some practices completely, for instance.
This application proudly demonstrates dynamic object creation in Python. practice/toolkit includes methods to dynamically return class names / objects from within the given package name.
This technique would be particularly useful if you want your application to support plug-ins. Just put a new external .py file under the package folder, and there you go!