This repository has been created for the first lab session on audio analysis with Python of the Multimedia Systems subject at the University of Extremadura (UEx).
The instructions below help you replicate this repository.
Anaconda distribution is recommended. You can install it following the official installation guide.
Check if Anaconda is installed:
conda --version
conda -V
The file environment.yml contains all the necessary packages to use this project inside the environment with the name audiopy provided. You can create a conda environment from the .yml file as follows:
conda env create -f environment.yml
Activate the conda environment:
conda activate <env_name>
where <env_name> is the name of the conda environment we have just created. It appears in the first line of the file environment.yml; audiopy in this particular case.
Add the conda environment to JupyterLab so that it appears as a kernel:
python3 -m ipykernel install --user --name=audiopy
Check that the kernel has been installed correctly:
jupyter kernelspec list
Now we can run JupyterLab and select audiopy as the running kernel:
jupyter-lab
Alternatively, we can use Visual Studio Code.
Now that we have everything set up, we can start playing with this repository! 😎
The instructions below help you create everything you need to start working on your own repository.
You can create an environment in the default folder as follows:
conda create --name=<env_name>
where <env_name> is the name of the conda environment.
Alternatively, we can create an empty environment inside the repository folder:
conda create --prefix=./<env_name>
conda config --append=envs_dirs <path_to_parent_dir_env>
where <path_to_parent_dir_env> is the path to the repository (you can use . if the terminal points to the target folder).
Check that the environment has been created correctly:
conda env list
Activate the conda environment:
conda activate <env_name>
Check the packages installed with:
conda list
Kernels are programming language-specific processes that run independently and interact with JupyterLab.
Manually install all required packages:
conda install -c conda-forge <package_name>
Install the Jupyter kernel for the conda environment by running:
python3 -m ipykernel install --user --name=<env_name>
where <env_name> is again the name of our conda environment.
Check that the kernel has been installed correctly:
jupyter kernelspec list
Install JupyterLab using:
conda install -c conda-forge jupyterlab
The only thing left is starting JupyterLab and choosing the new kernel:
jupyter-lab
Alternatively, we can use Visual Studio Code.
Export an environment to be replicated (while activated):
conda env export > environment.yml
Now you can play on your own with your repository! 🤓
This project is licensed under the GNU General Public License v3.0 - see the LICENSE file for details