This manual is to help in setting up the environment for running python code as well as Jupyter notebook.

1. Center for Research and Application for Satellite Remote Sensing
Yamaguchi University
Setting-Up Python Environment
(Jupyter Notebook)

2. Contents:
This manual is to help in setting up the environment for running
python code as well as Jupyter notebook. Contents are arranged in
following manners:-
1. Creating a project
2. Activating the Environment
3. Installing the libraries
4. Listing the libraries
5. Making the virtual environment compatible with jupyter notebook
6. Jupyter notebook running

3. • Create a folder for the project
• Using GUI or
• Through shell: $ mkdir <project name>
• Change path: $ cd <project path>
• Creating a virtual environment for our project (generally same as project name for easy to remember) .
• $ conda create --name <virtual environment name> <python=version>
*In place of ‘conda’ we can also
use Python package manager
(‘pip’ or ‘pip3’). It will be mostly
same with few exceptions.
Creating a Project

4. • $ conda info —envs (For listing all the virtual environments)
• $ conda activate <virtual environment name> OR
• $ source activate < virtual environment name> (Activate the virtual
environment that we want to use for our project)
• After that we can see virtual environment name in starting of prompt.
• For deactivating this: $ conda deactivate
• For removing: $ conda env remove -–name <virtual environment name>
Activating the Environment

5. • $ conda install <libraryName1 libraryName2>
• Libraries for ex. OpenCV, TensorFlow, PyTorch, Keras etc.
• $ conda install tensorflow
• $ conda install pytorch torchvision -c pytorch
*detail description has been provided on other manual namely libraries_setup
Installing the libraries

6. • $ conda list (this command will list all the installed libraries/packages)
Listing the libraries

7. • $ conda install ipykernel
• $ ipython kernel install --user --name=<virtual environment name>
• $ jupyter notebook & (For running jupyter notebook)
• It will give a string with token (Highlighted with red ellipse) which can be copy pasted in browser
to run the instance of the notebook
Making the Virtual Environment compatible with Jupyter

8. • Create a new notebook using the Kernel which has been created in last exercise (for example here
Python_Learning).
Jupyter Notebook

9. • Jupyter notebook gives the flexibility to run a block of code (called cell) at a time, by using Run
button( ) or using shortcut Shift+Enter(return) key.
Output
Kernel
Writing a Simple Program in Jupyter Notebook